Freediving, trading, randomness, win rates and probabilities.

Freediving, trading, randomness, win rates and probabilities.

Hey folks,

I would like to bring our attention to something that I find very fascinating and mind-blowing. The concept of randomness and the markets, and how randomness, win rates, and a decent R-ratio play a very key role in trading. The thing I like most about these concepts and how they marry, is how they can help us build confidence, even after a streak of losing trades. It reminds me of when I got my freediving certification. Before we even got into the water, we discussed the theory in a classroom around breath holding and oxygenation. When we got in the water, I had confidence in my ability to hold my breath, as I did so for almost 5 minutes in the classroom. I understood the discomfort that is associated with the need to breathe, I knew what it meant, what my body was telling me, and what I needed to do when I started to feel it. So, by the time we were diving to 30 meters, I could do so with confidence, as I knew what to expect, and I knew how my body would react and what those reactions felt like. Additionally, if things went bad, and I blacked out, there were security measures in place (safety divers) who were trained and able to get me out of the water safely. The very same practice can be applied to trading.

Trading is hardly the same as freediving, but I like to apply the safety concepts I learned in freediving, to trading. Having the understanding of how long I could hold my breath and what it felt like, physically, emotionally and psychologically, gave me confidence because I had experienced and explored these feelings of being scared and stressing, in a classroom. Similarly, after a string of losing trades, over time, one is able to build the intuition of losing trades and recovering from them. All I have to do it trust my edge and continue to apply it when it was validated. The safety diver is my stop-loss. If things go against me, which they often do, I am quite comfortable paying a little tuition, because I know what it will cost me (I made that decision before I opened the trade), and I know that there will be other opportunities. It's a numbers game really - and with a significant sample size, patterns will emerge that can be observed, measured and used to build intuition.

I don't know if this makes sense or if you can relate to it, but all I want you to understand is that trading is a game of probabilities, where your strategy is your edge. If you ensure a decent R-ratio greater than about 2.3 R, and win rate greater than about 36%, you are in good shape. Let's explore these concepts in a little greater detail.

Market prices are influenced by a multitude of factors, including economic data, political events, investor sentiment, and unforeseen events. These factors interact in complex ways, making it impossible to predict price movements with absolute certainty. Even with sophisticated analysis, there's always an element of randomness. This means that any given trade can be influenced by factors beyond our control, leading to unpredictable outcomes. Think of it like flipping a coin. You know there's a 50/50 chance of heads or tails, but you can't predict the outcome of each individual flip - in fact, you don't need to, as you know that after about 100 coin tosses, there will be an approximate distribution between heads and tails of about 50/50, which I will explore in the video. Chaos theory suggests that even seemingly random systems have underlying patterns, but these patterns are highly sensitive to initial conditions. In trading, this means that small changes in market conditions can lead to significant and unpredictable price swings. The "butterfly effect" is a classic example, whereby a butterfly flapping its wings in Brazil could, theoretically, can cause a tornado in Texas. This illustrates how small, seemingly insignificant events can have large, unpredictable consequences. In financial markets, this can be seen in how news events may cause large and rapid price fluctuations. This theory helps us to understand that we can find patterns, but that complete prediction is impossible.

The R-ratio is the ratio of the potential profit of a trade to the potential loss. For example, an R-ratio of 3 means that you're risking one unit of capital to potentially gain three units. A favourable R-ratio is crucial for long-term profitability, even with a low win rate. For example, if you have an R-ratio and a 30% win rate, you can still be profitable. For every 10 trades, you'll win 3 and lose 7, so your wins will generate 9 units of profit (3 wins x 3 units), and your losses will cost 7 units of capital, which gives you a new profit of 2R. The win rate is the percentage of trades that result in a profit. Many traders focus excessively on achieving high win rates, but this is often counterproductive, as strategies with a win rate of 99% can still result in negative returns. Chasing high win rates can lead to taking small profits and large losses, which ultimately erodes capital and requires enormous psychological capital. A trader with a 90% win rate, that loses 10 times the amount they win on the 10% of losing trades, will lose money.

The law of large numbers is a statistical principle that states as the number of trials increases, the average of the results will converge towards the expected value. In trading, this means that the true edge of a strategy will only become apparent over many trades, which is exactly why casinos always win, they just need to keep that roulette wheel spinning. In fact, I visited a casino and spoke with the manager about this. I was told that for every 1000 spins, the roulette wheel results in about 3-5% profit. Short-term results can be heavily influenced by randomness, leading to misleading conclusions, which is why casinos invest considerable amounts of money into ensuring the randomness of their roulette tables, as randomness is their friend, when you have an edge of course. By tracking a significant sample size of trades (roulette spins), you can identify patterns in your strategy's performance, such as average win rate, average R-ratio, and maximum drawdown (largest consecutive loss). This data allows you to assess the viability of your strategy and make necessary adjustments. Losing streaks are an inevitable part of trading, even with a profitable strategy. A large sample size helps you to understand that losing streaks are just statistical fluctuations and not necessarily a sign that your strategy is broken. Emotional control is important during losing streaks.

Trading is a probabilistic endeavour. By understanding the concepts of randomness and chaos theory, traders can adopt a more realistic and effective approach. Focusing on favourable R-ratios and observing a large sample size of trades allows for consistent profitability, even with low win rates and inevitable losing streaks - and most importantly, it helps us build confidence.

So, I challenge you, not necessarily to become a free-diver but a free-trader, where the concepts of freediving education and risk mitigation can be applied to trading.

I created a video about this concept I would like to share. If you have insights, ideas, experiences or feedback, I'd be thrilled to hear from you.

https://youtu.be/2g_nuBPr8io

Thank you.

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