CAPM models with risk-neutrality and loss-aversion, consistency and predictability on emerging stock markets of BRIC (Brazil,

Russia, India and China)

Contents

Introduction Theoretical aspects of research• Classical CAPM model• Betting against beta model

Empirical tests. Results• Correlation tests• Beta-based portfolios

Conclusion

Introduction

Idea of market risk factor • Fama-French 3-factor model• FCF-models• WACC model etc.

CAPM deals with 2 factors• Idiosyncratic risk (alpha)• Market risk (beta)

Microstructure of developing markets differs from those of developed ones

Introduction

Aim of the thesis: analysis of CAPM model consistency and predictability in application to emerging markets stock returns

Subject of the study: application of CAPM model (and/or inverse CAPM model) as a tool for making successful and efficient investment decisions

Object of the study: stocks traded on emerging markets of BRIC

Introdcution

Hypothesis 1 - beta estimations have descriptive power for stock returns on emerging stock markets of BRIC

Hypothesis 2 - CAPM model implications are consistent on stock markets of BRIC-countries

Hypothesis 3 - Low beta stocks provide highest returns across stock market

Theoretical aspects

Classical CAPM model By Sharpe, Lintner and Mossin in 1960s General formula:

𝐸(𝑟𝑖)=𝑟𝑓+𝛽𝑖( (𝐸 𝑟𝑚)−𝑟𝑓)

Higher beta coefficient - greater market risk to which the asset is subjected

During market gains, high beta assets provide higher returns, in comparison to low-beta assets

Theoretical aspects

Betting against beta model Frazzini & Pedersen (2010) and Baker,

Bradley & Wurgler (2011) Deals with behavioral biases and agent

investment confines Leverage constraints and margin

requirements => overinvestment in high-beta stocks, lowering their returns

Stocks with lower CAPM market risk estimations provide higher returns

Empirical tests

Data analyzed A decade of years starting from 2001 (covering

“dot.com” bubble burst & recent financial crisis) Data acquired via Thomson Reuters DataStream Weekly stock returns (to avoid non-synchronous

trading) Basis period equals one year (52 weeks) Risk free rates: 90 day interbank rate (Russia),

overnight financial rate (Brazil), 91 day treasury bill (India) and 3 months relending rate (China)

Benchmark indices: RTS &MICEX (Russia), MSCI stock indices (Brazil, China, India)

Empirical tests

Data analyzed China - 793 stocks on A-shares

market & 53 stocks on B-shares market, India – 255 stocks, Russia – 133 and Brazil – 134

General formula applied:

𝑟𝑡−𝑟𝑡𝑓= + (𝛼 𝛽 𝑟𝑡𝑚−𝑟𝑡𝑓)+𝜀

OLS & GLS regressions, beta-based portfolios

Empirical testsCorrelation tests. China (A-shares)

Empirical testsCorrelation tests. China (A-shares). Positive outcomes

Empirical testsCorrelation tests. Brazil

Empirical testsCorrelation tests. Brazil. Negative outcomes

Empirical testsBeta-based portfolios. China

Empirical testsBeta-based portfolios. Brazil

Conclusions

Logic of original CAPM model didn’t hold true for every BRIC country

Russian and Indian stock markets showed mixed results Chinese market almost perfectly fit the logic of original

CAPM model (remark: model kept true only for a specific part of the market –A-shares )=> original CAPM model could be successfully applied when making investment decisions in regard to Chinese A-shares

BAB model to be consistent when applied to shares traded on Brazilian stock market

Low-beta stocks overperform on Brazilian stock market BAB model can be applied in constructing investment

strategy for Brazilian market

Questions are welcome