A Comprehensive Comparison of Alternative Tests for Jumps in Asset Prices

This paper presents a comprehensive comparison of nonparametric tests for jumps in the prices of financial assets. The relative performance of eight tests is examined in a Monte Carlo simulation covering scenarios of both finite and infinite activity jumps, and stochastic volatility models with continuous and discontinuous volatility sample paths. The main contribution of the paper is an investigation of the performance of the tests in the presence of various market microstructure effects, including microstructure noise, infrequent trading and deterministic diurnal volatility. The simulation results reveal important differences in terms of size and power of the tests across the different data generating processes. Zero intraday returns and microstructure frictions are shown to induce important distortions. An empirical application to prices from the forex market, stock market and futures market complements the analysis.Quadratic variation, jumps, stochastic volatility, realized measures,high-frequency data

Semiparametric Conditional Quantile Models for Financial Returns and Realized Volatility

This paper investigates how the conditional quantiles of future returns and volatility of financial assets vary with various measures of ex-post variation in asset prices as well as option-implied volatility. We work in the flexible quantile regression framework and rely on recently developed model-free measures of integrated variance, upside and downside semivariance, and jump variation. Our results for the S&P 500 and WTI Crude Oil futures contracts show that simple linear quantile regressions for returns and heterogenous quantile autoregressions for realized volatility perform very well in capturing the dynamics of the respective conditional distributions, both in absolute terms as well as relative to a couple of well-established benchmark models. The models can therefore serve as useful risk management tools for investors trading the futures contracts themselves or various derivative contracts written on realized volatility

Volatility Transmission in Emerging European Foreign Exchange Markets

This paper studies the dynamics of volatility transmission between Central European currencies and euro/dollar foreign exchange using model-free estimates of daily exchange rate volatility based on intraday data. We formulate a flexible yet parsimonious parametric model in which the daily realized volatility of a given exchange rate depends both on its own lags as well as on the lagged realized volatilities of the other exchange rates. We find evidence of statistically significant intra-regional volatility spillovers among the Central European foreign exchange markets. With the exception of the Czech currency, we find no significant spillovers running from euro/dollar to the Central European foreign exchange markets. To measure the overall magnitude and evolution of volatility transmission over time, we construct a dynamic version of the Diebold-Yilmaz volatility spillover index, and show that volatility spillovers tend to increase in periods characterized by market uncertainty.foreign exchange markets, volatility, spillovers, intraday data, nonlinear dynamics

Testing and Modeling Distributions of Returns and Volatility of Financial Assets

This thesis exploits the information contained in high-frequency data to test and model the distributions of returns of financial assets and their volatility. In Chapter 1 we study the asymptotics of some common tests for normality when applied to returns standardized by noise measures of volatility based on the use of high-frequency data. Chapter 2 proposes dynamic models for conditional quantiles of daily returns and realized volatility exploiting the information contained in various components of historical volatility as well as option-implied volatility. Chapter 3 provides a comprehensive simulation-based comparison of alternative tests for jumps in asset prices in order to get a better understanding of the performance of the tests under different, empirically relevant, scenarios. Chapter 4 extends the testing procedures studies in Chapter 1 to the multivariate context and provides new empirical evidence about the validity of the mixture of normals hypothesis in foreign exchange markets. Chapter 5 studies the dynamics of the tail risk in the hedge fund industry. Finally, Chapter 6 introduces a new method for estimating large covariance matrices

Modeling and forecasting persistent financial durations

This paper introduces the Markov-Switching Multifractal Duration (MSMD) model by adapting the MSM stochastic volatility model of Calvet and Fisher (2004) to the duration setting. Although the MSMD process is exponential \udf-mixing as we show in the paper, it is capable of generating highly persistent autocorrelation. We study analytically and by simulation how this feature of durations generated by the MSMD process propagates to counts and realized volatility. We employ a quasi-maximum likelihood estimator of the MSMD parameters based on the Whittle approximation and establish its strong consistency and asymptotic normality for general MSMD specifications. We show that the Whittle estimation is a computationally simple and fast alternative to maximum likelihood. Finally, we compare the performance of the MSMD model with competing short- and long-memory duration models in an out-of-sample forecasting exercise based on price durations of three major foreign exchange futures contracts. The results of the comparison show that the MSMD and the Long Memory Stochastic Duration model perform similarly and are superior to the short-memory Autoregressive Conditional Duration models

Volatility Transmission in Emerging European Foreign Exchange Markets

This paper studies the dynamics of volatility transmission between Central European (CE) currencies and the EUR/USD foreign exchange using model-free estimates of daily exchange rate volatility based on intraday data. We formulate a flexible yet parsimonious parametric model in which the daily realized volatility of a given exchange rate depends both on its own lags as well as on the lagged realized volatilities of the other exchange rates. We find evidence of statistically significant intra-regional volatility spillovers among the CE foreign exchange markets. With the exception of the Czech and, prior to the recent turbulent economic events, Polish currencies, we find no significant spillovers running from the EUR/USD to the CE foreign exchange markets. To measure the overall magnitude and evolution of volatility transmission over time, we construct a dynamic version of the Diebold-Yilmaz volatility spillover index and show that volatility spillovers tend to increase in periods characterized by market uncertainty.http://deepblue.lib.umich.edu/bitstream/2027.42/133036/1/wp1020.pd

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