Essays On Financial Return And Volatility Modeling
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Essays On Financial Return And Volatility Modeling
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Author : Jing Wu (Ph. D.)
language : en
Publisher:
Release Date : 2012
Essays On Financial Return And Volatility Modeling written by Jing Wu (Ph. D.) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
My dissertation consists of three essays focusing on modeling financial asset return and volatility. The first essay proposes a threshold GARCH model to describe the regimeswitching in volatility dynamics of financial asset returns. In the threshold model the switching of regimes is triggered by an observable threshold variable, while volatility follows a GARCH process within each regime. This model can be viewed as a special case of the random coefficient GARCH model. We establish theoretical conditions, which ensure that the return process in the threshold model is strictly stationary, as well as conditions for the existence of finite variance and fourth moment. A simulation study is further conducted to examine the finite sample properties of the maximum likelihood estimator. The second essay extends our study of the threshold GARCH model to an empirical application. The empirical results support the use of the threshold variable to identify the regime shifts in the volatility process. Especially when VIX is used as the threshold, we are able to separate the clustering of volatile periods corresponding to various financial crises. According to 5 common measures on forecasting evaluation, the threshold GARCH model provides better volatility forecasts for stocks as well as currency exchange rates. The third essay examines the effect of time structure on the estimation performance of independent component analysis (ICA) models and provides guidance in applying the ICA model to time series data. We compare the performance of the basic ICA model to the time series ICA model in which the cross-autocovariances are used as a measure to achieve independence. We conduct a simulation study to evaluate the time series ICA model under different time structure assumptions about the underlying components that generate financial time series. Moreover, the empirical results support the use of the time series ICA model.
Three Essays In Financial Econometrics
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Author : Gang Xu
language : en
Publisher:
Release Date : 2010
Three Essays In Financial Econometrics written by Gang Xu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.
This thesis documents the research and findings in the following three related areas of financial econometrics: The first essay examines whether volatility contains information to predict the likelihood of a price jump during the next trading day. It is motivated by the theoretical model of Bansal & Shaliastovich (2008) who develop a long-run learning model, arguing that market volatility should be able to predict the likelihood of jumps. I use S&P 500 futures prices and extensions of the GARCH jump model of Maheu & McCurdy (2004) to relate jump probabilities to conditional volatility. Since volatility is a latent variable, which can be measured using different variables, I consider predictions based upon squared daily return, at-the-money implied volatility, model-free im- plied volatility and high-frequency realized volatility. I find evidence that volatility can predict jump likelihood and the best predictive variable is the model-free implied volatility: which is constructed using cross-section of option prices. Therefore, this thesis contributes to the current literature by documenting the information efficiency of option prices when predicting the future likelihood of jumps. In addition. I also develop a new approach based on Poisson regression which compares the jump intensity obtained from the GARCH jump model with the intraday jump numbers counted using the method of Andersen et al. (2007b). I find the two measures of jumps match fairly well with each other in the period from 1990 to 1997. However, any such relationship seems to disappear in the later period from 1998 to 2004. The second essay is motivated by the affine jump-diffusion model of Duffie et al. (2000), which allows jump intensity to be an affine function of state variables. I examine whether volatility can predict the intensity of price jumps in stochastic volatility jump models, estimated using Markov Chain Monte Carlo simulation. Comparing implied volatility with high-frequency realized volatility, I find allowing the jump intensity to be an affine function of model-free implied volatility yields the best model, based on either the Deviance Information Criterion or on diagnostic tests. Further comparison are made for candidate AR(l) process which specify the stochastic volatility. I find a jump model with the log variance an AR( 1) process performs better than a jump model with Ornstein-Uhlenbeck stochastic volatility. In a Monte Carlo simulation, I find the Deviance Information Criterion is a reliable criterion to differentiate between competing equity price dynamics when there are price jumps and volatility is stochastic. In addition to examining univariate equity return models, in the third essay I also develop a bivariate equity return model which simultaneously captures time-varying correlation and volatility spillovers in the international equity markets. This model is calibrated using the weekly equity index returns from the US. UK, Germany, India and Brazil stock markets and it is compared with simplier model specifications. I find evidence that supports time varying correlation between equity markets in both developed and developing economics. How- ever, the volatility spillovers mainly exist from US equity returns to equity returns in other economies. This thesis concludes with a short discussion of its limitations and future research directions.
Volatility And Time Series Econometrics
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Author : Tim Bollerslev
language : en
Publisher: OUP Oxford
Release Date : 2010-02-11
Volatility And Time Series Econometrics written by Tim Bollerslev and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-02-11 with Business & Economics categories.
Robert Engle received the Nobel Prize for Economics in 2003 for his work in time series econometrics. This book contains 16 original research contributions by some the leading academic researchers in the fields of time series econometrics, forecasting, volatility modelling, financial econometrics and urban economics, along with historical perspectives related to field of time series econometrics more generally. Engle's Nobel Prize citation focuses on his path-breaking work on autoregressive conditional heteroskedasticity (ARCH) and the profound effect that this work has had on the field of financial econometrics. Several of the chapters focus on conditional heteroskedasticity, and develop the ideas of Engle's Nobel Prize winning work. Engle's work has had its most profound effect on the modelling of financial variables and several of the chapters use newly developed time series methods to study the behavior of financial variables. Each of the 16 chapters may be read in isolation, but they all importantly build on and relate to the seminal work by Nobel Laureate Robert F. Engle.
Essays On Stochastic Volatility And Jumps
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Author : Diep Ngoc Duong
language : en
Publisher:
Release Date : 2013
Essays On Stochastic Volatility And Jumps written by Diep Ngoc Duong and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Econometrics categories.
This dissertation comprises three essays on financial economics and econometrics. The first essay outlines and expands upon further testing results from Bhardwaj, Corradi and Swanson (BCS: 2008) and Corradi and Swanson (2011). In particular, specification tests in the spirit of the conditional Kolmogorov test of Andrews (1997) that rely on block bootstrap resampling methods are first discussed. We then broaden our discussion from single process specification testing to multiple process model selection by discussing how to construct predictive densities and how to compare the accuracy of predictive densities derived from alternative (possibly misspecified) diffusion models. In particular, we generalize simulation steps outlined in Cai and Swanson (2011) to multifactor models where the number of latent variables is larger than three. In the second essay, we begin by discussing important developments in volatility modeling, with a focus on time varying and stochastic volatility as well as the "model free" estimation of volatility via the use of so-called realized volatility, and variants thereof called realized measures. In an empirical investigation, we use realized measures to investigate the role of "small" and large" jumps in the realized variation of stock price returns and show that jumps do matter in the relative contribution to the total variation of the process, when examining individual stock returns, as well as market indices. The third essay examines the predictive content of a variety of realized measures of jump power variations, all formed on the basis of power transformations of instantaneous returns. Our prediction involves estimating members of the linear and nonlinear extended Heterogeneous Autoregressive of the Realized Volatility (HAR-RV) class of models, using S & P 500 futures data as well as stocks in the Dow 30, for the period 1993-2009. Our findings suggest that past "large" jump power variations help less in the prediction of future realized volatility, than past "small" jump power variations. Our empirical findings also suggest that past realized signed jump power variations, which have not previously been examined in this literature, are strongly correlated with future volatility.
Volatility And Time Series Econometrics Essays In Honor Of Robert Engle
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Author : Tim Bollerslev
language : en
Publisher: OUP Oxford
Release Date : 2010-02-11
Volatility And Time Series Econometrics Essays In Honor Of Robert Engle written by Tim Bollerslev and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-02-11 with Business & Economics categories.
Robert Engle received the Nobel Prize for Economics in 2003 for his work in time series econometrics. This book contains 16 original research contributions by some the leading academic researchers in the fields of time series econometrics, forecasting, volatility modelling, financial econometrics and urban economics, along with historical perspectives related to field of time series econometrics more generally.Engle's Nobel Prize citation focuses on his path-breaking work on autoregressive conditional heteroskedasticity (ARCH) and the profound effect that this work has had on the field of financial econometrics. Several of the chapters focus on conditional heteroskedasticity, and develop the ideas of Engle's Nobel Prize winning work. Engle's work has had its most profound effect on the modelling of financial variables and several of the chapters use newly developed time series methods to study thebehavior of financial variables. Each of the 16 chapters may be read in isolation, but they all importantly build on and relate to the seminal work by Nobel Laureate Robert F. Engle.
Essays On Investment Fluctuation And Market Volatility
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Author : Chaoqun Lai
language : en
Publisher:
Release Date : 2008
Essays On Investment Fluctuation And Market Volatility written by Chaoqun Lai and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Electronic dissertations categories.
This dissertation includes two different groups of objects in macroeconomics and financial economics. In macroeconomics, the aggregate investment fluctuation and its relation to an individual firm's behavior have been extensively studied for the past three decades. Most studies on the interdependence behavior of firms' investment focus on the key issue of separating a firm's reaction to others' behavior from reaction to common shocks. However, few researchers have addressed the issue of isolating this endogenous effect from a statistical and econometrical approach. The first essay starts with a comprehensive review of the investment fluctuation and firms' interdependence behavior, followed by an econometric model of lumpy investments and an analysis of the binary choice behavior of firms' investments. The last part of the first essay investigates the unique characteristics of the Italian economy and discusses the economic policy implications of our research findings. We ask a similar question in the field of financial economics: Where does stock market volatility come from? The literature on the sources of such volatility is abundant. As a result of the availability of high-frequency financial data, attention has been increasingly directed at the modeling of intraday volatility of asset prices and returns. However, no empirical research of intraday volatility analysis has been applied at both a single stock level and industry level in the food industry. The second essay is aimed at filling this gap by modeling and testing intraday volatility of asset prices and returns. It starts with a modified High Frequency Multiplicative Components GARCH (Generalized Autoregressive Conditional Heteroscedasticity) model, which breaks daily volatility into three parts: daily volatility, deterministic intraday volatility, and stochastic intraday volatility. Then we apply this econometric model to a single firm as well as the whole food industry using the Trade and Quote Data and Center for Research in Security Prices data. This study finds that there is little connection between the intraday return and overnight return. There exists, however, strong evidence that the food recall announcements have negative impacts on asset returns of the associated publicly traded firms.
Volatility Duration And Value At Risk
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Author : Pujin Liu
language : en
Publisher:
Release Date : 2012
Volatility Duration And Value At Risk written by Pujin Liu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
The thesis consists of three essays dealing with the modeling of volatility in financial markets, trade durations, and Value-at-Risk (VaR). The first essay models nonlinearities in the return series to estimate time-varying volatility by incorporating both regime changes and jumps. Two types of regime-switching GARCH-jump models with autoregressive jump intensity are presented. The first model follows the traditional Markov regime-switching model proposed in Hamilton (1989). As the unknown regimes in the Markov model lead to difficulty in forecasting, a threshold GARCH-jump model, in which regimes are known after observing the threshold variable in the previous period, is also proposed. The second essay models the intraday durations between two adjacent trade transactions by considering the impact of unaccounted struc- tural changes on parameter estimates. Monte Carlo simulations show that the observed high persistence in trade durations can be spurious and caused by unaccounted structural changes in the data generating process. The third essay investigates the use of realized moments in VaR forecasting, which is an important issue in risk management. Many VaR models rely only on the mean and volatility and ignore higher moments of returns, which leads to un- derestimation of VaR due to the unaccounted fat-tail property of the return series. Applying the Cornish-Fisher expansion to incorporate realized higher moments constructed from high frequency data, the proposed realized moment models outperform the realized volatility model and the traditional RiskMet- rics model, especially during the financial crisis period (2008-09).
Essays In Financial Economics
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Author : Mohammadjavad Pakdel
language : en
Publisher:
Release Date : 2016
Essays In Financial Economics written by Mohammadjavad Pakdel and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Investments categories.
This dissertation consists of two self-contained essays. The first essay compares out-of-sample performance of asset allocation using forward-looking information and backward-looking information. The existing literature processes forward-looking and backward-looking information using different models and consequently different sets of assumptions. Therefore, one might wonder if superior performance of portfolios using these two sources of information should be attributed to superiority of sources of information or superiority of models underlying them. In contrast, this study uses the identical stochastic volatility model to process both forward-looking and backward-looking information. The empirical results of this study show that the investor will be significantly better off when using the forward-looking information in her asset allocation compared to using the backward-looking information. In the second essay, I investigate the relationship between idiosyncratic risk at industry level and stock prices. The Capital Asset Pricing Model (CAPM) predicts that idiosyncratic risk would not be priced by investors, since investors can avoid it through portfolio diversification. In contrast to CAPM's prediction, the authors of existing literature usually conclude that this type of risk is priced by investors at firm level. I hypothesized that risk at industry level, like risk at firm level, is priced by investors. Surprisingly, I found some evidence that net industry-level volatility innovations are contemporaneously positively correlated to respective industry excess returns in some industries. This positive relation is interpreted as lower prices for industries with higher idiosyncratic risk, in contrast to my assumption.
Forecasting Volatility In The Financial Markets
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Author : Stephen Satchell
language : en
Publisher: Elsevier
Release Date : 2011-02-24
Forecasting Volatility In The Financial Markets written by Stephen Satchell and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-02-24 with Business & Economics categories.
This new edition of Forecasting Volatility in the Financial Markets assumes that the reader has a firm grounding in the key principles and methods of understanding volatility measurement and builds on that knowledge to detail cutting-edge modelling and forecasting techniques. It provides a survey of ways to measure risk and define the different models of volatility and return. Editors John Knight and Stephen Satchell have brought together an impressive array of contributors who present research from their area of specialization related to volatility forecasting. Readers with an understanding of volatility measures and risk management strategies will benefit from this collection of up-to-date chapters on the latest techniques in forecasting volatility. Chapters new to this third edition: * What good is a volatility model? Engle and Patton * Applications for portfolio variety Dan diBartolomeo * A comparison of the properties of realized variance for the FTSE 100 and FTSE 250 equity indices Rob Cornish * Volatility modeling and forecasting in finance Xiao and Aydemir * An investigation of the relative performance of GARCH models versus simple rules in forecasting volatility Thomas A. Silvey * Leading thinkers present newest research on volatility forecasting *International authors cover a broad array of subjects related to volatility forecasting *Assumes basic knowledge of volatility, financial mathematics, and modelling
Nonlinear Economic Dynamics And Financial Modelling
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Author : Roberto Dieci
language : en
Publisher: Springer
Release Date : 2014-07-26
Nonlinear Economic Dynamics And Financial Modelling written by Roberto Dieci and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-26 with Business & Economics categories.
This book reflects the state of the art on nonlinear economic dynamics, financial market modelling and quantitative finance. It contains eighteen papers with topics ranging from disequilibrium macroeconomics, monetary dynamics, monopoly, financial market and limit order market models with boundedly rational heterogeneous agents to estimation, time series modelling and empirical analysis and from risk management of interest-rate products, futures price volatility and American option pricing with stochastic volatility to evaluation of risk and derivatives of electricity market. The book illustrates some of the most recent research tools in these areas and will be of interest to economists working in economic dynamics and financial market modelling, to mathematicians who are interested in applying complexity theory to economics and finance and to market practitioners and researchers in quantitative finance interested in limit order, futures and electricity market modelling, derivative pricing and risk management.