Trading Thoughts and Recommendations

I finally made some solid initial summer travel plans, starting with a one-way ticket to Utah on June 11.  I’ve been planning to visit my friend Jeff in Montreal and then head to Sweden for the summer for a long time, but closed borders changed things.  Fortunately my friend Ari in Utah has offered to host us, and we can visit Canada/Sweden when things change. 

It’s been hot in Puerto Rico, but it’s reasonable.  I spent last Sunday swimming in the ocean waves and returning calls while laying out on the beach, and it made me wonder why I was itching to leave.  Outdoor (and everything else) activities have been shut down for months, so I’m just starting to enjoy the island amenities again.  There are disadvantages to living on a tropical island, but I stop caring when I get into the bathtub-warm ocean.  With no beach/coffee/gym/office, I began to forget why I’m here.  Given that, I’m still very excited to see friends this summer, and get back into (non-tropical) nature.  It’s going to be good to change up my workspace too.  I typically variate where I work, with the last place that I would choose being my apartment (which has been the only option for months now).

I’ve been studying trading/hedge fund/financial history for a little while now, and it’s been very interesting.  There are so few good books in the trading world, which is not surprising given the secrecy, but definitely relieving.  I can easily finish all of the “good” books in the industry this year via listening to the audiobooks while I shower/walk, and reading a chapter on my Kindle as motivation before I start my workday.  At a leisurely pace I would guess I finish a trading book once every other week, and I’ll be done with my que (even though I find at least one new book every month) in a few months.  So far my favorites are: “Reminiscences of a Stock Operator”, the series “The Market Wizards” especially the Hedge Fund edition, “More Money than God”, and “The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution”.

The same stories play out repeatedly (myself also having lived through these seemingly unavoidable learning lessons): 

  1. Guy who is good at trading making tons of money and forgets that he will eventually be very wrong, bets too big, and gets wiped out during a freak market event, or is at least severely humbled.
  2. Markets can trend up or down far beyond and longer than what is rational, so trade accordingly.
  3. If you have investors when you hit your eventual downswing they will be furious and heap abuse on you no matter how successful you were in the past or how small your downswing is.  It’s actually correlated: the more you make, the more pissed they will be after getting used to those big earnings.  You can’t take it personally, and that part of the business hurts traders’ mental game more than the actual swings in the market.
  4.  Be more cautious with your bet size than you think.  A lot of the catastrophic trades that ruin accounts actually end up being profitable, but traders bet too big too early.  
  5. Be wary of illiquid markets.  If you can’t sell your mortgage derivatives/Ethereum options/Russian oil stocks without losing a huge chunk of your money, you don’t want that to be a large percentage of your portfolio. 
  6. 99%+ of the time trading is basic buying/selling for the normal reasons, but understanding the tiny and normally unimportant details on the fine print of a financial instrument can be huge.  Oil prices going under -$30 a barrel for one day, how many ETFs are pseudo-scams, etc.

It has been a few good months of trading, and I periodically question myself about how good I want to get at the game.  The easy (but still time consuming) stuff is learning about new financial products and how they work.  It’s fascinating for me learning about how interdependent each major asset is (gold, s&p 500, oil, interest rates, etc.), and the nitty gritty of how you calculate what the price of something should be based on everything else.  I really enjoy it, and it’s important as I work to create more trading models/strategies in different products.  Much harder is the computer science/machine learning work I do to optimize/create these new strategies.  

Imagine you’re a professional poker player that is enjoying a comfortable living.  Your “work” options each week (assuming a normal non-pandemic reality) are basically to play poker games you are good at and earn money, study those poker games you normally play so you can earn more when you do play, or learn new poker games.  If you just play and study No-Limit hold-em and never learn new games you (or at least I would) burn out miserably in boredom.  If you’re always learning new games you aren’t going to have the time to play/study your main games where you’re earning, and subsequently earn less.  To keep getting better at your main games, you’re going to have to continue to study more and more micro-situations (eventually everyone learns all of the standard plays, and the real edge against competent players is doing unique things in very niche situations) likely to the point that you’re spending a large chunk of time memorizing computer solver programs output that are supposedly game-theory optimal.  For most people the fun of poker is the social aspect and getting to test yourself mentally against other people trying hard to beat you.  If you get to the point where you’re memorizing computer program outputs it’s a lot less thrilling to keep training than what originally attracted you to the game, but that’s the reality if you want to be a top pro playing against other top pros in 2020. 

In trading all of the major markets are teams of top pros playing against everyone else, but fortunately no memorization is required.  You can program your own computer, and it plays for you.  Of course you can make money without any programming skills, and I’m inspired by the many people who are successfully trading huge sums of money this way.  The top-top earners who win consistently a huge amount every year though are running automated systems.  That’s where the question of how good I want to be comes up.  In poker there’s people making good money without doing hardcore game theory study, but they are playing in private games against other people like this, they are playing in lower-stakes, or perhaps they do have some unique edge that allows them to win, but they could likely be winning that much more if they understood the latest poker game theory plays (if at the very least to be able to exploit the other players in the game who are trying to use it).  

For me in trading after years of research and training I feel like I can make money if I could only trade once a week/day/hour using logical strategies I come up with, but the shorter the time-frame (minutes/seconds) I am successful in, the more money I can make.  If I make 2 good trades a year with a 70% chance of winning, I’m only 49% to win on both, even though of course I’d be happy to place those bets given the good EV of each bet.  Contrast this with making 2000 trades with a 51% chance of winning (assuming transaction costs are baked into the winning percentage), especially if I can compound the money on each trade.  The shorter time frames necessitate automation, and if I want to keep improving and winning larger, I need more to advance in everything, particularly data/algorithms/machine learning/knowledge.  I’m inherently a bit lazy like most people, especially when things are going well overall, but I’ve gone so deep with trading now that it would be too anti-climatic if I don’t keep pushing forward seeing where I can take all of this.  

I’ve needed to think through this often as I get bored/tired pushing past my current skills, and consider just coasting. I think it applies to anyone who has put a lot of time into something, and starts to consider what next. Apologies to my sane readers who could care less about ramblings of my nerd mind and trading.  I hope to have some pictures from the mountains in Utah next week for you.  Until then, leaving you with some pictures from the beaches here in Puerto Rico.   

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