Game Theory in Trading
Most trading strategies put their emphasis on finding out when to enter the market. Whether it’s technical or fundamental, everyone is looking for an entry signal. However, this only covers half of the trade.
As any trader knows, there are two parts of any trade: getting in the market, and getting out of the market. Arguably, the more important of these actions is the last one; since that ultimately is where you decide to take profit or stop loss.
With everyone so eager to jump into the market, it’s understandable but unfortunate how most trading strategy articles online neglect to talk about the “back” side of trading; risk management and how to get out of the market at the appropriate time.
Using a strategy in reverse
Many strategies can be re-purposed from giving you an entry signal to giving you an exit signal. If, for example, you use your strategy to find points to buy in the market; you can use a sell signal from the same strategy as an exit.
However, that’s a simple solution to a more complex problem that still puts the emphasis on entry and not exit.
Trading as a game
Very often, people look to a strategy to answer the question: “When do I start a trade?” But that’s the wrong question. While some people can make a killing on just one trade, that’s just a matter of luck; the majority to the point of exclusion of traders achieve success by trading many times. The question you need answered is “When do I start my trades?”
Each time you trade, you take a risk; it can go in your favor as well as it may not. You can win, or you can lose. So we’ll call each time you trade a “game”. There is no limit to the number of times you can play the “game” of Forex, and these repetitions of the game are called “iterations”.
But by combining that together, and you have game theory. There is a reason that people who are good at game theory are good at forex. It focuses on the outcome of the trade, more than just the start of the trade.
Game theory in trading: what’s the price?
In fact, using game theory, you can forget your entry signals altogether: since trading can basically go up or down, in a very rudimentary form, there is a 50:50 chance of success with randomization. Like flipping a coin.
So, let’s consider a coin toss for illustrative purposes. If someone were to offer you a bet on a coin toss; if they were right, you’d pay them $10 and if you were right, they’d pay you $20, would you take the bet?
Well, sure: you have 50% chance of winning $20, and a 50% chance of losing $10. Makes sense.
Let’s make it a better deal (assuming you aren’t already a millionaire): they offer $1,000,000 if you are right on the coin toss – but if you are wrong, they get your house. Is this a good deal? The odds are the same – you could say, the “strategy” here is the same. But a 50% chance of losing $10 is very different than a 50% chance of losing your home.
What makes this a “good” or a “bad” strategy isn’t how accurate it is in predicting the outcome, but how you handle your risk exposure.
Game theory in trading: Iteration reduces cost
If we take this coin toss scenario and instead of it being a one-time offer, say it repeats over time. The second case – $1,000,000 or your home – can’t really iterate, because you can lose your home only once.
But you can probably lose $10, and still have money to play again. Maybe you can lose two, three times? Let’s say four. That would be pretty unlucky; there is only a 6.25% chance of that happening. However, with your next win, you can keep playing. Over time, if you play enough, you’re going to win twice as much money as you lose; you’ll be consistently profitable.
Sure, you won’t make your cool $1,000,000 in one trade; but if you can make that much money virtually guaranteed if you play 200,000 times.
Gambling v Investing
The bottom line is that if you focus only on when to get into the market, then you are banking on luck to become profitable. This is also known as gambling. If you focus on how you exit the market, then you are considering statistical returns on investment.