MikeMooreBacktests

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Michael Moore / Mail: mmoore1865@gmail.com / Phone: 312-9337021

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Options market environment strategy
Within today’s unique market environment, we are seeing new equity highs at basement level low vols.
This is a distinct risk profile. Today’s environment, like all risk environments, displays unique, quantifiable
patterns.
Compare the 2008 crash to 2013 bull market for example.
By studying historical data within different market environments, we are able to identify and extract alpha
through customized options strategies designed for each environment.
The Big Idea: Using 1 to 10 day expiring options, we will manage and grow a highly-scalable, algorithmic
strategy to consistently extract alpha from the current trading environment, every day.
Extracting Alpha:
Step 1: Measure and Define the Risk Environment
We algorithmically target the proper risk for the current environment.
To do this from historical data we first identify key characteristics that define any market environment.

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Ex: 30day Implied Vol
This is a chart of atm 30-day out IV’s, and each vol bins’ corresponding average profit for a (middle row)
short 1-day iron condor, and (bottom row) short 1-day straddle.

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Notice the clear drop in average edge per days’ worth of the above short premium risk as 30-day IV goes
> .27
Using the defining market characteristics, we filter historical data for similar market environments.
Within this filtered subset we then compare today’s vol surface relative value to the relevant historic data:
After we identify the target risk, we move on to price modeling and execution.
Spy Vol Surface
value
days to expiration
30day 60day 90day 120day 150day 180day
3deltaPut 19.56% 23.74% 26.02% 27.57% 28.63% 29.20%
12deltaPut 14.21% 17.62% 19.26% 20.78% 21.28% 21.81%
25deltaPut 12.50% 14.43% 15.68% 16.97% 17.49% 17.87%
atm 9.31% 10.13% 10.75% 11.30% 11.71% 12.05%
25deltaCall 9.19% 9.69% 10.15% 10.76% 10.96% 11.18%
12deltaCall 9.12% 8.94% 9.23% 9.97% 10.04% 10.20%
3deltaCall 9.44% 10.41% 10.01% 10.30% 10.26% 10.22%
% historical ranking
days to expiration
3deltaPut 0.7 11.8 19.2 26.7 27.5 28.9
12deltaPut 1.3 7.0 12.8 19.1 20.2 19.9
25deltaPut 1.0 5.8 9.3 13.9 13.9 12.8
atm 1.7 2.3 4.1 5.3 6.0 6.6
25deltaCall 6.3 6.3 6.8 9.5 7.6 8.1
12deltaCall 11.4 8.5 7.1 17.1 11.3 10.1
3deltaCall 29.7 38.6 38.8 45.3 38.6 35.2
Skew
((P -C implied vol)/atm implied vol)
Value days to expiration
3 deltaSKEW 1.087 1.316 1.490 1.528 1.569 1.576
12deltaSKEW 0.547 0.856 0.933 0.957 0.960 0.964
25deltaSKEW 0.356 0.468 0.515 0.550 0.558 0.555
% historical ranking days to expiration
3 deltaSKEW 34.826 69.320 86.070 87.065 94.527 94.693
12deltaSKEW 7.131 96.020 99.005 99.005 99.337 99.502
25deltaSKEW 26.036 90.547 94.030 99.337 99.171 98.839
Estimated days to reversion days to expiration
3 deltaSKEW
12deltaSKEW
25deltaSKEW

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Step 2: Execute the Daily Strategy
To model the edge of market to TV’s, we compare
1) All historical data 1-day underlying distribution:
-and-
2) Current filtered environment 1-day underlying distribution:
-to-
Market options values.

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By comparing the option values expected from our filtered empirical subset to those in the market we can
see the edge represented between our empirically expected option values and the market values. This
edge allows us to define the necessary binary classification thresholds on top of which we can manage
the execution and risk management of our strategies.
Example: On 8/9/2016 models identified a 1-day short condor as the target risk. The august 10th
expiring
2160/70 2190/2200 iron condor closed yesterday (8/8/2016) @ $2 mid-market. 12 years of unfiltered
historic data suggests a value of 1.75 for that condor, however our filtered market environment subset
suggest a theoretical value = $1.43 for that condor. Therefore, we sold that condor for best price available
that morning of $1.65.
Trading Principles and Risk Management
-Always (and only) stay exposed to proper risk for the environment.
-Limited risk per bet (day)
-Every concept is quantified.
-Sophisticated, exhaustive analysis. Simple risk.
-Always have a plan.
-Human judgment is trusted above models.
Backtests
Tests thus far support the powerful daily alpha extraction concept.
“Sophisticated, exhaustive analysis. Simple Risk” as applied to back-testing. We first run models over the
last 12 years of historic SPX closing data. For each Monday, Wednesday, Friday (spx weekly options expire
every Monday/Wednesday/Friday) trade date, models suggested the relevant key risk characteristics, as
well as an expected underlying distribution from a comparable filtered subset.
From this analysis we make 1 of 3 decisions 1) sell 1-day condor, 2) stay in cash until next trading day, or
3) buy ATM 1-day straddle.
This test assumed a weekly max spread notional value of $20k. Since we do not want to risk more than
2% on any day, size traded times max spread width is limited to 2% ($20k) of my notional (assumed $1
million) AUM.

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Out of 1693 trading days examined, we sold a condor 849 times and bought a straddle 96 times. Total
profit is around $1.3 million over 11 years, with a max drawdown of 8%.
Compare these results to selling a condor every day with no filter. While selling a condor worth 2% of max
risk every day would have realized $380k of profits, this strategy would have experience a drawdown of
over 40%.
Notes:
In practice, our team will add customized features for delta/vol/skew/calendar biases as needed daily.
The 3 weekly SPX expirations and the weekly vix/equity/futures options products all allow for a limitless
pool of daily trading opportunity for low risk, consistent alpha extraction.
This strategy is designed to keep costs and trading at a minimum. We trade smarter, and less often.

MikeMooreBacktests

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