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Contrarian Investment Strategies based on the FTSE 100 constituents

Author:
Ferat Oeztuerk  


Issue Date:
2010


Abstract(summary):

This part of the thesis will briefly summarize the findings and draw the conclusion of the thesis. Abnormal returns are generated for the five year CAR model with 18 stocks assigned to the winner and loser portfolios. I find that a strategy which sells past winners and buys past losers generates significant abnormal returns of 31.6% on average, 60 months after portfolio formation. However, the results only provide weak evidence in favour of the overreaction hypothesis. While investors overreact to information with respect to past losers, they do not overreact to information regarding past winners. The theory suggests that - > 0, while is expected to be positive and is assumed to be negative. This holds for the losers, but not for the winners as extreme movements of the winners are not followed by subsequent movements in the following period. However, considering the strategy as a whole, contrarian profits are still generated, even though these profits are reduced by the positive performance of the winners. The overreaction hypothesis states that the winners should become losers in the future. This is not the case as the winners continue their positive development, even though the loser portfolio’s returns are higher. However, I conclude that implementing a contrarian investment strategy based on the FTSE 100 constituents is profitable over the last two decades. I additionally analyze the source of two major points of criticism regarding the reliability of contrarian profits which has been raised by scholars, namely the riskiness of the strategy and seasonality of returns. I reject these points of criticism as possible sources of contrarian profits. The analysis provides evidence that the strategy is not more risky than an investment in the FTSE 100 and indicates that the January profits are too marginal in order to attribute these profits to the January effect. Other than that I believe that size related criticism plays a minor role for this thesis, since the analysis focuses on the largest UK stocks. Finally, I compare different methods to compute returns. I observe the pattern that there are large differences in returns when different methods are applied, whereas profits calculated according to the buy-and-hold method exceed the returns calculated using cumulative abnormal returns. I suggest using cumulative abnormal returns to analyze long-term returns due to two different reasons. First, major asset pricing models are based on monthly returns and not on buy-and-hold methods, which makes it intuitive to implement cumulative abnormal returns into long-term studies. Second, buy-and-hold returns do not consider price fluctuations within the testing period and can therefore give a wrong intuition about the performance of the underlying stock. Even though some scholars like Conrad and Kaul (1993) argue that buy-and-hold returns should be implemented into long-term studies, I agree with Fama (1998) who favours cumulative abnormal returns as method to compute long-term returns. Referring to the debate on market efficiency, I find that the weak form of the EMH is not confirmed, since a contrarian investment strategy is based on historical prices and clearly outperforms the benchmark without bearing additional risk. The timeframe is long enough in order to reject the notion that the outperformance might be due to pure luck. I believe that this is driven by investors which do not react correctly to new information, rather than assuming that asset prices do not reflect all information concerning a stock.


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44


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