We develop a discrete-time affine stochastic volatility model with time-varying conditional skewness (SVS). Importantly, we disentangle the dynamics of conditional volatility and conditional skewness in a coherent way. Our approach allows current asset returns to be asymmetric conditional on...

This book brings together domains in financial asset pricing and valuation, financial investment theory, econometrics modeling, and the empirical analyses of financial data by applying appropriate econometric techniques. These domains are highly intertwined and should be properly understood in...

The purpose of the paper is to propose a global discrete-time modeling of the term structure of interest rates able to capture simultaneously the following important features : (i) an historical dynamics of the factor driving term structure shapes involving several lagged values, and switching...

The purpose of this paper is to propose a general econometric approach to no-arbitrage asset pricing modelling based on three main ingredients: (i) the historical discrete-time dynamics of the factor representing the information, (ii) the Stochastic Discount Factor (SDF), and (iii) the...

We propose an asset pricing model where preferences display generalized disappointment aversion (Routledge and Zin, 2009) and the endowment process involves long-run volatility risk. These preferences, which are embedded in the Epstein and Zin (1989) recursive utility framework, overweight...

An attempt is made in this paper to examine whether stock returns in two premier two exchanges in India namely, Bombay Stock Exchange (BSE), and National Stock Exchange (NSE) follow a random walk. Towards this end, data on major indices during the period 1997 to 2009 are analyzed by using...

We propose an asset pricing model where preferences display generalized disappointment aversion (Routledge and Zin, 2009) and the endowment process involves long-run volatility risk. These preferences, which are embedded in the Epstein and Zin (1989) recursive utility framework, overweight...

This paper presents a new modelling framework for day–ahead electricity prices based on multivariate Lévy semistationary (MLSS) processes. Day–ahead prices specify the prices for electricity delivered over certain time windows on the next day and are determined in a daily auction. Since...

We examine the Stein-rule shrinkage estimator for possible improvements in estimation and forecasting when there are many predictors in a linear time series model. We consider the Stein-rule estimator of Hill and Judge (1987) that shrinks the unrestricted unbiased OLS estimator towards a...

This paper is concerned with methods for analysing spatial data. After initial discussion on the nature of spatial data, including the concept of randomness, we focus most of our attention on linear regression models that involve interactions between agents across space. The introduction of...