Empirical Techniques in Finance
Springer Science & Business Media, Jan 17, 2006 - Business & Economics - 243 pages
This book offers the opportunity to study and experience advanced empi- cal techniques in finance and in general financial economics. It is not only suitable for students with an interest in the field, it is also highly rec- mended for academic researchers as well as the researchers in the industry. The book focuses on the contemporary empirical techniques used in the analysis of financial markets and how these are implemented using actual market data. With an emphasis on Implementation, this book helps foc- ing on strategies for rigorously combing finance theory and modeling technology to extend extant considerations in the literature. The main aim of this book is to equip the readers with an array of tools and techniques that will allow them to explore financial market problems with a fresh perspective. In this sense it is not another volume in eco- metrics. Of course, the traditional econometric methods are still valid and important; the contents of this book will bring in other related modeling topics that help more in-depth exploration of finance theory and putting it into practice. As seen in the derivatives analysis, modern finance theory requires a sophisticated understanding of stochastic processes. The actual data analyses also require new Statistical tools that can address the unique aspects of financial data. To meet these new demands, this book explains diverse modeling approaches with an emphasis on the application in the field of finance.
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NonParametric Method of Estimation
Unit Root Cointegration and Related Issues
Time Varying Volatility Models 67
StateSpace Models II
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algorithm analysis apply approach arbitrage ARCH model asset price assume autoregressive bond bubble solution causal chapter coefficients cointegrating cointegrating vector computed conditional variance constant covariance matrix defined density function dynamic econometric Economic elementary prices empirical EViews example forecast forward exchange rate fundamental futures GARCH given Harvey interest rate Journal of Finance Kalman filter kernel lag length lease likelihood function linear linkages market price Markov multivariate node normal null hypothesis observations obtained optimization option parameters percentage price change period portfolio prediction error premia price of risk probability random variables rational bubbles recursive residual regression Review risk premium sample short rate lattice specification spot exchange rate spot rate standard state-space form state-space model stationary stochastic differential equation stochastic process stock market stock price Table term structure test statistic tion trading volume trend uncorrelated unit root unobserved component volatility Wiener process zero