Levy and Levy (2002, 2004) develop the Prospect and Markowitz stochastic dominance theory with S-... more Levy and Levy (2002, 2004) develop the Prospect and Markowitz stochastic dominance theory with S-shaped and reverse S-shaped utility functions for investors. In this paper, we extend Levy and Levy's Prospect Stochastic Dominance theory (PSD) and Markowitz Stochastic Dominance theory (MSD) to the first three orders and link the corresponding S-shaped and reverse S-shaped utility functions to the first three orders. We also provide experiments to illustrate each case of the MSD and PSD to the first three orders and demonstrate that the higher order MSD and PSD cannot be replaced by the lower order MSD and PSD. Prospect theory has been regarded as a challenge to the expected utility paradigm. Levy and Levy (2002) prove that the second order PSD and MSD satisfy the expected utility paradigm. In our paper we take Levy and Levy's results one step further by showing that both PSD and MSD of any order are consistent with the expected utility paradigm. Furthermore, we formulate some other properties for the PSD and MSD including the hierarchy that exists in both PSD and MSD relationships; arbitrage opportunities that exist in the first orders of both PSD and MSD; and that for any two prospects under certain conditions, their third order MSD preference will be 'the opposite' of or 'the same' as their counterpart third order PSD preference. By extending Levy and Levy's work, we provide investors with more tools for empirical analysis, with which they can identify the first order PSD and MSD prospects and discern arbitrage opportunities that could increase his/her utility as well as wealth and set up a zero dollar portfolio to make huge profit. Our tools also enable investors to identify the third order PSD and MSD prospects and make better choices.
Gordon and Shapiro (1956) first equated the price of a share with the present value of future div... more Gordon and Shapiro (1956) first equated the price of a share with the present value of future dividends and derived the well-known relationship. Since then, there have been many improvements on the theory. For example, Thompson (1985, 1987) combined the "dividend yield plus growth" method with Box-Jenkins time series analysis of past dividend experience to estimate the cost of capital and its "reliability" for individual firms. Thompson and Wong (1991, 1996) proved the existence and uniqueness of the cost of capital and provided formula to estimate both the cost of capital and its reliability. However, their approaches cannot be used if the "reliability" does not exist or if there are multiple solutions for the "reliability". In this paper, we extend their theory by proving the existence and uniqueness of this reliability. In addition, we propose the estimators for the reliability and prove that the estimators converge to a true parameter. The estimation approach is further simplified, hence rendering computation easier. In addition, the properties of the cost of capital and its reliability will be analyzed with illustrations of several commonly used Box-Jenkins models.
In this paper, we develop some stochastic dominance theorems for the location and scale family an... more In this paper, we develop some stochastic dominance theorems for the location and scale family and linear combinations of random variables and for risk lovers as well as risk averters that extend results in Hadar and Russell (1971) and Tesfatsion (1976). The results are discussed and applied to decision-making.
This paper extends the work on location-scale (LS) family with general n random seed sources. Fir... more This paper extends the work on location-scale (LS) family with general n random seed sources. First, we clarify and generalize existing results in this multivariate setting. Some useful geometrical and topological properties of the location-scale expected utility functions are obtained. Second, we introduce and study some general non-expected utility functions defined over the LS family. Special care is taken in characterizing the shapes of the indifference curves induced by the location-scale expected utility functions and non-expected utility functions. Finally, efforts are also made to study several welldefined partial orders and dominance relations defined over the LS family. These include the first-and second-order stochastic dominances, the mean-variance rule, and a newly defined location-scale dominance.
By incorporating both majorization theory and stochastic dominance theory, this paper presents a ... more By incorporating both majorization theory and stochastic dominance theory, this paper presents a general theory and a unifying framework for determining the diversification preferences of risk-averse investors and conditions under which they would unanimously judge a particular asset to be superior. In particular, we develop a theory for comparing the preferences of different convex combinations of assets that characterize a portfolio to give higher expected utility by second-order stochastic dominance. Our findings also provide additional methodology for determining the second-order stochastic dominance efficient set.
This study proposes a new model by partially combining personality traits (PT) and Technology Acc... more This study proposes a new model by partially combining personality traits (PT) and Technology Acceptance Model (TAM) attributes to examine the influences of personality characteristics (conscientiousness, openness) and perception of technology (perceived usefulness, perceives ease of use) on e-purchase intention. We use truncate sampling technique and survey questionnaire to target the sample of Taiwanese online consumers and collect data. We find that consciousness (CON) (personality attribute) significantly influences perceived usefulness (PU) (technology perception attributes), perceived ease of use (PEOU) (technology perception attributes) and openness to experience (OPE) (personality attribute). PU, PEOU and OPE have significant impacts on e-purchase intention (INT). PEOU has the strongest positive impact on (INT). In addition, PU, PEOU and OPE combined together mediate the relationship between CON and INT. Further post hoc analysis of the mediation shows that both PU and PEOU are sustainable mediators. However, OPE is not a significant mediator.
Since the pioneering work of Gerhard Grüss dating back to 1935, Grüss's inequality and, more gene... more Since the pioneering work of Gerhard Grüss dating back to 1935, Grüss's inequality and, more generally, Grüss-type bounds for covariances have fascinated researchers and found numerous applications in areas such as economics, insurance, reliability, and, more generally, decision making under uncertainly. Grüss-type bounds for covariances have been established mainly under most general dependence structures, meaning no restrictions on the dependence structure between the two underlying random variables. Recent work in the area has revealed a potential for improving Grüss-type bounds, including the original Grüss's bound, assuming dependence structures such as quadrant dependence (QD). In this paper we demonstrate that the relatively little explored notion of 'quadrant dependence in expectation' (QDE) is ideally suited in the context of bounding covariances, especially those that appear in the aforementioned areas of application. We explore this research avenue in detail, establish general Grüss-type bounds, and illustrate them with newly constructed examples of bivariate distributions, which are not QD but, nevertheless, are QDE. The examples rely on specially devised copulas. We supplement the examples with results concerning general copulas and their convex combinations. In the process of deriving Grüss-type bounds, we also establish new bounds for central moments, whose optimality is demonstrated.
In this paper we present two dynamic models of background risk. We first present a stochastic fac... more In this paper we present two dynamic models of background risk. We first present a stochastic factor model with an additive background risk. Thereafter, we present a dynamic model of simultaneous (correlated) multiplicative background risk and additive background risk. In so doing, we use a general utility function.
Levy and Levy (2002, 2004) develop the Prospect and Markowitz stochastic dominance theory with S-... more Levy and Levy (2002, 2004) develop the Prospect and Markowitz stochastic dominance theory with S-shaped and reverse S-shaped utility functions for investors. In this paper, we extend Levy and Levy's Prospect Stochastic Dominance theory (PSD) and Markowitz Stochastic Dominance theory (MSD) to the first three orders and link the corresponding S-shaped and reverse S-shaped utility functions to the first three orders. We also provide experiments to illustrate each case of the MSD and PSD to the first three orders and demonstrate that the higher order MSD and PSD cannot be replaced by the lower order MSD and PSD. Prospect theory has been regarded as a challenge to the expected utility paradigm. Levy and Levy (2002) prove that the second order PSD and MSD satisfy the expected utility paradigm. In our paper we take Levy and Levy's results one step further by showing that both PSD and MSD of any order are consistent with the expected utility paradigm. Furthermore, we formulate some other properties for the PSD and MSD including the hierarchy that exists in both PSD and MSD relationships; arbitrage opportunities that exist in the first orders of both PSD and MSD; and that for any two prospects under certain conditions, their third order MSD preference will be 'the opposite' of or 'the same' as their counterpart third order PSD preference. By extending Levy and Levy's work, we provide investors with more tools for empirical analysis, with which they can identify the first order PSD and MSD prospects and discern arbitrage opportunities that could increase his/her utility as well as wealth and set up a zero dollar portfolio to make huge profit. Our tools also enable investors to identify the third order PSD and MSD prospects and make better choices.
Gordon and Shapiro (1956) first equated the price of a share with the present value of future div... more Gordon and Shapiro (1956) first equated the price of a share with the present value of future dividends and derived the well-known relationship. Since then, there have been many improvements on the theory. For example, Thompson (1985, 1987) combined the "dividend yield plus growth" method with Box-Jenkins time series analysis of past dividend experience to estimate the cost of capital and its "reliability" for individual firms. Thompson and Wong (1991, 1996) proved the existence and uniqueness of the cost of capital and provided formula to estimate both the cost of capital and its reliability. However, their approaches cannot be used if the "reliability" does not exist or if there are multiple solutions for the "reliability". In this paper, we extend their theory by proving the existence and uniqueness of this reliability. In addition, we propose the estimators for the reliability and prove that the estimators converge to a true parameter. The estimation approach is further simplified, hence rendering computation easier. In addition, the properties of the cost of capital and its reliability will be analyzed with illustrations of several commonly used Box-Jenkins models.
In this paper, we develop some stochastic dominance theorems for the location and scale family an... more In this paper, we develop some stochastic dominance theorems for the location and scale family and linear combinations of random variables and for risk lovers as well as risk averters that extend results in Hadar and Russell (1971) and Tesfatsion (1976). The results are discussed and applied to decision-making.
This paper extends the work on location-scale (LS) family with general n random seed sources. Fir... more This paper extends the work on location-scale (LS) family with general n random seed sources. First, we clarify and generalize existing results in this multivariate setting. Some useful geometrical and topological properties of the location-scale expected utility functions are obtained. Second, we introduce and study some general non-expected utility functions defined over the LS family. Special care is taken in characterizing the shapes of the indifference curves induced by the location-scale expected utility functions and non-expected utility functions. Finally, efforts are also made to study several welldefined partial orders and dominance relations defined over the LS family. These include the first-and second-order stochastic dominances, the mean-variance rule, and a newly defined location-scale dominance.
By incorporating both majorization theory and stochastic dominance theory, this paper presents a ... more By incorporating both majorization theory and stochastic dominance theory, this paper presents a general theory and a unifying framework for determining the diversification preferences of risk-averse investors and conditions under which they would unanimously judge a particular asset to be superior. In particular, we develop a theory for comparing the preferences of different convex combinations of assets that characterize a portfolio to give higher expected utility by second-order stochastic dominance. Our findings also provide additional methodology for determining the second-order stochastic dominance efficient set.
This study proposes a new model by partially combining personality traits (PT) and Technology Acc... more This study proposes a new model by partially combining personality traits (PT) and Technology Acceptance Model (TAM) attributes to examine the influences of personality characteristics (conscientiousness, openness) and perception of technology (perceived usefulness, perceives ease of use) on e-purchase intention. We use truncate sampling technique and survey questionnaire to target the sample of Taiwanese online consumers and collect data. We find that consciousness (CON) (personality attribute) significantly influences perceived usefulness (PU) (technology perception attributes), perceived ease of use (PEOU) (technology perception attributes) and openness to experience (OPE) (personality attribute). PU, PEOU and OPE have significant impacts on e-purchase intention (INT). PEOU has the strongest positive impact on (INT). In addition, PU, PEOU and OPE combined together mediate the relationship between CON and INT. Further post hoc analysis of the mediation shows that both PU and PEOU are sustainable mediators. However, OPE is not a significant mediator.
Since the pioneering work of Gerhard Grüss dating back to 1935, Grüss's inequality and, more gene... more Since the pioneering work of Gerhard Grüss dating back to 1935, Grüss's inequality and, more generally, Grüss-type bounds for covariances have fascinated researchers and found numerous applications in areas such as economics, insurance, reliability, and, more generally, decision making under uncertainly. Grüss-type bounds for covariances have been established mainly under most general dependence structures, meaning no restrictions on the dependence structure between the two underlying random variables. Recent work in the area has revealed a potential for improving Grüss-type bounds, including the original Grüss's bound, assuming dependence structures such as quadrant dependence (QD). In this paper we demonstrate that the relatively little explored notion of 'quadrant dependence in expectation' (QDE) is ideally suited in the context of bounding covariances, especially those that appear in the aforementioned areas of application. We explore this research avenue in detail, establish general Grüss-type bounds, and illustrate them with newly constructed examples of bivariate distributions, which are not QD but, nevertheless, are QDE. The examples rely on specially devised copulas. We supplement the examples with results concerning general copulas and their convex combinations. In the process of deriving Grüss-type bounds, we also establish new bounds for central moments, whose optimality is demonstrated.
In this paper we present two dynamic models of background risk. We first present a stochastic fac... more In this paper we present two dynamic models of background risk. We first present a stochastic factor model with an additive background risk. Thereafter, we present a dynamic model of simultaneous (correlated) multiplicative background risk and additive background risk. In so doing, we use a general utility function.
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Papers by Alan Wong