Contrarian Investment Strategies: An Assessment of the Value Premium in context to Recessions

Thesis written by

Rebekka Petersen

&

Philip Arnstedt

Copenhagen Business School

Finance & Strategic Management

Institute of Finance

Counseling by Ole Risager

October 2010

Executive Summary

Contrarian investment strategies have been present for decades, generating superior returns for the investors. Investors who follow the contrarian investment strategy are known as value investors. Value investors follow a strategy where stocks with low prices relative to book value and other measures of fundamental value are bought, to be able to generate abnormal returns.

The magnitude of the value premium is huge and it has been persistent on the American stock market. We have investigated how the value premium performs in general and around recessions in order to draw conclusions on the strategy that a value investor should follow when the economy is faced with a recession. We have found that the value premium, sorted on Book-to-Market values, exists throughout our period of investigation from 1947 until 2009 on the American stock market, generating an average quarterly premium of more than 3 % for the investor. We have also found that the value premium is skewed towards the right, implying that value stocks have a higher upside potential than growth stocks.

On average in the four quarters prior to recessions the quarterly value premium is 0.92 %. During the 11 different recessions in our time period of investigation, we found that the average quarterly value premium is 1.37 %. Therefore, we come to the conclusion that value stocks perform worse prior to recessions and during recessions than on average. We have also found that in the four quarters after recessions the value premium is positive in ten out of 11 different recessions, which indicates that there is a clear tendency towards higher returns on value stocks after recessions. The average quarterly value premium is 5.95 %.

We have established that the standard finance theory does not explain the value premium. The traditional systematic risk measure, beta, is on average lower for our value portfolio than for our growth portfolio. This completely contradicts the traditional finance theory.  We believe that the explanation is found within the behavioral finance theory. Investors are subject to several kinds of decision biases, which originate from limited cognitive capacity. We expect that as long as naive investors are challenged by limited cognitive capacity and keep extrapolating past performance into the future the value premium will continue to exist, hence generating possibilities for the value investors.

Introduction

For many years, contrarian investment strategies has been utilized and discussed. Recent, financial researchers have found statistical evidence of a superior return on these strategies. Investors who follow the contrarian investment strategy are often known as value investors because they attempt to buy stocks that are underpriced and sell stocks that are overpriced.

The theory of value investing‘ was formulated by Benjamin Graham and David Dodd as early as  1934 and is based on the assumption that two values are attached to all companies. The first is the market price – the value of the company on the stock exchange. The second is a company‘s intrinsic value. Value investors look for securities with prices that are unjustifiably low based on their intrinsic worth. The intrinsic value is sometimes referred to as the business value. The business value can be interpreted as the value of the company in the event of a merger, a takeover situation, or the amount that could be achieved by breaking up the company and selling all its assets. For long-term investors, business value is the stream of future dividends.

Most often, intrinsic worth is estimated by analyzing a company's fundamentals. Like a bargain hunter, the value investor seeks assets that are beneficial and of high quality but underpriced. In other words, the value investor searches for stocks that he/she believes are undervalued by the market. Like the bargain hunter, the value investor tries to find those items that are valuable but not recognized as such by the majority of other buyers. As the prominent value investor Warren Buffet declares, ”It's far better to buy a wonderful company at a fair price than a fair company at a wonderful price.”

In order for the value investor to be successful it requires that the market is inefficient. The key question for many researchers is therefore to establish, whether the superior returns on contrarian investment strategies compensate for a higher fundamental risk or if the returns in fact are better because naive investors systematically perceive some companies‘ future performance as being too high compared to reality.

Considering the vast amount of empirical support, on the existence of excess return on value stocks, it would be interesting to see if there is any correlation between the excess return, also known as the value premium, and the periodic changes in the economy as a whole. The world economy faces downturns and upturns. This nature of contractions and expansions is known as either recessions or booms.

During recessions, many macroeconomic indicators follow the same path. Production as measured by the Gross Domestic Product (GDP), employment, investment spending, household income, business profits and inflation all fall during recessions, while bankruptcies and the rate of unemployment rises. The opposite is true during a boom.

The majority of recessions have been anticipated by declines in the stock market. Earlier academic studies acknowledge that the value premium also appears to diminish prior to recessions. Siegel (1994) observe that since 1948, ten recessions in America has been preceded by a stock market decline. It is often argued, by private investors, that during recessions value stocks tend to hold up better. However, when the economy starts to recover and the bottom of the market has passed, growth stocks tend to recover faster.

Therefore, it is interesting to investigate if the value premium follows the same trends. Are the returns on a value portfolio superior during recessions but inferior once the economy picks up the pace again or does the value premium defy the conventional direction. If there is any correlation between recessions and the value premium, investors might take advantage of this when deciding on entry and exit strategies in the stock market.

In other words, we will conduct an investigation on whether there is any correlation between the value premium and the cyclical nature of the world economy.

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Behavioral Heterogeneity in Stock Prices

H. Peter Boswijk

Cars H. Hommes

Sebastiano Manzan

CeNDEF, University of Amsterdam, the Netherlands

Abstract

We estimate a dynamic asset pricing model characterized by heterogeneous boundedly rational agents. The fundamental value of the risky asset is publicly available to all agents, but they have different beliefs about the persistence of deviations of stock prices from the fundamental benchmark. An evolutionary selection mechanism based on relative past profits governs the dynamics of the fractions and switching of agents between different beliefs or forecasting strategies. A strategy attracts more agents if it performed relatively well in the recent past compared to other strategies. We estimate the model to annual US stock price data from 1871 until 2003. The estimation results support the existence of two expectation regimes. One regime can be characterized as a fundamentalists regime, because agents believe in mean reversion of stock prices toward the benchmark fundamental value. The second regime can be characterized as a chartist, trend following regime because agents expect the deviations from the fundamental to trend. The fractions of agents using the fundamentalists and trend following forecasting rules show substantial time variation and switching between predictors. The model offers an explanation for the recent stock prices run-up. Before the 90s the trend following regime was active only occasionally. However, in the late 90s the trend following regime persisted and created an extraordinary deviation of stock prices from the fundamentals. Recently, the activation of the mean reversion regime has contributed to drive stock prices back towards their fundamental valuation.

Introduction

Historical evidence indicates that stock prices fluctuate heavily compared to indicators of fundamental value. For example, the price to earnings ratio of the S&P500 was around 5 at the beginning of the 20s, but more than 25 about nine years later to fall back to about 5 again by 1933. In 1995 the price/earnings ratio of the S&P500 was close to 20, went up to more than 40 at the beginning of 2000 and then quickly declined again to about 20 by the end of 2003. Why do prices fluctuate so much compared to economic fundamentals?

 This question has been heavily debated in financial economics. At the beginning of the 80s, Shiller (1981) and LeRoy and Porter (1981) claimed that the stock market exhibits excess volatility, that is, stock price fluctuations are significantly larger than movements in underlying economic fundamentals. The debate evolved in two directions. On the one hand, supporters of rational expectations and market efficiency proposed modifications and extensions of the standard theory. In contrast, another part of the literature focused on providing further empirical evidence against the efficiency of stock prices and behavioral models to explain these phenomena. The debate has recently been revived by the extraordinary surge of stock prices in the late 90s. The internet sector was the main driving force behind the unprecedented increase in market valuations. Ofek and Richardson (2002, 2003) estimated that in 1999 the average price-earnings ratio for internet stocks was more than 600.

A recent overview of rational explanations based on economic fundamentals for the increase in stock prices in the late 90s is e.g. given by Heaton and Lucas (1999). They offer three reasons for the decrease of the equity premium, i.e. the difference between expected returns on the market portfolio of risky stocks and riskless bonds. A first reason is the observed increase of households’ participation in the stock market. This implies spreading of equity risk among a larger population, which could explain a decrease of the risk premium required by investors. Secondly, there is evidence that investors hold more diversified portfolios compared to the past. In the 70s a large majority of investors concentrated their equity holdings on one or two stocks. More recently households have invested a large proportion of their wealth in mutual funds achieving a much better diversification of risk. Both facts justify a decrease of the required risk premium by investors. Although the wider participation seems unlikely to play an important role in the surge of stock prices in the 90s, the increased portfolio diversification could at least partly account for the decrease in the equity premium and the unprecedented increase in market valuations. A third, fundamental explanation for the surge of the stock market that has been proposed is a shift in corporate practice from paying dividends to repurchasing shares as an alternative measure to distribute cash to shareholders. In this case dividends do not measure appropriately the profitability of the asset and such a shift in corporate practice explains, at least partly, an increase in price-earnings or price-dividend ratios or equivalently a decrease of the risk premium. Further evidence on this issue is provided by Fama and French (2001).

Some recent papers attempt a quantitative evaluation of the decrease in the equity premium. Fama and French (2002) argue that, based on average dividend growth, the real risk premium has significantly decreased from 4.17% in the period 1872-1950 to 2.5% after 1950. Jagannathan, McGrattan, and Scherbina (2000) go even further and, comparing the equity yield to a long-term bonds yield, reach the conclusion that the risk premium from 1970 onwards was approximately 0.7%. That is, investors require almost the same return to invest in stocks and in 20 years government bonds. The explanations above indicate structural, fundamental reasons for a long-horizon tendency of the risk premium to decrease, or equivalently for an increase of the valuation of the aggregate stock market. However, to quantify the decrease in the equity premium is difficult and the estimates provided earlier are questionable. Although fundamental reasons may partly explain an increase of stock prices, the dramatic movements e.g. in the nineties are hard to interpret as an adjustment of stock prices toward a new fundamental value.

Another strand of recent literature has provided empirical evidence on market inefficiencies and proposed a behavioral explanation. Hirshleifer (2001) and Barberis and Thaler (2003) contain extensive surveys of behavioral finance and empirical results both for the cross-section of returns and for the aggregate stock market. Much attention has been paid to the continuation of short-term returns and their reversal in the long-run. This was documented both for the cross-section of returns by de Bondt and Thaler (1985), and Jegadeesh and Titman (1993) and for the aggregate market by Cutler, Poterba, and Summers (1991). At short run horizons of 6-12 months, past winners outperform past losers, whereas at longer horizons of e.g. 3-5 years, past losers outperform past winners.

A behavioral explanation of this phenomenon is that at horizons from 3 months to a year, investors underreact to news about fundamentals of a company or the economy. They slowly adjust their valuations to incorporate the news and create positive serial correlation in returns. However, in the adjustment process they drive prices too far from what is warranted by the fundamental news. This shows up in returns as negative correlation at longer horizons. Several behavioral models have been developed to explain the empirical evidence. Barberis, Shleifer, and Vishny (1998), henceforth BSV, assume that agents are affected by psychological biases in forming expectations about future cash flows. BSV consider a model with a representative risk-neutral investor in which the true earnings process is a random walk, but investors believe that earnings are generated by one of two regimes, a mean-reverting regime and a trend regime. When confronted with positive fundamental news investors are too conservative in extrapolating the appropriate implication for the immediate asset valuation. However, they overreact to a stream of positive fundamental news because they interpret it as representative of a new regime of higher growth.

The model is able to replicate the empirical observation of continuation and reversal of stock returns. Another behavioral model that aims at explaining the same stylized facts is Daniel, Hirshleifer, and Subrahmanyam (1998), henceforth DHS. Their model stresses the importance of biases in the interpretation of private information. DHS assume that investors are overconfident and overestimate the precision of the private signal they receive about the asset pay-off. The overconfidence increases if the private signal is confirmed by public information, but decreases slowly if the private signal contrasts with public in- formation. The model of BSV assumes that all information is public and that investors misinterpret fundamental news. In contrast, DHS emphasize overconfidence concerning private information compared to what is warranted by the public signal. These models aim to explain the continuation and reversal in the cross-section of returns. However, as suggested by Barberis and Thaler (2003), both models are also suitable to explain the aggregate market dynamics.

In this paper we consider an asset pricing model with behavioral heterogeneity and estimate the model using yearly S&P 500 data from 1871 to 2003. The model is a reformu- lation, in terms of price-to-cash flow ratios, of the asset pricing model with heterogeneous beliefs introduced by Brock and Hommes (1997, 1998). Agents are boundedly rational and have heterogeneous beliefs about future pay-offs of a risky asset. Beliefs about future cash flows are homogeneous and correct, but agents disagree on the speed the asset price will mean-revert back towards its fundamental value. A key feature of the model is the endogenous, evolutionary selection of beliefs or expectation rules based upon their relative past performance, as proposed by Brock and Hommes (1997). The estimation of our model on yearly S&P 500 data suggests that behavioral heterogeneity is significant and that there are two different regimes, a “mean reversion” regime and a “trend following” regime. To each regime, there corresponds a different (class of) investor types: fundamentalists and trend followers. These two investor types co-exist and their fractions show considerable fluctuations over time. The mean-reversion regime corresponds to the situation when the market is dominated by fundamentalists, who recognize a mispricing of the asset and expect the stock price to move back towards its fundamental value. The other trend following regime represents a situation when the market is dominated by trend followers, expecting continuation of say good news in the (near) future and expect positive stock returns. Before the 90s, the trend regime is activated only occasionally and never persisted for more than two consecutive years. However, in the late 90s the fraction of investors believing in a trend increased close to one and persisted for a number of years. The prediction of an explosive growth of the stock market by trend followers was confirmed by annual returns of more than 20% for four consecutive years. These high realized yearly returns convinced many investors to also adopt the trend following belief thus reinforcing an unprecedented deviation of stock prices from their fundamental value.

The outline of the paper is as follows. Section I discusses some closely related literature. Section II describes the asset pricing model with heterogeneous beliefs and endogenous switching, while Section III presents the estimation results. Section IV discusses empirical implications of our model, in particular the impulse response to a permanent positive shock to the fundamental and a simulation based prediction of how likely or unlikely high valuation ratios are in the future. Finally, Section V concludes.

Corresponding author: Sebastiano Manzan, Center for Nonlinear Dynamics in Economics and Finance (CeNDEF), Department of Quantitative Economics, University of Amsterdam, Roetersstraat 11, NL-1018 WB Amsterdam, The Netherlands; e-mail: s.manzan@uva.nl, webpage: http://www.fee.uva.nl/cendef/.

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Investor Sentiment and Stock Market Response to Corporate News

G. Mujtaba Mian

The NUS Business School

National University of Singapore

Singapore

E-mail: bizgmm@nus.edu.sg

Srinivasan Sankaraguruswamy

The NUS Business School

National University of Singapore

Singapore

E-mail: bizsrini@nus.edu.sg

November 13, 2007

ABSTRACT

We test the hypothesis that the prevailing market-wide investor sentiment sways the stock market response to good and bad corporate news in the direction of the sentiment. We use the Baker and Wurgler (2006) index of investor sentiment, and investigate stock price response to earnings shocks. Consistent with our hypothesis, we find that the three-day announcement period return for positive (negative) earnings news is greater for the earnings that are announced during high (low) sentiment periods than those announced during low (high) sentiment periods. Furthermore, the effect of sentiment persists in the near term. Over the 60 days following the announcement of earnings, the well-documented stock price drift associated with positive (negative) earnings news is greater for the earnings that are announced during high (low) sentiment periods than those that are announced during low (high) sentiment periods. In the cross-section, the relation between sentiment and the stock price response to news is more pronounced for small stocks, young stocks, volatile stocks, non-dividend paying stocks and distressed stocks.

Keywords: Investor Sentiment, Corporate News, Event Studies, Behavioral Finance

JEL Classification: D14, D21, G24

Introduction

Do waves of market-wide optimism or pessimism, or investor sentiment, influence the stock market response to firm specific news? According to the efficient markets view, the answer is an unequivocal no—stock prices in efficient markets have little to do with non-fundamental factors such as sentiment. Motivated by this view, the voluminous event study literature in finance and other areas of economics typically pool together events that happen during boom times with events that happen during bear periods. Tests are then conducted, for instance, to quantify the impact of various corporate events on the fundamental value of the firm2 under the maintained assumption that stock price reaction to corporate news is independent of the state of the stock market.

In contrast, both the anecdotal evidence3 and several papers in the recent behavioral finance literature suggest that the prevailing sentiment could significantly influence the way investors respond to new information and update their belief. One strand of this literature provides evidence that the optimism reflected in generic non-economic proxies of investor mood is positively correlated with the optimistic beliefs about future economic conditions (Hirshliefer and Shumway (2003), Edmans, Garcia and Norli (2007), and Puri and Robinson (2007)). To the extent that extreme bouts of market-wide investor sentiment and the mood of marginal investor are intertwined, the link between positive mood and optimistic assessments of future prospects implies a similar relation between positive sentiment and optimistic assessment of new information by investors. Furthermore, a related strand of the recent behavioral literature focuses directly on developing measures of sentiment and relating these to expected stock return (Baker and Wurgler (2006, 2007), Lemmon and Portniaguina (2006), Qiu and Welch (2006), Brown and Cliff (2005)). This literature begins with the premise that shocks to speculative demand combine with limits on arbitrage to generate mispricing in stocks. The speculative demand tends to be high (low) during periods of high (low) sentiment, which pushes up (down) the contemporaneous stock prices, and lowers (increases) the future stock returns. Given that investors often trade heavily around significant corporate news announcements4, during high (low) sentiment periods when speculative demand is high (low), investors are more likely to bid up (down) the price around a corporate news announcement. Specifically, the stock price response to good (bad) news that arrives in high sentiment period is likely to be greater (lower) than the stock price response to good (bad) news that arrives during low sentiment period, other things being equal.

Equally importantly, some of the most cited cognitive biases on the part of individuals, observed in the experimental psychology and noted in the behavioral finance literature, provide micro foundations for a hypothesized relation between sentiment and stock marker response to corporate news. Individuals tend to suffer from confirmatory bias whereby they interpret new evidence in a fashion consistent with their prior beliefs. They are reluctant to accept the inconsistent facts, attributing these to luck or faulty data gathering (Barberis and Thaler (2003), and Hirshliefer (2001)). The confirmatory bias would, therefore, lead investors to respond more strongly to good (bad) news during periods of high (low) sentiment. Moreover, as Shiller (2005) argues, investors have a tendency to form their expectations about future price changes by anchoring on recent price changes. The representativeness heuristic reinforces such extrapolation of the recent price trends. The problem gets especially severe if, as Statman, Thorley and Vorkink (2006) note, investors ignore that “rising water lifts all boats” and anchor on the absolute value of recent price changes rather than on changes relative to the market. Consequently, in time of high (low) sentiment, which tend to be preceded by stock price increases (drops), investors underreact to bad (good) news as they believe the stock price would continue its recent rise (drop). Overconfidence, social interaction5 and media also play a critical role in reinforcing the representativeness heuristic and in persuading investors to underreact to evidence that contradicts the prevailing sentiment (Shiller (2005)).

Understanding the impact of sentiment on stock market resposne to news could yield new perspectives on key debates in financial economics. First, despite a number of recent studies, the debate on the importance of sentiment is far from settled, and much remains to be learnt about the role sentiment plays in financial markets. The evidence in recent studies that stocks are mispriced in the direction of the sentiment raises the possibility that a significant amount of this mispricing occurs on the days of the arrival of news. Specifically, overreaction (underreaction) of investors to good news or undereraction (overreaction) to bad news during periods of high (low) sentiment could be an important channel through which stocks become overpriced (underpriced) during high (low) sentiment periods. A confirmation of this would not only help identify a channel through which sentiment causes mispricing but would also suggest that the importance of sentiment documented in the recent literature is not spurious. Second, by focusing on the effect of sentiment on stock price response in the short window around the announcement of news, one could garner fresh evidence on the efficiency of the instantaneous response of the stock market to new information. Many researchers interpret the evidence accumulated in the voluminous event studies literature as an indication that human psychology plays no role in how markets respond to news, and treat the evidence as a key pillar in support of the efficient market hypothesis (see, for example, Fama (1991) and Ross (2005)).6 Any evidence that proxies of sentiment influence the stock market response to news would call into question the efficiency of the stock market’s instantaneous reaction to news. Finally, the event-study methodology has been widely used by researchers in finance and other areas of economics, to quantify the impact of various corporate events on the fundamental value of the firm.7 In a world where the stock market reaction to news varies significantly across periods of high and low sentiment, it is not clear how useful it is to rely solely on the market reaction as a measure of the valuation impact of the news event.

In this paper, we examine empirically how the prevailing sentiment influences stock market response to news. Specifically, we test the hypothesis that prevailing sentiment sways the stock market response to news in the direction of the sentiment. That is, stock market response to good news is greater during high sentiment periods than that during low sentiment periods. Similarly, stock market response to bad news is greater during low sentiment periods than that during high sentiment periods.

To test our hypothesis, we rely on the proxies of the sentiment developed by Baker and Wurgler (2006, 2007). Baker and Wurgler (2007) sentiment index is based on six proxies: trading volume as measured by NYSE turnover, the dividend premium, the closed-end fund discount, the number and first day returns on IPOs, and the equity share in new issues. This index is available at monthly frequency. The corporate news event we primarily focus on is earnings surprises, although in the latter part of our paper, we confirm the robustness of our results for several other corporate events including dividend changes, stock splits and stock repurchases. Earnings news is perhaps the most prominent news event, which unlike many other corporate events, is not voluntary and is a regular feature of corporate calendars. We measure the news content of an earnings announcement by comparing the actual earnings with the analyst consensus forecast in the month prior to the earnings announcement date. We use the standard event study methodology and examine the 3-day abnormal returns around the announcement of the news events. Our analyses incorporate standard control variables that have been identified by prior research to explain the stock price reaction to earnings surprises. Our results indicate that market reacts more to good news during high sentiment periods than during low sentiment periods. Similarly, market reacts more to bad news during low sentiment periods than during high sentiment periods. We confirm that our results also hold for other corporate events, namely dividend changes, stock splits and stock repurchases.

We also examine the stock returns in the 60 days following the announcement of earnings news to see if the effect of sentiment persists or reverses during this period. The results indicate that sentiment continues to impact the stock price behavior in the period subsequent to the earnings announcement. That is, the upward stock price drift following positive earnings news, commonly documented by prior literature, is greater when earnings are announced in high sentiment periods than those that are announced during low sentiment periods. Similarly, the downward stock price drift following negative earnings news is greater for earnings that are announced during low sentiment periods. In fact, we find that there is no drift associated with negative earnings shocks that are announced during high sentiment periods. This is probably not surprising given that the sentiment measure we use has very high persistence—the autocorrelation coefficient for the monthly Baker-Wurgler index is 0.95 during our sample period. This is also consistent with the recent sentiment literature that argues that the effect of sentiment persists over weekly and monthly frequency, and reverses only at yearly horizons (Brown and Cliff (2004, 2006) and Baker and Wurgler (2006)).

The behavioral finance literature suggests that firms that are more difficult to value and harder to arbitrage are more susceptible to sentiment impacting their stock prices (see, for example, Shleifer and Vishny (1997)). More specifically, Baker and Wurgler (2006) argue that firm size, age, stock price volatility, and growth prospects are the characteristics that delineate firms that are more or less susceptible to market sentiment. Therefore, we examine whether the influence of sentiment is stronger on investor response to news for small firms, young firms, volatile firms, and growth firms. We find that sentiment indeed plays a greater role in determining the stock price reaction to corporate earnings news for these firms than for other firms.

While we document that stock market response to good (bad) news is stronger during high (low) than low (high) sentiment periods, our tests, per se, cannot discern whether stock market overreacts to good (bad) news during high (low) sentiment period or underreacts to good (bad) news during low (high) sentiment periods. For this, we rely on recent studies, example, Baker and Wurgler (2006). These studies find that both high and low sentiment periods contributes to mispricing—stocks that are more prone to sentiment such as small stocks, earn unusually high returns following periods of low returns and earn unusually low returns following periods of high sentiment.

We also consider alternative explanations for our results, but rule them out for being inconsistent with some of the evidence. One possibility is that that investors’ risk aversion changes across periods of high and low sentiment, and that explains market’s differential reaction to news over time. However, we note that for this explanation to hold, stock price response to both good and bad news should be muted during periods of low sentiment. This is because during these times, investors’ increased risk aversion pushes up the discount rate; and any news about the future cash flows is, therefore, worth less in present value terms. Our results are not consistent with this explanation as we find that stock price reaction to bad news is greater during periods of low sentiment. It is also possible that good (bad) news released during high (low) sentiment period has greater information content, and market’s greater response to good (bad) news during high (low) sentiment period simply reflects this differential strength of the news signal. To control for this possibility, we introduce the ex-post earnings change associated with each earnings surprise as an additional variable in our regression analyses. We find that our conclusion remains robust to the inclusion of this variable.

At least two recent papers have documented instances, albeit in narrow settings, where the stock market ignored the firm-level fundamentals apparently under the influence of the broad market sentiment. Lamont and Thaler (2003) document how in the case of equity carve-out of technology companies at the peak of the Internet bubble, investors valued non-technology parent and technology-oriented subsidiary companies at prices that violated the fundamental law of one price. Cooper, Dimitrov and Rau (2001) document that a mere alignment of a company’ name to what is considered fashionable in the market can enhance stock price, even when the operations of the company are little changed. They document that at the peak of the Internet bubble, companies that added dotcom to their names experienced a cumulative abnormal return of 74% in the ten days surrounding the announcement of the name change. Our paper generalizes the findings in these studies by showing that the influence of sentiment on stock market reaction to news extends beyond the narrow settings of these studies.

The rest of the paper is organized as follows. In Section II, we discuss our data selection process and research methodology. In Section III, we report our results on the effect of sentiment on stock price response to earnings news. We then examine the effect of sentiment on stock price response for three other corporate events, namely, dividend changes, stock splits and stock repurchases in Section IV. We conclude the paper in Section V.

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Accounting Anomalies and Information Uncertainty

Francis, Jennifer., Ryan LaFond, Per Olsson,  and Katherine Schipper. Accounting Anomalies and Information Uncertainty.

We examine whether rational investor responses to information uncertainty explain properties of and returns to accounting-based trading anomalies. We proxy for information uncertainty with two measures of earnings quality: the standard deviation of the residuals from a Dechow and Dichev [2002] model relating accruals to cash flows, and the absolute value of performance- adjusted abnormal accruals from a modified Jones [1991] model. Over 1982-2001, we find that accounting-based trading anomalies (post-earnings announcement drift, value-glamour, and accruals strategies) are correlated with earnings quality. Specifically, extreme anomaly portfolios have poorer earnings quality than non-extreme portfolios, and within the extreme anomaly portfolios, poor earnings quality securities are more prevalent and earn larger abnormal returns than good earnings quality securities. Consistent with greater resolution of uncertainty for poor earnings quality securities, the abnormal returns to poor quality securities converge to the abnormal returns to good quality securities as the post-portfolio formation period lengthens. Taken as a whole, these results indicate that information uncertainty plays an important role in explaining accounting anomalies.

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AN EMPIRICAL STUDY ON PRICE DISCOVERY IN THE HONG KONG EQUITY MARKET

SHI YUAN CHEN *

SUBMITTED TO THE DEPARTMENT OF ECONOMICS OF AMHERST COLLEGE

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF

BACHELOR OF ARTS WITH HONORS

PROFESSOR STEVEN RIVKIN, FACULTY ADVISOR

MAY 8, 2008

*Undergraduate student, Amherst College, Amherst, MA 01002.

Tel: (504)905-7341. E-mail: schen08@amherst.edu

ABSTRACT

This thesis investigates the impact of two separate events on the Hong Kong Stock Exchange (HKEX): the opening of the stock options market in Hong Kong in 1995 and the announcement that the exchange would be open to mainland Chinese investors in 2007. In the first case, the Hang-Seng Index is tested for evidence refuting random walk hypothesis using the Geary run test. This test was run on 8-year periods before and after the opening of the options market. The run test detected evidence of serial dependence which can be interpreted as the market being predictable or inefficient. In the second case, I examine the price relationship between shares of Chinese companies traded on both the Hong Kong stock exchange and the New York stock exchange. Using recent daily data from 2003 through 2008 across fourteen companies, I first checked to see if the stock price time series were stationary by running the Dickey Fuller test. The stock prices were found to be non-stationary, but the first differences of the stock prices or return series were stationary. This evidence of co-integration allowed a Granger causality test to be run on the return prices of two stocks. I found that price discovery existed between HKEX and NYSE as one would expect. I subsequently tested for whether or not there were any persistent price disparities between US ADRs and Hong Kong H- shares shortly after the announcement was made. I found that although all of the stocks experienced a price increase of 10% to 30% during the week of the announcement, there were no arbitrage opportunities between the US and Hong Kong markets.

Keywords: Information and Market Efficiency; Hong Kong Stock Exchange; Adaptive Markets Hypothesis

INTRODUCTION

The famous American economist James Tobin once stated that the most important implication of the efficient markets hypothesis is the channeling of investment to the most efficient users of capital (Tobin, 1982). Under this generally accepted framework, inefficiency in the stock market results in poor business investment decisions, imparting a real cost onto the economy. In the past thirty years, the consensus among economists has been that stock prices follow a random walk process and that the stock market is semi- strongly efficient under the efficient markets hypothesis proposed by Eugene Fama (Fama, 1970). Recently however, a study has found evidence of weekly returns of the US stock market rejecting the random walk hypothesis (Lo and MacKinlay, 1988). The focus of this paper is to survey the price behavior and efficiency of the Hong Kong stock exchange in response to important events.

The Hong Kong stock market has developed rapidly since its establishment in the late 1800s. It has always played a large role in facilitating trade between China and the rest of the world, and this continues to be true in the capital markets today. It is currently the third largest stock market in Asia and the sixth largest in the world. For more than a decade, Hong Kong has been recognized for closely following free-market principles; the Wall Street Journal gave Hong Kong the title of World’s Freest Economy for the 13^th  consecutive year based on a ranking system that considers several factors such as trade freedom, investment freedom, financial freedom, and property rights.

The two events this paper looks at are the launch of the Hong Kong stock options market on September 8th, 1995 and China’s announcement on August 20th, 2007 that the Hong Kong stock market would finally become accessible to the millions of investors in  mainland China. The opening of the options market in the Hong Kong stock exchange coincided with a regulatory decision to allow naked short selling in 1995. I expect that the level of efficiency in the stock market will rise in the periods following 1995 due to these additional investment options and changes in regulation. China’s announcement in 2007 gave investors a place to invest their money outside of the Shanghai stock exchange and the Shenzhen stock exchange, both of which have inefficient prices due to constraints on short-sales. A study found that short-sales constraints in stock markets tend to cause stock price overvaluation (Chang, 2004). Because of the high premium on shares traded in Shanghai compared to Hong Kong and the US, I surmise that the opening of the Hong Kong market to Chinese investors created inefficiencies and possibly arbitrage opportunities for global investors. An estimated $100 billion USD of capital inflow within the first year alone would account for 3-4% of expected growth to the market value of the Hong Kong Stock Exchange.

Although mainland Chinese investors did not have direct access to the Hong Kong market until late 2007, anticipation of the entry of optimistic investors would have had an effect on the stock prices at announcement. Given a relatively efficient pricing structure in the free-market Hong Kong stock exchange and an overvalued prices in the restricted Shanghai stock exchange, it is not entirely obvious what would happen to prices when investors are allowed to move from inefficient markets to efficient ones.

In the second half of the paper, I discuss my testing for the following hypotheses: 1) there are long-term cointegrations between the prices of Hong Kong-traded shares and US-traded shares of the same company and 2) the opening of the market to Chinese investors in 2007 caused a period of high price volatility. As a result, the market faced  temporary inefficiencies and possible arbitrage opportunities that disappeared once the market caught on. In order to test for cointegration, the Granger causality test requires that the set of underlying time series be stationary. The Dickey-Fuller test, the standard test for autocorrelation, was used to detect whether or not the time series dataset had unit root (Dickey and Fuller, 1979). I then ran the Granger causality test on the first difference series or return time series which was found to be stationary. Finally, I simulated an arbitrage trading rule in an effort to detect if profitable opportunities materialized immediately after the announcement.

Section 2 discusses the theoretical foundations underlying the application and evaluation of the tests for price relationship. The section begins with a discussion of the efficient markets hypothesis and adaptive markets hypothesis followed by a summary of the characteristics of the daily price data collected from the Hong Kong and New York stock markets. Sections 3, 4 and 5 discuss the data set, methodology, and empirical results respectively. Section 6 concludes the paper with a summary of my results from testing the dual market and its importance in understanding price discovery in the Hong Kong stock exchange.

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An Empirical Study of the Presidential Elections Effect On Stock Market in Taiwan, South Korea, Singapore, Philippine, and Indonesia

by

LING-FANG LIU

A dissertation presented in part consideration for the

degree of MA Finance and Investment

The University of Nottingham

2007

Abstract

The behavior of stock market around election periods has been investigated for several decades but the presidential elections held in Asian countries have not been analyzed in the previous studies. The main objective of this study is to examine the return pattern around presidential election period in the stock markets of Taiwan, South Korea, Singapore, the Philippines, and Indonesia during the sample period 1996-2005. It has been found that stock markets generate positive abnormal returns fifteen-day period before and after the presidential elections, and that the magnitude of abnormal return is greatest in the presidential elections held in less-free countries when an incumbent loses. In addition, other financial and political factors have been found to play an important role in influencing the return pattern around presidential elections. This dissertation may be of interest to investors and financial analysts, especially those who intend to put money into Asian stock market during the coming South Korea 2007 and Taiwan 2008 presidential elections.

Introduction

One of the most fundamental theories in financial economics is the theory of market efficiency. In an efficient market all available information will be embodied in the stock price implying that investors cannot earn abnormal returns. Although the theory of market efficiency has been widely known in the real world, the various studies that investigate capital market efficiency have detected a large number of market anomalies that question the view on the efficiency of the markets. Some of the most profound market anomalies that have been found are as following. The P/E effect: Basu (1977) discovered that portfolios of low P/E ratio stocks have higher returns than do high P/E portfolios; The size effect: Banz (1981) found that the average annual returns are consistently higher for small than in large firms’ portfolio; The Fama and French three factor model: Fama and French (1993) found that the group with the highest book to market ratio outperformed those with the lower ratio; Seasonalities: Fama (1965), Bonin and Moses (1974) detected that stocks exhibit significant lower returns over the period between Fridays close and Mondays close. In addition, returns are much higher during the month of January than in any other month.

Besides these anomalies which are related to firms’ characteristic and special trading time, a large number of studies have discovered the pattern of common stock returns over the presidential elections.

Allvine and O’Neill (1980) presented strong evidence in support of the relation between stock market returns and the presidential election cycle. They found that stock market had a rising trend over the two years prior to the United State’s presidential elections. Also, Huang (1985), Smith (1992), and Johnson et al. (1999)  investigated that stock returns were significantly higher in the second half of the presidential term. However, these researches were constrained on the relationship between U.S. stock market and presidential elections.

In 2000, Pantzalis, Stangeland, and Turtle are the first researchers to examine the behaviour of stock market indices around political election dates in an international scale. Their findings displayed that positive abnormal returns lead up to the election week, and that the positive returns are shown to be a function of country degree of political, economic, and press freedom and a function of election timing and the success of the incumbent in being re-election.

Objectives

Although the study mentioned above have gathered a large number of election samples to examine the market behaviour around election dates, the presidential elections held by Asian countries in recent years were not included in the sample pool. As a result of the lack of empirical testing on the effect of Asian presidential elections on stock markets, this dissertation will concentrate on the stock markets of five Asian countries- Taiwan, South Korea, Singapore, the Philippines, and Indonesia that hold presidential elections in the period of 1996-2005 to examine their return patterns around elections. By analyzing these countries market behaviour, the following questions can be addressed:

1.   Are there abnormal returns during pre-election and post-election period in Taiwanese, South Korean, Singaporean, Philippines, and Indonesia stock markets?

2.    Does the political and press freedom rankings difference among these countries influence the level of abnormal returns during election period?

3.   Does the outcome of elections (incumbent win or lose) influence the level of abnormal returns during election period?

4.   Are there any other potential financial or political factors leading different level of abnormal return among these countries? Structure

The rest of the chapters within the dissertation are organized as follows. Chapter 2 gives a brief overview of the political background and stock market development of the five sample countries. Chapter 3 reviews previous empirical studies that analyze the stock market return pattern around elections and provides possible theories to explain the return pattern. Chapter 4 describes the data and methodology adopted in this dissertation. Chapter 5 presents the empirical results of the dissertation and analyzes the findings with literature reviewed. Chapter 6 summarizes the conclusions, limitations of the study and recommendations on future research directions.

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An Empirical Study of Serial Correlation in Stock Returns Cause-Effect Relationship for Excess Returns from Momentum Trading in the Norwegian Market

Maximilian Brodin and Øyvind Abusdal

Supervisor: Per Östberg

Master Thesis in Financial Economics

NORGES HANDELSHØYSKOLE

This thesis was written as a part of the Master of Science in Economics and Business

Administration program - Major in Financial Economics. 

Abstract

This paper documents the maximum theoretical excess return on the market to 3.8% monthly from momentum trading in Norway and estimates the economical excess return to be marginally higher than 1% per month when accounting for microstructure influences. We find that the excess returns of various momentum strategies are not explained by systematic risk or exposure to other factors such as size or book-to-market value. We uncover a positive correlation between types of investor and the degree of momentum in the market. Studying business cycles has provided evidence of reversals following bust periods which are in-line with behavioral theories of overreaction.

Introduction

Can historic observations of a publically traded company’s performance be used to predict their future performance? That question is the essence of this paper and there are several ways of answering it; for example one could look at various performance measures such as earnings or stock prices. We have chosen to work with the latter, or more specifically, we are examining whether there is a tendency for stock returns to trend in the same direction and thereby establish whether there is momentum in the stock market. We test whether or not it is possible to earn abnormal returns on the Oslo Stock Exchange by forming winner and loser portfolios on the basis of past stock returns.

Empirical evidence from vast research in several markets document this anomaly known as momentum. A recent London Business School research with 108 years of data covering about 85% of the world equity market capitalization concluded that “The momentum effect, both in the UK and globally, has been pervasive and persistent” (Dimson, Marsh and Staunton, 2008). Rouwenhorst (1998) finds in a study of 12 European countries including Norway in the period from 1978 to 1996 that an internationally diversified momentum portfolio earns about 1% excess return on the market per month.

Much of the research on momentum has been dedicated to trying to explain the excess return earned from following such a strategy by adjusting for various factors such as the size effect, book-to-market ratios and market risk. During the last 25 years, attempting to explain investor behavior has also gained a lot of attention in trying to explain the momentum effect.

Jegadeesh and Titman (1993) find that excess returns from following momentum strategies are not due to systematic risk or to delayed stock price reactions to common factors such as the January effect. Jegadeesh and Titman (2001) also present evidence which supports the prediction of behavioral finance models that suggest that the momentum effect is due to overreactions in the market. Grinblatt and Keloharju (2000) analyze different investor groups and find that the degree of momentum behavior seems to be strongly correlated to the degree of sophistication of the investor types.

Kloster-Jensen (2005) finds that a momentum strategy on the Oslo Stock Exchange (OSE) yields significant positive returns, but this is due to a large extent by compensation for taking on added systematic risk. Hence, he concluded that there is no momentum effect in the Norwegian market. Conversely, Myklebust (2007) examines sixteen different time-strategies for momentum trading on the Oslo Stock Exchange and finds that all strategies yielded positive excess returns, which could not be explained by market risk or the size effect.

Up until now OSE momentum research has been limited to using data samples of stocks that have been traded during the whole sample periods. This has narrowed the data sets to about 70 stocks which can be compared to the actual number of almost 600 stocks that have been listed during the last eleven years, which is the time period we examine. Our approach is different; and by analyzing a dataset of 598 stocks we can provide evidence of the maximum theoretical excess return that can be earned from a momentum strategy on the OSE. This is accomplished by 16 different time-strategies that are comprised of a forming period (ranking period of the stocks) and a holding period. These strategies are evaluated by accounting for risk exposure, or more precisely systematic risk (CAPM) and the size effect using a two- factor regression model.

The total data set is then screened based on a set of rules that provides us with 123 stocks suitable for evaluating the maximum economic excess return that can be earned (i.e. a dataset that gives us the opportunity to test the momentum strategy when accounting for microstructure influences such as transaction costs). In this part of the study we explore one time-strategy, which we call “the best strategy portfolio”.

As with many of our predecessors, we attempt to explain excess return by accounting for various factors; here we expand the model to include a third factor: book-to market ratio, using the Fama and French three factor model.

We also probe areas that have not been explored in earlier momentum research for the Norwegian stock market. We test for seasonality by deducting and secluding January returns. Through descriptive studies of the dataset we highlight any under or over-representation among sectors in the momentum portfolios and provide intuitive explanations to why some sectors are biased towards either the loser portfolio or the winner portfolio. Moreover, we examine the momentum returns throughout business cycles to identify any variations in good times and bad times.

Finally, we expand the discussion of momentum explanations by building on Grinblatt and Keloharju’s 2000 research on the behavior of different investor types. We find that there has been a development over time in the type of investors that are active on the Oslo Stock Exchange and we examine whether this could be correlated to an increase (or a decrease) in the momentum effect over time.

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