Progress Update 4

    Today my day was mainly spent reading Chapter 10: Trading Systems in the book Trend Following by Michael Covel. Reading all about what makes a trading system profitable was useful information and I learned of real-world examples of why the system of trend following is the most profitable long term.

    This chapter went over a few topics that I learned in my summer ECON200 Microeconomics course such as expected value and game theory. Covel talked a bit about Nash Equilibrium which I was the most intrigued by when I took my microeconomics course. If you don't know what Nash Equilibrium is, it's a concept in game theory where if you are rational and your opponent is rational, there is one optimal strategy. Applying this general concept to investing, Covel points out:

"If we own some stock, and there is a possibility of a price decline, we are at risk. The stock is not the risk, nor is the loss the risk. The possibility of loss is the risk. As long as we own the stock, we are at risk. The only way to control the risk is to buy or sell stock. In the matter of owning stocks, and aiming for profit, risk is fundamentally unavoidable and the best we can do is to manage the risk."

    What this means is applying the concept of Nash equilibrium and the knowledge that nobody can predict trends before they form, it is riskier to predict trends before they happen but also the most profitable is you manage to do so. So if you apply this to risk management, it is best to find a profitable trading system which caps your losses in trying to predict a trend, but doesn't cap your winners until the trend is broken. This is the trend-follower's Nash Equilibrium, their optimal strategy given the circumstances.

    But if you can take 100s of tries to predict a bottom with a stop loss, why can't you take as many tries trying to predict the top with stop losses. The answer to this is that in a good trading system, winners don't come often, so its best to let them run and not eat into the profits trying to catch the exact top. Also, markets are irrational. COVID stock market crash and rise is a perfect example of this. Stock markets were rising despite unemployment skyrocketing, Fed continually expanding it's balance sheet to unforeseen levels, etc. The idea that markets are irrational is based on the fact that human's irrational behaviors are usually based on emotions. As we all know, (or should know), irrational emotions shouldn't be your leading factor of why you make financial decisions or any decisions at all.

    So how does a Nash Equilibrium exist if one party (stock market) is irrational and the other (trend-follower) is rational? That is a tricky question. This leads into the concept of risk management. Your rational decisions should have levels of risk management applied otherwise they aren't considered rational.

    These concepts are getting very paradoxical and complicated so I'll just end these thoughts here. If there is something fundamentally wrong with the concepts here. Feel free to correct me. These are complicated topics and this blog is composed entirely of my thoughts.

    On a side note, today I also figured out why my trading algo was giving quick buy & sell orders in the middle of a trend-catching position. What is happening is my algorithm is coded to recalculate every tick and when a buy/sell signal is caught in one of those ticks, the order is pushed to execute at the close. Let's say you are in the middle of an uptrend and a bearish crossover happens in one tick then a couple ticks later it uncrosses itself. That action, in theory, should be ignored and the algorithm should stay in the position it is in. But instead what happens is when the initial bearish crossover happens in the tick, the algo sends a sell order to execute at the close. When the crossover undoes itself a few ticks later, it sees that as a bullish crossover therefore sending a buy order to execute at the close. So at the close of the bar, 1 buy order and 1 sell order is executed which ends up negating itself.

    This problem seems harmless, but in an effort to take discount brokerages selling my order flow into consideration, I applied a $0.01/contract fee to the calculation of the algorithm. These glitches are costing me $0.02/glitch/contract traded in the glitch.

    Good part about this is that since I now understand what is happening, I can better solve the problem to make my trading algorithm better as a whole and more profitable. I will start fixing this soon.

-Jamie