There is no secret trading or investment strategy, that will beat all others.
There are many ideas that work and related ideas all have very similar characteristics, leading to virtually the same risk-adjusted return over time across strategy types.
For example (average data from my backtests, books, articles, academic papers etc.):
For example (average data from my backtests, books, articles, academic papers etc.):
Trend following strategies
Whether you use moving averages, breakouts, RSI, Bollinger Bands etc., they will have a return profile with a win probability somewhere around 40% and a profit to loss ratio of 2 : 1 per trade. They work quite reliably over the right time-frame (3-15 months), but are hard to execute over time, because the low win probability will lead to frustrating strings of losses and drawdowns.
Mean reversion strategies
Should return within a win probability of around 60% and a profit to loss ratio of 1 : 1. I find these harder to construct and less robust, but academic research shows them to be a realistic possibility at shorter time frames below 1 month. Fundamental, long-term, mean reversion investing (e.g. value investing on a time horizon above 2 years) lies at the core of the success of many of the best investors on the planet – their returns are better characterized by the outperformance over market return then by the metrics above.
Strategies that provide insurance against exceptional risk
For example, short volatility strategies, will have an even more negatively skewed return stream with a high win probability around 80%, but that comes with the downside of small wins and huge losses with a ratio of something in the vicinity of 1 : 3 – they are vulnerable to tail risk, but can still have a positive expectancy. For me the most reliable measure is the carry of the instrument. Demand for insurance is likely to give a stable edge.
Similar risk-adjusted returns everywhere
The same holds true across asset classes and return factors: Long-term Sharpe ratios can be expected to be fairly equal.
My research indicates a somewhat hierarchical distribution as more sophisticated techniques had progressively higher risk-adjusted returns in the past:
Possible Sharpe ratios are about 0,4 for asset classes; 0,6 for return factors and 0,8 for strategies.
As smart beta (long-only return factors) and strategies like trend-following or shorting volatility become easier to access and knowledge about them more mainstream, I’m not certain whether these differences will continue to be as pronounced in the future.
This seems quite logical as markets are both smart and very competitive. Outliers in return will quickly be reigned in – if they are too low the asset or strategy will be shunned by investors, if too high investors will pile into the strategy, bringing returns back in line in the process.
Variations in returns are pretty much down to random luck, minor improvements and mistakes (which can quickly turn a profitable concept into a losing portfolio). As long as the basic concept is valid, the exact strategy doesn’t matter all that much – there simply is no holy grail. Nonetheless that is what drives most people´s interest and efforts – as it has in many fields throughout human history.
Uncertainty and randomness are the major component of financial markets and they will have to be accepted to avoid certain failure. A random distribution of profits and losses will always be the essence of this probabilistic game. Having these probabilities tilted just slightly in your favor is what a systematic approach to trading and investing is all about.
Of real importance are a strategy’s simplicity and its robustness and the trader´s determination, diligent execution and focus on the level of risk he takes – good process and a deliberate risk level will determine long-term outcomes much more than the actual strategy.
Real diversification enhances returns
By cleverly combining uncorrelated strategies, diversification can limit drawdowns, dampen volatility and thereby raise risk-adjusted returns. Thus it is possible to increase leverage and generate higher overall returns while maintaining an acceptable level of risk. These benefits seem to reliably top out at a sharpe ratio of 1 in real-world portfolios over the long term.
By cleverly combining uncorrelated strategies, diversification can limit drawdowns, dampen volatility and thereby raise risk-adjusted returns. Thus it is possible to increase leverage and generate higher overall returns while maintaining an acceptable level of risk. These benefits seem to reliably top out at a sharpe ratio of 1 in real-world portfolios over the long term.
So, why do so many traders fail?
Maintaining discipline, avoiding mistakes and our ingrained biases make even simple strategies hard to execute in reality. Chasing the perfect indicator, pattern or combination thereof will usually lead to over-optimizing strategies to past data (essentially optimizing to randomness) and over-leveraging your trades – this can quickly lead to large losses.
A major fallacy is the idea to simply transfer ideas from one time frame to another.
I don’t think that is possible. Different strategy concepts work within different time periods and lose their edge in others – a problem that is seldom articulated to aspiring traders and investors.
In general the longer the time period you invest in, the more reliable basic investment principles become, but the fewer opportunities you will have to bet on them.
Conversely at shorter time frames opportunities will be much more frequent, but random noise will overshadow these basic principles more and more. Each trade will have a smaller edge and be more vulnerable to mistakes.
On an intraday time frame many setups simply don’t have any sustainable edge at all. Most advantages take time to materialize. I have heard experienced investors say time and again that a long-term time horizon is one of the strongest edges there is – the longer people invest, the more they tend to gravitate to those time frames.
Here and here and here are some well researched resources on the validity of a variety of short and medium term signals, I found.
The (un)reliability of short term concepts is very hard to figure out as good data is hard to come by (in contrast to longer term investing strategies) and valuable information is scarce. The vast amount of results you get when starting your research will be connected to products, courses etc. that people want to sell to unexperienced traders. While generating superior profits solely from trading is extremely competitive and only a minority succeeds in this zero sum game (less fees), the industry that is selling ideas around this dream is very lucrative. The more outlandish, secretive (and unrealistic) the promises, the higher the profits for the peddlers.
Unfortunately there is no secret.
Any superior strategy that combines high win probability with a high profit to loss ratio is the holy grail for every trader and hedge fund in the world. It will be arbitraged away quickly by the extraordinary efforts market participants go to to find such edges and is bound to be unsustainable over the long term. Sustainable inefficiencies are small and rely on deeply ingrained behavioral biases or hidden risks.
I’m diving deep into the subject in my research (the dynamics are super interesting) and more short term strategy analysis is on the way…
Best of luck!