published_or_final_version / Economics / Master / Master of Social Sciences

published_or_final_version / Management Studies / Master / Master of Philosophy

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This dissertation contains two essays that study the implications of information arrival on asset prices. In the first essay, I study an important aspect of the firm-level information structure - the quantity of information - and its effect on the cross-section of stock returns. The main contribution of this essay is to propose a new proxy for information intensity (monthly information quantity) and establish a link between information intensity and stock returns. I find that higher information intensity reduces expected uncertainty and leads to a lower expected return, after controlling for a variety of traditional risk factors and asset pricing anomalies. An information-intensity-based long-short portfolio generates an abnormal return of 4.44% per year. My findings suggest that, as a key component of information structure, information quantity is of first order importance in determining stock returns, and more generally, that investor learning plays an important role in financial markets with incomplete information. The second essay, based on a joint work with John Maheu and Tom McCurdy, studies the asset-pricing implication of market-level information arrival, which can lead to large movements (jumps) in the market index. Deviating from the literature that studies the impact of jumps through option pricing and motivated by a nonlinear pricing kernel associated with general preferences, we focus on the pricing impact of jumps through the pricing of higher-order moments. We find that three components of a modeling device, including: a 2-component GARCH model for diffusive volatility, an autoregressive model for jump intensity, and a higher order moment specification of the equity premium, are particularly important for asset pricing with jumps. This modeling device enables us to be the first to uncover significant pricing of both diffusive risk and jump risk, using only a time series of equity return data. We find that the risk premium due to jumps is a significant part of the overall equity premium. Our results also suggest the existence of a significant skewness premium and offer a potential resolution to sometimes conflicting results on the intertemporal risk-return relationship. Furthermore, taking jumps into account improves the out-of-sample performance of a portfolio allocation application.

A model of a fishery with an uncertain fish stock is proposed to compare alternative management systems with individual transferable quotas (ITQs). Assumptions of the model include: (1) the fish stock fluctuates randomly year by year; (2) in-season stock depletion is small; (3) the total allowable catch (TAC) set by the quota authorities has a definite relation with the fish stock level; (4) the true value of the stock level is revealed only at the middle of each season, when the authorities revise the TAC; (5) fishers form rational expectations on future quota prices. The principal results are: (a) If fishers are risk-neutral, the share quota (SQ) system and the quantity quota (QQ) system generate the same amount of fishery rent, although the division of the rent between fishers and the authorities under one system is different from the other. If the TAC is proportional to the stock level, the more price-inelastic the demand for fish is, the more likely it is that fishers are better off under the QQ system at the expense of the authorities. (b) A quota tax and a harvest tax that collect the same amount of revenue for the authorities result in the same division of the fishery rent among heterogeneous fishers. The quota tax and the profit tax differ in this respect. Which fishers will prefer a quota tax over a profit tax will depend on fishers' shares of the initial quota endowment and in total inframarginal profits afterward. (c) If fishers are risk-averse, the SQ system and the QQ system are not equivalent in their allocative efficiency. An example shows that the SQ system is potentially better than the QQ system when fishers prefer the latter and the authorities prefer the former. This conclusion has to be modified if risk-neutral traders participate in the quota market

This dissertation contains two essays that study the implications of information arrival on asset prices. In the first essay, I study an important aspect of the firm-level information structure - the quantity of information - and its effect on the cross-section of stock returns. The main contribution of this essay is to propose a new proxy for information intensity (monthly information quantity) and establish a link between information intensity and stock returns. I find that higher information intensity reduces expected uncertainty and leads to a lower expected return, after controlling for a variety of traditional risk factors and asset pricing anomalies. An information-intensity-based long-short portfolio generates an abnormal return of 4.44% per year. My findings suggest that, as a key component of information structure, information quantity is of first order importance in determining stock returns, and more generally, that investor learning plays an important role in financial markets with incomplete information. The second essay, based on a joint work with John Maheu and Tom McCurdy, studies the asset-pricing implication of market-level information arrival, which can lead to large movements (jumps) in the market index. Deviating from the literature that studies the impact of jumps through option pricing and motivated by a nonlinear pricing kernel associated with general preferences, we focus on the pricing impact of jumps through the pricing of higher-order moments. We find that three components of a modeling device, including: a 2-component GARCH model for diffusive volatility, an autoregressive model for jump intensity, and a higher order moment specification of the equity premium, are particularly important for asset pricing with jumps. This modeling device enables us to be the first to uncover significant pricing of both diffusive risk and jump risk, using only a time series of equity return data. We find that the risk premium due to jumps is a significant part of the overall equity premium. Our results also suggest the existence of a significant skewness premium and offer a potential resolution to sometimes conflicting results on the intertemporal risk-return relationship. Furthermore, taking jumps into account improves the out-of-sample performance of a portfolio allocation application.

No description available.

The objective of this thesis was to analyse the empirical applicability of the Arbitrage Pricing Theory to international asset markets (UK stock market and US stock market) and to identify the set of economic variables which correspond most closely with the stock market factors obtained from the traditional factor analysis. Factor analysis and canonical correlation analysis were used as the principal tools for the empirical testing. Although factor analysis is frequently used, canonical correlation analysis is an new technique in this area and provides a method of linking factors extracted from the two sets of data. Various economic indicators were investigated as systematic influences on stock returns. It was shown that, based on the foundations of the APT and the characteristics of the factor scores from the factor analysis on the security returns and the economic indicators, canonical correlation analysis is an approximate technique to link the stock market and the economic forces. The results using the UK data imply that there is a good correspondence between factor scores generated by the factor analysis on the UK security returns and on the UK economic indicators. The results using the US data show that there is also a fair correspondence, but lower than that for the UK data, between factor scores generated by the factor analysis on the US security returns and on the US economic indicators. The APT was also investigated in an international setting by considering the UK data and the US data together. The results show that the canonical correlation analysis successfully links the stock returns and economic forces. The conclusion of these empirical findings is that security returns are influenced by a number of systematic economic forces. The validity and applicability of the APT were also empirically evaluated. The regression results show that the explanatory power of the APT model is fairly good. The overall results obtained here appear to suggest that the APT pricing relationship is supported by the testing methodology. In addition, the international correlation structure of financial markets movements between the UK economy and the US economy has been analysed. On balance, the evidence favours the APT and there is available evidence of inter-market linkage between the UK and the US. Individual sets of economic variables have been identified which correspond most closely with the UK and the US stock market factors by using the canonical correlation analysis. The results, at least partially, contribute to the understanding of security market pricing.

No description available.