Canadian investors and the discount on closed-end funds

Small investors' sentiment has been proposed by behaviouralists to explain the existence and behavior of discount on closed-end funds (CEFD). The empirical tests of this sentiment hypothesis so far provide equivocal results. Besides, most of out-of-sample tests outside U.S. are not robust in the sense that they fail to well control other firm characteristics and risk factors that may explain stock return and to provide a formal cross-sectional test of the link between CEFD and stock return. This thesis explores the role of CEFD in asset pricing and further validates CEFD as a sentiment proxy in Canadian context and augments the extant studies by examining the redemption feature inherent in Canadian closed-end funds and by enhancing the robustness of the empirical tests. Our empirical results document differential behaviors in discounts between redeemable funds and non-redeemable funds. However, we don't find supportive evidence of CEFD as a priced factor. Specifically, the stocks with different exposures to CEFD fail to provide significantly different average return. Nor does CEFD provide significant incremental explanatory power, after controlling other well-known firm characteristics and risk factors, in cross-sectional as well as time-series variation of stock return. This evidence, together with the findings from our direct test of CEFD as a sentiment index, suggests that CEFD, even the discount on traditional non-redeemable closed-end funds, is unlikely to be driven by elusive sentiment in Canada.

Are Idiosyncratic Skewness and Idiosyncratic Kurtosis Priced?

This thesis investigates the pricing effects of idiosyncratic moments. We document that idiosyncratic moments, namely idiosyncratic skewness and idiosyncratic kurtosis vary over time. If a factor/characteristic is priced, it must show minimum variation to be correlated with stock returns. Moreover, we can identify two structural breaks in the time series of idiosyncratic kurtosis. Using a sample of US stocks traded on NYSE, AMEX and NASDAQ markets from January 1970 to December 2013, we run Fama-MacBeth test at the individual stock level. We document a negative and significant pricing effect of idiosyncratic skewness, consistent with the finding of Boyer et al. (2010). We also report that neither idiosyncratic volatility nor idiosyncratic kurtosis are consistently priced. We run robustness tests using different model specifications and period sub-samples. Our results are robust to the different factors and characteristics usually included in the Fama-MacBeth pricing tests. We also split first our sample using endogenously determined structural breaks. Second, we divide our sample into three equal sub-periods. The results are consistent with our main findings suggesting that expected returns of individual stocks are explained by idiosyncratic skewness. Both idiosyncratic volatility and idiosyncratic kurtosis are irrelevant to asset prices at the individual stock level. As an alternative method, we run Fama-MacBeth tests at the portfolio level. We find that idiosyncratic skewness is not significantly related to returns on idiosyncratic skewness-sorted portfolios. However, it is significant when tested against idiosyncratic kurtosis sorted portfolios.

Are Idiosyncratic Skewness and Idiosyncratic Kurtosis Priced?

This thesis investigates the pricing effects of idiosyncratic moments. We document that idiosyncratic moments, namely idiosyncratic skewness and idiosyncratic kurtosis vary over time. If a factor/characteristic is priced, it must show minimum variation to be correlated with stock returns. Moreover, we can identify two structural breaks in the time series of idiosyncratic kurtosis. Using a sample of US stocks traded on NYSE, AMEX and NASDAQ markets from January 1970 to December 2013, we run Fama-MacBeth test at the individual stock level. We document a negative and significant pricing effect of idiosyncratic skewness, consistent with the finding of Boyer et al. (2010). We also report that neither idiosyncratic volatility nor idiosyncratic kurtosis are consistently priced. We run robustness tests using different model specifications and period sub-samples. Our results are robust to the different factors and characteristics usually included in the Fama-MacBeth pricing tests. We also split first our sample using endogenously determined structural breaks. Second, we divide our sample into three equal sub-periods. The results are consistent with our main findings suggesting that expected returns of individual stocks are explained by idiosyncratic skewness. Both idiosyncratic volatility and idiosyncratic kurtosis are irrelevant to asset prices at the individual stock level. As an alternative method, we run Fama-MacBeth tests at the portfolio level. We find that idiosyncratic skewness is not significantly related to returns on idiosyncratic skewness-sorted portfolios. However, it is significant when tested against idiosyncratic kurtosis sorted portfolios.

A stochastic dynamic programming approach for pricing options on stock-index futures

The aim of this thesis is to price options on equity index futures with an application to standard options on S&P 500 futures traded on the Chicago Mercantile Exchange. Our methodology is based on stochastic dynamic programming, which can accommodate European as well as American options. The model accommodates dividends from the underlying asset. It also captures the optimal exercise strategy and the fair value of the option. This approach is an alternative to available numerical pricing methods such as binomial trees, finite differences, and ad-hoc numerical approximation techniques. Our numerical and empirical investigations demonstrate convergence, robustness, and efficiency. We use this methodology to value exchange-listed options. The European option premiums thus obtained are compared to Black's closed-form formula. They are accurate to four digits. The American option premiums also have a similar level of accuracy compared to premiums obtained using finite differences and binomial trees with a large number of time steps. The proposed model accounts for deterministic, seasonally varying dividend yield. In pricing futures options, we discover that what matters is the sum of the dividend yields over the life of the futures contract and not their distribution.