A considerable literature in market microstructure has analyzed the information flows between stock index futures and spot markets. Most of those studies estimate deviations from the cost-of-carry model within the framework of vector equilibrium correction models (VECM). The typical finding is that futures prices lead spot prices and are the primary source of price discovery. Purely linear models can, however, lead to fallacious or at least incomplete inference in the presence of significant nonlinearities in the return generating process. Recent research has reported evidence for nonlinearity in the distribution of stock market returns. According to this literature, their empirical distribution can be characterized by a mixture of normal distributions whose dependence is well described by a hidden Markov chain. This thesis contributes to the former field by allowing for Markovian regime switches in the cointegrated system. The empirical analysis is carried out using high-frequency data for the German and Swiss markets, i.e. two closely interrelated markets which differ substantially in terms of liquidity. This thesis consists of three major parts. In the first part, an MS-VECM is estimated for each market and tested against the linear VECM. In both cases, the linear model is strongly rejected. The Markovian chain consists of three regimes, which can be well described in terms of volatility. Price discovery differs from regime to regime, but the overall evidence is consistent with the well-documented leading role of futures markets. The MS-VECM provides additional insights into the dynamics of price discovery. Interestingly, shocks are absorbed more rapidly in regimes of high volatility. A possible explanation is provided, based on trading activity. Intraday volatility is shown to be associated with the volume of trading. Heavy trading reveals more information per unit of time and thus improves index arbitrage and informational.

The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.

Written by a number of authors, this text is aimed at market practitioners and applies the latest stochastic volatility research findings to the analysis of stock prices. It includes commentary and analysis based on real-life situations.

With the internationalization of Renminbi (RMB), the gradual liberalization of China's capital account and the recent reform of the RMB pricing mechanism, the RMB exchange rate has been volatile. This book examines how we can forecast exchange rate reliably. It explains how we can do so through a new methodology for exchange rate forecasting. The book also analyzes the dynamic relationship between exchange rate and the exchange rate data decomposition and integration, the domestic economic situation, the international economic situation and the public’s expectations and how these interactions would affect the exchange rate. The book also explains why this comprehensive integrated approach is the best model for optimizing accuracy in exchange rate forecasting.

Financial market volatility forecasting is one of today's most important areas of expertise for professionals and academics in investment, option pricing, and financial market regulation. While many books address financial market modelling, no single book is devoted primarily to the exploration of volatility forecasting and the practical use of forecasting models. A Practical Guide to Forecasting Financial Market Volatility provides practical guidance on this vital topic through an in-depth examination of a range of popular forecasting models. Details are provided on proven techniques for building volatility models, with guide-lines for actually using them in forecasting applications.

The Efficient Market Hypothesis believes that it is impossible for an investor to outperform the market because all available information is already built into stock prices. However, some anomalies could persist in stock markets while some other anomalies could appear, disappear and re-appear again without any warning. A Special Issue on "Efficiency and Anomalies in Stock Markets" will be devoted to advancements in the theoretical development of market efficiency and anomaly in the Stock Market, as well as applications in Stock Market efficiency and anomalies.

Artificial intelligence (AI) has grown in presence in asset management and has revolutionized the sector in many ways. It has improved portfolio management, trading, and risk management practices by increasing efficiency, accuracy, and compliance. In particular, AI techniques help construct portfolios based on more accurate risk and return forecasts and more complex constraints. Trading algorithms use AI to devise novel trading signals and execute trades with lower transaction costs. AI also improves risk modeling and forecasting by generating insights from new data sources. Finally, robo-advisors owe a large part of their success to AI techniques. Yet the use of AI can also create new risks and challenges, such as those resulting from model opacity, complexity, and reliance on data integrity.

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