International stock portfolio selection and performance measures recognizing higher moments of return distributions

Since the seminal works of Markowitz (1952), Sharpe (1964), and Lintner (1965), numerous studies on portfolio selection and performance measure have been based upon the mean-variance framework. However, several researchers (e.g., Arditti (1967, and 1971), Samuelson (1970), and Rubinstein (1973)) argue that the higher moments cannot be neglected unless there is reason to believe that: (i) the asset returns are normally distributed and the investor's utility function is quadratic, or (ii) the empirical evidence demonstrates that higher moments are irrelevant to the investor's decision. Based on the same argument, this dissertation investigates the impact of higher moments of return distributions on three issues concerning the 14 international stock markets.^ First, the portfolio selection with skewness is determined using: the Polynomial Goal Programming in which investor preferences for skewness can be incorporated. The empirical findings suggest that the return distributions of international stock markets are not normally distributed, and that the incorporation of skewness into an investor's portfolio decision causes a major change in the construction of his optimal portfolio. The evidence also indicates that an investor will trade expected return of the portfolio for skewness. Moreover, when short sales are allowed, investors are better off as they attain higher expected return and skewness simultaneously.^ Second, the performance of international stock markets are evaluated using two types of performance measures: (i) the two-moment performance measures of Sharpe (1966), and Treynor (1965), and (ii) the higher-moment performance measures of Prakash and Bear (1986), and Stephens and Proffitt (1991). The empirical evidence indicates that higher moments of return distributions are significant and relevant to the investor's decision. Thus, the higher moment performance measures should be more appropriate to evaluate the performances of international stock markets. The evidence also indicates that various measures provide a vastly different performance ranking of the markets, albeit in the same direction.^ Finally, the inter-temporal stability of the international stock markets is investigated using the Parhizgari and Prakash (1989) algorithm for the Sen and Puri (1968) test which accounts for non-normality of return distributions. The empirical finding indicates that there is strong evidence to support the stability in international stock market movements. However, when the Anderson test which assumes normality of return distributions is employed, the stability in the correlation structure is rejected. This suggests that the non-normality of the return distribution is an important factor that cannot be ignored in the investigation of inter-temporal stability of international stock markets. ^

Three essays on the microstructure of exchange traded funds

Exchange traded funds (ETFs) have increased significantly in popularity since they were first introduced in 1993. However, there is still much that is unknown about ETFs in the extant literature. This dissertation attempts to fill gaps in the ETF literature by using three related essays. In these three essays, we compare ETFs to closed ended mutual funds (CEFs) by decomposing the bid-ask spread into its three components; we look at the intraday shape of ETFs and compare it to the intraday shape of equities as well as examine the co-integration factor between ETFs on the London Stock Exchange and the New York Stock Exchange; we also examine the differences between leveraged ETFs and unleveraged ETFs by analyzing the impact of liquidity and volatility. These three essays are presented in Chapters 1, 2, and 3, respectively. ^ Chapter one uses the Huang and Stoll (1997) model to decompose the bid-ask spread in CEFs and ETFs for two distinct periods—a normal and a volatile period. We show a higher adverse selection component for CEFs than for ETFs without regard to volatility. However, both ETFs and CEFs increased in magnitude of the adverse selection component in the period of high volatility. Chapter two uses a mix of the Werner and Kleidon (1993) and the Hupperets and Menkveld (2002) methods to get the intraday shape of ETFs and analyze co-integration between London and New York trading. We find two different shapes for New York and London ETFs. There also appears to be evidence of co-integration in the overlapping two-hour trading period but not over the entire trading day for the two locations. The third chapter discusses the new class of ETFs called leveraged ETFs. We examine the liquidity and depth differences between unleveraged and leveraged ETFs at the aggregate level and when the leveraged ETFs are classified by the leveraged multiples of -3, -2, -1, 2, and 3, both for a normal and a volatile period. We find distinct differences between leveraged and unleveraged ETFs at the aggregate level, with leveraged ETFs having larger spreads than unleveraged ETFs. Furthermore, while both leveraged and unleveraged ETFs have larger spreads in high volatility, for the leveraged ETFs the change in magnitude is significantly larger than for the unleveraged ETFs. Among the multiples, the -2 leveraged ETF is the most pronounced in its liquidity characteristics, more so in volatile times. ^