Why We Need a Statistical Revolution?

This article is written by Mark van der Laan.

He is a Jiann-Ping Hsu/Karl E. Peace Professor of Biostatistics and Statistics at the University of California, Berkeley.

https://senseaboutscienceusa.org/super-learning-and-the-revolution-in-knowledge/

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Deflated Sharpe Ratio can reduce false discovery

Introduction With the recent advent of large financial datasets, machine learning, and high-performance computing, analysts can backtest millions of alternative investment strategies. Backtest optimizers search for combinations of parameters to maximize a strategy's simulated historical performance, leading to backtest overfitting. The performance inflation problem goes beyond backtesting. More generally, researchers and investment managers tend to report only positive results, a phenomenon is known as selection bias. Failure to control the number of tests involved in a given finding can lead to overly optimistic performance expectations. The Deflated Sharpe Ratio (DSR) corrects for two major sources of performance inflation: selection bias under multiple tests and non-normally distributed returns . By doing so, DSR helps separate legitimate empirical results from statistical deception. Backtesting is a good example. Backtesting is a historical simulation of how a particular inv...

Alternative Sector Classification Methods

Abstract This paper offers two alternative sector classification methods in order to classify companies more accurately. Introduction During the early 1900s, various departments of the US government initiated research and studies on the various industries and their different functions. Due to the lack of set standards, each department ended up using its own methodology. Consolidating information across multiple sources became a challenge. The Standard Industrial Classification (SIC) was hence proposed as a uniform classification system, aimed to represent major industries, sub-class and specific function/product, and was formally adopted in 1937. However, SIC was facing a challenge because of the change in the economic environment. After that, the Global Industry Classification System (GICS) was launched by Standard & Poor's (S&P) and Morgan Stanley (MSCI) in August 1999. The standard provides a comprehensive, globally consistent definition of economic sectors a...

US equity market will not be affected by any foreign market crises

We study financial market contagion by applying the volatility index and the correlation between global markets. The first discovery is that it is difficult for any foreign economic crisis to spread to the US equity market. US market may be slightly affected and drops 1%-5%. However, when this event happens, it is usually a good buyback opportunity. Another discovery is that when there is an economic crisis in the US, the fear must spread to all global markets. In US financial crises, it often said, “all correlations go to 1.” Francois Longin and Bruno Solnik (2001) used “extreme value theory” to derive the distribution of extreme correlation between US, European, and Asian stock markets. They found that the S&P 500 seemed to lead the other two markets in terms of extreme positive or negative returns. Therefore, investing in other equity markets during the US financial crisis doesn’t reduce losses. Data: 1997 Asian financial crisis 1998 Russian financial crisis 1999 Argentina econo...

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