This thesis studies the stochastic behaviour of interest rates and commodity prices, extending the existing literature by allowing the underlying state variable to capture any possible seasonal or cyclical behaviour. In the first chapter, we propose a new model for the term structure of interest rates assuming that the instantaneous spot rate converges to a cyclical long-term level characterized by a Fourier series. Under this framework, we derive analytical expressions for the valuation of bonds and several interest rate derivative assets. The second chapter introduces a new square-root model for the yield curve where both the mean reversion level and the volatility are described by a harmonic oscillator. This model specification incorporates a good deal of flexibility preserving the analytical tractability. In the final chapter, we present a model for the logarithm of the commodity spot price with a reversion to a time dependent long-run level described by a Fourier series, obtaining closed-form expressions for a wide range of derivatives and study the fitting performance to market data.
The thesis analyzes the effect that the sample size, the asymmetry in the distribution of returns and the leverage in their volatility have on the estimation and forecasting of market risk in financial assets. The goal is to compare the performance of a variety of models for the estimation and forecasting of Value at Risk (VaR) and Expected Shortfall (ES) for a set of assets of different nature: market indexes, individual stocks, bonds, exchange rates, and commodities. The three chapters of the thesis address issues of greatest interest for the measurement of risk in financial institutions and, therefore, for the supervision of risks in the financial system. They deal with technical issues related to the implementation of the Basel Committee's guidelines on some aspects of which very little is known in the academic world and in the specialized financial sector. In the first chapter, a numerical correction is proposed on the values usually estimatedwhen there is little statistical information, either because it is a financial asset (bond, investment fund...) recently created or issued, or because the nature or the structure of the asset or portfolio have recently changed. The second chapter analyzes the relevance of different aspects of risk modeling. The third and last chapter provides a characterization of the preferable methodology to comply with Basel requirements related to the backtesting of the Expected Shortfall.
Commodities have become an important component of many investors' portfolios and the focus of much political controversy over the past decade. This book utilizes structural models to provide a better understanding of how commodities' prices behave and what drives them. It exploits differences across commodities and examines a variety of predictions of the models to identify where they work and where they fail. The findings of the analysis are useful to scholars, traders and policy makers who want to better understand often puzzling - and extreme - movements in the prices of commodities from aluminium to oil to soybeans to zinc.
Do financial derivatives enhance or impede innovation? We aim to answer this question by examining the relationship between equity options markets and standard measures of firm innovation. Our baseline results show that firms with more options trading activity generate more patents and patent citations per dollar of R&D invested. We then investigate how more active options markets affect firms' innovation strategy. Our results suggest that firms with greater trading activity pursue a more creative, diverse and risky innovation strategy. We discuss potential underlying mechanisms and show that options appear to mitigate managerial career concerns that would induce managers to take actions that boost short-term performance measures. Finally, using several econometric specifications that try to account for the potential endogeneity of options trading, we argue that the positive effect of options trading on firm innovation is causal.
This book adds to the resolution of two problems in finance and economics: i) what is macro-financial uncertainty? : How to measure it? How is it different from risk? How important is it for the financial markets? And ii) what sort of asymmetries underlie financial risk and uncertainty propagation across the global financial markets? That is, how risk and uncertainty change according to factors such as market states or market participants. In Chapter 2, which is entitled “Momentum Uncertainties”, the relationship between macroeconomic uncertainty and the abnormal returns of a momentum trading strategy in the stock market is studies. We show that high levels of uncertainty in the economy impact negatively and significantly the returns of a portfolio of stocks that consist of buying past winners and selling past losers. High uncertainty reduces below zero the abnormal returns of momentum, extinguishes the Sharpe ratio of the momentum strategy, while increases the probability of momentum crashes both by increasing the skewness and the kurtosis of the momentum return distribution. Uncertainty acts as an economic regime that underlies abrupt changes over time of the returns generated by momentum strategies. In Chapter 3, “Measuring Uncertainty in the Stock Market”, a new index for measuring stock market uncertainty on a daily basis is proposed. The index considers the inherent differentiation between uncertainty and the common variations between the series. The second contribution of chapter 3 is to show how this financial uncertainty index can also serve as an indicator of macroeconomic uncertainty. Finally, the dynamic relationship between uncertainty and the series of consumption, interest rates, production and stock market prices, among others, is analized. In chapter 4: “Uncertainty, Systemic Shocks and the Global Banking Sector: Has the Crisis Modified their Relationship?” we explore the stability of systemic risk and uncertainty propagation among financial institutions in the global economy, and show that it has remained stable over the last decade. Additionally, a new simple tool for measuring the resilience of financial institutions to these systemic shocks is provided. We examine the characteristics and stability of systemic risk and uncertainty, in relation to the dynamics of the banking sector stock returns. This sort of evidence is supportive of past claims, made in the field of macroeconomics, which hold that during the global financial crisis the financial system may have faced stronger versions of traditional shocks rather than a new type of shock. In chapter 5, “Currency downside risk, liquidity, and financial stability”, downside risk propagation across global currency markets and the ways in which it is related to liquidity is analyzed. Two primary contributions to the literature follow. First, tail-spillovers between currencies in the global FX market are estimated. This index is easy to build and does not require intraday data, which constitutes an important advantage. Second, we show that turnover is related to risk spillovers in global currency markets. Chapter 6 is entitled “Spillovers from the United States to Latin American and G7 Stock Markets: A VAR-Quantile Analysis”. This chapter contributes to the studies of contagion, market integration and cross-border spillovers during both regular and crisis episodes by carrying out a multivariate quantile analysis. It focuses on Latin American stock markets, which have been characterized by a highly positive dynamic in recent decades, in terms of market capitalization and liquidity ratios, after a far-reaching process of market liberalization and reforms to pension funds across the continent during the 80s and 90s. We document smaller dependences between the LA markets and the US market than those between the US and the developed economies, especially in the highest and lowest quantiles.
"High-Performance Quantitative Strategies: Trading at the Speed of Markets" offers an insightful exploration into the realm of quantitative trading, where financial acumen meets technological innovation. This book serves as an essential guide for those seeking to harness the power of mathematical models and algorithmic strategies to navigate and excel in today’s fast-paced financial markets. Tailored for both beginners and experienced traders, it presents a comprehensive framework that delves into the foundational principles of quantitative finance, data analysis, and risk management, equipping readers with the necessary tools to make informed, strategic trading decisions. Each chapter unfolds a distinct aspect of quantitative trading, from the intricacies of financial market fundamentals and advanced statistical techniques to the implementation of high-frequency trading strategies and machine learning models. The text is crafted with clarity and precision, fostering a deep understanding of complex concepts while emphasizing practical application in real-world scenarios. Alongside, it addresses the challenges posed by regulatory and technological dynamics, ensuring readers are well-prepared to meet the evolving demands of global financial markets. As you turn the pages, "High-Performance Quantitative Strategies" not only enlightens but also inspires a profound appreciation of the synergy between theoretical knowledge and market execution, elevating your trading prowess to new heights.
An introduction to the theory and methods of empirical asset pricing, integrating classical foundations with recent developments. This book offers a comprehensive advanced introduction to asset pricing, the study of models for the prices and returns of various securities. The focus is empirical, emphasizing how the models relate to the data. The book offers a uniquely integrated treatment, combining classical foundations with more recent developments in the literature and relating some of the material to applications in investment management. It covers the theory of empirical asset pricing, the main empirical methods, and a range of applied topics. The book introduces the theory of empirical asset pricing through three main paradigms: mean variance analysis, stochastic discount factors, and beta pricing models. It describes empirical methods, beginning with the generalized method of moments (GMM) and viewing other methods as special cases of GMM; offers a comprehensive review of fund performance evaluation; and presents selected applied topics, including a substantial chapter on predictability in asset markets that covers predicting the level of returns, volatility and higher moments, and predicting cross-sectional differences in returns. Other chapters cover production-based asset pricing, long-run risk models, the Campbell-Shiller approximation, the debate on covariance versus characteristics, and the relation of volatility to the cross-section of stock returns. An extensive reference section captures the current state of the field. The book is intended for use by graduate students in finance and economics; it can also serve as a reference for professionals.
This book presents practical Risk Management and Trading applications for the Electricity Markets. Various methodologies developed over the last few years are considered and current literature is reviewed. The book emphasizes the relationship between trading, hedging and generation asset management.
In "Algorithmic Market Making: Strategies for Liquidity and Profitability," readers are guided through the transformative landscape of modern financial markets, where algorithms dictate the pace and flow of transactions. This comprehensive volume delves into the core principles of market making, offering an in-depth exploration of the financial structures, mathematical models, and technological advancements that define this field. With an emphasis on both theoretical underpinnings and practical applications, this book equips readers with the essential tools to navigate the complexities of automated trading, from understanding market microstructure to implementing robust algorithms. Structured to benefit both novices and experienced traders, the book balances technical rigor with accessible insights. It covers critical topics such as risk management, regulatory compliance, and the ethical considerations of algorithmic trading, ensuring a holistic view of the industry. Through illustrative case studies and real-world examples, readers gain a rich understanding of how theory translates into practice. Whether you're looking to enhance your knowledge of quantitative finance, or aiming to develop and optimize your trading systems, this text provides a strategic advantage in the rapidly evolving world of financial markets.
Updated with a new chapter that draws on behavioral finance, the field that studies the psychology of investment decisions, the bestselling guide to investing evaluates the full range of financial opportunities.
