Search results for "Stochastic volatility"
showing 10 items of 36 documents
Dimension reduction for time series in a blind source separation context using r
2021
Funding Information: The work of KN was supported by the CRoNoS COST Action IC1408 and the Austrian Science Fund P31881-N32. The work of ST was supported by the CRoNoS COST Action IC1408. The work of JV was supported by Academy of Finland (grant 321883). We would like to thank the anonymous reviewers for their comments which improved the paper and package considerably. Publisher Copyright: © 2021, American Statistical Association. All rights reserved. Multivariate time series observations are increasingly common in multiple fields of science but the complex dependencies of such data often translate into intractable models with large number of parameters. An alternative is given by first red…
The stabilizing effect of volatility in financial markets
2017
In financial markets, greater volatility is usually considered synonym of greater risk and instability. However, large market downturns and upturns are often preceded by long periods where price returns exhibit only small fluctuations. To investigate this surprising feature, here we propose using the mean first hitting time, i.e. the average time a stock return takes to undergo for the first time a large negative or positive variation, as an indicator of price stability, and relate this to a standard measure of volatility. In an empirical analysis of daily returns for $1071$ stocks traded in the New York Stock Exchange, we find that this measure of stability displays nonmonotonic behavior, …
Understanding the determinants of volatility clustering in terms of stationary Markovian processes
2016
Abstract Volatility is a key variable in the modeling of financial markets. The most striking feature of volatility is that it is a long-range correlated stochastic variable, i.e. its autocorrelation function decays like a power-law τ − β for large time lags. In the present work we investigate the determinants of such feature, starting from the empirical observation that the exponent β of a certain stock’s volatility is a linear function of the average correlation of such stock’s volatility with all other volatilities. We propose a simple approach consisting in diagonalizing the cross-correlation matrix of volatilities and investigating whether or not the diagonalized volatilities still kee…
A Scenario Simulation Model of Stock's Volatility Based on a Stationary Markovian Process
2013
In this paper we discuss univariate statistical properties of volatility. We present a parsimonious univariate model that well reproduces two stylized facts of volatility: the power-law decay of the volatility probability density function with exponent α and the power-law decay of the autocorrelation function with exponent β. Such model also reproduces, at least qualitatively, the empirical observation than when the probability density function decays faster, then the autocorrelation decays slower. Another important feature investigated within the model is the mean First Passage Time (mFPT) Tx0 (Λ) of volatility time-series. We show that the proposed model allows to obtain the mFPT in terms…
A Multivariate Non-Gaussian Stochastic Volatility Model with Leverage for Energy Markets
2009
Spot prices in energy markets exhibit special features like price spikes, mean-reversion inverse, stochastic volatility, inverse leverage effect and co-integration between the different commodities. In this paper a multivariate stochastic volatility model is introduced which captures these features. Second order structure and stationary issues of the model are analysed. Moreover the implied multivariate forward model is derived. Due to the flexibility of the model stylized facts of the forward curve as contango, backwardation and humps are explained. Moreover, a transformed-based method to price options on the forward is described, where fast and precise algorithms for price computations ca…
Firm Size and Volatility Analysis in the Spanish Stock Market
2011
In this article, three strongly related questions are studied. First, volatility spillovers between large and small firms in the Spanish stock market are analyzed by using a conditional CAPM with an asymmetric multivariate GARCH-M covariance structure. Results show that there exist bidirectional volatility spillovers between both types of firms, especially after bad news. Second, the volatility feedback hypothesis explaining the volatility asymmetry feature is investigated. Results show significant evidence for this hypothesis. Finally, the study uncovers that conditional beta coefficient estimates within the used model are insensitive to sign and size asymmetries in the unexpected shock re…
Univariate and multivariate statistical aspects of equity volatility
2004
We discuss univariate and multivariate statistical properties of volatility time series of equities traded in a financial market. Specifically, (i) we introduce a two-region stochastic volatility model able to well describe the unconditional pdf of volatility in a wide range of values and (ii) we quantify the stability of the results of a correlation-based clustering procedure applied to synchronous time evolution of a set of volatility time series.
An empirical analysis of growth volatility: A Markov chain approach
2005
This paper studies the determinants of growth rate volatility, focusing on the effect of level of GDP, structural change and the size of economy. First we provide a graphical analysis based on nonparametric techniques, then a quantitative analysis which follows the distribution dynamics approach. Growth volatility appears to (i) decrease with per capita GDP, (ii) increase with the share of the agricultural sector on GDP and, (iii) decrease with the size of the economy, measured by a combination of total GDP and trade openness. However, we show that the explanatory power of per capita GDP tends to vanish when we control for the size of the economy. © 2005 Springer-Verlag Berlin Heidelberg.
Option-Implied Volatility Spillovers between Risk Factors in FX Markets and States of the Global Economy
2016
This study employs option price data to back out the implied portfolio volatilities of the dollar and carry trade risk factors of the G-10 currencies. To investigate expected volatility spillover effects between risk factors in FX markets, we extend Grobys (2015) and Diebold and Yilmaz (2009) by constructing expected volatility spillover indices based upon the forecast-error variance decomposition of Vector-Autoregression models employing option-implied portfolio volatilities. Surprisingly, the dollar and carry trade risk factors that are orthogonal in the first moment exhibit strong stochastic interrelations in the second expected moment. Our findings indicate that expected high spillover …
Pricing of Forwards and Options in a Multivariate Non-Gaussian Stochastic Volatility Model for Energy Markets
2013
In Benth and Vos (2013) we introduced a multivariate spot price model with stochastic volatility for energy markets which captures characteristic features, such as price spikes, mean reversion, stochastic volatility, and inverse leverage effect as well as dependencies between commodities. In this paper we derive the forward price dynamics based on our multivariate spot price model, providing a very flexible structure for the forward curves, including contango, backwardation, and hump shape. Moreover, a Fourier transform-based method to price options on the forward is described.