Search results for "Stochastic volatility"
showing 10 items of 36 documents
Dynamic Volatility Weighting in the Presence of Transaction Costs
2015
Numerous empirical studies demonstrate the superiority of dynamic strategies with volatility weighting over time mechanism. These strategies control the portfolio risk over time by adjusting the risk exposure according to updated volatility forecasts. Yet, in order to reap all benefits promised by volatility weighting over time, the composition of the active portfolio must be revised rather frequently. Transaction costs represent a serious obstacle to benefiting from this dynamic risk control technique. In this paper we propose a modified volatility weighting strategy that allows one to reduce dramatically the amount of trading costs. The empirical evidence shows that the advantages of the …
An Operator Splitting Method for Pricing American Options
2008
Pricing American options using partial (integro-)differential equation based methods leads to linear complementarity problems (LCPs). The numerical solution of these problems resulting from the Black-Scholes model, Kou’s jump-diffusion model, and Heston’s stochastic volatility model are considered. The finite difference discretization is described. The solutions of the discrete LCPs are approximated using an operator splitting method which separates the linear problem and the early exercise constraint to two fractional steps. The numerical experiments demonstrate that the prices of options can be computed in a few milliseconds on a PC.
A Stochastic Variance Factor Model for Large Datasets and an Application to S&P Data
2008
The aim of this paper is to consider multivariate stochastic volatility models for large dimensional datasets. We suggest the use of the principal component methodology of Stock and Watson [Stock, J.H., Watson, M.W., 2002. Macroeconomic forecasting using diffusion indices. Journal of Business and Economic Statistics, 20, 147–162] for the stochastic volatility factor model discussed by Harvey, Ruiz, and Shephard [Harvey, A.C., Ruiz, E., Shephard, N., 1994. Multivariate Stochastic Variance Models. Review of Economic Studies, 61, 247–264]. We provide theoretical and Monte Carlo results on this method and apply it to S&P data.
THE STOCHASTIC VOLATILITY MODEL OF BARNDORFF-NIELSEN AND SHEPHARD IN COMMODITY MARKETS
2010
We consider the non-Gaussian stochastic volatility model of Barndorff-Nielsen and Shephard for the exponential mean-reversion model of Schwartz proposed for commodity spot prices. We analyze the properties of the stochastic dynamics, and show in particular that the log-spot prices possess a stationary distribution defined as a normal variance-mixture model. Furthermore, the stochastic volatility model allows for explicit forward prices, which may produce a hump structure inherited from the mean-reversion of the stochastic volatility. Although the spot price dynamics has continuous paths, the forward prices will have a jump dynamics, where jumps occur according to changes in the volatility p…
Volatility co-movements: a time-scale decomposition analysis
2015
In this paper, we are interested in detecting contagion from US to European stock market volatilities in the period immediately after the Lehman Brothers collapse. The analysis is based on a factor decomposition of the covariance matrix, in the time and frequency domain, using wavelets. The analysis aims to disentangle two components of volatility contagion (anticipated and unanticipated by the market). Once we focus on standardized factor loadings, the results show no evidence of contagion (from the US) in market expectations (coming from implied volatility) and evidence of unanticipated contagion (coming from the volatility risk premium) for almost any European country. Finally, the estim…
HETEROGENEITY IN RISK PREFERENCES LEADS TO STOCHASTIC VOLATILITY
2018
This paper studies the price processes of a claim on terminal endowment and of a claim on firm book value when the underlying variables follow a bivariate geometric Brownian motion. If the state-price process is multiplicatively separable into time and endowment functions, our main result shows that firm (endowment) price volatility is stochastic (state-dependent) if, and only if, the endowment function is not a power function. In a pure exchange economy populated by two agents with constant relative risk aversion (CRRA) preferences we confirm the separability, and we show furthermore that firm (endowment) price volatility is stochastic (state-dependent) if, and only if, both agents are he…
Stochastic dynamical modelling of spot freight rates
2014
Based on empirical analysis of the Capesize and Panamax indices, we propose different continuous-time stochastic processes to model their dynamics. The models go beyond the standard geometric Brownian motion, and incorporate observed effects like heavy-tailed returns, stochastic volatility and memory. In particular, we suggest stochastic dynamics based on exponential Levy processes with normal inverse Gaussian distributed logarithmic returns. The Barndorff-Nielsen and Shephard stochastic volatility model is shown to capture time-varying volatility in the data. Finally, continuous-time autoregressive processes provide a class of models sufficiently rich to incorporate short-term persistence …
Does Inflation Targeting Affect the Trade-off Between Output Gap and Inflation Variability?
2002
We utilize a stochastic volatility model to analyse the possible effects of inflation targeting on the trade–off between output gap variability and inflation variability. We find that the adoption of inflation targets (in New Zealand, Australia, Canada, the UK, Sweden and Finland) might result in a more favourable monetary policy trade–off (except in Australia and Finland). This conclusion is reached by comparing, first, the economic performance of targeting countries in the 1980s and the 1990s; and second, the economic performance in the 1990s of targeting and non–targeting countries (the USA, Japan, Switzerland, Germany, France and the Netherlands). We focus on two possible explanations f…
Enhancement of stability in systems with metastable states
2007
The investigation of noise‐induced phenomena in far from equilibrium systems is one of the approach used to understand the behaviour of physical and biological complex systems. Metastability is a generic feature of many nonlinear systems, and the problem of the lifetime of metastable states involves fundamental aspects of nonequilibrium statistical mechanics. The enhancement of the life‐time of metastable states through the noise enhanced stability effect and the role played by the resonant activation phenomenon will be discussed in models of interdisciplinary physics: (i) Ising model (ii) Josephson junction; (iii) stochastic FitzHugh‐Nagumo model; (iv) a population dynamics model, and (v) …
On the Link Between Volatility and Growth
2011
A model of growth with endogenous innovation and distortionary taxes is presented. Since innovation is the only source of volatility, any variable that influences innovation directly affects volatility and growth. This joint endogeneity is illustrated by working out the effects through which economies with different tax levels differ in their volatility and growth process. We obtain analytical measures of macro volatility based on cyclical output and on output growth rates for plausible parametric restrictions. This analysis implies that controls for taxes should be included in the standard growth-volatility regressions. Our estimates show that the conventional Ramey-Ramey coefficient is af…