There is too much information in mainstream and social media about the markets. The signal to noise ratio is very low as expected. Here is what I ignore.
Yesterday I read this article in Forbes about the three quants in their 20s running a hedge fund using high frequency algo trading. This is how things are shaping nowadays and there will be more of those algo traders in the near future. These traders were taught machine learning, probability theory, statistical arbitrage R, Python and how to apply high tech in real life. They are taking control of trading and at the same time enforce a regime change where traditional approaches find it hard to compete.
On the other hand, the availability cascade cognitive bias still dominates most of trading and investing. Simple explanations to complex problems are very popular because many have adopted them. But the reason they adopted them was because they are easy to learn and require no hard work. As a result, you see many making references to things like:
- Trend lines and support and resistance lines
- Head and shoulders, triangles, pennants and other chart patterns
- Overbought and oversold conditions
- Moving averages and price oscillators
Maybe some or even all of the above were relevant during certain periods in a reflexive sense, meaning that if a network of people used them, then their significance was higher. For example, if many thought prices will rally due to an inverse head and shoulders formation, then they probably did for a while. Then, due to a regime change these patterns stopped being profitable.
Nowadays markets are driven by algos with chart patterns and indicators losing their significance. The algos operate on different principles, constantly arbitraging anomalies in price action and thus making it more efficient. This will go on until the anomalies are all arbitraged out. The targets range from classical chart patterns, such as head and shoulders, to price series and cross-sectional momentum.
Some do not understand the arbitrage process. This will not make all head and shoulders fail, for example, but just remove any edge these patterns might have had in the past due to availability cascade. The arbitrage of these traditional patterns makes their expected return fall close to zero before transaction cost. Some patterns will be profitable and some will be losers but in the longer-term the potential from trading them will be zero. This offers a chance to some old timers to still point to some profitable patterns while ignoring the unprofitable. If the old timers are convincing, and in most cases they are, the availability cascade cognitive bias is enforced.
This is a list of what I ignore:
- Classical technical analysis (chart patterns indicators, etc.)
- Subjective forecasting (of judgmental nature)
- Economic analysis (this is not a science but confirmation bias)
- Any references to probabilities of future trends (they are subjective)
- Any references to forecasting that do not disclose the exact method used
I pay attention to what has a measurable expectation and probability. Usually this is only possible with algo trading; the larger the sample, the higher the probability that the result is significant. This is one reason I ignore some allocation schemes for tactical investing; most suffer from selection and data-snooping biases.
The future is already here and most in financial and social media live in the past, suffering from the availability cascade cognitive bias. They are the ones that provide the profits to these high tech fund managers in their 20s. Profits must come from some place and those traders using outdated methods are the source for them. There is no hurry to educate them as they are providing the alpha. The best case scenario for the algo trading funds will be more people using these failed methods. Although not all funds using algo trading will survive, some will manage to amass large profits.
If you have any questions or comments, happy to connect on Twitter: @mikeharrisNY
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