Operations Research
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Operations Research
2016-10-23
Consistent tests for risk seeking behavior: A stochastic dominance approach
http://d.repec.org/n?u=RePEc:aeb:wpaper:201511:y:2015&r=ore
We develop non-parametric tests for prospect stochastic dominance Efficiency (PSDE) and Markowitz stochastic dominance efficiency (MSDE) with rejection regions determined by block bootstrap resampling techniques. Under the appropriate conditions we show that they are asymptotically conservative and consistent. We engage into Monte Carlo experiments to assess the nite sample size and power of the tests allowing for the presence of numerical errors. We use them to empirically analyze investor preferences and beliefs by testing whether the value-weighted market portfolio can be considered as efficient according to prospect and Markowitz stochastic dominance criteria when confronted to diversi cation principles made of risky assets. Our results indicate that we cannot reject the hypothesis of prospect stochastic dominance efficiency for the market portfolio. This is supportive of the claim that the particular portfolio can be rationalized as the optimal choice for any S-shaped utility function. Instead, we reject the hypothesis for Markowitz stochastic dominance, which could imply that there exist reverse S-shaped utility functions that do not rationalize the market portfolio.
Stelios Arvanitis
Nikolas Topaloglou
Non parametric test, prospect stochastic dominance efficiency,Markowitz stochastic dominance efficiency, simplical complex, extremal point, Linear Programming, Mixed Integer Programming, Block Bootstrap, Consistency
2015-11
Stochastic Dominance and Investorsâ€™ Behavior towards Risk: The Hong Kong Stocks and Futures Markets
http://d.repec.org/n?u=RePEc:pra:mprapa:74386&r=ore
This paper applies stochastic dominance (SD) tests to examine the dominance relationships between the futures and spot markets in Hong Kong. We also analyze the preferences for the risk averters, risk seekers, prospect investors, and Markowitz investors with further in dept of their positive and negative domains in these markets. We find that for the risk averters, spot dominates futures while for the risk seekers, futures dominate spot. This implies that the risk averters prefer to buy indexed stocks, while risk seekers are attracted to long index futures to maximize their expected utilities, but not necessary their wealth. We also conclude that in general, the prospect investors prefer spot in the positive domain and prefer futures in the negative domain while the Markowitz investors prefer spot in the negative domain and prefer futures in the positive domain.
Lam, Kin
Lean, Hooi Hooi
Wong, Wing-Keung
stochastic dominance; stock index futures; risk preference; S-shape utility functions.
2016-10-09
Measuring Uncertainty and Its Impact on the Economy
http://d.repec.org/n?u=RePEc:fip:fedcwp:1622&r=ore
We propose a new framework for measuring uncertainty and its effects on the economy, based on a large VAR model with errors whose stochastic volatility is driven by two common unobservable factors, representing aggregate macroeconomic and financial uncertainty. The uncertainty measures can also influence the levels of the variables so that, contrary to most existing measures, ours reflect changes in both the conditional mean and volatility of the variables, and their impact on the economy can be assessed within the same framework. Moreover, identification of the uncertainty shocks is simplified with respect to standard VAR-based analysis, in line with the FAVAR approach and with heteroskedasticity-based identification. Finally, the model, which is also applicable in other contexts, is estimated with a new Bayesian algorithm, which is computationally efficient and allows for jointly modeling many variables, while previous VAR models with stochastic volatility could only handle a handful of variables. Empirically, we apply the method to estimate uncertainty and its effects using US data, finding that there is indeed substantial commonality in uncertainty, sizable effects of uncertainty on key macroeconomic and financial variables with responses in line with economic theory.
Clark, Todd E.
Carriero, Andrea
Massimiliano, Marcellino
Bayesian VARs; stochastic volatility; large datasets;
2016-10-14
Frictional Unemployment with Stochastic Bubbles
http://d.repec.org/n?u=RePEc:cpr:ceprdp:11561&r=ore
Bubbles are recurrent events, which contribute to both macroeconomic and employment volatility. We introduce stochastic bubbles in the standard search-and-matching model of the labor market. The economy alternates between latent and bubbly states, each being associated with a distinct solution for the market value of firms (respectively, stable or explosive). Bubbles in firm value induce distortions in hiring decisions and wages, which we explicitly characterize. Faced with bubbles, the social planner optimally deviates from the standard Hosios efficiency condition. The optimal share of workers in total surplus must be above the elasticity of hiring rates, by a small but increasing amount as the bubble expands. Finally, our specification for bubbles significantly improves the quantitative ability of the model to match U.S. data, along both real and financial dimensions.
Vuillemey, Guillaume
Wasmer, Etienne
bubbles; labor frictions; Unemployment volatility
2016-10