Like investment returns trading profits tend to come and go in waves. While during one period money is made effortlessly with few losses, at other times one loss follows the other – often compounded by mistakes piled on top of it (e.g. not following your own rules). We hear this being called a trader who is in-tune or out-of-tune with the market, describing a strong tendency for serial correlation of good and bad trades. This is the essence of what I want to get into here.
I spend much of my research in trying to figure out how to quantify market regimes and align them with what I know to be my strengths and weaknesses. So, this is a very personal analysis of my own winning and losing periods (for others these can be completely different depending on the trader´s personality and strategies).
Analyzing our own trading patterns can give us useful information on how to trade at any given moment. Is it wise to be aggressive, defensive or take a break altogether? A distinction that can easily get swamped in the heat of the moment of a regime change and can help to diminish unnecessary, potentially crippling, losing streaks.
Strategy returns tend to cluster
Trading strategies are commonly described as a constant process with each trade showing independent, equal probabilities – much like a coin toss. This does not jibe with my practical experience and trading data (backtests and real time data).
Results actually show a strong tendency to cluster and streaks of winners are followed by streaks of losers. Very often these clusters coincide with distinct market regimes as a certain strategy (and trading style) performance is closely correlated to the market environment.
A generic short volatility strategy (SVXY, red) is an example of a market regime dependent trading strategy. It out- and underperforms (marked in yellow) in clusters to end up in the same place as the S&P500 (black) over time. A simple volatility regime filter effectively cuts losing streaks short soon after they begin and leads to a superior performance over time (blue).
In my own trading performance I also see the closest correlation in results when I look at volatility regimes: calm bull markets show profits whereas significant losing streaks predominantly appear in high volatility environments. This stands in contrast to the common narrative that active traders tend to thrive under high volatility.
There is a reason why that is the case. My active strategies concentrate on a time frame between 1 week and several months. They aggregate probabilities for future market returns by studying quantifiable historical patterns (e.g. what has happened over different time periods when today’s notable conditions occurred in the past?) In an uncertain environment, often coincident with volatility measures triggering danger signals, the range of outcomes becomes much greater. It happens more often, that the market takes an unlikely, extremely rare or even completely unprecedented path.
The current environment is a prime example of the market repeatedly taking an extremely rare path.
Dealing with losing streaks
The main advice I hear addressing this problem is to use different strategies for different market regimes. Unfortunately that has never worked very well for me in practice. I suspect the reason for this is behavioral – my frame of mind tends to take some time to adjust to new market regimes causing losses and mistakes to accumulate even when using different strategies.
A long streak of profits leads to complacency and over-optimism which turns out to be a poisonous combination when markets suddenly show a different face and a big dose of humility and caution is required.
I continue trading different strategies or instruments with the same mindset and it simply does not work. A switch of focus from profit optimization towards capital preservation is required.
Switching strategies is not enough to adjust to a new market environment – you need to change your frame of mind as well.
Take a break
A different route works much better for me. I need to scale down trading activity to very low levels (often it is best to take a break to reassess the situation) until I see the string of losses broken and see my adjustment to the new environment confirmed by actual positive trading results.
Don’t ignore the signs
Overconfidence and recency bias bred from a streak of profits leads to a blindness to risk that is a risk in itself that cannot be understated – even for a quantitatively oriented trader. It is so easy to fall into patterns that lead traders to be blindsided by unexpected changes. To recognize when things aren’t working is difficult. FOMO, revenge trading to recoup initial losses, addictive screens and other mechanisms need to be addressed actively (e.g. by using trading checklists to self-analyze) or they will happen subconsciously.
Even quantitative traders need to be aware of their behavioral biases. Source
Trading strategies work on the premise of recurring historic patterns. The problem is: the market does not have to do what any trader or strategy tells it to do. Often it follows predictable paths for extended periods of time and then it suddenly stops – figuring out when it doesn’t follow the patterns of the past is an important job for the trader.
Is the current market making any sense?
In a notable twitter thread Anil points out that the market makes perfect sense. But only under the premise that, “the market moves to cause the maximum pain to the greatest number“. I do not ascribe such human cruelty to a marketplace, but it perfectly describes an environment where the unexpected is happening repeatedly. While financial markets are prone to such behavior, I think, that most of the time they actually behave quite predictably and actively positioning yourself according to the probabilities of similar patterns in the past can yield considerable outperformance.
What we want to avoid is that this outperformance is completely given back during times of stress.
Thank you for reading and write in your own war stories – do your experiences rhyme with mine or are they completely different?
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