Efficient Market Hypothesis and Behavioral Finance

Investment in stocks and portfolio management involves analysing different parameters using various techniques. Fundamental analysis and technical analysis are two most commonly employed methods for stock selection. The study of macro-economic data and financial performance of an organization for evaluating the intrinsic value of a stock is referred to as fundamental analysis (Krantz, 2016). On the other hand, technical analysis involves examination of historical trends in stock movements and prediction of future prices on the basis of past trends (Grimes, 2012). This report involves construction of two portfolios of 10 stocks each. First portfolio is constructed on the basis on fundamental analysis and other one is based on technical analysis. Apart from this report also discusses about the efficient market hypothesis and behavioural finance. The report also gives view about the conflict between the EMH and behavioural finance.

Stock selection and evaluation is commonly carried using various methods of fundamental and technical analysis. This consists of analysis of past financial position of a company and studying movements of price fluctuations of its stock. On the other hand, efficient market hypothesis and behavioural finance add another dimension to stock selection and their performance evaluation According to Efficient market hypothesis, stock prices always reflect all the information that is available in the market and trade at their intrinsic value. New information is transferred to all the investors without any cost and is randomly distributed.  Therefore passive investment strategy will be more effective than active management. Behaviour finance believes that investors do not behave rationally and their emotional biases affect their choices. Overconfidence, conservatism and risk aversion are some of many such behavioural influences which affect market sentiments (Forbes, 2009).

 Overconfidence in markets leads excessive buying during market rally. Another empirical evidence of irrationality of investors is that low price to earnings ratio companies react more positively to good news than high P/E ratio companies (Byrne, 2008). Stock market crashes in one part of the world affect investor sentiments in other regions. This was particularly evident during global financial crisis of 2008 and dot com bubble, when market crash in USA not only had an effect on neighbouring markets but also in markets of China, Australia and other regions of the world. This was due to selling pressure which had built due to negative news from USA. However, macro-economic conditions in these countries were better than USA.  This is purely because of irrational investor behaviour (Baker and Nofsinger, 2010).  

Stock Selection and Technical Analysis

Various theories of finance lay their foundation on the basis of efficient market hypothesis. Capital asset pricing model (CAPM) and modern portfolio theory which form the basis of most of the investments are based on efficient market hypothesis.  Efficient market hypothesis has been useful in securities pricing. This is particularly true in the case of shareholder appraisal cases and benefit plans for employees. According to EMH, investors are assumed to rational and it is believed that markets are self-correcting. EMH also is contrary to technical analysis and believes that it cannot be used to outperform the market. Proponents of EMH argue that past prices and data cannot be used to predict future returns. So a portfolio can outperform a market only by chance and past information is already reflected in market (Harder, 2010).

There seems to be a conflict in ideologies of believers of EMH and behavioural finance. EMH believes in superiority of market and rationality of investors. EMH also causes no random price movements in the markets. Apart from stock market, EMH is also used in other fields of finance such as construction of portfolio, dividends and efficiency of funding. On the other hand, behaviour finance argues that prices of securities in markets are not the reflection of their intrinsic value. In many cases, human psychology is real force behind market movements. The research in the field of behavioural finance not only involves study of human emotions but also cultural trends and expectations of investors. In real world efficient market hypothesis rarely holds, primarily due to information asymmetry and psychological biases present in investors. Securities in markets are mostly not trading at their intrinsic values and it requires various financial techniques to take advantage of such mispricing (Akintoye, 2008). Various methods of technical analysis such as moving average, trend analysis and candle stick chart have been developed to determine real values of securities. Fundamental analysis also uses many methods such as Gordon dividend discount model and valuation on the basis of price multiples. Therefore, both EMH and behavioural finance have important role in play in markets. However, markets primarily do not behave rationally.

The methodology of portfolio management and stock selection consists of gathering of quantitative financial data for analysis to draw suitable conclusions. The crux of efficient financial management lies in adoption of right methods and their effective implementation (Phillips and Stawarski, 2016).  In this report, two portfolios have been constructed by use various methods with the intention to beat the market. Various methods of technical and fundamental analysis have been used successfully for active management of portfolio. Both the methods are based different principles. Technical analysis does not rely on the analysing the financial performance of a company, it attempts to draw conclusions from price movements and changes in volume of stock traded. On the other hand, fundamental analysis believes in analysing the financial performance of the company and does not give much of the importance to price trends. None of the methods is superior to other and both are complimentary to each other (Stanfield, 2005).

Stock Selection and Fundamental Analysis

In this report, company Jardine Cycle and Carriage Limited has been chosen on the basis of fundamental analysis because of it has generated a return on equity of 14.42% (Yahoo finance, 2018). On the other hand, stock of DBS Group Holdings has been selected because of exceptional profit margin of 40.74% and operating profit margin of 51.49%. (Yahoo finance, 2018). Thus using various parameters of financial performance and techniques of fundamental analysis one portfolio of 10 has been constructed. Another portfolio comprising of 10 stocks has also been constructed on basis of technical analysis. Both the methods will result rational choices and prudent judgments.

Dividend Discount Model

Gordon dividend discount model has been successfully used in fundamental analysis for finding the intrinsic value of a stock. According to this model, price of a stock is equal present value of all future dividends (Magiera, 2000). In this report, dividend discount model has been applied to Sembcorp Marine Ltd to compute its intrinsic value.

Market price of Sembcorp Marine Ltd is SGD 2.3 (Yahoo finance, 2018) on 19-Jan-18. However, intrinsic value arrived by using the dividend discount model is SGD 2.86.Therefore, the stock appears to be undervalued and a good opportunity for investment.

The PB Model technique is used to arrive at the fundamental value of Sembcorp Marine Ltd. P/B of an industry can be used along with book value of a company to find the intrinsic value of a share (Davidson & Tippet, 2012). Intrinsic value calculated using this technique is arrived as given below

The intrinsic value calculated using PB model is SGD 2.8, while the market price on 19 January, 2018 is SGD 2.3 (Yahoo finance, 2018). Therefore, Sembcorp Marine Ltd is undervalued.

Large number methods have been developed for evaluating stocks using technical analysis. Among all the methods, most commonly used are line chart and moving average. Apart from this support and resistance levels of movements of stocks are also studied to predict future prices (Wang, Mamaysky & Lo, 2000).

Moving Average

Moving average is calculated by taking average of stock prices during a particular period of time. Moving average can be calculated for various durations. Moving average of Star Hub has been calculated as SGD 2.92 (refer excel). Moving average can be used to define various cut off levels. Whenever the price of a stock goes above its moving average, price is further likely to increase. On the other hand, price of stock is likely to decrease if it goes below the moving average (Brooks, 2005). The price of Star Hub has reached SGD 2.99 which is above its moving average. So price of the stock is likely to increase in future.

Case Study: Sembcorp Marine Ltd

Figure 1: Stock Price

Line chart can be used to identify trends in prices of stocks. Continuous uptrend in movement can be signal of further price increase. As can been seen in the chart, trend of price of movement of stock is upwards, therefore Star Hub presents a good opportunity for investment.

Trading activity done in portfolio-1

Two trades were done in the portfolio based on fundamental analysis. 500 shares of SATS Ltd were sold for SGD 5.85 each on 19 January, 2018 and on the same day 1270 shares of Sembcorp Marine Ltd were bought for SGD 2.30 each. These trades were carried out after analysing these stocks on the basis of various methods of fundamental analysis.

Trading Activity done in portfolio-2

Similar to portfolio 1, 1160 shares of Star Hub were bought for SGD 3.00 each after realising the funds released from selling of 2500 shares of Genting Singapore Plc for SGD 1.39 each. Various technical analysis methods such as moving average, line chart; and support and resistance were applied to draw suitable conclusions.

In this report, two portfolios were constructed on the basis of various methods of fundamental and technical analysis. Each of the portfolio comprised of 10 stocks. Portfolio -1, which was based fundamental analysis, used various models such as dividend discount model and PB model to evaluate the stocks. Similarly, portfolio-2 used techniques of technical analysis for stock selection. Line chart and moving average methods of technical analysis were used to predict price movements of companies. During the period of study, both the portfolios were able to outperform the market. FTSE ST all share index generated a holding period return of 1.44% (Appendix 8). Portfolio-1 gave a return of 8.90% (Appendix 7), while portfolio-2 generated a return of 6.97% (Appendix 7). In portfolio-1, seven out of ten stocks gave positive holding period returns (Appendix 5). On the other hand, in portfolio-2, only two stocks gave negative returns over the period of study (Appendix 6). Overall, it was observed the portfolio-1 based on fundamental analysis was better performing than portfolio-2.

By analysing the results, it can be inferred that market can be beaten using various techniques of portfolio management. It also shows us the markets are not efficient in realty and are affected by behavioural biases. So, prices of stocks rarely trade at their intrinsic values. By using various techniques of fundamental and technical analysis, mispricing in stock values can be exploited. Efficient market hypothesis which was earlier discussed in this report does not hold in real world conditions. Markets and stocks also do not reflect all the information. Here various methods which were used for stock selection, were able to identity mispricing in markets and generate better return than market. That is why, in this report stocks not trading at their intrinsic value were identified and such opportunities were exploited to generate excess return over the market. In this study, both portfolio-1 and portfolio-2 were able take advantages of inefficiencies and psychological biases in markets. Overall it was observed that portfolio-1 was better performing than portfolio-2.

Trading Activity in Portfolio 1

Conclusion

This report presents construction of two portfolios of companies and discusses various methods of stock selection. Various methods discussed in this report fall under the category of fundamental and technical analysis. Different valuation models and trend finding techniques such as dividend discount model, moving average and line chart were used for portfolio evaluation. Apart from this, this report also discusses efficient market hypothesis and concepts behavioural finance. A view of conflict between EMH and behavioural finance has also been provided in this with reference many global events such as financial crisis of 2008. It is rarely seen that markets are efficient and personal choices affect market behaviour. Further, both the portfolios constructed on the basis of technical and fundamental analysis were able be beat the market and generate a holding period return in excess of 5%. For the period of study of 26 December, 2017 to 16 February, 2018 FTSE ST all share index generated a return of 1.44% (Appendix 8). On the other hand portfolio-1 based on fundamental analysis generated a return of 8.90% (Appendix 7) and portfolio-2 (Appendix 7) gave a return of 6.97%. Portfolio-1 outperformed the market as well as portfolio-2.

References

Akintoye, I. R. (2008). Efficient Market Hypothesis and Behavioural Finance: A Review of Literature. European Journal of Social Sciences. 7(2), 7-17.

Baker, H.K. and Nofsinger, J.R. (2010). Behavioral Finance: Investors, Corporations, and Markets. New Jersey, USA: John Wiley & Sons.

Brooks, J. C. (2005). Mastering technical analysis. Pennsylvania, USA :McGraw Hill Professional.

Byrne, A. (2008).  Behavioural finance: theories and evidence. The Research Foundation of CFA Institute Literature Review. Retrieved from https://www.cfapubs.org/doi/pdf/10.2470/rflr.v3.n1.1

Davidson, I. & Tippet, M. (2012). Principles of equity valuation. Abingdon, Oxon: Routledge.

Forbes, W. (2009). Behavioral finance. Sussex, UK:John Wiley & Sons.

Grimes, A. (2012). The art and science of technical Analysis: Market Structure, price action and trading strategies. New Jersey, USA: John Wiley & Sons.

Harder, S. (2010). The efficient market hypothesis and its applications to stock markets. Norderstedt, Germany: GRIN Verlag.

 Krantz, M. (2016).  Fundamental analysis for dummies. New Jersey, USA: John Wiley &  Sons.

 Magiera, F. T. (2000).Comparing the accuracy and explainability of dividend, free Cash flow, and abnormal earnings equity value estimates. Journal of Accounting Research. 38(1), 45-70.

Philips, P. P. and Stawarski, C.A. (2016). Data collection: Planning for and collecting all types of data. New Jersey, USA:John Wiley & Sons.

Stanfield, K. (2005). Intangible finance standards: Advances in fundamental analysis and technical analysis. California, USA: Elsevier.

Wang, J., Mamaysky, H. & Lo, A. W. (2000). Foundations of technical analysis: computational algorithms, statistical Inference, and empirical Implementation. The Journal of Finance, 9(1), 1705-1765.

Yahoo finance. (2018). DBS group holdings: statistics. Retrieved from https://finance.yahoo.com/quote/D05.SI/key-statistics?p=D05.SI

Yahoo finance. (2018). Jardine cycle and carriage limited: statistics. Retrieved from https://finance.yahoo.com/quote/C07.SI/key-statistics?p=C07.SI

Yahoo finance. (2018). Sembcorp marine ltd: statistics. Retrieved from https://finance.yahoo.com/quote/S51.SI/key-statistics?p=S51.SI