Market Anomalies in the BRIC Countries. Stock Market Evidence for Size and Price-to-Book Effects

Table of Contents

List of Abbreviations

List of Variables

List of Tables

1 Introduction

2 The BRIC Concept
2.1 Introducing the BRIC Countries
2.2 Heterogeneous Conditions
2.3 Volatility of the Investors’ Interest in the BRIC Markets
3 Theoretical Background of Stock Market Anomalies
3.1 Stock Market Anomalies - Definition
3.2 Capital Market Model - CAPM
3.2.1 The Model
3.2.2 Theory of Efficient Markets
3.2.3 Criticism of the CAPM
3.3 Conditions for Anomalies in the BRIC Countries
3.3.1 Market Efficiency in the BRIC Countries
3.3.2 Brazil
3.3.3 Russia
3.3.4 India
3.3.5 China
3.3.6 Hypothesis

4 Stock Market Anomalies
4.1 Valuation Anomalies
4.1.1 Size Effect
4.1.2 Price-to-Book Effect / Book-to-Market Effect
4.1.3 Price-Earnings-Ratio Effect
4.2 Calendar Anomalies
4.2.1 January Effect and Weekend Effect

5 Can further Risk Factors Invalidate Valuation Anomalies?
5.1 Fama and French’s Multi-Factor Model - Approach
5.2 Fama and French’s Three-Factor Model

6 Research Overview - Valuation Anomalies in the BRIC Countries
6.1 Brazil
6.2 Russia
6.3 India
6.4 China

7 Size and Price-to-Book Effect Analysis
7.1 Data and Methodology
7.1.1 Data
7.1.2 Methodology
7.2 Examination of the Brazilian Stock Market
7.2.1 The Brazilian Sample
7.2.2 Empirical Evidence for the Brazilian Stock Market
7.3 Examination of the Russian Stock Market
7.3.1 The Russian Sample
7.3.2 Empirical Evidence for the Russian Stock Market
7.4 Examination of the Indian Stock Market
7.4.1 The Indian Sample
7.4.2 Empirical Evidence for the Indian Stock Market
7.5 Examination of the Chinese Stock Market
7.5.1 The Chinese Sample
7.5.2 Empirical Evidence for the Chinese Stock Market
7.6 Discussion

8 Conclusion

Mathematical Appendix

References

List of Abbreviations

illustration not visible in this excerpt

List of Variables

illustration not visible in this excerpt

List of Tables

Table A1: Average monthly returns (in %) for portfolios, based on ME at different levels of systematic risk for the Brazilian stock market

Table A2: Average monthly returns (in %) for portfolios, based on BM at different levels of systematic risk for the Brazilian stock market

Table A3: Risk premia estimates from the cross-sectional regressions for the Brazilian stock market

Table B1: Average monthly returns (in %) for portfolios, based on ME at different levels of systematic risk for the Russian stock market

Table B2: Average monthly returns (in %) for portfolios, based on BM at different levels of systematic risk for the Russian stock market

Table B3: Risk premia estimates from the cross-sectional regressions for the Russian stock market

Table C1: Average monthly returns (in %) for portfolios, based on ME at different levels of systematic risk for the Indian stock market

Table C2: Average monthly Returns (in %) for Portfolios based on BM at different levels of systematic Risk for the Indian stock market

Table C3: Risk premia estimates from the cross-sectional regressions for the Indian stock mar- ket.

Table D1: Average monthly returns (in %) for portfolios, based on ME at different levels of systematic risk for the Chinese stock market

Table D2: Average monthly returns (in %) for portfolios based on BM at different levels of systematic risk for the Chinese stock market

Table D3: Risk premia estimates from the cross-sectional regressions for the Chinese stock market

1 Introduction

Most studies on stock market anomalies in the last 40 years have been done on anomalies in developed equity markets. Often, their focus has been on the size and the price-to-book effect. Based on these findings, many institutional investors apply strategies to comprise their portfo- lios accordingly. For instance, there are mutual funds, which specialize in smaller stocks, with an under-average market capitalization relative to the major stock market. Other funds concen- trate their investments on so-called value stocks, which trade at a relatively low multiple of stock price to book-equity value.¹ Investors are free to choose between different strategies, which are based on the findings of market anomaly examinations in the developed stock mar- kets.

In order to fill a gap in the research on developing equity markets, especially emerging markets, this study deals with market anomalies in the BRIC countries, specifically focusing on identi- fying the anomalies size and price-to-book effect. One problem for researchers on emerging stock market anomalies in the past might have been the limited quality and time horizon of data available for emerging markets. Today, as a satisfying timespan with high quality data for a decent analysis of BRICs market anomalies has been achieved, it is time to validate and possi- bly adjust former results.

However, the reason for an analysis regarding stock market anomalies in the BRIC countries is not exclusively limited to the lack of contemporary studies on this topic. The emerging markets in general, and, specifically, the BRIC stock markets are very interesting and valuable objects for respective examinations, since they still provide an enormous growth potential. The markets naturally show a high volatility. Under the current circumstances, most stocks in emerging stock markets seem to be undervalued. This is why at the moment, experts are quoted, who bring the emerging stock markets into the investors’ focus. This makes it even more interesting to exam- ine factors, which may have an effect on stock returns in these markets. Within the set of emerg- ing markets, the BRIC’s equity markets are analyzed specifically because of their sheer size, future prospective for international investors, and a number of important major financial re- forms implemented in the last years.

This study’s approach is to explain the established market anomalies and point at factors, which may enforce size and price-to-book effects in each BRIC country. Therefore, after presenting the BRIC concept in chapter 2, the standard method to estimate the stock return, the Capital Asset Pricing Model (CAPM), is introduced in chapter 3 in order to identify possible weak- nesses and certain anomalies, which have been identified in the research. The most common anomalies will be introduced in chapter 4. Subsequently, an alternative method to explain the stock return, the Fama / French three-factor model is discussed as a possibility to identify fur- ther risk factors, which can invalidate anomalies with respect to the CAPM, in chapter 5. Fur- thermore, a brief overview on previous studies, which include valuation anomalies in the re- spective countries, is given in chapter 6. In the empirical part of chapter 7, each country is analyzed individually with respect to size and price-to-book effects. However, the study applies the same empirical analysis for each stock market in order to obtain comparable results, choos- ing a timespan, which covers the maximum period for which sufficient data is available in all stock markets. Two approaches are used per country. The first, to identify the mentioned stock market anomalies, the second to explain the cross-section of stock returns by means of three proxies for risk, namely systematic risk in form of CAPM-beta, size and book-to-market equity ratio. The empirical part of this examination investigates the time frame from January 1996 until June 2015 and uses a total sample of 6,054 stocks throughout the four stock markets. In the conclusion, the study’s results are summarized and findings presented.

2 The BRIC Concept

This chapter gives an impression on the origin, the development and the current relevance of the BRIC country concept. Furthermore, different preconditions and prospects in the respective countries are discussed.

2.1 Introducing the BRIC Countries

In 2001, the term BRIC was established by the institutional investment firm Goldman Sachs as a catchy acronym for the four largest rapidly emerging markets Brazil, Russia, India and China. In the Goldman Sachs research paper “Building Better Economic BRICs”, Jim O’Neill, head of the firm’s global economic research department, emphasized the relationship between the G7 and the emerging market economies of the BRIC countries at the particular state of the world economy. G7 stands for the group of the world’s seven major advanced economies. Pre- dicting scenarios, in which the economic growth of the BRIC states significantly exceeds that of the G7 countries, investors started to zoom in on the equity of these countries for the first time.² In 2003, a second paper about the topic with more detailed predictions was published called: “Dreaming With BRICs: The Path to 2050”. According to this study, by 2050, the BRICs are likely to catch up with the six major advanced industrial economies at the time of writing, which are: The United States, Japan, Germany, Great Britain, France, and Italy. The paper paints the picture of the BRICs becoming the world’s major source of demand, growth, and purchasing power, whereas the advanced economies will suffer from slow growth and an aging population within the next 35 years.³ Subsequently, the term quickly became part of the com- mon Wall Street vocabulary, and an investment boom in these four markets began. In 2006, Goldman Sachs founded the first BRIC-dedicated investment fund, and many investment firms followed the lead by offering similarly structured financial products.

Although the four countries differ dramatically among each other in matters of strengths and development challenges, they have at least two things in common: They are large and have a significant growth potential. The first aspect is not only related to landmass, but especially to population. The second aspect is based on a certain underdevelopment to different extents. Ac- cording to the 2014 World Bank data, the four economies, headed by China and India, account for almost 42 % of the world’s population, but create only about 21 % of the world’s gross domestic product (GDP) in US dollar.⁴ This disproportion is both, an indicator for the potential that these economies adhere to, and a hint at the fact that O’Neill’s predictions are valid, since the disproportion in 2003 was far more extreme than the one shown by the last available data.

The cooperation of the four countries was particularly enforced in recent years by the Russian President Putin. Several multilateral agreements between the states were assigned and meetings are held annually primarily under his lead, giving the acronym BRICs a meaning beyond its employment as an investment term. At the end of 2010, the BRIC countries agreed to invite South Africa, which had shown a significant economic growth at the time, to join the so-called BRIC alliance. In this paper, only the primary BRIC countries are considered because the pop- ulation size of South Africa does not fit into the sample of countries exceeding the 100 million inhabitants threshold.

2.2 Heterogeneous Conditions

As mentioned above, the BRIC states are not a homogeneous group with a lot of joint charac- teristics. Besides, the countries being scattered across three continents, individual economic strengths and weaknesses can be observed. This chapter is meant to describe these differences in brief. Additionally, it is needless to say that both, domestic and foreign stock-investors were confronted with different degrees of market liberalization due to individual regulatory conditions in the particular countries, which can be important when it comes to possible market anomalies. These differences are considered in chapter 3.4, which deals with preconditions for anomalies in each BRIC country.

The 2003 Goldman Sachs research paper draws the conclusion that by 2016 China would be the world’s largest economic power after the USA. Being quite optimistic about the country’s growth rates, the study still underestimated its potential, and already in 2010, the forecasted event took place: China overtook Japan in terms of GDP. Especially the huge population, which represents a cheap workforce and domestic demand, is a key driver of this development. Cur- rently, China is the biggest player in exports as well, serving the world primarily with cheap mass products, but at the same time turning the focus on the development of more innovative products. Thus, China is highly dependent on foreign demand, and, therefore, on the world’s economic situation. A declining demand, due to the recent global economic lull, puts pressure on Chinese exporters, and, simultaneously, lowers the domestic consumption resulting in the government announcing an annual GDP growth rate of 6.9 percent for 2015, the lowest one since 1991. Nevertheless, still facing economic growth rates around the seven percent level, another significant threat is the growing demand for natural resources, especially fossil fuels. Since a long-term access to these resources is of major importance for the Chinese government, they have been deepening their ties with strategic partners like Brazil, Iran, and especially Af- rican states in the last years. China is the BRIC country that faced the strongest growth in the past years, with temporary rates in the double-digit range, and continues to grow steadily until today. This development makes investments in the Chinese stock market an exciting oppor- tunity.

The second Asian BRIC state, India, shows similar current GDP growth rates, yet finding itself in quite an early stage of the industrialization process compared to China. A lot of India’s enormous workforce is still bound to the agricultural sector whilst the lion’s share of the coun- try’s economic growth is generated in the service sector. Therefore, one opportunity in the In- dian economy is to increase efficiency in the agricultural sector in order to make a larger work- force available to the labor-intensive service and industrial sector. As a legacy of the British Empire, India has one of the largest English-speaking populations in the world, which makes it a target for outsourcing company activities like call centers and IT consulting. This is an economic development, which is likely to continue in the future. Also, domestic consumption represents a significant factor for India’s growth. In order to keep the consumption growing, one important challenge will be the government’s fight against poverty. Thus, the Indian government established several programs, for instance the supply of the poor with basic commodities at subsidized prices. This results in a higher disposable income of this part of the population leading to increased spending in other sectors.

The strong heterogeneity amongst the BRIC countries becomes particularly apparent when one focuses on Russia. While China and India essentially constitute an immense workforce in the industry and service sectors as well as a significant local consumption power, Russia is primar- ily a global player in the supply of raw materials like oil and other commodities. Therefore, Russia´s economic wellbeing is highly dependent on the international oil price. Especially the world financial crisis in 2008 affected Russia´s economy quite severely and led to a regression.

After having recovered from this crisis, the country currently finds itself in another precarious situation. On the one hand, the economy suffers from a historic decrease in the prices for oil and gas, due to a current excess supply on the global market, on the other hand, President Putin’s policy of expanding the Russian Federation westwards led to harmful EU and US sanctions. In March 2014, Russia annexed the Crimea peninsula, which had belonged to Ukrainian territory until then. In the same context, Russia is suspected of being involved in the civil war in eastern Ukraine, supporting separatists who intend to form an independent pro-Russian republic. As a respond to these arrangements at its western borders sanctions against trade with certain Rus- sian companies were imposed by the USA and the EU. Both, the sanctions and the decreasing oil price, led to a strong ruble devaluation and are likely to result in another recession, which is projected to occur in 2015 with a negative growth rate in GDP. Because of its low economic diversification, Russia’s main threat, therefore, will be a volatile oil price in the future and its foreign affair policies.

Compared to the rest of the BRIC countries’ economic preconditions, Brazil is located some- where in the middle. Equipped with natural resources in abundance, Latin America´s largest economy managed to become self-sufficient in oil by 2006. Drivers of the GDP are especially crude oil exports as well as agriculture and the manufacturing sector. Until 2002, the Goldman Sachs predictions regarding the economic growth of the BRICs could be proven true for Bra- zil. The country was one of the fastest-growing major economies in the world, with an average growth rate around five percent. However, since then, growth rates have been declining, until the bottom was reached in 2015, resulting in the worst recession since the last 25 years. The decreasing domestic consumption, induced by a galloping inflation, resulted in a plunging industrial production and an abysmal consumer confidence. The main challenge for the Brazilian government, therefore, is fighting inflation and supporting domestic consumption sustainably as well as keeping investors in the country.

For all the BRIC countries, the Goldman Sachs predictions were true to certain extents and at different time periods. However, the individual current situations do not exactly fit into the projection scheme, particularly concerning Russia and Brazil. Nevertheless, the countries main- tain to be the world’s largest and most interesting emerging markets, and, thus, present exciting stock investment opportunities with different risk factors for the respective economies.

2.3 Volatility of the Investors’ Interest in the BRIC Markets

After the coinage of the acronym BRIC in 2001, investors poured a lot of money in the countries’ stock markets, expecting high returns because of the favorable growth perspectives. Also, after the financial crisis in 2008, which exposed the weakness of the so-called advanced economies, investors were attracted to the BRIC stock markets.

The recent development shows that foreign investors seem to be threatened by the alarming economic signals, which are currently sent especially by Russia and Brazil. Even the founder of the term, Goldman Sachs, is in doubt of the BRICs’ future prospects, and the bank’s asset management unit folded its money-losing BRIC fund in October 2015. After 14 years, the BRIC era has come to an end for Goldman Sachs. Even though the economies may be stumbling, it is yet far too early to declare the end of this era. Stumbling does not necessarily mean crumbling, and each of the BRICs could easily rebound in a certain period of time, depending on the indi- vidual solutions of the respective problems that their economies are facing.

3 Theoretical Background of Stock Market Anomalies

In order to pinpoint factors, which make the BRIC countries exciting to look at concerning market anomalies, this chapter introduces the theoretical background, which prevalent market anomalies are based on. Eventually, the countries’ specificities of these factors present the pos- sibility to formulate presumptions about to which extent the anomalies, size and price-to-book effect, are likely to occur in the different markets. This is done by formulating a hypothesis in chapter 3.3.6.

3.1 Stock Market Anomalies - Definition

Market anomalies originate in markets consisting of stocks, which are traded at prices that differ from their intrinsic values at that time. The market, therefore, provides the possibility to gain abnormal returns by engaging in the trade of these stocks. Consequently, an important variable is the stock’s expected return, when it comes to the identification of market anomalies. The stock’s expected return can be obtained by applying a certain market model. Thus, difference between the observed return and the return determined by the market model is an abnormal return. The anomalies examined in research are generally determined as stock returns that mis- match the stock return explained by means of the capital asset pricing model (CAPM). Hence, whenever mentioning market anomalies, this thesis refers to the general approach and assumes the CAPM to be the standard market model. The abnormal return is defined as the gap between the return explained by the model and the actual return.

3.2 Capital Market Model - CAPM

The CAPM in financial theory is a method to explain the return on an investment in a risk- bearing asset. Developed in the 1960ies, by Sharp, Lintner and Mossin, based on Markowitz’ portfolio theory and the assumptions of the efficient market hypothesis, which is explained later on, has always been and still is the most common device to estimate stock returns in practice.⁵ The underlying principle is that company or industry-specific events have very little impact on an asset’s required return. The relevant risk is the market risk, which refers to the sensitivity of the assets’ returns to the returns of the market as a whole. The model breaks down the assets’ expected return only on one factor, the assets’ systematic risk, which cannot be eliminated by diversification.

3.2.1 The Model

The validity of the CAPM is linked to a certain set of major assumptions. Sharpe, Lintner and Mossin assumed that all market participants are risk-averse individuals, who base their invest- ment decisions on the stock return’s expectancy value and variance.⁶ Further assumptions re- garding the investors are homogeneous expectations and a planning horizon of one period. In- vestors are operating on a perfectly competitive market, which is endowed with a predefined set of perfectly divisible assets. Additionally, a risk-free asset exists, and market participants have the possibility to borrow or invest money at this asset’s risk-free rate.⁷ Thus, all investors have identical opportunity sets.⁸

Given these assumptions, the basic idea behind the CAPM is that investors can minimize their portfolio’s overall risk by investing in a mix of risky assets, which are not perfectly positively correlated. In such a diversified portfolio, a stock’s individual risk is no longer the main source of the overall risk. In fact, it is mainly determined by the portfolio stock return’s covariance, the systematic risk. The stock’s individual risks, such as management abilities or company- specific production decisions, can be eliminated by diversification. The remaining systematic risk of the investment assets is determined by general political and economic risks, which sur- vive the process of diversification and are compensated by a risk premium, by which the effi- cient portfolio outperforms the risk-free asset’s return.⁹ Since investors act rationally, as as- sumed in the CAPM, they will only hold portfolios, which are risk-efficient, meaning that nei- ther a portfolio with the same or a lower risk showing a higher return nor a portfolio which combines the same or a higher return with a lower risk level exist. A rational investor will, therefore, always invest in the efficient portfolio, regardless of the individual risk preference. According to Tobin’s separation theorem, the efficient portfolio creation is the first step, fol- lowed by the decision whether to lend or borrow, depending on the investor’s preference to- wards risks. Thus, every investor holds a combination of the risk-free asset and the efficient market portfolio.¹⁰ In the general equilibrium of the CAPM, demand and supply are equal so that the investors demand the exact market portfolio.

In order to determine an individual stock’s return, first, the capital market line (CML) is considered, which shows the expected overall return as a result of the standard deviation for combinations of the market portfolio and a risk-free asset.

The slope of the CML is given by:

illustration not visible in this excerpt

In this context, -0 denotes for the combined portfolios’ return, whereas -/ and -. refer to the market portfolio and a risk-free asset’s return. The standard deviation for the combined portfo- lio’s and the market portfolio’s returns is given by A0 and A/, respectively. In the next step, another portfolio is created, consisting of the market portfolio and a single stock. The expected return (#B-0C) for this portfolio and it’s standard deviation (A0) are:

illustration not visible in this excerpt

Here, stands for the rate of capital, which is invested in the individual stock. Depending on how is modified, it has a certain influence on both, the respective portfolio return and standard deviation. This relation can be traced out as a continuous graph with a slope that is determined by the quotient of the above-mentioned equation’s derivatives with respect to . In the opti- mum, must equal zero, since the optimal portfolio already includes the optimal share of stock

. Therefore, the optimum slope is given by:

illustration not visible in this excerpt

The equation shows the above-mentioned CAPM implication that the expected return on an

individual stock is a linear function of its systematic risk , which cannot be eliminated by

diversification. If stock return and market return are perfectly correlated, the stock’s risk premium equals the market portfolio’s risk premium ( =1). For further details of the calculations applied to obtain the CAPM, the author refers to the mathematical appendix.

3.2.2 Theory of Efficient Markets

One very important market condition that the CAPM is deeply associated with is the validity of the efficient market hypothesis (EMH).¹¹ In order to identify possible assumption weak- nesses in the subsequently discussed markets, the EMH must be plunged into beforehand.

This EMH asserts that investors cannot make any excess return above what is consistent with the stock’s systematic risk, since prices always include all relevant information as soon as they become available.¹² Fama (1970) brought together all relevant research that was done until that time, and describes three different specifications of capital market efficiency:

Weak-form efficiency is based on the assumption that all past information on stock price de- velopment is priced in a security’s value. Therefore, stock returns will follow a “random walk” and cannot be predicted. This “random walk model” implies that in stock prices, which are not characterized by it, the return-generating process is dominated by a temporary component, and, thus, future returns can be predicted by respective historical return rates.¹³ When researchers predominantly found proof for a weak-form efficiency in several markets, the concept was ex- tended to other publicly available information, resulting in the semi-strong form of market ef- ficiency. In the strong form of market efficiency, stock prices comprise all publicly and non- publicly available information, including information, which is exclusively at hand to a limited set of market participants. Most tests of market efficiency in research are being conducted on the weak form efficiency. Thus, the following chapters will mainly discuss the weak form of market efficiency. A review of the empirical research shows that most markets are at least semi- strong efficient. Factors in real world markets that can be a source of inefficiency are: transac- tion costs, information that is not freely available to all investors, and disagreement among investors about the implications of given information. Fama explicitly points out that these factors are sufficient rather than necessary conditions with respect to the EMH.¹⁴ Yet individual characteristics regarding these factors can at least give hints at the validity of the CAPM, and, thus, possible anomalies in the respective market.¹⁵

Following Loistl’s theory from 1990, the different contents of the term capital market efficiency can be further divided into three distinct kinds of efficiency: technical, informational and oper- ational efficiency.¹⁶ Besides the informational efficiency that is already covered by the Fama implications above, institutional efficiency could be of special interest regarding market effi- ciencies in emerging markets. Also named operational efficiency, institutional efficiency refers to the institutional framework of the processing of capital market transactions.¹⁷ Although in a perfect CAPM environment, there are no frictions by institutions or transaction costs in the market. Reality, especially in young markets, of course looks different. Thus, it might addition- ally be interesting to look at the BRIC countries’ operational efficiency, which contains the individual market’s efficiency regarding competition, trade, transaction and market access. In Loistl’s context, competition efficiency is given, if a single investor’s transaction has no influence on the investment asset’s price, which highly depends on the market’s liquidity. Trade efficiency refers to the investor’s possibility to take any risk position by combining any set of securities. Whenever there are prohibitions or limitations that put ties to this possibility, the market is trade-inefficient to a certain extent.¹⁸ Transaction efficiency deals with the occurrence of transaction costs and the ease of proceeding transactions at the respective market places, whereas market access efficiency demands a perfectly competitive market without barriers that prohibit new players from entering the market.

In summary, the degree of market efficiency is subject to the individual market’s information efficiency and also institutional preconditions.

3.2.3 Criticism of the CAPM

The traditional form of the CAPM has constantly been questioned, particularly regarding its fundamental assumptions. To give an impression, the most common approaches of CAPM criticism are summarized in this part.

For example, the creation of the efficient portfolio for an individual investor is argued to be problematic. Marginal adjustments of a portfolio, in order to maintain an efficient portfolio structure, might be prohibited by significant transaction costs that outweigh their future bene- fits. Also, the fiscal system can suffer from biases supplying incentives for investors to create portfolios that minimize their personal tax liability, known as the “clientele effect”.¹⁹

Others claim that even if the fact of risk-free lending and investing at the same rate is accepted, this assumption still ignores inflation effects, thus, -. does not stand for an investment in real terms. Future inflation rates are neither pre-determined nor do they affect individuals equally. In order to resolve this problem, several attempts have been made to include conditions of inflation into the CAPM framework, resulting in a bunch of CAPM variations.²⁰

Additional weaknesses are located in the selection of the market portfolio. Roll (1976) exam- ined the fact that the definition of the market portfolio is crucial to the CAPM’s output. By definition, the market portfolio should include every asset available to investors worldwide. Roll pointed out that the true market portfolio has an unknown composition, and that such a portfolio is almost impossible to constitute. He demonstrated that marginal variation in the mar- ket portfolio can result in a radical altering of a security’s expected return, as determined by the CAPM.²¹ Regardless of the capital market definition problem, a further approach of challenging the CAPM is that up and down market portfolio movements are dominated by price changes in the securities of larger companies, which account for significant shares of total market capitalization. In the sense of Fama and French (1992), institutional portfolio fund managers are driven to invest in these companies, although they might be outperformed by smaller companies in relative terms. Put simply, fund managers, with perhaps billions to spend, neither have the time nor the research budgets to investigate on innumerable companies with small capitalizations. Thus, these companies are partly neglected by the market.²²

3.3 Conditions for Anomalies in the BRIC Countries

As seen in the foregoing chapter, the CAPM has been challenged a lot in research. For those in favor of the CAPM, results that are inconsistent with the model often incorporate a lack of market efficiency. For instance, Lakonishok, Shleifer and Vishny (1994) were convinced that their findings of abnormal return-generating “value stocks” with a comparatively high book-to- market equity ratio in the US market from 1963 until 1990 occur due to irrational investors’ strategies.²³ In contrast to this, Malkiel (2003) defended the EMH and named the CAPM’s ina- bility to capture all stock-specific risks as the source of the above-mentioned abnormal re- turns.²⁴ This chapter presents an assessment of the BRIC countries being efficient stock mar- kets, and tries to give hints to which extent anomalies regarding the CAPM are likely to be found in this study’s empirical part.

3.3.1 Market Efficiency in the BRIC Countries

Chong, Cheng and Wong (2010) delivered results that show discrepancies in the degrees of market efficiency among the BRIC stock markets. As a reason for this they identify differences in the history of the stock exchanges of these countries. The main stock exchanges in India and Brazil were founded in the 19th century, while Russia and China founded their stock exchanges in the 1990s. The paper’s finding of evidence for the general observation that stock markets are getting more efficient over time is in line with Li et al. (2008).²⁵ A similar result was provided by Rockinger and Urga (2001) who applied a model to central and eastern European financial markets, including Russia, in order to test if an emerging market becomes more efficient over time. In their model, they tested the random walk model by testing the respective markets for stock return predictability. They found a general tendency towards weak-form market ineffi- ciency in young and illiquid markets. Furthermore, they pointed out that governmental interfer- ence, which negatively impacts market liquidity, results in periods of market inefficiency.²⁶

Another factor, which goes together with young markets, is a lack of investor experience. A common theory in behavioral research states that individuals show the tendency to overreact on information. This context was extended by De Bondt and Thaler (1985), showing that this behavior, which contradicts the rational investor in the CAPM world, results in stock prices overreacting on information, and, therefore, in an inefficient stock market environment. They assumed that contrarian strategies (buying past losers and selling past winners) achieve abnormal returns.²⁷ Yet, there is no general consensus in research that these abnormal returns are generated entirely by overreactions on the stock market. Nevertheless, they indicate that investor inexperience can promote market inefficiency.²⁸

Russia and China, which are the youngest of the BRICs, are likely to still suffer from market inefficiency due to inexperienced investors. Weak form inefficiency has also been reported for the Bombay stock exchange, finding evidence that at least in the period from 1987 to 1994, returns did not follow a random walk. Others of the very few studies on the testing of market efficiency of Asian emerging stock markets came up with the same result. Chan, Gup, and Pan (1992) showed that there is no evidence that the stock prices in major Asian markets are weak form efficient individually and collectively in the long run.²⁹ Nevertheless, studies on the im- pact of market liberalization of emerging equity markets indicated, that not only the founding of the respective stock markets, but also announcements of liberalization can induce a process towards more market efficiency. Since the late 1980s, many emerging market countries have amended their laws to allow foreigners to legally invest in their markets.³⁰ India and Brazil liberalized their markets in 1992 and 1988 respectively. Thus, these markets had a common timespan, in which they could develop, and could therefore be in a likewise condition of market efficiency. In China, on the contrary, the stock exchanges Shanghai and Shenzhen were primar- ily founded in the early 1990s. A little later, in 1995, the Russian stock exchange was founded. In terms of market evolution, these two markets must be seen separately from Brazil and India.

3.3.2 Brazil

Results of empirical studies for market efficiency in the Brazilian stock market are quite am- biguous. Evidence was found that the Brazilian market is the most efficient one within the set of BRIC markets.³¹ Founded in 1895 and liberalized in 1988, the Brazilian stock exchange in Sao Paolo has a long tradition of free stock trading, thus, the assumption of being the most efficient one sounds reasonable, but does not mean that it is perfectly efficient, however. Em- ploying both, co-integration analysis and a variety of Granger causality tests, Guttler et al. (2008) could reject the semi-strong market efficiency for the Brazilian stock market in the pe- riod from 1995 to 2005.³² Furthermore, there seem to be different degrees of efficiency in dif- ferent market segments. Ely (2011) grouped stocks by sector and firm size and conducted an automatic variance ratio test to the data from 1999 to 2008. He could find evidence that the market segment of low-capitalized firms and the industrial segment are less efficient than the rest of the market. Additionally, he stated that the Brazilian stock market showed an increase of efficiency. However, as mentioned above, the general estimation of market efficiency in Brazil is not straightforward. Thus, there is still a lack of clear-cut evidence that supports or invalidates the weak form market efficiency for the Brazilian stock market.³³

3.3.3 Russia

The case of the Russian market is a significantly different one. The same study by Chong, Cheng and Wong (2010) that ranked Brazil number one, when it comes to market efficiency, found that the Russian market is the most insufficient, with regard to that characteristic among the BRICs.³⁴

In order to understand the current status of evolvement of the Russian stock market, one has to deal with its origin beforehand. This is interesting because when the country founded its stock exchange in 1995, the former leader of the Soviet Union was in the middle of an economic transformation process. The restructuring from planned economy to market economy was ac- companied by harsh economic crisis. Established in these challenging circumstances, the Rus- sian stock market rapidly developed to one of the largest emerging markets worldwide. Never- theless, since its founding, the market has constantly been suffering from different structural shortcomings, like high concentration, high transaction costs and other operational inefficiency.

Due to its relatively short history, the Russian market has not been subject to detailed examination like other emerging markets.³⁵

However, some evidence can be found that gives an impression of the market conditions re- garding efficiency. It documents that the Russian market has been gaining efficiency throughout the first years of this millennium.³⁶ However, the world financial crisis in 2008 challenged the young Russian stock market once more, and resulted in the founding of the new Russian stock exchange in 2011. The Moscow exchange was founded by merging the largest and state-con- trolled securities exchange, MICEX, with the second largest and privately owned securities exchange, RTS. Two main objectives were pursued with this merger. On the one hand, a strengthening of state control over the Russian financial market, and, on the other hand, quality improvement of the Russian financial market performance. Evidence exists that these changes in the Russian stock market could increase their overall efficiency, however, there is still de- mand to further investigate the evolvement after the restructuring.³⁷

3.3.4 India

Located in former Bombay, now Mumbai, the Bombay Stock Exchange (BSE) is the oldest stock exchange in Asia, and, besides the National Stock Exchange, which is also located in Mumbai, the most important one in the country. Founded in 1875 with the formation of “Native Share & Share Broker Association”, the BSE celebrated its 140th anniversary in 2015.

Although the stock exchanges can look back on a long history, market inefficiency is reported for the Indian stock market within the period from 1987 until 1994.³⁸ However, the main share of observations within this test approach is within a timespan before market liberalization. The International Finance Corporation considers the market fully open from November 1992 on- wards, when the obligation of foreign investment institutions to register for investments in pri- mary and secondary markets with the Securities and Exchange Board of India was disposed by the Ministry of Finance.³⁹ Therefore, market efficiency is likely to have increased from 1994 onwards. Nevertheless, Majumder (2011) still found evidence for market inefficiency in the Indian stock market, which he explained with irrational investor sentiment, and, thus, suggested an alternative asset-pricing model, which accounts for market sentiments.⁴⁰ Although the ap- proach is quite different, the finding is in line with Mishra, Sehgal and Bhanumurthy (2011), who found that stock return in the Indian market does not follow a random walk. They examined tests in order to find evidence that Indian stock returns are generated by an irregular oscillatory process, generally characterized by three conditions: irregular periodicity, sensitive dependence on initial conditions, and the lack of predictability, per definition a chaotic system. The tests resulted in weak support for the hypothesis, and a rejection of the random walk hypothesis.⁴¹ Concluding, the Indian stock market seemed to be quite inefficient after all.

3.3.5 China

In spite of its rather late founding, the Chinese stock market has already been subject of many researchers. In order to shed light on the market conditions, one has to examine the origins of the Chinese stock markets in the first place.

In the early 1990s, the Chinese government pursued the goal of attracting international capital inflows. Therefore, the stock exchanges in Shenzhen and Shanghai were founded and supplied with two segments each in order to mitigate adverse international impact on the stock market. One segment of each stock exchange is dedicated to A-shares, which represent stocks that are denominated in renminbi, the local currency, and could only be traded by both residents and legal entities in the People’s Democratic Republic of China. In contrast, the second segment is designed for the trade of B-shares, denominated in US- or Hong Kong dollars. B-shares were only tradable by foreign investors. This state of strict separation between domestic and foreign trade held until February 2001, when the Chinese government decided to loosen the ties and partly liberalize the market. Under the new regulatory circumstances, residents are allowed to trade stocks in the B-share markets. The A-share market has yet remained quite insular giving only a limited set of foreign investors the possibility to engage in equity trade. However, the market has still been in a liberalization process with reforms and governmental programs in 2014 and 2015.⁴²

Most of the studies that were done on pre-liberalization data, found evidence that the Chinese market was far from weak-form efficient, especially in the B-share segment. For the A-share segment especially, the inexperienced Chinese resident investor was an issue, whereas the B- share trade was constrained by a lack of information for the foreign investors. However, using Chinese stock market data from 1992 to 2001, Li (2003) found that the market has continued to move in a direction towards more efficiency. As possible sources for this tendency he named higher levels of market liquidity and a strengthening of regulations.⁴³ For the period after the

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¹ Cf. Malkiel / Jun, (2009), p. 228.

² Cf. Goldman Sachs Global Economics Paper: 66 (2001), p. 3.

³ Cf. Goldman Sachs Global Economics Paper: 99 (2003), p. 1 f.

⁴ Cf. The World Bank (2016)

⁵ Cf. Bruner et al., (1998), p. 15.

⁶ Cf. Mossin, (1966), p. 770.

⁷ Cf. Sharp, (1964), p. 433.

⁸ Cf. Lintner, (1965), p. 15.

⁹ Cf. Sharp, (1964), p. 441 f.

¹⁰ Cf. Tobin, (1958), p. 67.

¹¹ Cf. Dempsey, (2013), p. 9 f.

¹² Cf. Fama, (1970), p. 383.

¹³ Cf. Worthington / Higgs, (2004) p. 60 f.

¹⁴ Cf. Fama, (1970), p. 387.

¹⁵ Ibid, p. 388.

¹⁶ Cf. Loistl, (1990), p. 63.

¹⁷ Cf. Güttler, (2000), p. 23.

¹⁸ Cf. Loistl, (1990), p. 63 ff.

¹⁹ Cf. Elton / Gruber, (1970), p. 73.

²⁰ Cf. Landskroner / Liviatan (1983), p. 205 f.

²¹ Cf. Roll (1977), p. 148 ff.

²² Cf. Fama (1992), p. 427 ff.

²³ Cf. Lakonishok / Shleifer / Vishny, (1993), p. 1575.

²⁴ Cf. Malkiel (2003), p. 69 f.

²⁵ Cf. Chong / Cheng / Wong, (2010), p. 236 ff.

²⁶ Cf. Rockinger / Urga, (2001), p. 80 ff.

²⁷ Cf. De Bondt / Thaler, (1985), p. 804.

²⁸ Cf. Jegadeesh / Titman, (1993), p. 65 f.

²⁹ Cf. Poshakwale, (1996), p. 615.

³⁰ Cf. Hamwakatsu / Morey, (1999), p. 368.

³¹ Cf. Chong / Cheng / Wong, (2010), p. 237.

³² Cf. Guttler / Meurer / Da Silva, (2008), p. 16 f.

³³ Cf. Ely, (2011), p. 582.

³⁴ Cf. Chong / Cheng / Wong, (2010), p. 237.

³⁵ Cf. Goriaev / Zabotkin, (2006), p. 381 f.

³⁶ Cf. McGowan (2011), p. 38.

³⁷ Cf. Teplova / Rodina, (2016), p. 375 ff.

³⁸ Cf. Poshakwale, (1996), p. 615.

³⁹ Cf. International Finance Corporation, (1996), p. 53.

⁴⁰ Cf. Majumder, (2011), p. 584.

⁴¹ Cf. Mishra / Sehgal / Bhanumurthy, (2011), p. 96 ff.

⁴² Cf. Seddighi / Nian, (2004), p. 785 ff.

⁴³ Cf. Li, (2001), p. 53 f.