This paper addresses two important questions that have, so far, been studied separately in the literature. First, the paper aims at explaining the high volatility of long-term interest rates observed in the data, which is hard to replicate using standard macro models. Building a small-scale...

We use a simple New Keynesian model, with firm specific capital, non-zero steady-state inflation, long-run risks and Epstein-Zin preferences to study the volatility implications of a monetary policy shock. An unexpected increases in the policy rate by 150 basis points causes output and inflation...

Econometric estimation using simulation techniques, such as the efficient method of moments, may betime consuming. The use of ordinary matrix programming languages such as Gauss, Matlab, Ox or S-plus will very often cause extra delay. For the Efficient Method of Moments implemented to...

We demonstrate that the parameters controlling skewness and kurtosis in popular equity return models estimated at daily frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information content of realized volatility measures extracted...

This essay is aimed to provide a straightforward and sufficiently accessible demonstration of some known procedures for stochastic volatility model. It reviews the important related concepts, gives informal derivations of the methods and can be useful as a cookbook for a novice. The exposition...

We propose a jump robust positive semidefinite rank-based estimator for the daily covariance matrix based on high-frequency intraday returns. It disentangles covariance estimation into variance and correlation components. This allows to estimate correlations over lower sampling frequencies, to...

An enhanced option pricing framework that makes use of both continuous and discontinuous time paths based on a geometric Brownian motion and Poisson-driven jump processes respectively is performed in order to better fit with real-observed stock price paths while maintaining the analytical...

A new version of the local scale model of Shephard (1994) is presented. Its features are identically distributed evolution equation disturbances, the incorporation of in-the-mean effects, and the incorporation of variance regressors. A Bayesian posterior simulator and a new simulation smoother...

We compare more than 1000 different volatility models in terms of their fit to the historical ISE-100 Index data and their forecasting performance of the conditional variance in an out-of-sample setting. Exponential GARCH model of Nelson (1991) with “constant mean, t-distribution, one lag...

We present an embarrassingly simple method for supervised learning of SABR model's European option price function based on lookup table or rote machine learning. Performance in time domain is comparable to generally used analytic approximations utilized in financial industry. However, unlike the...