AbstractThis thesis investigates the role of two prominent concepts in finance: the role of limit to arbitrage and investor sentiment in stock prices. Fundamentally, the Efficient Market Hypothesis (EMH) contends that, at every point in time, stock prices reflect all available information and the effect of irrational behaviour on stock prices will be eliminated by sophisticated arbitrageurs (Fama, 1970). However, given the theoretical and empirical challenges to the EMH, academic interest in the area has broadened to question the setting in which only economic and firm-specific factors influence asset prices (Barberis and Thaler, 2003). Behavioural economists have suggested that real world arbitrage is both risky and expensive and, therefore, that it is ineffective in eliminating sentiment-driven mispricing. They have suggested that a theory that combines limits to arbitrage and investor sentiment may explain more precisely the behaviour of stock prices (Shleifer and Summers, 1990; Shleifer, 2000; Barberis and Thaler, 2003). This thesis builds on the theoretical work and previous literature to explore the effect of investor sentiment and limits to arbitrage on nine equity market anomalies using data for a broad cross-section of UK stocks. The importance of empirically examining the impact of sentiment and limits to arbitrage on the performance of stock market anomalies is paramount for different stakeholders. For example, the outcome of this thesis has important implications for investors aiming to improve market timing and asset allocation strategies, as well as providing them with information on more advanced assets pricing models applicable to the UK stock market. In addition, the findings from this thesis will be of interest to policy-makers aiming to curb the impact of investor sentiment on stock prices by waiving arbitrage limitations for market players.
The first part of the thesis examined the effect of UK investor sentiment, managers sentiment and foreign sentiment on the profitability of nine equity market anomalies. Consistent with the previous studies, this thesis found that eight of the nine anomalies examined under this thesis to produce statistically significant alphas relative to Fama and French (1993) three factor model. The investigation of the effect of UK, managerial and US investor sentiment on the performance of the UK stock market anomalies showed that UK investor sentiment had the strongest effect on the profitability of the nine strategies, where five anomalies had significantly stronger long-short returns following periods of high UK sentiment than periods of low sentiment. On the other hand, managers sentiment and US investor sentiment had a limited effect on the nine anomalies.
The second part of the thesis studied the impact of limits to arbitrage on the performance of stock market anomalies. In addition, this part of the thesis examined in one model the combined effect of limits to arbitrage and investor sentiment on stock market anomalies. The overall findings showed that limits to arbitrage measures played either a partial or no role in the profitability of the nine stock market anomalies. Out of the six limits to arbitrage measures, idiosyncratic volatility had the strongest impact on the performance of stock market anomalies in the UK. However, findings from the interaction of investor sentiment and limits to arbitrage demonstrated that the effect of limits to arbitrage was more important when combined with investor sentiment.
The final part of the thesis assesses the performance of an asset pricing model that incorporates investor sentiment and limits to arbitrage as risk factors to examine whether such a model explains the abnormal returns of the nine anomalies. Further, it provides an evaluation of the performance of the model relative to Fama and French (1993) three factor model, Carhart (1997) four factor model and the Fama and French (2015) five factor model. Overall, a comparison of the four asset pricing models in this thesis showed that the Fama and French (2015) model, augmented with the sentiment risk factor, provided the best explanation for the UK stock market anomalies.
|Date of Award||2023|
|Sponsors||Umm Al-Qura University|
|Supervisor||Suzanne Fifield (Supervisor) & Sudharshan Reddy Paramati (Supervisor)|
- Investor sentiment
- Limits to arbitrage
- Stock market efficiency
- Behavioural finance