This dissertation consists of a collection of studies on two areas in quantitative finance: asset return volatility and the term structure of interest rates. The first part of this dissertation offers contributions to the literature on how to test for sudden changes in unconditional volatility, on modelling realized volatility and on the choice of optimal sampling frequencies for intraday returns. The emphasis in the second part of this dissertation is on the term structure of interest rates.

This paper uses the term structure of interest rates to explain the variations of stock prices and stock returns. It shows that interest rates have an important impact on stock returns, especially at long horizons. The hypothesis that expected stock returns move one-for-one with ex ante interest rates, which has been rejected strongly in other studies using short horizon data, is supported by long horizon data. The paper proposes, for the first time, a single measure--the present value of forward interest rates--to summarize the information of the term structure that is useful in characterizing the comovements of the equity market and the bond market, and finds that such a single measure explains a significant part of variation in dividend-price ratios. The paper also suggests that the high volatility of the stock market is related to the high volatility of long-term bond yields and may be accounted for by changing forecasts of discount rates. The findings of this paper are quite different from the typical findings of the previous work and may provide a reasonable economic explanation for the predictability of long-horizon stock returns.

We present a model to forecast the probability of bear markets in the Spanish IBEX 35 with a congruent and concise parameterization which selects the explanatory factors from a wide set of variables like the yield curve of Spain, US and Europe, as well as several macro variables, and numerous leading indicators.To this end, we first use a data-guided algorithm to select an in-sample optimal Probit model that is employed as a benchmark. We then form alternative Probit models obtained from combinations of levels, slopes and/or curvatures in the yield curve of Spain, US and Europe, as well as several macro variables and compare their estimated probability of bear markets in the out-of-sample period with that from the benchmark model. Our results suggest that the slopes of US and Europe yield curves have some information content (not implicitly present in the slope of the Spanish yield curve) that helps to better forecast the probability of bear markets in the IBEX 35.

It is well known that in the postwar period stockreturns have tended to be low when the short term nominal interest rate is high. In this paper I show that more generally the state of the term structure of interest rates predicts stock returns. Risk premia on stocks appear to move closely together with those on 20-year Treasury bonds, while risk premia on Treasury bills move somewhat independently. Average returns on 20-year bonds have been very low relative to average returns on stocks. I use these observations to test some simple asset pricing models. First I consider latent variable models in which betas are constant and risk premia vary with expected returns on a small number of unobservable hedge portfolios. The data strongly reject a single-latent-variable model. The last part of the paper examines the relationship between conditional means and variances of returns on bills, bonds and stocks. Bill returns tend to be high when their conditional variance is high, but there is a perverse negative relationship between stock returns and their conditional variance. A model is estimated which assumes that asset returns are determined by their time-varying betas with a fixed-weight "benchmark" portfolio of bills, bonds and stocks, whose return is proportional to its conditional variance. This portfolio is estimated to place almost all its weight on bills, indicating that uncertainty about nominal interest rates is important in pricing both short- and long-term assets

This ultimate guide contains an excellent blend of theory and practice This comprehensive guide covers various aspects of model building for fixed income securities and derivatives. Filled with expert advice, valuable insights, and advanced modeling techniques, Interest Rate, Term Structure, and Valuation Modeling is a book that all institutional investors, portfolio managers, and risk professionals should have. John Wiley & Sons, Inc. is proud to be the publisher of the esteemed Frank J. Fabozzi Series. Comprising nearly 100 titles-which include numerous bestsellers—The Frank J. Fabozzi Series is a key resource for finance professionals and academics, strategists and students, and investors. The series is overseen by its eponymous editor, whose expert instruction and presentation of new ideas have been at the forefront of financial publishing for over twenty years. His successful career has provided him with the knowledge, insight, and advice that has led to this comprehensive series. Frank J. Fabozzi, PhD, CFA, CPA, is Editor of the Journal of Portfolio Management, which is read by thousands of institutional investors, as well as editor or author of over 100 books on finance for the professional and academic markets. Currently, Dr. Fabozzi is an adjunct Professor of Finance at Yale University's School of Management and on the board of directors of the Guardian Life family of funds and the Black Rock complex of funds.

In Volatility and Correlation 2nd edition: The Perfect Hedger and the Fox, Rebonato looks at derivatives pricing from the angle of volatility and correlation. With both practical and theoretical applications, this is a thorough update of the highly successful Volatility & Correlation – with over 80% new or fully reworked material and is a must have both for practitioners and for students. The new and updated material includes a critical examination of the ‘perfect-replication’ approach to derivatives pricing, with special attention given to exotic options; a thorough analysis of the role of quadratic variation in derivatives pricing and hedging; a discussion of the informational efficiency of markets in commonly-used calibration and hedging practices. Treatment of new models including Variance Gamma, displaced diffusion, stochastic volatility for interest-rate smiles and equity/FX options. The book is split into four parts. Part I deals with a Black world without smiles, sets out the author’s ‘philosophical’ approach and covers deterministic volatility. Part II looks at smiles in equity and FX worlds. It begins with a review of relevant empirical information about smiles, and provides coverage of local-stochastic-volatility, general-stochastic-volatility, jump-diffusion and Variance-Gamma processes. Part II concludes with an important chapter that discusses if and to what extent one can dispense with an explicit specification of a model, and can directly prescribe the dynamics of the smile surface. Part III focusses on interest rates when the volatility is deterministic. Part IV extends this setting in order to account for smiles in a financially motivated and computationally tractable manner. In this final part the author deals with CEV processes, with diffusive stochastic volatility and with Markov-chain processes. Praise for the First Edition: “In this book, Dr Rebonato brings his penetrating eye to bear on option pricing and hedging.... The book is a must-read for those who already know the basics of options and are looking for an edge in applying the more sophisticated approaches that have recently been developed.” —Professor Ian Cooper, London Business School “Volatility and correlation are at the very core of all option pricing and hedging. In this book, Riccardo Rebonato presents the subject in his characteristically elegant and simple fashion...A rare combination of intellectual insight and practical common sense.” —Anthony Neuberger, London Business School

This book provides different financial models based on options to predict underlying asset price and design the risk hedging strategies. Authors of the book have made theoretical innovation to these models to enable the models to be applicable to real market. The book also introduces risk management and hedging strategies based on different criterions. These strategies provide practical guide for real option trading. This book studies the classical stochastic volatility and deterministic volatility models. For the former, the classical Heston model is integrated with volatility term structure. The correlation of Heston model is considered to be variable. For the latter, the local volatility model is improved from experience of financial practice. The improved local volatility surface is then used for price forecasting. VaR and CVaR are employed as standard criterions for risk management. The options trading strategies are also designed combining different types of options and they have been proven to be profitable in real market. This book is a combination of theory and practice. Users will find the applications of these financial models in real market to be effective and efficient.