Hybrid journal (It can contain Open Access articles) ISSN (Print) 1479-8409 - ISSN (Online) 1479-8417 Published by Oxford University Press[396 journals]

Authors:Barra I; Borowska A, Koopman S. Pages: 384 - 424 Abstract: We investigate high-frequency volatility models for analyzing intradaily tick by tick stock price changes using Bayesian estimation procedures. Our key interest is the extraction of intradaily volatility patterns from high-frequency integer price changes. We account for the discrete nature of the data via two different approaches: ordered probit models and discrete distributions. We allow for stochastic volatility by modeling the variance as a stochastic function of time, with intraday periodic patterns. We consider distributions with heavy tails to address occurrences of jumps in tick by tick discrete prices changes. In particular, we introduce a dynamic version of the negative binomial difference model with stochastic volatility. For each model, we develop a Markov chain Monte Carlo estimation method that takes advantage of auxiliary mixture representations to facilitate the numerical implementation. This new modeling framework is illustrated by means of tick by tick data for two stocks from the NYSE and for different periods. Different models are compared with each other based on the predictive likelihoods. We find evidence in favor of our preferred dynamic negative binomial difference model. PubDate: Thu, 03 May 2018 00:00:00 GMT DOI: 10.1093/jjfinec/nby010 Issue No:Vol. 16, No. 3 (2018)

Authors:Savva C; Theodossiou P. Pages: 486 - 521 Abstract: The relationship between risk and expected returns has been investigated extensively in the financial economics literature. Theoretical models generally predict a positive relation between the two. Nevertheless, the empirical findings so far have been inconclusive. Using a generalization of the analytical framework developed by Theodossiou and Savva (2016) along with time-varying asymmetry, linked to the upside and downside uncertainty, the risk–return puzzle is investigated across international stock markets. The investigation reveals that the contradictory findings are the result of ignoring the impact of skewness on the total price of risk. That is, in the absence of skewness the relationship between risk and return is positive as depicted by finance theory. However, negative skewness results in lowering the total price of risk and in some cases reverting its sign from positive to negative. PubDate: Mon, 16 Jul 2018 00:00:00 GMT DOI: 10.1093/jjfinec/nby014 Issue No:Vol. 16, No. 3 (2018)

Authors:Feunou B; Jahan-Parvar M, Okou C. Pages: 341 - 383 Abstract: We propose a new decomposition of the variance risk premium (VRP) in terms of upside and downside VRPs. These components reflect market compensation for changes in good and bad uncertainties. Empirically, we establish that the downside VRP is the main component of the VRP. We find a positive and significant link between the downside VRP and the equity premium, and a negative but statistically insignificant link between the upside VRP and the equity premium. The opposite relationships between these two components and the equity premium explains the stronger link found between the downside VRP and the equity premium compared with the well-established relationship between VRP and the equity premium. A simple equilibrium consumption-based asset pricing model, fitted to the U.S. data, supports our decomposition. PubDate: Wed, 28 Jun 2017 00:00:00 GMT DOI: 10.1093/jjfinec/nbx020 Issue No:Vol. 16, No. 3 (2017)

Authors:Yeap C; Kwok S, Choy S. Pages: 425 - 460 Abstract: We study a generalized hyperbolic (GH) time-changed Lévy process for option pricing and examine six three-parameter special cases: the variance gamma (VG) model of Madan, Carr, and Chang (1998), t, hyperbolic (H), normal inverse Gaussian (NIG), reciprocal hyperbolic (RH), and normal reciprocal inverse Gaussian (NRIG) option pricing models. We study the GH model’s moment properties of the associated risk-neutral distribution of logarithmic spot returns, and obtain an explicit pricing formula for European options facilitated by the time-change Lévy process construction. Using S&P 500 Index European options during low and high volatility sample periods, we compare the GH model empirically with existing benchmark models such as the finite-moment log-stable model and the Black–Scholes model. The GH model offers the best in- and out-of-sample performance overall, and a proposed t model special case generally outperforms the existing VG special case. We also present a stochastic volatility extension of the GH model. PubDate: Tue, 17 Oct 2017 00:00:00 GMT DOI: 10.1093/jjfinec/nbx030 Issue No:Vol. 16, No. 3 (2017)

Authors:Kokoszka P; Miao H, Reimherr M, et al. Pages: 461 - 485 Abstract: Motivated by testing the significance of risk factors for a cross-section of returns, we develop an inferential framework which involves function-on-scalar regression. Asymptotic theory is developed assuming the factors form a weakly dependent vector-valued time series, and the regression errors are weakly dependent functions. To accommodate the empirical behavior of the cross-section of returns and of the factors, we allow both the factors and the error functions can exhibit mild departures from stationarity. This requires new asymptotic theory which leads to several tests for the significance of function-valued regression coefficients. The new approach to the study of the significance of risk factors for a cross-section of returns complements the established Fama–French approach based on portfolio construction. It is more suitable if the statistical significance of the risk factors is to be rigorously controlled. PubDate: Mon, 28 Aug 2017 00:00:00 GMT DOI: 10.1093/jjfinec/nbx027 Issue No:Vol. 16, No. 3 (2017)