- Most econometric analyses typically rely on structured datasets, whereas the most interesting datasets are unstructured. In other words, “econometric models effectively model uninteresting data.”
- Most econometric studies do not include methods to de-noise correlation matrices. As a result, “most econometric studies reach spurious conclusions, supported by noise, not signal.” Cross-sectional studies are particularly prone to classification errors .
- Econometric specifications attempt to adjudicate the variance of a random variable in-sample, but in-sample adjudication is rarely useful for strategy development. In general, “regression is the wrong tool for investing.”
- Many econometric methods require that the user simultaneously get the predictive variables and the functional form correct. Given the complexity of financial systems, these are unrealistic demands.
- At a statistical level of p = 0.05, most strategies are false. Suppose, for instance, that the probability of a backtested strategy being profitable is 1%. Then at standard thresholds of 5% significance and 80% power, users are expected to make 58 discoveries, where 50 are false positives. In other words, 86% of the discoveries will be false. In practice, the percentage is even higher, often nearly 100%, due to multiple testing, specification errors and arbitrage forces.
- Statistical models can be overfit in two ways: training set overfitting and testing set overfitting. The traditional econometric toolset fails to quantify, much less address these problems.
- Many researchers employing traditional econometric tools and models fail to understand the extent to which overfitting compromises financial strategies. This is because even with Sharpe ratios of, say, three or higher, selection bias and confirmation bias errors can lead to false positives, often with financially disastrous outcomes.
This presentation reviews the main reasons why investment strategies discovered through econometric methods fail. As a solution, it proposes the modernization of the statistical methods used by financial firms and academic authors.
López de Prado, Marcos, The 7 Reasons Most Econometric Investments Fail (April 16, 2019).
Nassimm Taleb ja fala isso há muito tempo: econometria é inútil.