Empirical Study On Greed
University of Rochester, Students
January 31, 2016
Abstract:
This paper studies cross-sectional stock returns from intrinsic and extrinsic point of view. We extend the model from Yin (Dec. 2015) to moving averages and we show a series of trading strategy that could explain some of the anomalies in the market. Intrinsically, investors can study Enterprise Value to interpret cross-sectional stock returns. Extrinsically, traders can generate alphas with great significance by trading off moving averages. We interpret the underlying emotions, greed and hope, in the market by looking at empirical results intrinsically and extrinsically.
Empirical Study On Greed – Introduction
To explain the underlying emotions, greed and hope, in the market, we present two paths to analyze these psychological feelings. By looking at cross-sectional data, we can interpret empirical results from intrinsic and extrinsic point of view. Securities sold on the market bare certain amount of value. It is the value of how much each security worth by itself, hence it is the intrinsic value. Early literatures by Benjamin Graham discussed a lot of the fundamental indicators that we could be studying to understand intrinsic value. On the other side, market in which the securities are sold is on an auction bases. That is, traders buy and sell freely by bid and ask. This is largely due to negotiation and communication aspects between market participants. To date, we do not have any literature proving that this is completely rational. However, this does not hinder us to draw some reasonable arguments from applying the moving averages.
Based on Modigliani and Miller Theory, Yin (Nov. 2015) has examined the Market Value Balance Sheet (MVBS) from an accounting standpoint. The work, derived from MM Theory, describe a corporation from sum of Cash and Enterprise Value (EV) on the left side and sum of Debt (D) and Market Equity (ME) on the right side. The goal is to describe corporate activities with Enterprise Value (EV). Yin (Nov. 2015) pointed out that the scholars in behavioral finance and asset pricing barely used the model. Traditional cross-sectional study done by De Bondt and Thaler (1985) put a lot of attention on Long Run Reversals and in particular updating Fama-French three-factor model. Their work sort of stock universe by winners and losers which is a measurement of stock returns. They are able to construct a replica portfolio and generate a market-like return by a long portfolio in long-run losers and a short portfolio in long-run winners. However, this sort solely depends on market returns and does not take any other fundamental factors into consideration. Hawanini and Keim (1995) attempted to sort the stock pool by the size. They claim that small stocks have outperformed large stocks by about 12% a year over 1951-1989 time period. This argument has been developed on stock-picking skills between buying a lot of small stocks or big stocks. The answer goes back to study the risk-return in the stock profiles. Their paper also studied the stock universe by market- to-book sort, yet book value does a poor job of describing corporate activities. Fama and French (1993) also put a lot of effort in studying risk of book-to-market ratio. On the market value side, Jegadeesh (1990) examined the cross-sectional returns by the returns of small-, medium-, and large size-quintile portfolios in time t. However, these studies do not to describe how corporate activities over time affect cross-sectional stock returns.
First, this paper takes MM Theory and examine Enterprise Value by applying cross-sectional study on compustat stocks universe. We provide three methods to sort the stock universe. Among them, 
is the most important one and it describes the change of Enterprise Value (EV) over Market Equity. The results are consistent with Piotroski (2000). We conclude an investor can construct a “greed” strategy such that he can generate alpha by buying the most “greedy” stocks and selling the least “greedy” stocks.
Next, we present a model looking at different time period persistence and momentum among cross-sectional returns. There are some literatures related to this topic. Hendricks, Patel, and Zeckhauser (1993), Goetzmann and Ibbotson (1994), Brown and Goetzmann (1995), and Wermers (1996) find evidence of persistence in mutual fund performance over short-term horizons of one to three years. Brinblatt and Titman (1992), Elton, Gruber, Das, and Hlavka (1993), and Elton, Gruber, Das, and Blake (1996) study mutual fund return predictability over longer horizons of five to ten years, and attribute this to manager stock picking skills. Jen (1969), however, presents contrary evidence and explains that good subsequent performance follows good past performance. Carhart (1992) explains that it is persistence in expense ratios that drive a lot of the long-term persistence in mutual fund performance. We are using moving averages, both Simple Moving Average and Exponential Moving Average EMA , to measure the stock returns.
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