SPY Short Vertical Put Spread 45 DTE Options Backtest
There are 40 backtests in this study evaluating over 123,000 SPY short vertical put spread trades.
In this post we’ll take a look at the backtest results of opening one SPY short vertical put spread each trading day from Jan 3 2007 through June 11 2019 and see if there are any discernible trends. We’ll also explore the profitable strategies to see if any outperform buy-and-hold SPY.
Let’s dive in!
Systematically holding short vertical put spreads till expiration, as well as managing at 75% max profit was profitable across all tested delta targets.
The 10D/5D strategy held till expiration had the best risk-adjusted return of all short vertical put spread strategies.
If managing early, narrower spreads take longer to reach profit targets than wider spreads.
No SPY short vertical put spread strategy outperformed buy/hold SPY with regard to total return.
- Symbol: SPY
- Strategy: Short Vertical Put Spread
- Days Till Expiration: 45 DTE +/- 17, closest to 45
- Start Date: 2007-01-03
- End Date: 2019-06-11
- Positions opened per trade: 1
- Entry Days: daily
- Entry Signal: N/A
- Timing: 3:46pm ET
- Strike Selection
- 2.5 delta +/- 1.5 delta, closest to 2.5
- 5 delta +/- 1.5 delta, closest to 5
- 10 delta +/- 1.5 delta, closest to 10
- 16 delta +/- 1.5 delta, closest to 16
- 30 delta +/- 2.0 delta, closest to 30
- Trade Entry
- 5D short / 2.5D long
- 10D short / 2.5D long
- 10D short / 5D long
- 16D short / 2.5D long
- 16D short / 5D long
- 16D short / 10D long
- 30D short / 2.5D long
- 30D short / 5D long
- 30D short / 10D long
- 30D short / 16D long
- Trade Exit
- 25% max profit or 21 DTE, whichever occurs first
- 50% max profit or 21 DTE, whichever occurs first
- 75% max profit or expiration, whichever occurs first
- Hold till Expiration
- Margin requirements are always satisfied
- Margin calls never occur
- Margin requirement for short CALL and PUT positions is 20% of notional
- Margin requirement for short STRADDLE and STRANGLE positions is 20% of the larger strike
- Margin requirement for short VERTICAL SPREAD positions is the difference between the strikes
- Early assignment never occurs
- Prices are in USD
- Prices are nominal (not adjusted for inflation)
- All statistics are pre-tax, where applicable
- Margin collateral is held as cash and earns no interest
- Assignment P/L is calculated by closing the ITM position at 3:46pm ET the day of expiration / position exit
- Commission to open, close early, or expire ITM is 1.00 USD per contract
- Commission to expire worthless is 0.00 USD per contract
- Commission to open or close non-option positions, if applicable, is 0.00 USD
- Slippage is calculated according to the slippage table
- For comprehensive details, visit the methodology page
Managing trades at 50% max profit or 21 DTE underperformed holding till expiration with regard to win rate.
The lower the short delta position the higher the win rate.
The narrower the spread the lower the win rate.
Early management underperformed holding till expiration with regard to annual volatility. 5D-2.5D and 10D-2.5D @ 75% max profit were exceptions.
The higher the short position delta the higher the volatility.
Worst Monthly Return
Early management outperformed holding till expiration with regard to worst monthly return when the short delta position was 10 or less.
The higher the short position delta the more severe the worst monthly return.
Average P/L Per Day
Early management outperformed holding till expiration with regard to average daily P/L. The narrowest spread for each short delta target was an exception.
The higher the short delta position the higher the average daily P/L.
Average Trade Duration
Managing trades at 50D max profit or 21 DTE yielded trade durations roughly 66% shorter than holding till expiration.
Compound Annual Growth Rate
Managing trades early had mixed performance vs holding till expiration with regard to compound annual growth rate.
The higher the short delta position the higher the CAGR.
Early management underperformed holding till expiration with regard to sharpe ratio. The 30D short-leg trades were an exception.
The sharpe ratio was mixed across delta targets.
The 10D/5D hold-till-expiration strategy had the greatest risk-adjusted return among the option strategies.
Profit Spent on Commission
50.13% – the blended average percent of profits spent on commission across all short vertical put spread strategies.
Early management underperformed holding till expiration with regard to total P/L.
The higher the short position delta the higher the total P/L.
36 of the 40 option strategies were profitable.
Spreads were configured as a function of delta and not a fixed dollar width such as $1, $5 or $10. This allows for consistent risk profiles across the backtest duration.
Consider 2007 when SPY was $141 per share. A $5-wide spread allows for a 3.5% movement in the underlying ( 5 / 141 ). In 2019 the same $5-wide spread allows only a 1.73% movement in the underlying ( 5 / 288 ). It would require a strike width just north of $9 ( 262.5 / 0.035 ) to have a comparable present-day trade.
Of course, volatility – namely vega – plays a role in this as well. A $5 (or $9) wide spread can mean two very different things when VIX is 20+ vs 13.
By using delta to anchor short and long positions we can maintain risk profiles across varying VIX regimes and we are not impacted by any appreciation/depreciation of the underlying’s price.
When positions are closed before expiration a trader forfeits potential profits. In the process they shorten the time capital is at risk. Early management is essentially a form of risk management.
Suppose we open a 10-delta 44-DTE short put on SPY with a strike of 262.5 and collect $0.97. We have $26,250 at risk for 44 days.
Assuming we hold till expiration we have a return on capital of 0.37% ( 97 / 26,250 ) which is 3.11% [ ( 1 + .0037 ) ^ ( 365 / 44 ) – 1 ] annualized.
Let’s instead assume we close the short position after 1 day at 10% max profit.
Return on capital becomes 0.037% – just under 4 basis points – ( 9.7 / 26,250 ). Annualized, it becomes 14.43% [ ( 1 + ( 9.7 / 26250 ) ) ^ ( 365 / 1 ) – 1 ].
In this scenario, managing early increases annualized return on capital by over 4.6x.
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June 17, 2019 @ 4:34 am
Using SPX instead of SPY must transform these results if sufficient capital is available?
June 17, 2019 @ 8:25 am
Great question! Unfortunately it doesn’t. Suppose we make the portfolio 10x larger ($1M) to support the 10x larger position of SPX. We’ll save on commissions but we’ll lose [even more] on slippage. More on the slippage methodology used in the backtesting here.
I’ll add a note about this in the methodology section.
Slippage was apparent in the naked put strategy backtests that I ran for comparison in the last post. Perhaps I’ll post a comparative example in the next post.
July 25, 2019 @ 9:10 am
I disagree. $0.01 slippage in SPY is $0.10 slippage in SPX, which is more than ample for a single-leg trade. I’ve seen many traders report SPX fills at the midprice.
July 25, 2019 @ 12:13 pm
I’m looking on IB’s mobile app at the Sept 6 2019 (43 DTE) SPX 2700 put. Width is $0.20 (5.10 – 5.30). The SPY 270 is $0.01 wide; $.10 if scaled for SPX. That’s a 2x difference. Looking at SPX 2705 it’s $0.30 wide.
There’s also the issue of SPX pricing granularity. When credit received is sub $10 bids can be placed in $0.05 increments. When credit is over $10 the granularity becomes $0.25. Not sure if this is market mechanic or an IB mechanic.
July 26, 2019 @ 9:07 am
I get midprice fills on SPX about half the time (verticals too), but looking at the spread alone I would have to agree with you on this. In the general scheme of things, it’s a bit more complicated when you factor in 60/40 tax treatment for broad-based indices.
SPX options under $3.00 have minimum tick size of $0.05 (otherwise $0.10). That’s dictated by CBOE.
June 17, 2019 @ 2:51 pm
Thanks for the reply.
How many 25 point SPX spreads would you open in a $1M portfolio?
June 17, 2019 @ 8:28 pm
None. I prefer to trade naked puts and manage early 🙂
June 17, 2019 @ 8:47 pm
Stephen, Using the VIX as a guide, if I was investing using my Revolver Method, I’d invest no more than 60% of the $1M while VIX is less than 17.5. So while it’s lower than 17.5 (like now) I’d open positions every trading day and close them 28 days later. Since over the 20 trading day period you’d be looking to invest equal amounts of the 60%, I’d open 12 positions at 6% away from the ATM price per day.
While VIX is low, Revolver is very similar to Spintwig’s model. I open 40-72 days out on the monthlies and close 28 days later. I let bigger losers ride for awhile to allow the market to come back up .
Applying this to today, the market closed at 6889.67 x .94 = 2716, so opening spreads at 2715/2690 would get a credit of $300 per position x 12 contracts or $3600 (minus commissions). based on my data, these close out 28 days later for an average of 51.5% of the initial credit. So the net would be expected to average about $1800 after commissions.
So a net of $1800 against $30,000 = 6% for the 4 week period.
June 18, 2019 @ 3:38 am
Great explanation. Thanks.
I’ve been doing 45/60 DTE spreads for several years with much success, although the last 2 years are by far the most ‘challenging’!
Recently, I’ve added the 2 DTE spreads inspired by the work of ERN and Spintwig. Too soon and too benign a market to form much of an opinion yet. Everything has expired worthless. I’m using less than 25% of the cash in my portfolio.
[there’s an unimportant typo in your post. Should be 2889.67 not 6889.67]
June 18, 2019 @ 10:50 am
A further comment.
Using today’s figures (market up quite sharply), I get the following using your example above:
12 contracts of SPX at 58 DTE. 2750/2725 total credit $3600. Margin is $30,000 and Delta is 19%.
If we aim for the same credit using 2 DTE spreads (i.e. 12 consecutive trades each 4 weeks):
10 contracts of SPX at 2 DTE. 2830/2805 total credit $300. Margin is $25,000 and Delta is 5%.
The drop in VIX has had quite an effect on these short term spreads. Yesterday, I could do this trade
5 contracts of SPX at 2 DTE. 2835/2810 total credit $350. Margin is $12,500 and Delta is 5%.
June 18, 2019 @ 11:18 am
Stephen, thanks for catching the typo, I think I just got typing too fast! You are absolutely correct that as the VIX drops pricing of the 2 DTE trades PLUMMETS, but when the VIX goes back up pricing spikes up just as fast, that’s why I move to longer trades when the VIX is low, it becomes more of a Theta play at the longer expirations and when the VIX is high you’re really playing Vega more than anything.
When VIX is low and I’m an doing 28 day trades, I don’t go over 60% of my portfolio in 28 day trades. That 40% is my reserve for both losses, but especially if the VIX spikes I can use the remaining 30% for 2 DTE trades that make up lost ground really fast. It allows for transitions into high VIX periods and out pretty well.
Doing this had 2018 at 18% return compared with S&P down 4.4%. Only 28 day trades was down 3%, and only 2 DTE trades were down 29.4%! As this Blog post from Spintwig shows a single strategy is ineffective at really beating the Buy/Hold strategy. 2017 (where the VIX never ended above 16) had 2 DTE trades up 29.3%, 28 Day trades were up 60.7%! The combo of these actually stayed in 28 day trades the whole year because of the low VIX environment.
I’m really enjoying these conversations! First place I feel like I’ve been able to share with similar minded folks. Thanks!
June 18, 2019 @ 2:07 pm
What are your (and other readers’) thoughts on me starting a quantitative options forum here? I know there’s an options reddit but it’s not necessarily data driven. Trying to get a feel for level of interest and potential audience size to see if it’s worth pursuing.
June 18, 2019 @ 2:17 pm
I, for one, would welcome it. I subscribe to r/options, but it is 70-80% about buying options and the quantitative discussions are few and far between.
June 18, 2019 @ 5:33 pm
I would like to see that!
June 19, 2019 @ 10:25 am
Take a look at SPX June 21 exp (weekly) pricing for 2.7% away from ATM Put Spread. usually pricing drops as you get closer. but a 4 strike wide spread yesterday was $70 and this morning it is $90-$105. I’m curious if the price will IV Crush after the Fed announcement at 2pm Eastern. I may be placing a trade after the announcement if the pricing does not fall too much.
with SPX at 2918, 2.7% out is 2840 and 2820 for the strikes of the spread.
For $2000 capital, if this really returns $70-$100 by Friday, what a nice trade! BTW, When VIX is between 14-17, the market has moved more than 2.7% only 1.14% of the time.
August 21, 2019 @ 8:54 pm
RE: the forum idea, I’ve been following along with some discussions in the Facebook tastytrade discussion group. There have been a few posts recently discussing backtests, short SPX put strategies, 0DTE strategies, etc.
August 22, 2019 @ 11:38 am
I don’t have a FB account so can’t view the content, but 0DTE strategies do sound interesting.
My thoughts are to backtest popular strategies on popular underlying then begin exploring more novel strategies such as these and work through those.
Looking to have a critical mass of viewership before launching a forum to ensure it isn’t a ghost town. According to some preliminary research there’s a bit more activity needed.
June 18, 2019 @ 5:36 pm
Do you mean a loss of 18% on your options in 2018?
June 18, 2019 @ 5:52 pm
I do not 🙂
2018 would have been positive 18% with the combo of 28 day and 2 day trades. Either system by themselves would have lost.
I had not yet discovered the 2 DTE and how it meshed and I ended with a small loss in 2018.
I would have much rather had an 18% gain than the small loss I ended with.
June 17, 2019 @ 6:22 pm
Great data work, Spintwig! I think it certainly points to the fact that a one-sized-fits-all approach does not outperform. Does your backtest software have the ability to shorten the duration of trades depending on how elevated the VIX is like we discussed on your last post?
Does it also have the ability to close at 21 DTE automatically rather than expiration or a specific profit target? I ask this last question because in the manual back-testing that I did, I often found that as the market has moved up closing at 28 days from entering the trade often generated 70-90% and I think cutting out early hurts performance. On the other side, many trades closed at 28 days making 25-40% and I’d take that as letting them ride to expiration gave more time for the market to move against the position.
I love all this review and data crunching you’re doing. I’ve been watching your backtesting closely as I’ve not been able to find software or data that allows me to fully test my method other than the manual backtesting I’ve done which is tedious and not very easy to just tryout different ideas because of the amount of work it takes.
June 17, 2019 @ 8:56 pm
It unfortunately does not. OptionStack can do this but ORATS, the tool I’m using, cannot.
As for closing at 21 DTE regardless of trade profitability, yes, this is a mechanic that ORATS can backtest. TastyTrade did a study comparing managing time vs managing profits on strangles and straddles. They concluded managing profits was more profitable than managing time.
My strategy is to sell short puts and manage @ 25% or sooner; exploring optimizing around the 21+ days into the trade is not an activity I’ve not yet looked into.
Simply using the backtester is tedious! API access will make generating the actual tests significantly easier. However, compiling the outputs into Excel and organizing them into a reportable format is also quite time consuming. I couldn’t imagine having to also scan and build a trade log from raw data. Impressive work manually building those backtests, sir!
Where did you get your data source(s)?
June 17, 2019 @ 11:54 pm
So, I started out by downloading the daily closing price of the S&P 500 back to 1993. I did the same with the VIX daily numbers. Then I wrote a calculator in Excel that would evaluate if a trade would with based on the VIX range I entered, along with how far away from ATM and the time duration. Playing around with that for quite awhile gave me some good idea of how far out I needed to go to win the majority of the time.
Then the real time hog started…I hardcoded the % away from ATM and what those Strike prices were, then used the Think-back feature in TOS to look up what the Premium would be for that day at that strike. I then projected forward 4 weeks and recorded the profit/loss of each of those trades. I manually backtested about 600 of those making sure to have a good representative sample of all VIX ranges (0-12, 12-14, 14-16 etc). After that I took the averages of those values and applied it to the other 6000 days and ended up with some really compelling results. I then built the capital allocation to grow as the portfolio grew.
Then the real fun started when I started to explore shorter time frame trades. I looked at 8 trading DTE and 2 DTE. After entering about 200-250 historical premium values I then ran multiple pivot tables and found some really interesting results. For instance the 28 day Revolver got more profitable as the VIX went up…until it hit 17.5. From 17.5-20.5 is was barely above breakeven. This made me look at the mean and median changes in the VIX after 20 days I expected that since the VIX is a mean reversion entity that the mean and median values would be lower 20 days later as the median value of the VIX over the last 26 years is 17.3. What I found amazed me! The mean and median values both went UP 20 day later. This was where I saw that the 8 day model made significantly more in that particular range and indeed as the VIX went up I say that the shorter duration trades with their faster cycling were FAR more valuable.
I wrote several variables to mix and match the 3 strategies and came up with a model that seems to win far better than any one of them alone. But I’d estimate that I have somewhere between 150-200 hours sunk into these spreadsheets, so that’s why I’ve been asking about the tools you’ve been using. I’m not sure I have it in me to test any more than what I have already done…the spreadsheet goes out 80 columns and 6600 rows already! Sheesh!
The main timeframe I’m looking at is since 9/1/2016 since all the MWF weeklies existed by then and options volume has continued to climb following that. From 9/1/16-5/10/19 The SPX returned 40.25% (with Dividends reinvested), the 28 Revolver by itself returned 101%. The full revolver with 2-Revolver trades at high VIX got to 164%
September 5, 2019 @ 9:47 pm
As Spintwig has said, OptionStack could indeed backtest along the lines you state – changing DTE based on VIX level. I am an OptionStack subscriber and could backtest your ideas over the period of April 2011- present day.
If you’re interested, let me know what the exact trade rules should be on this and I’ll see what I can do in OptionStack.
Always looking for new ideas to backtest and maybe this would help confirm your spreadsheet backtesting?
September 6, 2019 @ 11:32 am
Hi Pushpaw, thanks for the offer! I believe I heard that the basic flaw in this backtest software is an inability to compound the gains. So as the account gets bigger would it continue to scale up the number of contracts?
Let’s try a simple experiment
– When VIX is under 17.5 Open 45 DTE trade at 16 Delta/14 Delta and close if it hits 50% or 28 days.
—The position size should be max 3% of Portfolio size
– When VIX is over 17.5 open 2 DTE Expiration trade at 5 Delta/4 Delta
—Position size should be max 33% of Position size (as funds allow).
Do you think that would be easy enough to program?
September 6, 2019 @ 1:38 pm
hi Jeff, actually OptionStack supports portfolio level testing and does Indeed compound returns and select number of contracts based on margin/buying power as account size increases. Ill see what I can do!
September 8, 2019 @ 12:50 am
Hi Jeff – I ran some backtests. Hopefully it’s all not too confusing. Results can be viewed at this GoogleDrive link:
And the folder containing all the trade logs etc is here:
Basically, I ran the test on both SPY and SPX/SPXW.
SPY would not execute the Friday trades with monday expiration, so ran also on SPX/SPXW as those trades work on SPXW.
However, had to overcome some data anomalies in SPX/SPXW so ran the backtest in two parts.
Unfortunately, the results weren’t so great. It all worked well until 2018 mini-crash, when it pretty much lost all gains. On SPX (which, remember was executing the Friday trades that were skipped by SPY) it ended with negative return.
I did a modified version of the strategy that has the 2 DTE trades at 16/14 delta the same as the 45 DTE trades. This substantially altered the outcome by adding much needed credit and reducing risk on these very risky 33% allocation trades. This version beat the market by the end on both SPY and SPX, returning over 100% in both.
I did a “Pushpaw” version of the strategy as well at 10-20 delta for all set ups. This one returned triple what the other modified version returned.
I think there’s a good strategy here, but I do think it needs optimizing/tweaking as it’s at risk of tanking seriously and wiping out an account given the 33% allocation trades.
Do you have access to an options backtester? If it can save you from wiping out your account down the road, it’s a worthwhile investment.
September 8, 2019 @ 11:28 am
Pushpaw, thanks so much for taking the time to do this for me, I really appreciate it! I have a somewhat busy Sunday schedule today, but I will take some time over the next few days to review and the trades and compare to the spreadsheet I made during those times and see what either I’m missing or what assumptions I did not give to you.
One thing that I know I did some of on my spreadsheet back-test was if a 28 day trade was losing by enough I would not close it and let it ride, usually to expiration, while this was a manual and tedious process it cut several of those losses down.
The biggest risk of big loss is certainly the 2 DTE trades when there is a big move. I’m really interested in seeing the 10-20 version as well as the 16/14 2 DTE versions, are they included in the Google folder? I should probably just check, but I’m about to start frying 9 lbs of Carnitas and that will take awhile 😉
I really may need to invest in this software. As the amount investing has grown I am at greater risk of losing a larger chunk.
September 8, 2019 @ 11:52 am
No problem Jeff. I get a lot from backtesting other people’s strategies too, so it’s a pleasure.
I did some addition tests this morning, modifying the allocations on the 10-20 delta version.
So, the best I came up with is to do the following:
On the low VIX trade, allocate it at 5% AND also allow up to 6 positions to be open at a time (for total allocation of 30%). However, the strategy waits at least 5 calendar days between entries, aiming to achieve an “averaging in” effect. The exit rule is 50% profit. The rationale for upping the allocation on the low VIX trades was that low volatility is actually a good time to sell put credit spreads because it means SPX is going up.
On the high VIX trades, allocate them at 20% instead of 33%.
The result was a 2800% return on SPX/SPXW, though the sharpe ratio was low.
I ran this same scenario with the 33% allocation on the high VIX trades and the return was still decent at 1300%, but lowering the high VIX trade allocation seemed to help optimize this strategy during the backtest period.
And yes, you’ll find all the tests in the first link, which is a GoogleDocs document that I pasted all the screenshots in.
The other link is to the folder, which contains all the trade logs etc, though I would look first at the document with the screenshots.
Regarding your spreadsheets – are you able to use Delta in these? I thought I read that you use % below market price? That could be one difference. Delta takes volatility into account, so there’s actually no need to go down to 5 delta on a high volatility trade because 20 delta will be further from the market if volatility is high.
September 8, 2019 @ 6:39 pm
sheesh…a 29x return…not too shabby brother! 🙂
I did not use delta, because I did not have them available at the time. I use a semi-sliding scale based on VIX that as VIX goes up I move farther out. So for instance during August my average 2 DTE trade was 2.75%-4.25% away from ATM and that made a range of 3-5 Delta for those trades.
For testing I think I told you 5 delta and 4 delta for the trades, I wonder if a slightly larger spread would do anything, like 5 delta to 2 delta?
I have to get the kids ready to go to the youth Mass, so I’ll take a look at your 10-20 delta plan…pretty exciting!
September 8, 2019 @ 11:50 pm
Jeff – after going through the data on that 2800% return, turns out it was yet another data anomaly. It “sold” a put at the price of the strike itself. As in, it sold a 1500 put at 1500 credit per contract. After running it again a couple times, the actual return acheived by this setup is more around 300-400%. Really gotta watch that data…yeesh. I removed this screenshot from the Google Docs document since it’s basically bogus.
September 8, 2019 @ 5:10 pm
So I started looking at this and something just did not make any sense at all and that is those big drops around April of 2018…they would not have happened in real life. Look at the trade and you’ll see what I mean on row 484 and 485 of the SPX 2015-2019 file. on 4-25-2018 is has you selling to open 46 shares at $1.00 but the buy to open to complete the spread is at $7.50, so this creates a huge Debit spread which would never have happened if actually placing a trade.
I noted another strange one. At expiration it has the long put closing out for a $2.45 profit but it should have closed out worthless. (4-11-2018 row 479).
2018 was choppy in February and again in October through December, but this strategy never would have lost money in April which is why I dived into the data…but somethings is wrong here.
A side question, when closing at expiration do the trades include a commission to close or are they at $0.00? What is the commission rate per contract otherwise or does this software not support commission rates?
I’ll keep looking but these two simple errors makes be doubt the veracity of much of the rest of this.
September 8, 2019 @ 6:09 pm
Yeah, that’s a clear error in the data. It’s also present in the SPY data. I ran it on both SPX and SPY in order to avoid an error like that, but clearly it didn’t.
This is a problem across the board with options backtesters. The data has errors. The sheer quantity of data involved in option chains makes it all but inevitable. We’re also talking about data around the 5/4 delta mark. The far OTM data can contain errors at times.
Apologies for missing that one. I should have checked given the big drop there. It was pretty late a night.
I get it if you think the whole backtest is a crock. I’m going to rerun it and exclude that date on both tests and will post the result. Do with it what you will.
One thing I will offer is that I’m not sure this anomaly changes the possibility that using a higher delta on the high vol trades would improve the strategy. Or that allocating more trades/percent of account to the low vol trades would also improve the strategy. But that’s just my own thoughts – you may disagree.
September 8, 2019 @ 6:28 pm
Hi Pushpaw, I spent some more time reviewing the rest of the data and I think it is pretty solid other than a few of these issues. I think it just sows that even if I do go through and back-test I’ll still have to do a pretty solid manual review to account for any relics of far OTM pricing.
My own testing absolutely says that you are correct on the 2DTE trades, that a higher Delta will return higher rewards…but oh man does it scare the crap out of me! 🙂 I think that if you can stomach the loss of capital that you can certainly do better. It all comes down to both managing risk as well as managing one’s own risk tolerance (or the perception of that risk really).
I’m seriously thankful fro what you’re doing here it is really both vindicating and giving me a little something extra to look at and consider.
September 8, 2019 @ 7:44 pm
By the way, the answer to your question about commissions is OptionStack does not account for them and does not have the option to in its visual editor. I think you can if you use the scala editor, which is basically coding.
Especially on the SPY backtests, where some of the spreads at 5 delta are only a couple of cents wide, commissions would be an issue and undoubtedly eat away the profits. SPX would be better given the higher leverage. But commissions are an issue for sure in any option strategy and can eat anywhere from 100%+ to less than 5% of profits. I have a spreadsheet I use to determine my ideal spread width and credit in order to keep at least 70% of my profits (at 50% profit targets, which I tend to use). On SPX trades, I usually keep upwards of 90% of my profits.
September 8, 2019 @ 11:46 pm
I retested the SPY and SPX with high VIX trades at 4-7 delta for short leg, allowing backtester to select long delta. This avoided the same data issue as before in April 2018.
You can find the screenshots in the original link: https://docs.google.com/document/d/1nOuBuyBKzvhXzPiz_SSkRCNAiG6Vne6OyeQa10-tnlU/edit?usp=sharing
Transaction logs in general folder here labelled as retests:
The results were much better this time:
83% for the SPY test and 73% for the SPX test (which also runs a bit shorter).
I didn’t notice any glaring data anomalies, though that’s not to say there are none at all. I didn’t go through all the data.
My main observation about the very low delta trades is that I personally would be unable to trade them because the commissions at Interactive Brokers (Canada) would eat most of my profits. They simply don’t take in enough credit.
June 17, 2019 @ 6:56 pm
Another thought just occurred to me…Does this calculator take into account the compounding of profits? After downloading the Strategy Returns for the 16D-10D spread, it was interesting to see that the Max number of Trades open at any one time seem to max out at 44. I would have expected to see the number of contracts increasing as the value of the account grew.
June 17, 2019 @ 9:14 pm
There are two things at play: trade mechanics and capital allocation.
The trade mechanics says to open a new trade daily and hold till expiration. Done systematically, that will generate a backlog of about 44 trades.
Capital allocation is NOT considered when the backtests are executed in ORATS. What we’re seeing is theoretical results in this regard. The practicality of the max concurrent trades is a manual evaluation that has to be performed after looking a the data. OptionStack has the ability to limit concurrent trades to a capital/margin ceiling, which is a great feature.
In practice the number of concurrent trades a portfolio can support will decrease if portfolio growth is less than the underlying. The increased margin required for a higher-valued SPY underlying is being chased by a portfolio of capital that hasn’t grown as much. If the portfolio outperforms the underlying then the # of concurrent contracts can increase.
June 17, 2019 @ 11:57 pm
That all makes sense. I think that the real power of the shorter DTE is when you can start opening extra positions because the value of the account is going up very fast in a short period of time. I think Einstein said that there is no force on earth more powerful than compound interest! 😉
June 18, 2019 @ 2:04 pm
Nice write-up. One thing I don’t understand: why did you use 16D/5D in your conclusion rather than 30D/10D? (“implement the 16D/5D strategy on an existing SPY portfolio”). Does this spread width not scale as easily, or is it about maximum drawdown?
June 18, 2019 @ 2:26 pm
Thanks and welcome back!
The 30D/x strategies had rough risk-adjusted returns.
10D/5D was optimal when ignoring capital allocation ceilings (i.e. less capital efficient than others but has best risk adjusted return). The 16D/5D had second best risk adjusted return and required 20% less capital and less than half the contracts of 10D/5D to yield nearly identical results.
June 19, 2019 @ 11:21 am
So what’s next?
I can think of a few things:
– replicate BXMD with commissions (& taxes, if possible).
– figure out where the sweet spot is for taking profits balancing risk and commissions. Something finer grained than 50%/75%/expiration, like maybe 60% is actually the best.
– try other deltas that might not be obvious, e.g. ITM
– since 30d-10d had the highest returns, what does 40d-20-d etc do (i.e. go riskier), although I think you did something like this in your first posts.
– replicate Jeff’s 28DTE/2DTE strategy
So exciting! I feel like there’s a giant “what are your actual returns” hole in all of the resources I’ve been absorbing (r/options for one, but also OptionAlpha and Options Bootcamp).
As for the forums, where are the other folks interested in this stuff? r/options has a few posts that ask for data, but the answers are pretty lacking. Is everyone in one of the paid forums on OptionAlpha, etc?
June 19, 2019 @ 12:04 pm
JEI, sounds like our experiences are the same over at r/options. I speculate that a lot of people who have found something that works really well don’t like talking about it and “giving away their secret”. I know that I felt the same way myself as was finishing the manual backtesting for the 28/2 DTE hybrid (or “Revolver” just because I wanted to give it a cool name ;))
I’ll see if I can post a link to an image of the Back-test results that I ran.
One thing I’m seeing in the results for the vertical spread that can improve results drastically for smaller accounts is the width of the strikes for the spread:
One spread that is 16 Delta to 5 Delta is about 160 points right now. Comparing the premuim (and commission) on a 10 point width spread means that at 16 contracts, you’d pocket about 40% more total premium than the 160 width. There is obviously a practical limit to how many contracts you can open at $1000 per position though. You’d have a lot of trouble getting filled at 100 contracts for instance.
June 19, 2019 @ 12:30 pm
This shows each year’s return for SPX (with Dividend), 2-DTE only trades, 28-Day only trade, and then my hybrid. These results take into account letting the larger 28-Revolver losers ride until the market recovers. the 2-Day trades are all at 10 strike width/50 points and the 28-Day trades are all 3 strikes.
above 1000 a strike is 5 points. between 600-1000 a strike is estimated at 2.5. below 600 a strike is estimated at 1 point.
Again this was all manual, so while not perfect, it is directionally right.
June 20, 2019 @ 3:07 pm
Holy cow, I’m not sure I can believe those numbers. One year was almost 400%? Once I finish moving and have some time free up, I’ll have to learn how to do my own backtesting.
So summarized, the Revolver is:
when VIX > 17.5, PUT spreads 2DTE @16D with 3 strike widths, ride to expiration
when VIX 30, PUT spreads 90DTE @ATM width ?, manage @50%
when VIX >16 <17.5, PUT spreads 8DTE @?D width ?
when VIX <= 16, PUT spreads 45DTE @16D with 10 strike widths
In any case, I think this means I should abandon all other strategies ASAP, except in my IRAs.
June 20, 2019 @ 3:21 pm
I agree that it looks unbelievable. Remember that before 2016 there were no Monday and Wednesday expirations which would cut out 2/3 of the gains you see in years previous to that. Those years did have VERY elevated VIX though and it was through cycling your money quickly at high premiums and compounding the number of positions/amount of capital at risk that they would have delivered this kind of result.
I highly suggest to start out small and grow slowly. PLEASE do your own back-testing and see what makes you comfortable.
The width of the strikes is really whatever you want, but I recommend keeping them relatively tight (2-10 strike width).
I’ll post try to post the guidelines I wrote up in a Google Sheet that I use to mechanically follow the program regardless of my emotions at the time. I am actually really excited about using this method in my Roth IRA as the growth will come out tax free (in about 16 years when I am 59.5 years old).
June 20, 2019 @ 3:29 pm
This was a formatting disaster so I re-wrote much of it. Hope this works.
VIX below 14 sell 40-72 DTE 4% below ATM – Close after 28 days
VIX below 17.5 sell 40-72 DTE 6% below ATM – Close after 28 days
VIX below 20 Sell 2 trading DTE 2.7% below ATM allow to expire.
VIX below 24 sell 2 Trading DTE 3.25% below ATM allow to expire.
VIX below 30 sell 2 Trading DTE 4.5% below ATM Allow to expire.
See below for more details
1 Review the VIX
2 Determine Tactic (28-Revolver, 9-Revolver, or 2-Revolver)
3 For each account Determine if it is time to place a trade
a. For small accounts – if 2-Revolver cut the time inbetween trades in half
b. For Large accounts – Multiply the number of contracts by the specified Contract Multiplier at the specified Strike Prices unless carrying losses, then reduce.
4 Write Put Credit spread two strikes wide until using 10 contracts a day or more, Then widen spread. 2-Revolver spread should be ~3x wider.
5 Close any 28-Revolver trades from 4 weeks ago
Write Put Credit Spreads at appropriate distance below ATM price (4% for VIX between 0-14)
2 STRIKES WIDE – Only invest in the Monthlies Sell Contracts 40 – 72 DTE
Close out after 4 weeks – Put one on, take one off.
During periods of Ultra High Volatility (VIX>30) add supplemental long duration trades when stock is at 2 week low.
Supplemental trades are usually 5-6 normal strikes wide (25-30 dollars) and should be put on at double the normal contract count
If a loss is over $500 per 3-strike contract, let it ride until Index is over the Strike price, then sell
Invest no more than 60% of your capital at any one time, this will give you the available cash to handle losses and the High Volatility periods
If VIX is high (20.5-30) Run 2-Revover
Only trade 2 DTE Credit Spreads on Monday close/Tuesday Open, Wednesday Close/Thursday Open, and Thursday Close/Friday Open.
only use the weeklies for 2-Revolver, Not the Monthlies. Use a 3.3X width on the spread
Initially increase the number of 28-Revolver contracts by 1.5X If less than 60% of Capital is invested, the Multiply by 3.0X
Allow to expire worthless to save on Commission and if still in High VIX environment, Revolve your money into another 2-Revolver trade
This is the most gut wrenching part of this whole strategy. Follow the program and over long periods of time the program will win mightily.
– If a 2 Revolver trade is a big loser, try to close early in the day on Expiration day. Even if deep in the money it may cost less to Close than to leave open to expiration and take a full loss. Loss mitigation is really limited with 2-Revolver because of the short window.
– If a 28-Revolver trade is losing more than $333 net of the premium you took in (2-strike Width), let it ride until the SPX has risen above the Strike price. This has historically limited losses to ~$250 for a 3-strike width spread
June 27, 2019 @ 12:47 pm
Hope you had a good camping trip… It feels like everything I have read points to using at least the .15 deltas, because the premium isn’t enough to cover a loss below that level. You’re using @4% and @6% above, which is more like the .10 delta level (at least today, with VIX around 16). I’m curious what the results would look like if you used the .15 or .30 deltas for all the trades, whether 2-day or 28-day.
June 28, 2019 @ 10:04 am
Hi JEI, Camping in Big Bear was really good, we then drove to Utah and have been hiking Zion’s and Bryce Canyon National parks (which were incredible, especially Bryce!)
When I built my model and backtested it, I did not have historical Delta nor POP% so all I did was figure out what % of the SPX I needed to move to have a good result. It took TONS of number crunching and manual testing the various price levels, so I don’t doubt at all that there might be something that would make more money. This is why I’ve been bugging Spintwig so much about the backtest tools that he uses.
I think though there may be some confusion about the percentages I use though so I’ll try to explain better than I did previously using an example.
As I write this, The VIX is at 16.06 and SPX is at 2930.
-Using my Grid I’d know that this means I’m going to find an expiration that is 40-72 days out on the monthlies (Aug 16th) and plan to close it exactly 4 weeks from now.
-Since VIX is over 14 I’ll chose a strike price that is 6% below the current SPX price. So 2930 x 0.94 = 2755.
-Right now this is at 17 Delta and about 19% chance ITM I’d buy insurance 2 strikes below that at 2745 for a credit of $115. My 26 years of daily market moves tells me that at this VIX range, the market has only closed below this price 3.82% of the time, so I feel FAR safer than the 19% ITM that I see.
All the percentages that I use are about strike price selection being the distance from the current stock price. When placing 28-Revolver trades, I see Deltas between 17 and 19 for my Strike price selection and when it moves to 2-Revolver, I see it around 5-7 Delta based on those percentage moves from the Underlying’s current price.
I hope that helps. Let me know if you have any other questions! 🙂
July 25, 2019 @ 9:20 am
The Revolver seems interesting, Jeff. Why would you argue it not to be overfit?
July 26, 2019 @ 12:19 pm
I had the same thoughts, it looks incredibly overfit. Tons of parameters, very little justification for some of the weirdness (e.g. how was exactly 2.7% below ATM determined?). At least manually backtesting makes it hard to test a huge number of possible parameters, but still it looks to me like the parameters were massaged several times to avoid large drawdowns in idiosyncratic ways.
July 27, 2019 @ 4:52 pm
I agree with both you and Mark, it is very much over fit to the data. 2.7% was figured out by trying to get to a roughly 98%+ win rate historically, at that VIX level, 2.7 was how far out to go. I think I’m still struggling with the weirdness frankly which is why I’m talking about it and trying to get better back testing. Generally it seems that as the VIX rises, the trade duration should get shorter to reduce the risk of loss. Pricing gets better and allows for a faster revolution of your capital. That’s the best I have come up with frankly. I’m running it for several months now and it certainly seems to be working, but only time will tell.
July 29, 2019 @ 12:55 pm
Personally, I could never trade an overfit system. Of course the historical numbers are going to look great, and consensus is that future, live performance is likely to be [much?] worse.
I would give some thought toward what you can do with your backtesting to avoid overfitting.
July 29, 2019 @ 3:19 pm
I’ve been thinking about this a lot this weekend. If you look at the discovery process that I went through, I’d say that the concepts that I’m seeing in the data are actually fairly simple.
1) When VIX is low trade like Spintwig (sell 45 DTE and close about a month later)
2) When VIX is high trade like BigERN (sell 2 DTE and let expire)
3) within these two tactics, trade farther away from ATM the higher the VIX goes.
Spintwig ran a side by side comparison of pros and cons for each system, I think I’m just putting the two together where they both perform the best. I arrived at this point through my own analysis and was happy to see that there are similar strategies being employed
I will grant that the strategy emerged from the data and that has always concerned me, but I do believe that the premise is sound.
July 30, 2019 @ 8:13 am
For those of us evaluating the process, your methodology is flawed (overfit).
If your backtesting in combination with live-trading experience has given you the necessary confidence to execute and stick with the system through ordinary drawdowns, then you are all set.
I think it often comes down to the trader vs. the outsider. Traders will trade–quite often in ways that include discretion (vs. systematic guidelines). Outsiders should be critical in their evaluation to make sure they’re not being deceived–something that happens way too often in this domain. One who promotes a discretionary approach is not necessarily trying to deceive even though this may not be sufficient to sway those on the outside.
Will either the discretionary or systematic trader be profitable long-term? That is an entirely different question.
June 20, 2019 @ 3:30 pm
I’m about to leave with the family to go camping so I’ll not be able to reply much for the next 9 days. Happy trading everyone!
July 30, 2019 @ 2:11 pm
Mark, you make very good points. I have put an enormous amount of time into the backtesting that I could do manually and then trying to understand the results. What I presented here was certainly not an exhaustive description of all the “why”s behind the method, more just what the method was. I think what the challenge that I’m seeing is that my backtesting of put credit spreads (with nearly any methodology) beats an SPY buy and hold, but we see in the back-testing in the post than NONE of them do, and I find that hard to believe.
I’ll also say that every systematic investing strategy is fit to the data. there are not so many parameters in what I am doing that I would say it is overly fit despite my early concerns that it was. I’ve been through a small drawdown May 7th through June 3rd and the system performed very well. So to your point, I’m certainly comfortable with it. I’m not trying to necessarily convince others to use my method.
If folks are interested in it I have no problem sharing my results at time rolls on. Looking just at my Roth IRA account since May 1st the SPX is up 2.14% and my account is up 13.28%. Even if I run worse than that over the next few months, I’m pretty happy beating the S&P.
I really appreciate the discussion. The more I can analyze what I am doing and challenging the why’s behind it, the better prepared I’ll be. Thanks!
July 30, 2019 @ 5:52 pm
Always pleased to follow your results and to follow the discussion on spintwig’s backtests.
Like you, I find it difficult to accept that just dropping the whole options thing and investing in SPY is the best strategy.
Following my discovery of ERN’s site and then spintwig’s work, I started selling a few 2 day SPX credit spreads, 3 times a week. I aimed for 5 delta for my short put and varied the long put from 25 points to 10 points below (a learning period). I started with only 3 contracts and have been as high as 20 contracts, but I never exceeded $30,000 at risk.
Over this very benign, low volatility period I’m only getting about 1.5% below the index with my short put.
Starting on June 7th, I’ve completed 22 trades and made just over $12,000 profit. This is real trading. I aim for the mid price on selling the spreads and drop 5 cents if necessary. Interactive Brokers take between 8% and 3% of the trade depending on delta/volatility/no. of trades etc.
Of course, one decent down day will take the whole $30,000…
Because of the low volatility, I just started to follow your idea and move to longer trades. In my case the 8 day trade where I can get about 3% below the index.
[I also continue with a 45 day trade as I have done for a decade or more].
A question: do you think 3 small concurrent 8 day trades (opened Mon, Wed, Fri) is better than a larger single weekly trade (say every Monday)?
Keep up the good work chaps!
July 30, 2019 @ 11:24 pm
1.5% scares me for 2 DTE trades. Looking at the VIX and the SPX tonight 13.94 and 3013.18 respectively, and comparing that to my database/spreadsheet, I see that when the VIX is between 12.94 and 14.94 Going 1.5% out on 2DTE trades wins 94.8% of the time (1000 days have fallen in that range over the last 26.5 years). Since it is Tuesday night I only have current pricing for 1 DTE and 3DTE available so I’ll look at the 3 day to walk you through how I adjust for risk.
3 DTE 1.5% out wins 91.5% of the time, so to get closest to 94.8% I have to move out to 1.9% from the current price of 3013.18 or a short put price of 2955. Putting the long put 20 points further at 2935 shows a price of $195 per contract. (That is actually really high from what I have seen over the last 3 months, I think that is because of the FOMC decision tomorrow.) At a 5.2% historical risk of loss ($2000) compared with a 94.8% chance of winning $195 ends up with a ratio of 4.49:1 dollars won vs lost.
If instead I move out to 2.75% away for my short put, I am at 2930 and long at 2910. This has a historical win of 98.5% at this VIX level. That does not seem like much of a difference. Price is significantly lower at only $75 per contract, so most of us would instinctively want to place the $195 trade. The problem is that doing the math shows me that the ratio of won dollars to lost dollars at 2.75% out is actually 6.07:1, which is ~33% better than moving out only 1.9%.
For me the name of the game is wealth preservation. so when John V asked where exactly the 2.7% came from in my example from several posts above…well it came form this kind of painstaking backtesting that allows me to limit risk while still gaining a very high compounded return. Moving too far out while still reducing losses tends to eat away at the premium too fast especially when accounting for commissions. For me, aiming for a 98.5% win rate has been the most comfortable, but the 94.8% win rate should return more dollars per transaction, but has a higher chance of loss.
Going further – the average loss for 3 DTE, 1.9% out is 43.3% meaning the average loss in this situation is not $2000 but only 43.3% of that, or $866. The average loss for the 2.75% out scenario is 40.75% or $815 so that also factors into the ratios I look at above.
To answer your question about spreading your trades out or doing them once a week, I’m a big fan of doing trades every day. this allows those positions to move up or down with the market and further reduce risk of any single loss wiping out a significant percentage of my account. I have started very small initially. I have steadily moved from the 20K I started investing up to a total of only 120K today. At any one time I will not have more than 60% at risk while the VIX is less than 17.5 (when I do 45 DTE close after 28 days). When I start making 2 DTE trades my backtesting indicates to do no more than 33% max per trade. I also only trade 2 DTE on Monday, Wed, Thursday. This helps prevent the risk of a sequence loss where you could lose two days in a row and blow up your account.
That’s a whole lot. if you want you can contact me via email if you want more info and not tie up Spintwig’s blog. jeff.c.jewell at gmail.com
July 31, 2019 @ 8:40 am
Thanks for the detailed answers.
I hope spintwig steps in if he thinks we are hogging his website, but I’d like to continue here as others may have good input or, like me, may learn a lot.
Can you explain your calculation for the ratio of dollars won to dollars lost? I’ve tried everything I can think of but can’t match your figures.
I agree about 1.5% being too close to the index. The 8 days figure of 3% feels a lot more comfortable. 9% on a 45 day trade, even more so… The problem with the 45 day trade is when the market moves against you and your losses balloon – do you sit tight or close the position?
Thanks for the comment on spreading out the 8 day trades. Confirms my feelings.
July 31, 2019 @ 11:46 am
Please, keep the conversation going here. It’s edifying for me as well as other readers.
July 31, 2019 @ 11:52 am
No problem, Stephen. I’ll try to detail the math that I use to adjust for risk.
Using the 3DTE 1.9% below current price with the $195 premium at 20 points spread
Of the 1000 times that the VIX was between 12.94 and 14.94 over the last 26 years, you would have won 948 times. $195-$2.5 commission = $192.5 x 948 wins = $182,490
(On the losses I actually found a small error that overstated losses by about 14% in my last post)
You would have lost 52 times. The average of those losses (penetration into your credit spread) was 43.3% or an average loss of $866. Subtracting the net premium received from the loss gives $673.5 per loss x 52 losses = ($35017)
The Ratio is merely showing $182490 total win/ ($35017) = 5.21:1 Ratio. This is totally dependent on current trade pricing, but allows me to assess risk and adjust for that.
With the fixed formula going 2.75% out is 6.41:1, so only 23% better than the 1.9% out. Going farther out will improve the ratio, but at a slower pace.
I look at what I am doing as “providing a niche financial insurance product”. As an insurance provider, I have to adjust for risk using data on the occurrences of payouts. There is no perfect ratio, but rather a comfort level for the individual placing the trades.
Based on our conversation I went ahead and placed that 3 DTE (Expires Friday 8/2), 2.75% out trade this morning for $75 per contract. 🙂
July 31, 2019 @ 1:06 pm
Ah…I also forgot to answer your question about the 45DTE trade when it goes against me.
So, when I get to 28 days from placing the trade and I’m looking to close, I will close at a loss for any that is less than 1/3 of my max loss. So if I had a Credit Spread that was 15 points wide for a $1500 max loss, I would close any position that had a loss of less than $500. If it is greater than $500 I let it ride until the current price of the SPX is higher than my short put strike price. Looking at this over the last 26 years there are often points where the day you are supposed to close out for a huge loss is the day the market is at the bottom and it bounces up for a few days and you settle out at less than ½ of the loss.
July 31, 2019 @ 10:52 pm
So Stephen, did you place any trades this afternoon when the VIX spiked following Powell’s comments? I managed to get 3 trades in expiring this Friday with great pricing!
August 1, 2019 @ 3:58 am
I opened my regular Wednesday weekly spread.
I sold the 2860/2845 expiring on Aug 07 for $0.40. So a potential 2.55% over the next 7 days (and 2 other concurrent trades, of course).
In selecting this trade, I moved further from the market (4%) whilst maintaining a delta of about 5, rather than trying to cash in closer to the market.
I didn’t make any adjustment due to the VIX spike – trying to interpret ongoing financial information is not my thing… Perhaps I should pay more attention!
August 1, 2019 @ 5:51 pm
With the Spikes in VIX the last two days, I have put in a total of ~33% of my accounts into 2 DTE trades, most of them expiring end of day Friday the 2nd. the closest to ATM is currently 0.80% away which historically has an 84.12% chance of expiring worthless. Most of the trades are between 1.64% to 3.00% away from the ATM price. Historically the 1.64% expires worthless 96.11% of the time. at 3% it is 99.68%.
My spreadsheet calculator allowed me to have some pretty solid confidence in the risk levels associated with each trade. I’ll update my results end of day Friday with a screenshot of my trading log so anyone who is interested can take a look.
It has certainly been a wild ride though. Exciting and somewhat scary as well. My typical trade was 2 contracts with a 20 point spread. the pricing was ALL OVER THE PLACE with Premium from $70 up to $100 per contract. If the SPX closes above 2930 Friday, the return on the capital risked will be 3.53% for 2DTE trades. That makes a ridiculous annualized percentage.
Wish me luck, lads!
August 1, 2019 @ 6:14 pm
What a nail biter Jeff! How many different positions do you have your 33% in? I can’t imagine having $40k of risk all dependent on what the president tweets over the next 36 hours.
For the longer DTE trades, are you ever tempted to take earnings off the table early? I’ve been conditioned to take trades off at 50%, and so far I’ve had a really high win rate, but if I do that with this system it will mess with my daily allocation %, and probably won’t help the win rate enough to be worth it.
When you were doing your initial calculations, did you calculate risk/reward for options closer in with lower win rates? Having a delta as small as what your percentages suggest means that when you do lose on that 4% of trades, it will really hurt relative to the premium.
Good luck tomorrow.
August 1, 2019 @ 8:15 pm
Weird, I cant seem to reply directly to JEI, Stephen or my post about the spikes in the VIX the last two days. Maybe there is a limit to how many levels down the replies can go?
JEI, I do take earnings early on the longer trades. I agree with the concern about taking profits at 50% reduces your capital allocation. So I only take profits at 70% – this number is still an experiment frankly. At the end of July I closed out about 20% of my open positions because they got to that 70% level.
I do calculate multiple distances from the underlying current price. While moving closer can result in significantly higher net cash numbers, I really, REALLY, don’t like losing money so I move out to where the numbers indicate a really high ratio of winning dollars compared to losing dollars
Since I trade credit spreads, the chance of losing is multiplied by the average of the losses based on how wide the strikes are. So a max loss can easily be 15-20x bigger than the premium, but the average loss historically is usually only 8-12x. That’s also why I move relatively far away rather than move in closer, I aim for 20-25x more wins than losses to make sure I net a profit even after a black swan event
As far as my reaction to presidential tweets…the uncertainty they cause is what sends the VIX up…that makes pricing far better and gives me a chance to make really crazy outsided gains. Hell, there is risk in options trades even when he is not tweeting, so you’ll never get away from risk. I find myself being more excited by what is happening than fearful.
August 2, 2019 @ 8:54 pm
Well Gentlemen…I got lucky. more lucky than I deserve to be actually. I broke a rule that I have heard in a couple of places “don’t chase pricing, follow your strategy” Attached you’ll see a snippet of my log and the yellow highlighted cells show that I was trading 2 DTE contracts below 17.5 which I’m not supposed to do. I should have waited and loaded up at the end of the day instead of trying to catch a falling knife and placing 2DTE trades until the VIX got to 17.5.
Having said all of that I did not lose any money…in fact, I made 997.5 on a max loss of just under $28K. In the last 5 minutes I went from losing on two trades to locking in all the profit – WHEW!
I have quite a few trades that expire Monday and I’m in the same boat there. a couple of trades I placed when the VIX was too low and those I’m pretty worried about. the others that I placed when the VIX was over 17.5, I have zero concern about. There is about $1500 profit that I may lock in on Monday if the market closes above 2935 so we’ll see what happens.
I’ll post another snippet of my log on Monday night and we’ll see how I did!
August 3, 2019 @ 12:33 pm
Those trades under 17.5 were much closer in, < 1%. I can't remember, were your backtests using only the closing prices? One potential difference here is that you're laddering into these positions, so even if you've got 30% of your account at risk, odds are only a few of your trades will go against you. If you lost one or two of those, you would potentially make up the losses with another 3 or 4 high IV days, although I personally don't know if I'd have the guts for it.
August 3, 2019 @ 10:28 pm
JEI, you make really good points about laddering in and you’re correct, my backtesting is based on closing values. I’m not sure what you’re looking at about the trades where VIX was less than 17.5 though. Looking at the first one, I when I opened the short put, the SPX was at 3011 and the put was opened at 2930 which is 2.69% lower. Now at CLOSE the SPX was only 7 hundredth of one percent above my strike, but upon opening it was much further out. Again, had I just awaited a VIX that was higher than 17, even if I had put my full amount in a single transaction, I’d not be worried at all.
Certainly was a nail-biter, but like I said, I learned my lesson and at least Friday it was not painful just stressful 🙂
August 6, 2019 @ 12:59 am
I think we bumped against the “10 levels deep” comment ceiling. No worries, this seems to be working just fine 🙂
Been busy elsewhere but have been following along behind the scenes; what a nail biter it was! I was looking at the SPX on Friday trying to figure out if you came out profitable. Congrats on the win!
As for the positions expiring on 8/6, did those have enough runway or did they close unfavorable?
I got the itch and opened a short SPX on Thursday when I saw the VIX break 17.5 – that’s my trigger for bigger trades, too (need to crunch the numbers on profitability of VIX contraction [as opposed to theta decay] vs long SPY, but that’s another post). 44 DTE @ 2685; 9.5% OTM / 10.7 delta. I’m currently underwater but it’s early and I still have another 6% of downside runway available.
Meanwhile, opened another short SPX @ 2500; 12.5% OTM / 10.7 delta today – VIX was at 23.98 – and closed it after about 25 minutes for a $106 gain (7% max profit).
August 6, 2019 @ 12:54 pm
I didn’t do so well — I had a 2865-2875 spread that I was assigned on. That one I put on too early — I saw the VIX go up over 17.5 last Wed mid-day and jumped the gun. I had another 2840-2850 that I was able to roll to next week, so we’ll see if this market stabilizes. Maybe I can get out early on that one.
August 6, 2019 @ 1:39 pm
Yesterday was bad for me, too!
My 2925/2915 cost me my entire winnings for the previous 23 trades…
August 6, 2019 @ 9:56 pm
So Monday was pretty darn rough. I had 3 trades open that I placed below my 17.5 VIX threshold and all 3 lost. I had two other positions that took some loss that were placed correctly, but the losses were small enough that I would have just been flat for the last 3 days instead of down almost $14K or 10% loss of my total capital (should have only been about a 3% loss had I waited until VIX was over 17.5)
With Tuesday’s moves up, I currently have several very safe positions that expire Wednesday that will net $2512.50. What I have learned is to trust my program. While there have been arguments made that it is “overly fit” to the data…it would have been right. Looking that this big of a move in one day (2.98% drop) and comparing to the last 26 years, that has only happened 5 times while the VIX was below 23.5. So while my program aims for 98.5% success, this was a 0.7% occurrence that still would have had a small loss. The real benefit is how much we stand to make making short 2 DTE trades 3.25% below current price.
I traded this morning at open in all of my accounts for 2 DTE expiring Wednesday. I will not actually trade Wednesday at all. Thursday morning I will then open 2DTE positions expiring Friday giving them all day Thursday and all day Friday.
August 7, 2019 @ 3:52 am
No too bad!
Is it your normal routine to trade early on Tuesday, Thursday rather than Monday, Wednesday last thing? How do you trade the Monday closing trade?
August 7, 2019 @ 9:05 am
Hi Stephen, When the VIX is below 17.5 I trade every day. When it is above, I really try to only trade for full 2 days of trading, so end of the day Wednesday is fine for a Friday expiration, but Wednesday morning is not since that would be 3 days of trading for the price of the index to move around. As far as today specifically, I need the buying power that is locked up in my Wednesday trades to free up to place full positions for the Friday expiration. I will likely split my available BP between Friday Expiration (placed Thursday morning), and Monday Expiration, placed Friday Morning.
Waiting until the morning also allows overnight big price moves to occur. For instance if you traded Tuesday afternoon based off of yesterday’s close of 2881 you’d be pretty scared watching the futures market drop to 2846 as of 6 AM Pacific time. especially if you still had two full days to trade (for a fictional Thursday expiration) When Volatility is this high I think limiting exposure to overnight moves is a good idea 🙂
The other reason I trade in the morning is just a practical schedule one. Since I live in the Pacific timezone, I can place trades right at 7 AM before i leave for work. With my work schedule, I’m sometimes not available to trade in the last hour of the trading day since that is noon-1PM my time.
August 20, 2019 @ 10:40 am
I have an interesting situation.
On July, 23rd with the VIX around 12.6 I sold to open a 45 day vertical spread on the SPX as follows:
Sept06 2780/2750 for $1.45 ($1.42 net)
It was about 5 Delta, 8.1% OTM and the intention was to close after 28 days (today!) or when I had made 50% of the potential profit.
Needless to say this position has been through hell.
To buy it back now will cost $2.90 for a loss of about $145 per contract, instead of a gain of $142 per contract.
How about I let it run and it becomes a 17 day position 14 Delta, 4.4% OTM
Any thoughts appreciated (and, of course, do not represent financial advice).
August 20, 2019 @ 3:05 pm
Jeff’s the keeper of all the probability info. He reminds me of the RedSkyMarkets probability data, but Jeff’s is more useful 😎
My $.02 is to ride it till the end. The risk was already defined up front and the data suggests holding spreads till expiration has a higher Sharpe ratio on a lower-delta spreads. If aiming for peace of mind, create a limit order to close your position for roughly what you paid for it, allowing you to get out and break even if it’s possible.
August 20, 2019 @ 3:16 pm
Thanks for the reply. I will let it run a while at least.
Jeff replied to me directly (also suggesting to let it run), because he seems unable to reply here on your website (blocked as a suspected bot?). Maybe you could look in to that?
August 20, 2019 @ 3:22 pm
Yeah, we traded emails. I relaxed a few settings in the backend that should hopefully address the issue. Let me know via the contact form if you guys encounter any issues with posting. Sorry for the trouble!
Good luck on the trade.
August 20, 2019 @ 5:32 pm
I appreciate being seen as useful! Really it just makes me feel like an Actuary…but that’s fitting with how I see what I am doing as “providing a niche financial insurance product to retail investors” 🙂
Hoping this post comes through…
August 21, 2019 @ 2:14 pm
Speaking of Probability and Data…I’m looking to see if I can find Hourly SPX data going back as far as I can get it.
Does your back-testing software include that data in a database? Is there anyway to extract?
August 21, 2019 @ 10:48 pm
Oh my! I found a treasure trove of FREE data:
Has SPX data back to 2012 minute by minute…I’m going to write some formulas that sum up the hourly activity, then see if overlaying that with my other database shows me anything of interest.
August 22, 2019 @ 11:25 am
Nice find! Thanks for sharing. Let us know what you discover. I too downloaded some of the datasets. No immediate plans for them but I’m sure they’ll come in handy.
August 22, 2019 @ 12:28 pm
The backtesting software only has EOD pricing and I unfortunately can’t extract or otherwise access the data tables containing the raw pricing data.
September 3, 2019 @ 5:02 pm
So August is in the Books Gents!
I used this weekend to do a ton of analysis and roll numbers up.
Despite having the biggest loss of my Options trading carrier on August 5th, I ended the month with a gain of 3.04% of my total capital! As I mentioned back when it happening, I incurred $14K of losses but had I followed my program’s rules I would have only lost $4K that day. if that had not happened, I would have had 8.96% gain on capital for the Month.
I’m also going to make an adjustment to my business plan. During low VIX periods I will trade at 16 Delta as opposed to what I have experienced at the 19-22 Delta based on my trades. This move to 16 Delta does two things, it gives me much more room should the market go against me to allow contracts to expire worthless after 45 days, as well as closing at a net 50% gain, it will have fewer positions open and at risk when the next big move occurs. By doing that, I can move my money much more quickly into 2DTE trades and that will drive the rich profitability faster while making it easier to preserve my capital. Win-WIn!
September certainly has some risk and I will be closely monitoring my positions from July that expire Friday the 6th and Friday the 13th. Here’s hoping that I come out even better in September than I did in August!!!
September 4, 2019 @ 2:13 pm
Hi Fellas, I just got my commission rate lowered with TD Ameritrade! I sent them a note yesterday asking for a review and identifying that I have spent $1573 in commissions in the last 4 months with $751 in August alone. I was at $1.25 per contract and asked for a reduction to $0.75 (40% reduction) expecting to get $1 (20% reduction)…I got the 20% reduction!
If you have not asked for a reduction, it’s probably worth the ask.
September 5, 2019 @ 11:12 pm
Glad to hear August was a profitable month! Sounds like you made out well despite with the steep loss early on.
Great news on the commission reduction, too! Over what span of time did you accumulate $1573 in commission costs? Maybe it’s just me but that seems like a lot.
*opens trade log*
I spent $414.30 from Mar 1 through present on a final P/L of $4974 – 7.6% of revenue was spent on commissions. There were no trades placed in July.
I opened a few short puts on SPX last month with the intention to profit off vol crush (note: I stopped “regularly” trading and have only been dabbling when VIX is >17.5). Made a few bucks but the process was unnerving. One of these days I’ll do a study that compares opening short puts when VIX is elevated vs purchasing a comparable amount of underlying and see which one outperforms. The data suggests b/h is the winner relative to continuous option trading on SPY but I haven’t looked at only trades when VIX is elevated and observing the “crush” on long underlying.
On an unrelated note, been de-risking a tad due to FIRE. Went from 100% equities to 96% equities 4% cash (held at Vio Bank earning 2.52% – more than any gov’t bond is paying). Looking to offset sequence of returns risk by giving myself some runway. Leveraging the portfolio by implementing options strategies only amplifies SoRR so I have reason above and beyond the data to back off.
September 6, 2019 @ 11:39 am
The 1500 in commissions was from May 1 – August 30th. It may seem high, but looking at the dollars gained and the return on total account capital has beaten the S&P.
My Roth account where I stayed on target and ran my program saw a 35.67% account growth (net of commission) over that time where as the S&P was basically flat (down 0.76% if I remember correctly).
My practical experience does not indicate that buy/hold is better. It is certainly less risky, so it is better in that way for sure. It all depends on your goals and risk tolerance.
July 31, 2019 @ 11:51 am
Jeff, remind us again where / how you generated the POP data for “x” % OTM over a given DTE? I feel like you mentioned this before but I can’t find it. If it’s in another post just point us in the direction and I can put a link in your comment referencing it.
July 31, 2019 @ 12:58 pm
Just to clarify I do NOT use x% OTM, I use x% away from the current price of the SPX.
For the win percentage it’s pretty easy, I have a spreadsheet that I made which has the daily closing prices of the SPX and the VIX. Then based on 4 inputs
1) Trading Days to Expiration
2) Percent away from the current SPX price
3) Low VIX
4) High VIX
I get the rest of the information in the blue bar in the image below.
September 5, 2019 @ 9:56 pm
Anyone seen this backtester: https://www.turingtrader.org/category/showcases/
You kind of have to know how to code C# to use it, but it’s totally free. Oh, except you have to bring in your own data, so if you’re using option data you’d have to pay for that. Though TuringTrader has a way of using Black-Scholes to guestimate certain option data based on standard (and free) stock data (OHLC).
I imagine this thing would be up to backtesting something like the revolver strategy.
September 5, 2019 @ 11:24 pm
Yes! Good find. I stumbled onto that when I was determining which approach to take. It’s open-source, too, I believe.
To your point about needing some development skills, I find it funny many of the articles in the “Quick Start Guide” say “unfortunately, we didn’t write this article yet.” They then go on to talk about opening a project in Visual Studio *cringe*. Brings back nightmares of software development classes in undergrad and grad school. Doesn’t seem there’s any “quick” way to “start” the tool.
For what it’s worth, institutions / pros use splines to estimate option prices and solve for the vol smile. Didn’t dig through the docs to see if a framework for splines exists or if one would need to be built.
Anyone here a developer / enjoy coding?
September 6, 2019 @ 11:17 am
I’m a developer. I haven’t seen turingtrader, but I have been looking at quantiopian and quantconnect for developing strategies (and it seems like both of these have their own data). These both use Python, which is significantly easier to start out on.
I haven’t gotten very far (actually haven’t started), but there are some strategies I’m hoping to test out. For example, one idea I had was to use a momentum filter to choose a handful of stocks to sell ATM puts on. Logic-invest has a “Low Volatility Nasdaq 100” strategy that has a 24% 10yr CAGR. I backtested 6 months of selling ATM puts on the monthly 4 stocks, and it seemed to do well… but I don’t trust the results I got because I could have easily fat fingered something in ThinkOrSwim, and 6 months isn’t a long time.
Anyway, my priority is getting a better P&L tracking system. My spreadsheet is about to explode, and I’m afraid to add anything else. I’ve heard WingMan works pretty well, but I’d rather try to write something myself.
September 6, 2019 @ 10:53 pm
Interesting site – I’d never seen Logic-invest before. So you’re saying you would follow the picks in the Nasdaq 100 but sell puts on them instead of buying the stocks?
If you want, I could use on OptionStack I’d be happy to run a sample backtest of this put selling strategy that goes back to April 2011. I would need a basket of tickers and the “momentum indicator”, as well as DTE and any profit taking rules for the put selling.
June 19, 2019 @ 12:49 pm
I’m very early in the forum idea and haven’t yet done a thorough evaluation to get a good idea of what all is out there. Frankly, I’m thinking of just standing one up and letting it ride to see what happens. That being said, I’m floored to hear existing quantitive-research forums are behind paywalls. This isn’t magical trade-secret stuff, it’s empirical research anyone with enough motivation can perform on their own and draw similar conclusions.
The randomness of the market prevents optimizing beyond a certain resolution. For example, taking profits at 30% may have outperformed 25% one year but taking at 20% may have outperformed the next. Splitting the difference at 25% may have yielded a “good enough” or “viable” approach. the finer the resolution the more difficult it becomes attributing success to randomness (luck) vs strategy.
As for BXMD, I’ll need to do some research to understand why, but there’s a reason it’s not touted as the S&P500 replacement in all the FIRE blogs (other than the fact no product exists to track that index; people will have to execute the strategy on their own and eat the tax space is consumes). Heck, there’s a reason this strategy isn’t already wrapped up in an easy-to-buy ETF. If it was a SPY killer the ETF sponsor would make a killing. All the charts show outperformance over 25 years. Some quick googling turns up zero results for measuring its performance over the least decade. Hmm…
June 19, 2019 @ 1:24 pm
Spintwig, any chance you can re-run using the Short at 19 Delta and the Long at 17 Delta? I’m very curious on if that would improve returns due to the tighter spread generating more premium per dollar at risk.
June 19, 2019 @ 1:47 pm
And the source files.
SPY Vert Put Spread, 28 to 62 DTE closest to 45, open one trade daily from 2007-01-03 through 2019-06-18
19D/17D +/- 1.5 each leg, $1 commission to open each leg
Exit: hold till expiration
July 7, 2019 @ 1:15 am
Spintwig: I’ve been reading the posts here as time allows, and:
1) Like Jeff, I’m getting a great amount of enjoyment (and benefit) out of your data-driven approach to options. Kudos!
2) I’d certainly join a forum of the sort you’re describing. Having spent the last 5+ years working in Big Data and rubbing shoulders with data scientists on a regular basis has changed my outlook on a number of things – and considered from that perspective, options trading *without* serious back-testing seems like sheer lunacy.
I will note that my stats knowledge is of… non-recent vintage (and was sub-par even back then); as an ML/DS “mechanic” who generally implements stuff that others have thought up, I haven’t needed to dust it off. But playing with my own money is likely to get me cracking the books again.
July 8, 2019 @ 5:22 pm
Hi Ben, glad to hear you’re enjoying the material!
As for the forum, I’ve done some homework on selecting a platform but I’m not sure there are enough readers to avoid it being a ghost town for the near future.
I’m rusty too. It was my least favorite class in uni and I still try to avoid or workaround it where possible 🙂
July 25, 2019 @ 9:04 am
I applaud you for the time and effort here, Spintwig. I’m not sure what to take away from all this, though. Here are some comments.
1. I don’t understand the Slippage% calculation. Slippage is based on the mark. If you have 0% slippage then you get the midprice–not the market maker’s price. If you buy a 1.20/1.40 option for 1.35, then I guess I’d calculate Slippage% on the mark (0.05 / 1.30 * 100% = 3.8%).
2. In the “Preface” spreadsheet, I understand how you’re calculating Scale. How are you calculating ROC efficiency, though? I would just reiterate the impact of leverage here, too. While equal regarding gross risk, a scaled spread trade is not the same as a NP trade because the latter would lose 100% were the market to move to the long strike whereas the NP trade would lose only a fraction of that were the market to move the same amount.
3. I don’t understand how you’re calculating CAGR in both individual and scaled graphs. Are all these numbers based on an account with varying numbers of trades from one day to the next? Is the SPY account matched for that?
4. Moving down to the “Risk Management” section, I have never seen traders annualize ROI in a compound fashion (this may be the only way I’ve seen traders not exaggerate positive returns). I am strongly against calculating in this way (but I suppose that does not make it any less of a stylistic preference). To me, 1% over 30 days is 12% annualized [(365 / 30) * 1 = 12.2% if you were going to be particular about it]. 0.37% / 44 days = x% / 365 days.
5. I’m more confused by what you’re doing with the $9.70 NP profit. Average daily capital doesn’t matter: the brokerage is going to reduce your BP by $26,250 for the one day. This is, therefore, an annualized return of (9.70 / 26,250) * 365 * 100% = 13.5% (not 352%). For me, this boosts ROC by 4.4x (13.5% / 3.07%).
6. I think you had some typos in the next subsection and didn’t even report a final annualized return, but I’d say it should be $5.40 / $1000 * 365 = 197%.
7. I think you really got confused in the next section on commissions. You wrote “(9.9 / 15.1 – 1),” which is a negative number and not correct. Of much more importance, though, is the 100x multiplier that applies to option prices only–not commissions. $5.20 profit on the vertical is $520, which is $516 less commissions (not $1.20). Profit is cut by 0.77% (not 77%). For Trade 2, the gross proceeds are $350 and $4 should be subtracted from that. The result is not a losing trade.
8. Why are there crossed-out numbers (application output) in the “Replication” section?
9. Under “Scaling Strategies,” do the equity curves have matched notional risk on every trading day? In the tables, why does it say 43 max concurrent trades when in the “Portfolio Sizing” section above, you wrote “in a worst-case scenario the portfolio may see, on average, 35 concurrent positions” (and why did you write “average” there?)?
July 25, 2019 @ 11:59 am
Glad to have you back Mark!
Takeaway: systematically selling vertical put spreads does not outperform buy-and-hold SPY.
1. I’ll clarify that the % number is the percentile of the spread width, where 50% = midpoint and 100% = market maker’s price.
2. Great point! After publishing I realized I never spoke to the scaled losses 3 spreads would generate vs 1 naked put. I’ve been building a list of revisions / tweaks to the various studies and have been updating them as time permits. Short version goes: yes, 3 spreads would lose 3x more in an unfavorable trade until the underlying is below the strike of the spread’s long put. Nevertheless, the performance depicted takes this scaling into consideration re: P/L.
3. I’ll add a section highlighting the CAGR calculation. I’m using:
(end value / start value ) ^ ( 1 / ( calendar days in study / 365 ) ) -1
4. Tomato, potato 🙂
5. Agree on margin mechanics. However, from a risk perspective I argue duration of exposure is absolutely a factor. Having 26k exposed to downside risk for 44 days vs 2 days are very different risk propositions. This calculation accounts for the time exposure. Open to other approaches to measure for performance improvements due to reduced time exposure [risk].
6. Perhaps I’m overlooking. I see 54.69% listed as the annualized return (1+.054)^(365/44)-1. The 0.054 is 54 credit / 1000 capital at risk.
7. Good catch on the calculation. It needs to be 1 – ( 9.9 / 15.1 ). I have corrected in both trade examples. Correct outputs, typo in the display of the formulas.
Another good catch on the trade examples. I need to clarify these numbers are AFTER the 100x multiplier has been factored in. In other words, these are the actual dollar amounts hitting the account. There’s no way we could get $3,340 ($33.40) from selling a single 10D SPY put at a 132 strike on Jan 3 2007.
8. The answer is in the paragraph immediately below the image :). The several of the KPIs generated by ORATS are not accurate / not reproducible – a theme I’m finding across the automated backtest tools. The primary value in the automated tools appears to be limited to generating a trade log when then needs to be manually crunched in your favorite spreadsheet application.
Easy example: download the trade log and sum all the returns. They don’t equal the $7,489 that’s depicted in the screenshot and recorded in other results files in the backtester outputs.
9. They do not. This is a limitation of the backtester and is briefly touched on in the “Margin” section at the top. The lower the option strategy performance relative to SPY the fewer concurrent contracts are possible and the lower the actual option strategy performance. It’s essentially a spiral of underperformance.
The average trade duration of a hold-till-position is 43 days. Due to weekends and other non-trading days there are, on average, up to 35 positions open over a ~43 day trade duration. I say average because during triple and quadruple witching positions are opened with durations anywhere between 28 and 62 DTE and this influences the max number of positions that are open over a rolling 43-day window.
July 26, 2019 @ 8:58 am
In response to your comments:
3. What formula are you using? You have a subtraction sign followed by a division sign.
4. Again, this may be stylistic but I’m vehemently against it. The financial landscape is littered with charlatans that try to sell their wares by showing eye-popping numbers. One way they do this is by showing unrealistic, geometric returns. Don’t be that guy. If you want credibility then establish a pattern of leaning conservative in your statement of returns: use an arithmetic calculation. To me, compounding annual returns is a bit less controversial.
5. I agree that less time in the market is less risky, but from a ROC standpoint the denominator is $26,250. Again, don’t give the impression like you’re trying to artificially inflate returns. Here you would be doing it by using a geometric calculation and by fudging the Reg T margin requirement. If you wanted, you could do some sort of ROC/day calculation. You can’t do ROC/year and ROC/day at the same time, though.
6. I was referring to the “Managing Short Vertical Spreads Early” section.
7. Looking at the historical option chain, “there’s no way we could get $3,340 ($33.40) from selling a single 10D SPY put at a 132 strike on Jan 3 2007.” You did not show the chain, though, so this confused me. By the way, in order to get $33.40 and $18.30, you needed historical option quotes to the thousandths place. Where did that come from?
9. I’m still confused. If 43 is the max number of concurrent positions, then why did you use a $100K account to “support 35 concurrent positions at the start of the study” rather than 43, which you would be getting to eventually?
With regard to your takeaway, is notional risk equal on every day for all curves shown in the graphs “Worst Monthly Return” and “SPY vs. 1-5x Daily Spread Write?”
July 29, 2019 @ 1:21 pm
3. typo; previous comment now contains the calculation
4. I’ll take your suggestion under advisement.
5. The math is still the same. If I set the denominator to 26,250 I’d multiply by (44 / 2) to derive the same annualized return equivalent. Nevertheless, the point of this particular section is about risk management implementation costs (commissions). Strategy return calculations are depicted in the results section above.
6. I didn’t write the number because it has far too many zeros, a consequence of annualizing a 23.76% one-day return. Hat tip to your point in #4…
7. The thousandths place is a result of the spread mechanics. The option prices are available to two places and the spread calculations on SPY – typically having one-cent-wide spreads – gives us the fraction of a cent.
9. 43 is not the max number of concurrent positions, 35 is the average max number of concurrent positions. Over a rolling 43-day window there are, on average, 35 concurrent positions open in the hold-till-expiration strategies.
No. The Worst Monthly Returns chart and table are based on individual performance, not scaled, and align with the 1x daily chart. I’ll add a scaled Worst Monthly Returns chart and table to correspond with the 1-5x daily chart soon.
July 30, 2019 @ 7:56 am
7. SPY didn’t start to be quoted in pennies until 9/28/07 (see here: https://www.cboe.org/publish/InfoCir/IC07-150.pdf). Does your data show something different?
9. “Worst case” suggests a particular value–not an average–and in a worst-case scenario the portfolio may see 43 concurrent positions (according to the table at the end). Go with that. Continuing on, under the Portfolio Sizing section: “100k is roughly the portfolio size needed to support 35 concurrent positions at the start of the study.” Why not use an account size that can handle 43? 35 is insufficient for a five-week cycle.
Finally, you said the takeaway is “systematically selling vertical put spreads does not outperform buy-and-hold SPY.” How can you say that when you have not normalized for risk?
July 31, 2019 @ 2:59 pm
The scaled worst monthly returns chart and table have been added.
7. That’s interesting. Let me clarify – the data from ORATS is showing hundredths and/or thousandths values in the trade prices. I have visibility into the raw option dataset that lists the buy/ask prices, only the resulting trade logs generated by the tool. As such, I’m unable to validate the accuracy of spread mechanic execution.
9. Valid point – it does suggest a value as opposed to an average. I’ll update verbiage. The table at the end speaks to average trade duration, which is different than average number of concurrent contracts.
The point about portfolio sizing starts to enter the topic of capital management. If I had a tool that was margin aware this would be moot as it’ll cap the number of trades/contracts once margin thresholds were hit. While being capital aware is a more realistic implementation of the strategy it opens the can of worms called timing luck. Starting the backtest one, two or three days or weeks later could yield significantly different results because we may enter or be unable to enter trades that are very profitable or unprofitable. More on that backtesting methodology problem in the backtesting mechanics post. 100k is used since it’s the size necessary to support opening a single position every trading day when the strategy starts and achieves capital use parity relative to the buy-and-hold strategy.
When you say “normalized for risk,” are you asking about risk-adjusted returns?
August 1, 2019 @ 1:45 pm
7. Thousandths for the bid and ask quotes?
With regard to your last two comment paragraphs, if I’m going to compare two positions then something must be equal. If nothing is equal then I have an invalid apples-to-oranges comparison.
You are comparing a dynamic options portfolio with a static $100,000 stock investment. What equates between the two groups being compared?
August 15, 2019 @ 7:16 pm
Hey Mark, sorry for the delay in response. The latest study on USO that’s slated to go live tmrw generated some “impossible” numbers, such as a negative equity curve on long stock, which raised several questions about the ORATS outputs.
The details about inaccurate equity curves is addressed in last week’s housekeeping post, so we’re good to go there.
7. typo: I do NOT have visibility into the raw option dataset and am unfortunately unable to confirm. Consequently, I’m unable to confirm the accuracy of the spread mechanics – a feature that can can be expected to generate fractions of a penny in the execution prices in the trade log. Without having my hands on the raw data, agreed, it’s a black box and trust is required. Worst case all the prices are made up and we’re all wasting our time. Best case everything is as described.
Agree, and this is a consequence of having a tool that’s not capital / margin aware. Hence, I do my best to have the strategies start out on equal footing but once they’re in motion there’s not much I can do.
If the option strategy underperforms the long stock in the overall graph, the actual option strategy will performance will be less than depicted in practice due to margin ceilings capping max number of consecutive trades. Conversely, if the option strategy outperforms long stock in the overall graph, the actual option strategy performance may be true (again, no visibility to potential margin calls while holding due to volatility before profits/losses are realized).
I speak to this assumption in the methodology section.
While it may be easy to dismiss the research due to it not having 100% realistic mechanics re: margin, I believe there’s still value in highlighting the theoretical strategy performance relative to buy/hold.
August 19, 2019 @ 2:50 pm
Great news Mark – the return calculations of the strategies have been updated to be calculated as a daily notional return. In other words, it isolates the performance of the option strategy from the leverage options can generate. This allows a dollar-for-dollar, apples-to-apples comparison.
In other words, the performance is depicted as if the option strategies are implemented in an ETF. This allows amounts as small as $1 to experience strategy return profile.
Methodology section updated to highlight the calculations.
Let me know your thoughts —
August 19, 2019 @ 4:48 pm
I haven’t seen last week’s housekeeping post. I’ll be interested to read that.
I think it’s always worthwhile trying to check out validity of data. In this case, I’d probably shoot Matt an e-mail and ask where those values we were discussing came from. I’m not a nihilist and I don’t want to adopt such an outlook. Personally, when potential flaws stare me in the face, I have to do some digging.
Critique this suggestion for generating an apples-to-apples comparison. Start with equal notional risk on Day 1 by dividing SPY price into notional risk of the vertical position and buying that number of shares. Every day, buy or sell equal numbers of SPY shares needed for the increased/decreased BP needed for the spreads: as you add a new daily position, SPY shares are bought; as you close verticals, SPY shares are sold. The total amount of shares held at the end of each day are multiplied by % change in SPY price to get a change in account value.
I think this sort of approach gives reason to plot SPY shares and vertical spreads on the same performance graph. Without doing this, even if you say the verticals are holding up to and not to exceed SPY’s margin requirement, I would challenge any conclusion that SPY outperforms.
This also begs the question of how you are defining performance.
By the way, I think you have some mad quant skills and I admire the work. In my eyes, what we’re doing here is just a form of peer review.
August 22, 2019 @ 12:12 pm
Agree. I can add that to the list.
Your suggestion is essentially what I’m doing now, although my mechanics are slightly different. Since the strategy indeed requires opening a position daily, the daily notional exposure is divided by the count of contracts open in order to remove leverage from the equation, creating an average daily exposure. The average exposure is then measured against underlying performance to identify the daily return for building curves.
Because this approach gives us the daily return as a %, we can apply that to a portfolio of any size / granularity. By purchasing shares of “x” as parity, we run into granularity issues where fractional shares or fractional contracts would be needed put can’t be implemented in practice.
Since this methodology looks at notional in all scenarios, margin mechanics such as capital efficiency benefits of spreads is eliminated. The strategy returns what it returns; it’s cash secured. Useful for seeing strategy performance separate from the influence of leverage. Thus, I need to remove the “scaled” sections in this and the other spread-oriented posts.
From what I can observe, and I could easily be overlooking something, this methodology does not work when it comes to leverage. Namely, the dollar-for-dollar comparison. Reg-T will prevent new positions from being opened on certain days throughout the backtest. We can either accept this limitation and display performance as if margin ceilings did not exist or we can run the strategy 45 times (for the hold till-expiration strategies) each with a 1-day offset from each other in order to identify a strategy variance attributed to timing luck (see https://spintwig.com/backtesting-mechanics/#Timing_Luck for more details on this).
Thank you! And absolutely! I find our interactions exceptionally valuable and is just the kind of scrutiny / review that keeps us sharp, always improving, finding errors, and ensuring great, accurate, defensible content for everyone.
August 27, 2019 @ 4:09 pm
I agree with the unrealistic nature of doing a comparison like this. I think you have to multiply the number of contracts to avoid the fractional shares problem. That’s also done with complete knowledge of the future and past, which is arguably a flaw. Maybe you say “I’m going to add $25M capital per day” and buy either shares or verticals. When verticals close, you sell the corresponding number of shares to keep notional risk roughly equal on every day.
Alternatively, you could just look at individual trade statistics from opening a trade every day. The matched long SPY group, for comparison, would open/close trades on the same dates as the corresponding verticals.
I really didn’t understand where the “scaled” sections fit in.
Did you think about standard deviation of returns (or max drawdowns) in this study?
P.S. You can delete my comment in the other thread about “how exactly did you generate that CAGR graph.” We’re discussing it here.
August 29, 2019 @ 10:36 pm
Been kicking ideas around and crunching some numbers – the best approach I’ve found to calculate a leveraged strategy is…
At a high level, this 1) runs the strategy using an unlimited size portfolio then 2) figures out how small of a portfolio could have sustained the strategy.
It’s a way of anchoring the portfolio size such that the strategy could run without ever worrying about failing to open a position due to not enough margin. I find this superior to picking arbitrary portfolio sizes and empirically “guessing” until the right size is found. It’s also an elegant way of solving the “if I can’t open a position daily due to margin requirements the subsequent performance is now [more heavily] subject to timing luck”.
The only limitation I see, and this only affects naked strategies, is the inability to calculate fluctuations in buying power reduction due to VIX movement. If VIX spikes a margin call is possible because of the expanding margin requirement.
What are your thoughts on solving for that? Accept it as a limitation? I have daily IVR of the underlying but I don’t have access to VIX or a way to correlate it to the strategy trades.
Also, comment removed per your request.
September 4, 2019 @ 3:25 pm
I’m confused about what you’re trying to do. I’m not sure if you were responding to my last comment or not.
I think I’ve said all I have to say on this. It’s a complicated topic, to be sure! I don’t think you can support a comparison between B&H SPY and SPY verticals yet. I’ve given all the suggestions I have on that.
The Reg T return of NPs is paltry. When normalized for notional risk, I suspected risk-adjusted returns (e.g. SD in the denominator) are better than long SPY. The danger is the uncertainty of the next big correction… but that’s off-topic for this blog post.
September 4, 2019 @ 7:50 pm
Re your “Risk Management/short puts” paragraph: that’s almost an exact description of what I’ve been doing lately – and it’s been working out very well for me. One thing I’ve done that has improved the process even more is that I stay abreast of current volatility and look at the way the stock is going; when vol is high and the stock is trending up (like today), I shoot for 1.5-2x the “usual” percentages – especially toward the end of the day. It’s not even about the gain from the greeks; 10% of 10-delta premium isn’t a big reach for swings in a $300 stock…
Worth a thought: if managing early is such a big win, then what would be the problem with using shorter expirations? I recall the research that you (and TastyWorks) have done, but I believe the underlying assumption was holding till expiration. My usual process starts with looking at the premiums 45 days out but also checking the ones closer in for disproportionate increases in premium, and I often find such critters there. With one annoying exception (X sucks. I wish I could meet it in a dark alley, just ONCE), that has also been a definite plus.
September 6, 2019 @ 1:29 am
That was my strategy through most of August – aggressive management. If I’m at 7% max profit 50 minutes into a position and $100+ is sitting in front of me, I’m taking it.
Shorter expirations trade vega (vix expansion) risk for gamma (convexity) risk – also known as your unrealized P/L volatility.
The SPY straddle study https://spintwig.com/spy-short-straddle-strategy-performance/ indirectly evaluated the effect of varying levels of gamma risk (exposure to short DTE positions). The total P/L stat, for example, experiences ~9-15% hit when positions are held sub 21 DTE. Daily P/L, worst monthly return, share ratio – all suffer when held sub 21 DTE / during elevated gamma. Do the trades work? Sure. Are they optimal? Depends on the goal at hand.
At least it wasn’t a naked put on ULTA. As one of the analysts so elegantly phrased it: “Why Ulta Beauty Shares Got Hit With the Ugly Stick.” 🙂
September 6, 2019 @ 1:06 pm
> My practical experience does not indicate that buy/hold is better. It is certainly less risky, so it is better in that way for sure.
Take a look at 2008 and try saying that with a straight face, Jeff. 🙂
B&H is pretty decent overall, but in the tweet-driven market we’re in, I’d much rather trade the shorter term.
September 6, 2019 @ 1:28 pm
I think we’re saying the same thing here…I advocate trading shorter term puts during higher volatility, NOT buying and holding. If you had bought the SPX in September of 2007 for 1526, you would have broke even after 5 years (with dividends reinvested). Compared to options trades where you can blow up your account completely and never recover, it can be seen as less risky. I think it all depends on how long you hold through the volatility.
having said that…
If M/W/F expirations on the SPX existed in 2008, then trading ONLY 2 DTE expirations would have returned 135% in 2008.
Looking at my backtesting through the whole financial crisis is a big part of what has driven me to explore this further.
September 6, 2019 @ 1:34 pm
…and now I’m motivated to replicate the 45 DTE SPY study using 1 or 2 DTE positions. Working on a few other studies for the time being but it’ll be out sooner than later.
September 6, 2019 @ 1:37 pm
I get it 😉
Again, those Monday and Wednesday expirations did not exist before Mid 2016…so your software may be limited.
September 6, 2019 @ 1:43 pm
Spintwig, I would love to see that. Most of my trades recently have been between 14 and 4 DTE, and every one of them has turned out great. Yeah, bull pop and all that – but the premium wouldn’t be there when the market is down, so I’d be further out.
I think I’m saying that (my own informal version of) Jeff’s strategy works for me. 🙂 Heck, I just might try regularizing it to what he’s talking about and see what happens.
September 6, 2019 @ 1:48 pm
> Compared to options trades where you can blow up your account completely and never recover, it can be seen as less risky.
Can you explain how a short put strategy can blow up your account completely without you taking risks that you would never take with holding stock? TTBOMK, what blows up your account is taking inappropriate risks – not the instrument you use.
September 6, 2019 @ 5:02 pm
Options are always more risky that holding stock, even if you are trying to use options as a stock replacement. Since the two are so different, I’m not exactly sure how I’d answer your question about taking risk with an option that you would not with a stock.
What I can illustrate is that a flash crash at expiration is not something that really impacts you when you just own a stock. Look at what happened from the 31st of July to the 8th of August. The 5th saw a 2.98% drop in one day. If you hold stock until the 8th all you saw was a 42 point drop in the SPX, but if you had credit spreads expiring on the 5th, entire positions were wiped out.
While you hopefully would not have had 100% of your portfolio in that credit spread, the losses would have been magnified greatly compared to just holding on. That’s what I mean about the risk. (what is TTBOMK?)
September 6, 2019 @ 4:51 pm
Jeff, what have you learned by backtesting through the crash and how would it change your trading in a future crash? Can you make money, or would you focus on defensive maneuvering to not lose too much money?
In the TuringTrader backtests of Larry Connor’s strategies, what struck me most is how the equity curve goes up even during the big crash. https://www.turingtrader.org/2019/04/showcase-strategies-larry-connors-and-cesar-alvarez-short-term-strategies/
September 6, 2019 @ 5:27 pm
I think the core of what I learned is that Volatility, which I measure through the VIX, drives premium pricing up far faster than the risk of a drop goes up. So what I saw was that longer term options trades (28 days) lose more often than shorter (2 days).
Frankly I’m pretty excited to see what I can do during the next recession (whenever that actually is). I’m happy to see the market go up as I’ll still make outsized gains using my longer duration trades, but I see much higher profits when volatility spikes up.
As I’ve said in other places on this site, I do not consider myself some kind of stock/ options trader. I look at myself as the Owner/Actuary of a niche insurance company that uses the instrument of options to provide catastrophic portfolio insurance. So I look at the statistical probability that there may be certain sized moves over a certain period of time and compare that to the historical ACTUAL moves that have occurred when the VIX is at similar levels and typically the statistical is far higher than the historical. That lets me collect the insurance premiums (which are higher because the are based on the statistical probability) at the risk levels of Historical, which I see usually as 1/3 the risk.
During a recession people will pay more for portfolio insurance than they do at other times and thus I make more money for the same risk levels I run at today.
I’ll check out that link you posted when I get some free time.
September 6, 2019 @ 8:32 pm
> Options are always more risky that holding stock, even if you are trying to use options as a stock replacement.
I’m sorry, but the bald statement without anything to support it is just opinion. Mine happens to be the direct opposite – but with data and examples. 🙂
Stock is, by definition, 100 delta. If you hold it, your losses are 100% of however much it goes down. Options can never go over 100 delta, so the _maximum_ risk with them is the same as the stock – minus the “runup” to 100 delta, and minus the premium you’ve received.
> What I can illustrate is that a flash crash at expiration is not something that really impacts you when you just own a stock. Look at what happened from the 31st of July to the 8th of August. The 5th saw a 2.98% drop in one day. If you hold stock until the 8th all you saw was a 42 point drop in the SPX, but if you had credit spreads expiring on the 5th, entire positions were wiped out.
The underlying assumptions here – that someone holding spreads would a) simply watch and wait for an entire week while this was going on and b) hold till expiration – are neither reasonable nor even probable. B&H is specifically intended to be a “set and forget” strategy, which means that GE, Enron, Blockbuster, Motor Liquidations Co, and the (dozens? hundreds?) of companies that get delisted every year are opportunities for total wipeout for stock holders with little or no possibility of prevention. Options, unless we’re talking about buying puts as hedges, are never used in this manner.
> While you hopefully would not have had 100% of your portfolio in that credit spread, the losses would have been magnified greatly compared to just holding on. That’s what I mean about the risk.
I’m trying to put this as politely as I can, but… either your understanding of risk is seriously flawed, or you’ve lost track of it in an attempt to support a false point. Someone who has a certain amount in credit spreads does so in expectation of a *reward* – one MUCH higher than that which would be realized in the same underlying for simply holding that amount of stock. If you compare _actual_ risk – i.e., risk vs. reward, not just single numbers devoid of context – then option are, again, much safer than holding stock.
Example from today (one of a dozen or so this week; I’m experimenting with/adapting to the wheel strategy; VIX averaging just a bit under 15.5):
SPY @ $298.30 STO 191018P291 $3.60
SPY @ $298.51 BTC 191018P291 -$3.40
$20 in less than 3 hours, which someone holding stock would have made twenty one cents. My BPR was (estimated) ~$5700, while theirs would have been ~$30,000 for the same period. My absolute maximum exposure in case of loss (do, please, consider the chances of SPY going to zero) is equal to theirs – minus the premium I’ve received.
In the simpler, and more common case of holding for ~1/2 the period to expiration – let’s call it 30 days – someone holding SPY will earn just about 1% on the average; i.e., $1k on $100k of exposure. To get the same outcome from writing a put, the exposure is much less than half of that if 2 out of 3 trades are successful.
I.e., there’s not a single case you’ve listed in which holding stock is safer when equivalent risks are taken.
> (what is TTBOMK?)
September 7, 2019 @ 7:51 am
I totally agree with Ben here about your statement “options are always more risky that holding stock, even if you are trying to use options as a stock replacement,” Jeff. With everything you have posted here, you seem like an experienced option trader and I find it interesting to see you write that. Maybe the discrepancy is semantic.
If you’re going to compare the two, then I think you have to equalize notional risk. I’ve suggested Spintwig do just that with regard to the graphs presented here. Without this, I think the comparison loses much of its relevance in a hurry (which is why I say his presentation does not support the takeaway that SPY B&H outperforms).
September 7, 2019 @ 2:03 pm
Notional risk has been equalized. This was one of the changes I made when doing the study and site refresh a few weeks ago. Consequently the methodology section is now longer than the results section, as it probably should be. Thank you for your constructive feedback and dialog that lead to this improvement!
September 7, 2019 @ 7:54 am
In your example, Ben, the SPY shares would have made $21 (not cents) in less than three hours. Like you said, though, it would have been on a much larger capital requirement.
September 7, 2019 @ 8:55 am
You’re right, Mark; thanks for the correction.
In an amusing bit of synchronicity, someone on EliteTrader rolled out the “options are always more risky than stock” line last night. Predictably, experienced and professional traders reacted much as I did – with arguments that, in one case, echoed mine here almost word for word.
One rather stark consideration that comes to mind is that, if options were _always_ more risky than stock, they would present an arbitrage opportunity… and we all know what happens to those. It’s also worth a note that Warren Buffett – not exactly the icon of extreme risk-takers – has made at least a few dollars selling insurance (and has actually sold puts on KO and BNI in the past.)
September 7, 2019 @ 11:27 am
This is certainly an interesting conversation and I’m open that I may be wrong on some of my thoughts here. I also probably should not have said “Always”. Perhaps as Mark says it is somewhat semantic and like I said the two instruments are so different. I will also say that I am not an “experienced trader” in the sense that I don’t see myself as a trader.
>I’m sorry, but the bald statement without anything to support it is just opinion. Mine happens to be the direct opposite – but with data and examples.
True, this is just my opinion , but be fair…I did provide an example and it had data.
> I’m trying to put this as politely as I can, but… either your understanding of risk is seriously flawed, or you’ve lost track of it in an attempt to support a false point. Someone who has a certain amount in credit spreads does so in expectation of a *reward* – one MUCH higher than that which would be realized in the same underlying for simply holding that amount of stock. If you compare _actual_ risk – i.e., risk vs. reward, not just single numbers devoid of context – then option are, again, much safer than holding stock.
I think you are really getting at the heart of the difference in views on risk that we have with this paragraph. I’m not trying to support a false point I’m just probably doing a poor job of explaining one of my views on risk. I’ll try to do a little better here. I absolutely agree with you that the reward aspect of options is much higher…it’s why I use them :).
I’m looking at risk of loss in the sense of the probability that something bad could occur and the severity if it does which is perhaps an incorrect view? I certainly do layer reward on top of it to drive my decisions. I’ll also say that typically what I see is that when volatility is higher, reward is significantly higher and thus the Risk/reward ratio is better. So I think you are looking at Risk:Reward and I’ve been only talking about the risk side.
In the example that I used which you said was unreasonable, I believe it illustrated that the risk of severe loss was higher than holding the stock. You are correct that if someone was watching closely enough and had their wits about them, they MIGHT have been able to do something about it, but if the stock fell through their spread fast enough (and it moved really big over the weekend when the Chinese devalued their currency) then to roll the position or close it out you could have easily taken 50% or higher losses on your position and I was illustrating that Stock would not have experienced the same losses.
> SPY @ $298.30 STO 191018P291 $3.60 SPY @ $298.51 BTC 191018P291 -$3.40
I’ll try to explain my thoughts with this example also. Imagine if the market had moved the other way by the same amount. The option would have lost $20/$5700 = 0.35% loss, but SPY would have lost $21/$30,000 = 0.07%. From a risk only view this appears to be a 5x greater loss on the option than the stock. For any investment the question is always: “is the reward worth the risk?” but in these cases the risk being higher in options is what drives the reward higher.
So again I probably take a (too?) simple view of this but hopefully this post helps illustrate my thought process as to why I said there is more risk in Options.
I really appreciate you taking the time to discuss, I really get a lot out of these conversations
September 7, 2019 @ 1:37 pm
> I’m looking at risk of loss in the sense of the probability that something bad could occur and the severity if it does
That is exactly how I look at risk. It’s also how insurance companies and their actuaries *hat tip* look at risk.
September 7, 2019 @ 1:03 pm
This conversation has got me thinking about different uses of options that are not as risky as just buying stocks.
1) the famous Warren Buffet KO example. Buffet said that he wanted to own KO at a certain price and sold naked Puts so that if the price fluctuated down to that level he would get the price he wanted. This instrument was better than a simple Limit Buy order because he also got to keep the premium. So in this case I would say that there was really a zero risk because both possible outcomes were perfectly acceptable to Buffet.
2) using options to Hedge a risky stock position would actually reduce total risk of the portfolio.
Again, I appreciate this discussion and you guys helping me think through more of this.
September 7, 2019 @ 10:45 pm
> Buffet said that he wanted to own KO at a certain price and sold naked Puts so that if the price fluctuated down to that level he would get the price he wanted.
Are you familiar with his $1B 20-year short against Lehman (ATM, $2.05M premium)? Interesting story, and certainly _not_ about owning the underlying. Worth looking up – especially his rationale for it.
September 8, 2019 @ 11:12 am
I’ll look up the Lehman brothers case, I was not aware of it. Thanks!
September 8, 2019 @ 6:10 pm
This really was a good read!
It is really interesting to analyze how some things that traders take for granted and test the weaknesses.
Thanks for the suggestion!
I also just downloaded Cottle’s Options Trading: The Hidden Reality – Ri$k Doctor Guide to Position Adjustment and Hedging (“Options: Perception and Deception” & “Coulda Woulda Shoulda” revised & expanded, Printed in Color)
I’m very interested in the risk-mitigating actions that can be taken even in this “tweet reactionary” world we live in today.
September 9, 2019 @ 9:26 am
> This really was a good read! https://alphaarchitect.com/2018/12/28/warren-buffett-is-wrong-about-options-except/
Just scanned that one – there’s a problem with their analysis of the problem 🙂 ; they think that MMs use Black-Scholes to calculate option prices… oh, dear. But yeah, the Buffet cite is pretty much what I was thinking of.
> Thanks for the suggestion!
You’re welcome! It is interesting to consider how an option’s price is likely to move at those time spans… suddenly, selling ATM puts makes all kinds of sense. And a 100-year loan at 0.7% sounds pretty good, too.
> I also just downloaded Cottle’s Options Trading: The Hidden Reality – Ri$k Doctor Guide to Position Adjustment and Hedging (“Options: Perception and Deception” & “Coulda Woulda Shoulda” revised & expanded, Printed in Color)
That book blew my mind. Put/call parity, synthetics, hedging, and strategy decomposition… wow. Over just the past couple of weeks, I’ve managed a good dozen trades for profit that I *know* I’d have either scratched or taken a small loss on before.
> I’m very interested in the risk-mitigating actions that can be taken even in this “tweet reactionary” world we live in today.
Follow the Volfefe index. 🙂
September 7, 2019 @ 10:37 pm
> This is certainly an interesting conversation and I’m open that I may be wrong on some of my thoughts here. I also probably should not have said “Always”.
I think that’s very likely the crux. There’s just something that strikes me as deeply wrong about using ‘always’ when applied to the topic of options. 🙂
> I think you are really getting at the heart of the difference in views on risk that we have with this paragraph. I’m not trying to support a false point I’m just probably doing a poor job of explaining one of my views on risk. I’ll try to do a little better here. I absolutely agree with you that the reward aspect of options is much higher…it’s why I use them :).
My point was related but different: since the rewards in options are higher, the two could not be compared on the basis of something as simple as “account size”. You’d need to look at the rate of return per unit of risk – in which, to the best of my knowledge, options have an edge. You would also (and this is _much_ more difficult) need to consider how the two asset classes are actually used, and try to draw whatever inferences were possible from that data. As I’ve mentioned, they are quite different – and each comes with a list of risks based on that as well. (To be frank, I see passivity in investment as being one of the riskiest approaches possible today – and that’s something that no backtest would be able to demonstrate. Sorry, spintwig! 🙂 )
> I’m looking at risk of loss in the sense of the probability that something bad could occur and the severity if it does which is perhaps an incorrect view?
Let’s define “something bad”. The commonly-parroted advice about B&H goes something like “whatever you do, DO NOT look at your P&L on a regular basis; only check it quarterly/biannually/annually.” Although I understand the psychological reasoning that underlies it (as well as the marketing hook buried in it for the average fearful investor), that kind of behavior is something I see as insanely risky. The problem is, how do you calculate the actual probability of, say, GE getting caught with their hand in the till? Read your Taleb: it’s not calculable. Neither are any of the other “black swan” event risks.
(I see spintwig’s comment about it further down, and disagree. Utterly. The two situations are nothing alike. Insurance companies deal with a very large statistical universe in which most of the relevant probabilities can be calculated, since they define most of the terms of the contract – via political leverage, narrow supply channels, etc. As retail investors, we have NONE of these advantages, so the often-used metaphor of traders as insurance companies breaks down on even the slightest examination.)
> I’ll also say that typically what I see is that when volatility is higher, reward is significantly higher and thus the Risk/reward ratio is better. So I think you are looking at Risk:Reward and I’ve been only talking about the risk side.
You’re right; I do. I think I’ve forgotten how to do it the other way. 🙂 More precisely, it no longer makes any sense to me to do so – to the degree that I simply don’t do that any more.
> In the example that I used which you said was unreasonable, I believe it illustrated that the risk of severe loss was higher than holding the stock. You are correct that if someone was watching closely enough and had their wits about them, they MIGHT have been able to do something about it, but if the stock fell through their spread fast enough (and it moved really big over the weekend when the Chinese devalued their currency) then to roll the position or close it out you could have easily taken 50% or higher losses on your position and I was illustrating that Stock would not have experienced the same losses.
It’s always possible to come up with an out-of-band situation for anything by scaling large enough. I just can’t see how that makes for a rational argument. What if the CEO of the one company that you’re invested in is caught injecting cancer-causing chemicals into the product while cackling like a demented hen? What if Trump finds a way to outlaw stock trading come Monday? What if the majority of the companies comprising the S&P have been conspiring with the Russians and are about to bring down the entire economy by a maneuver that sends all their companies into the toilet at once? All of your stock would become worthless – while, say, LEAP options, PMCCs, skip-strike butterflies, and many, many other option trades would be perfectly safe, or small losses at the worst.
The reality is that, despite our ability to imagine them, these are not actual risks. The chances of them happening are so tiny that you have to ignore them, or hide under the bed for the rest of your life.
> SPY @ $298.30 STO 191018P291 $3.60 SPY @ $298.51 BTC 191018P291 -$3.40 I’ll try to explain my thoughts with this example also. Imagine if the market had moved the other way by the same amount. The option would have lost $20/$5700 = 0.35% loss, but SPY would have lost $21/$30,000 = 0.07%. From a risk only view this appears to be a 5x greater loss on the option than the stock.
And this is a perfect example of why the “risk-only” view is incorrect. That option trade would not have lost anything at all, since it hadn’t been closed – and there would be no reason to close it. I could wait and see what it does – since I sold it at high IV, I’d have reversion to mean on my side – or hedge it with stock or futures, or convert it to a strangle… take a look at Cottle on options; there’s an entire universe of actions I could take to improve its eventual P&L, and I could keep doing it for as long as I want to. With stock… not so much. Unless you have a whole lot of dry powder, there’s not a lot of leverage you can apply – unless you get into those “risky” options.
> So again I probably take a (too?) simple view of this but hopefully this post helps illustrate my thought process as to why I said there is more risk in Options.
Thanks for confirming that I understood your premise. I still disagree with it, of course – and I hope that I’ve shown why quite clearly. And just to clarify my intent here: it’s not even so much to show that you’re “wrong” per se, but to illustrate that what you’re already doing is not nearly as risky as you think. At least if you do it from the correct perspective (which, to me, means being aware of the actual risks in the situation and having a plan to mitigate them; something you cannot do if you start from a false premise.)
> I really appreciate you taking the time to discuss, I really get a lot out of these conversations
It’s my pleasure, Jeff. I’m learning this stuff as I go, and “practicing” live (a single lot at a time; I’m very much a believer in “earning size”) – but I’ve also been lucky enough to come in contact with some crusty old “gurus”, guys who got their chops trading in the CBOE pits, etc. They have little hesitation about kicking my ass one one wall and down the other if I trot out stuff like “options are riskier than stock” (or really, any absolute or over-self-assured statements that I can’t back with solid facts)… hopefully, I’ve been able to distill what I’ve learned from them minus the bruises. 🙂
August 31, 2020 @ 7:12 am
Important FYI: Your calculation of profit is wrong, which would change this entire study and potentially all studies you have done. please see below:
In your example of TRADE 1: Jan 3 2007. You take in a credit 15.10 then close for 9.90. for a profit of 5.20; and you subtract comission of $4.00 to give a net profit of 1.20*100 = $120 which is not correct.
This is on 100 shares!!!! you cant take your profit 5.20 – 4.00 comission, instead the correct calculation is 5.20*100 – $4.00 which is $516.
Big difference between 516 and 120.
Please let us all know, because if this is how you do you calculations, all the studies are wrong.
August 31, 2020 @ 8:57 am
Great catch Jcash! You’re spot on.
Thankfully, this is merely an error in my written example and it is not how I calculate commissions. I’ll be correcting this momentarily.
The primary tool I use to build backtests is publicly accessible with formulas intact and a change long that tracks issues found. Feel free to take a look. https://spintwig.com/options-backtest-builder/
October 27, 2020 @ 11:42 pm
This is awesome, very interesting.
How does this work with portfolio margin/margin utilisation? I presume this used Reg T margin for put selling, is that right, and used 100% of available buying power? Would be interesting to see a backtest which adjusts like like for on buying power utilisation
October 28, 2020 @ 12:25 am
Great question! Yes, this is based on Reg-T and is designed to set the starting capital such that max margin utilization reaches between 99-100% over the life of the backtest. Average margin utilization throughout the life of the backtest is generally less due to methodology mechanics associated with daily entry and “lumpy” exits (many contracts expiring or reaching profit targets at the same time).
As for portfolio margin, short answer is that it’s depends on the broker’s PM risk model. While generally similar, each broker has their own implementation nuance(s). Thus, a backtest would need to be designed with a specific broker (or formal counterparty agreement) in mind if looking to optimize within those parameters.
Custom backtests / models that use “current buying power utilization” as an entry signal are supported. PM me if you’d like to explore in more detail.