1. CAPM models with risk-neutrality
and loss-aversion, consistency and
predictability on emerging stock
markets of BRIC (Brazil, Russia,
India and China)

2. Contents
 Introduction
 Theoretical aspects of research
• Classical CAPM model
• Betting against beta model
 Empirical tests. Results
• Correlation tests
• Beta-based portfolios
 Conclusion

3. 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

4. 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

5. 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

6. Theoretical aspects
Classical CAPM model
 By Sharpe, Lintner and Mossin in 1960s
 General formula:
𝐸(𝑟𝑖)=𝑟 𝑓+𝛽𝑖(𝐸(𝑟 𝑚)−𝑟 𝑓)
 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

7. 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

8. Empirical tests
Data analyzed
 A decade of years starting from 2001 (covering
“dot.com” bubble burst & recent financial crisis)
 Data acquired viaThomson 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)

9. 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−𝑟𝑡
𝑓=𝛼+𝛽(𝑟𝑡
𝑚−𝑟𝑡
𝑓)+𝜀
 OLS & GLS regressions, beta-based
portfolios

10. Empirical tests
Correlation tests. China (A-shares)

11. Empirical tests
Correlation tests. China (A-shares). Positive outcomes

12. Empirical tests
Correlation tests. Brazil

13. Empirical tests
Correlation tests. Brazil. Negative outcomes

14. Empirical tests
Beta-based portfolios. China

15. Empirical tests
Beta-based portfolios. Brazil

16. 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

17. Questions are welcome