Updates for the Quarter

Finished the quarter at 8.5% which was a good look given the S&P was down about 5% but I felt like things could have been managed better especially the initial response and the adjustment to the huge bearish rallies we had. I have two accounts (EDF w/ a seat in Chicago to trade futures) and IB. The EDF account I purposely left on as totally systematic and had traded the IB account more discretionary. The systematic account did beat the discretionary account. Now some caveats there, when we have a large market event like this quarter, we often pause new entries of OTM trades, allow convexity to play out in our tail structures and move to more defined risk structures like ATM trades but only until we get an all clear, this is usually days to weeks max. 99% of the time we’re in our systems. Some learning nuggets in there but mostly nothing we didn’t already know. Interestingly, the account would have published >20% result if the market closed anywhere near 4350 or below but alas, we had a bullish run into EOQ. A little lotto almost. The good news is that this quarter (Q2) is almost up the same as Q1 and it’s only 18 days in. The expectation based on models is that Peak will end up around 25% for H1 2022.

We officially Just finished the first two years for the fund which did awesome. An average of 40% a year which matches the arithmetic backtests we’ve done. I had about 2 years before that with personal trading, so I now have 4 years out of sample matching the available back-testing. All in all, couldn’t ask for anything more. What a successful start. The fund setup was as legit as you could setup and was pretty interesting, it requires 2 independent directors as oversight, a 3rd party fund administration company, that has access to the platform back-end and reviews all trade logs daily, an auditor (Grant Thornton) and loads of administrative tasks by the government. Literally have 10+ people reviewing our trade logs for accounting/oversight. I don’t even have access to the bank account. How neat. Who would have thought. At first, I thought it was a lot of pressure especially given short term swings/dynamics, but I am quite used to it now. As it grows, so does the need for very robust systems, checklists and daily verifications of models/trades. It’s been an interesting experience and I’m loving that our results are published and audited. It’s opening up a lot of pathways and keeping me to task. I am not living my semi-retired life I was on the path to living a few years back but I love what I do so it’s not work.

As I always harp on about my focus being on risk reduction as a way to increase geometric returns, it’s really taking in the point of ergodicity vs non-ergodicity and an example I really liked that Spitznagel used in his book (safe haven) was that of a merchant company who had ships going back and forth in Europe which were prone to pirate attacks. They determined that 1/20 ships would sink and they’d lose 10k (just an example) but had been offered insurance at the price of $600 per ship. Seems like a bad bet right? $12k is more than the 10k they’d lose every 20x on average. But it isn’t when looked at geometrically. The stable cost of $600 per sailing and not having that 10k draw down actually generates more $ over time. It’s a win win for both the merchant and the insurance company. A paradox! But it has one assumption, that the merchant is actioning his money to increase business. If so, then having less cash draw down allows for better compounding in the number of ships he can send. Having that 10k drawdown and having to recover from that drawdown is more of a cost than paying 12k to insure the 20 ships. Go figure. On paper, it’s -2k worse but geometrically it’s better. Here’s another example, if you flip a coin and heads you gain 50% of your worth and tails you lose 40% of your worth, most professional gamblers would all agree that you’ve got POSEV of 5% and it’s a great bet. But geometrically it is a terrible bet. Given enough trials, all participants will go bust. Having been a professional gambler in my university days (only with edges!) I’ve witnessed people through out the years, taking insane $ bets for small edges, I guess if their bankroll is enough, it’s fine but else, it’s eventually a bust. It’s not just about POSEV situations but also bankroll management and risk mitigation via volatility reduction. Most bets aren’t an ergodic process. There’s mathematical equations you can use to figure out how to size bets like these, but rarely do professionals or gamblers alike do that. It’s like Russian roulette (where the 1/6 will end the game forever). Sure, if you had 1000 of you spinning that revolver (picture a multi-verse), you’ll obtain the arithmetic average, but as an independent single trial, it’s an assured total loss. We don’t care that we on average beat the game but what happens if we KEEP playing the game! It’s the life pathway in investing/trading that we care about most not the EV of a specific trade. Large draw-downs along the way are inhibitive to growth more so than the EV itself (for the most part and being reasonable). Everyone says (I stole this) that “Man I wish I invested in Amazon in 1999, I’d be Rich” But that’s pretty stupid, because during that time amazon had 90% draw downs. Imagine following the trajectory of that persons investments.

Volatility tax is such an important concept in finance and one that many ignore. It’s my focus and it’s why I have such positive exposure to tail events and work to have mid-way hedges to reduce drawdown in a campaign setting. I went from being a professional risk taker (I’d define myself this before up until a few years ago) to becoming a professional risk reducer. The entire premise of my trading style is risk reduction (volatility reduction) by way of diversification (as best as I can within the framework I work in) to provide better geometric returns. Just having a risk focused mindset is a win. I don’t focus on returns so much anymore, but rather, smart defined ways to reduce risk via diversification so that my edges are better compounded.

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