Value Investing GitHub Repository

(MENAFN- ValueWalk) We are fascinated by the empirical evidence showing that value investing has outperformed the market most of the time for as far back in history as the data allows us to see. It fascinates us because it seems counterintuitive that a well-known, simple process could survive for long without becoming so popular that it no longer worked.

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There is hot debate about the cause of this anomaly. One school of thought is that value stocks are riskier than the market as a whole and investors are compensated with higher expected returns for the additional risk. Another school of thought is that human behavior — our — causes investors to be irrational, which, in turn, sometimes causes a stock to be priced lower (or higher) than what the underlying company's inherent worth would justify. is that maybe a little of both phenomena, risk compensation and our animal spirits, are at play.

Regardless of the cause, to help illustrate the empirical evidence of this phenomenon, we put together a of scripts that allows anyone to run one of several data analysis experiments related to the value anomaly. It is organized as a series of 'studies', and each one demonstrates an empirical aspect of value investing. To execute a study, all a user needs is an and the .

Many of the studies were not originally conceived by Euclidean. In particular, William Bernstein first a version of the study in 2001. Star Capital a version of the analysis in 2016. However, this repository is meant to be a self-contained, one-stop-shop for reproducing these studies and others from the original source data. We also hope that it will serve as an easy-to-use launching point for future studies on this topic.

One does not need to have access to proprietary data to execute these studies. Rather, each script downloads the required data necessary to execute them from the original source data. We would like to thank and for making this data available through their websites and , respectively. The equity investment return data is copyrighted by Kenneth R. French.

Finally, it is important to point out that, in these studies, value stocks are defined as companies with high book equity to market value (book-to-market). This is a very crude way of defining a value stock. Examining only the result of a company's assets minus its liabilities (its book value) is akin to looking at a company as if it was merely a bank account. Yet, there are so many other factors that comprise a company's intrinsic value, such as its products, customers, brands, operating capacity, and intellectual property. Perhaps this is why many researchers have found that other measures of value yield better results than book-to-market when building value stock portfolios.

This said, the book-to-market time series that Ken French provides on his website offers a unique opportunity. No other data source goes as far back in time or is freely available for public consumption. Therefore, we believe our repository is useful for examining the high-level behavior of value investing and how it has performed relative to other investment approaches over long periods of time.

Article by John Alberg and Michael Seckler,

This repo is a collection of data anaysis studies that examine the performance and characteristics of value investing over long periods of time. Each directory is a study dedicated to a particular form of data analysis on value investing. The studies depend only on the code herein and publicly available stock market and economic data. We would like to thank and for making this data available through their websites and , respectively. The equity investment return data is copyrighted by Kenneth R. French.

The studies in this repo are:

• :
  • Characterizes the relationship of value stock performance with respect to inflation as measured by the consumer price index
• :
  • Characterizes the relationship of value stock performance with respect to long-term interest rates
• :
  • Compares performance of a hypothetical value fund to S & P500 returns
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  • Analyzes the performance of value stocks vs. growth stocks over long time horizons
• This is experimental software. It is provided under the , so you can do with it whatever you wish except hold the authors responsible if it does something you don't like.

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