Critical analysis of the implication of overreaction to the return predictability in UK stock market
Over the past decades, overreaction has drawn attention from many economic researchers, the most significant studies being Jegadeesh and Titman, (1993), De Bondt and Thaler (1985) proving the existence of overreaction. In their framework, they violated the EMH assumption. Then many later studies examined the overreaction effect through different market anomalies with One of the important anomalies being arbitrage trading strategies.
This paper will follow the Jegadeesh and Titman, (1993) framework and the Hons and Tonks (2002) method to construct a momentum strategy for UK market with winner and loser portfolio. The aim of this
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Third, review and examine the impact of different investment strategies to generate abnormal return and to find out the return predictability of the overreaction in UK market.
The evidences from the finding should be able to provide an advice for both existing and potential investors in UK stock market.
1.3 Structure layout of research.
Chapter 1 Introduction to research
Illustrate the research aim and outline the research objective
Chapter 2 Literature Review
Critically review previous literature to develop a fundamental knowledge of overreaction and it anomalies.
Chapter 3 Methodology
Demonstrating how momentum strategy is formed based on previous literature and how serial correlation is used to predict future return
Chapter 4 Data Analysis
Interpretation of result, compare and contrast the result with previous literature
Chapter 5 Conclusion.
Outlines the limitation of research and further suggestions
Chapter 2 Literature Review
2.1 Overreaction Hypothesis
Overreaction is one of the pricing behaviours in the security market. In order to understand the mechanism of this pricing behaviour, it is useful to understand the impact of influencing factor to the security price change. Efficient market
The behaviour of markets and investors, the decision making in the market place and the dynamics of demand and supply in any given market cannot be determined with a hundred percent accuracy. However master minds in the past have designed various techniques and theories that help investors make a particular buying decision, or to make choices logically. These theories and techniques help today’s investors to peep into the future and make almost immaculate predictions regarding the future behaviour of the market and the ongoing trends. A lay man night view the decision making of an investor as being solely based upon speculation but in reality every move that an investor makes today in the market place is backed up by sound calculation and
The authors jointly examine momentum and value in eight different markets and asset classes. Asness, Moskowitz and Pederson found two main phenomena associated with returns across 8 various markets and asset classes in their research. These findings challenge previous, well-established theories, like the existence of significant premia in value and momentum return strategies across asset classes and global markets. This innovative research includes some new asset classes not previously used, such as government bonds, currencies, and commodities. The authors look to prove the
In February 1995, Adam Bain, investment advisor in the London, Ontario branch of RBC Dominion Securities Inc. (RBC DS), was considering whether or not to implement a price momentum strategy for his clients. Trend and Cycle, DS’s technical research department, had recently circulated a copy of a study which described a simple price momentum model and referred to its “startling results” based on back testing the strategy over a 15 year period. The Trend and Cycle group had long promoted the importance of price momentum and relative strength to potential clients. Bain needs to determine whether the proposed model was “too good to be true” or, if it did not look promising, how he would go about
If you are a new investor who is interested in investment history or how to make investments, purchase this book by Burton G. Malkiel. This book is ideal for any experienced investor who wants to brush up on their knowledge of investment techniques and theories also. There are not many books that have been written about investing. A Random Walk Down Wall Street is broken down into four parts which include; Stocks and Their Value, How the Pros Play the Biggest Game in Town, The New Investment Technology and A Practical Guide for Random Walkers and Other Investors. In total, there are fifteen chapters that cover a lot of key points that many will find interesting and informative.
Such decisions may affect the company’s profitability today but judging from the fact that high risk means low stock price and vice-versa, high return waits in the future.
This document is authorized for use only by Yen Ting Chen in FInancial Markets and Institutions taught by Nawal Ahmed Boston University from September 2014 to December 2014.
Momentum is the phenomenon that stocks which have performed well in the past will continue to perform well in the future, and that stocks which have performed poorly will continue to perform poorly. Therefore a momentum investment strategy is to invest in short term portfolios that have high returns in the past, and to short those with low returns over the same period.
In order to analyze the momentum effect of different specifications, stocks were divided into ‘winner’ stocks and ‘loser’ stocks according to their rankings.
UK equities returned 7.7% (in pounds) over the UK risk-free rate for the period 1919 – 1993 and 6.8% over the UK risk-free rate for the period 1970-1996. How might this observation affect your decision?
As indicated by the case study S&P 500 index was use as a measure of the total return for the stock market. Our standard deviation of the total return was used as a one measure of the risk of an individual stock. Also betas for individual stocks are determined by simple linear regression. The variables were: total return for the stock as the dependent variable and independent variable is the total return for the stock. Since the descriptive statistics were a lot, only the necessary data was selected (below table.)
There is great potential for large returns when investing in high-risk, aggressive shares, but there is no guarantee. As there are not many aggressive strategies that will work in every market, a maximum point could be selected that would lead to either the re-evaluation or liquidation of the investment when reached. Rubber Plc should also consider their investment time horizon– the longer the better when it comes to investing in aggressive shares. The preference for an extensive investment horizon is due to the fact that it will enable them to endure market fluctuations better. Since this type of investment is likely to be much more volatile, demanding more frequent alterations to adapt it to changing market condition, it requires a more active management rather than a conservative, buy-and-hold approach. The CAPM (Capital Asset Pricing Model) can be used by Rubber Plc to price the portfolio; it helps calculate risk and what type of return to be expected from the investment. The general idea behind the model is that investors should be compensated for their time value of money along with their risk. The model is described in this formula: expected return = risk free rate + Beta * (expected market return - risk free rate) If the aggressive shares have a beta of 1.5, for example, for every 10% increase in the market index return, the share return will increase by 15%. However, if the market return falls, then
Even though there are flaws in the CAPM for empirical study, the approach of the linearity of expected return and risk is readily relevant. As Fama & French (2004:20) stated “… Markowitz’s portfolio model … is nevertheless a theoretical tour de force.” It could be seen that the study of this paper may possibly justify Fama & French’s study that stated the CAPM is insufficient in interpreting the expected return with respect to risk. This is due to the failure of considering the other market factors that would affect the stock price.
During this time period, prices for the stocks increase substantially, accordingly reducing risk premium demanded by the traders. Also, shares should amount from 30 to 55 percent of the entire investment portfolio to optimize the investor’s expected profitability. Proximity of the evaluated results to the reality reveals excellence of the myopic loss aversion model (Siegel and Thaler, 1997).
Historically, investors have proven the UIP wrong by gaining positive average returns on carry trade activities. However, these carry trades are uncertain as the returns derived reflect on a risk premium. Any risk based explanation for the returns to carry trades, requires us to identify the risk factors that contribute for the returns. Identifying the particular risk factor that causes fluctuations in returns and how it interacts with the result is to be studied. A few common traditional models that were built to understand these returns include, The Fama French three factor model, the CAPM the C-CAPM model to name a few. However these traditional models have been successful in explaining the returns to a stock market portfolio, but not the returns on carry trade. The do not provide