High Returns from Low Risk


Book Description

Believing "high-risk equals high-reward" is holding your portfolio hostage High Returns from Low Risk proves that low-volatility, low-risk portfolios beat high-volatility portfolios hands down, and shows you how to take advantage of this paradox to dramatically improve your returns. Investors traditionally view low-risk stocks as safe but unprofitable, but this old canard is based on a flawed premise; it fails to see beyond the monthly horizon, and ignores compounding returns. This book updates the thinking and brings reality to modelling to show how low-risk stocks actually outperform high-risk stocks by an order of magnitude. Easy to read and easy to implement, the plan presented here will help you construct a portfolio that delivers higher returns per unit of risk, and explains how to achieve excellent investment results over the long term. Do you still believe that investors are rewarded for bearing risk, and that the higher the risk, the greater the reward? That old axiom is holding you back, and it is time to start seeing the whole picture. This book shows you, through deep historical simulation, how to reap the rewards of smarter investing. Learn how and why low-risk, low-volatility stocks beat the market Discover the formula that outperforms Greenblatt's Construct your own low-risk portfolio Select the right ETF or low-risk fund to manage your money Great returns and lower risk sound like a winning combination — what happens once everyone is doing it? The beauty of the low-risk strategy is that it continues to work even after the paradox is widely known; long-term investment success is possible for anyone who can shake off the entrenched wisdom and go low-risk. High Returns from Low Risk provides the proof, model and strategy to reign in your exposure while raking in the profit.







Malliavin Calculus for Lévy Processes with Applications to Finance


Book Description

This book is an introduction to Malliavin calculus as a generalization of the classical non-anticipating Ito calculus to an anticipating setting. It presents the development of the theory and its use in new fields of application.




Volatility and Time Series Econometrics


Book Description

A volume that celebrates and develops the work of Nobel Laureate Robert Engle, it includes original contributions from some of the world's leading econometricians that further Engle's work in time series economics




Moving Beyond Modern Portfolio Theory


Book Description

Moving Beyond Modern Portfolio Theory: Investing That Matters tells the story of how Modern Portfolio Theory (MPT) revolutionized the investing world and the real economy, but is now showing its age. MPT has no mechanism to understand its impacts on the environmental, social and financial systems, nor any tools for investors to mitigate the havoc that systemic risks can wreck on their portfolios. It’s time for MPT to evolve. The authors propose a new imperative to improve finance’s ability to fulfil its twin main purposes: providing adequate returns to individuals and directing capital to where it is needed in the economy. They show how some of the largest investors in the world focus not on picking stocks, but on mitigating systemic risks, such as climate change and a lack of gender diversity, so as to improve the risk/return of the market as a whole, despite current theory saying that should be impossible. "Moving beyond MPT" recognizes the complex relations between investing and the systems on which capital markets rely, "Investing that matters" embraces MPT’s focus on diversification and risk adjusted return, but understands them in the context of the real economy and the total return needs of investors. Whether an investor, an MBA student, a Finance Professor or a sustainability professional, Moving Beyond Modern Portfolio Theory: Investing That Matters is thought-provoking and relevant. Its bold critique shows how the real world already is moving beyond investing orthodoxy.




Nonparametric Econometric Methods and Application


Book Description

The present Special Issue collects a number of new contributions both at the theoretical level and in terms of applications in the areas of nonparametric and semiparametric econometric methods. In particular, this collection of papers that cover areas such as developments in local smoothing techniques, splines, series estimators, and wavelets will add to the existing rich literature on these subjects and enhance our ability to use data to test economic hypotheses in a variety of fields, such as financial economics, microeconomics, macroeconomics, labor economics, and economic growth, to name a few.




Quantifying Systemic Risk


Book Description

In the aftermath of the recent financial crisis, the federal government has pursued significant regulatory reforms, including proposals to measure and monitor systemic risk. However, there is much debate about how this might be accomplished quantitatively and objectively—or whether this is even possible. A key issue is determining the appropriate trade-offs between risk and reward from a policy and social welfare perspective given the potential negative impact of crises. One of the first books to address the challenges of measuring statistical risk from a system-wide persepective, Quantifying Systemic Risk looks at the means of measuring systemic risk and explores alternative approaches. Among the topics discussed are the challenges of tying regulations to specific quantitative measures, the effects of learning and adaptation on the evolution of the market, and the distinction between the shocks that start a crisis and the mechanisms that enable it to grow.







Risk-Return Relationship and Portfolio Management


Book Description

This book covers all aspects of modern finance relating to portfolio theory and risk–return relationship, offering a comprehensive guide to the importance, measurement and application of the risk–return hypothesis in portfolio management. It is divided into five parts: Part I discusses the valuation of capital assets and presents various techniques and models used in this context. Part II then addresses market efficiency and capital market models, particularly focusing on measuring market efficiency, which is a crucial factor in making correct investment decisions. It also analyzes the major capital market models like CAPM and APT to determine to what extent they are suitable for use in developing economies. Part III highlights the significance of risk–return analysis as a prerequisite for investment decisions, while Part IV examines the selection and performance appraisals of portfolios against the backdrop of the risk–return relationship. It also examines new tools such as the value-at-risk application for mutual funds and the applications of the price-to-earnings ratio in portfolio performance measurement. Lastly, Part V explores contemporary issues in finance, including the relevance of Islamic finance in the increasingly volatile global financial system.




Handbook of Volatility Models and Their Applications


Book Description

A complete guide to the theory and practice of volatility models in financial engineering Volatility has become a hot topic in this era of instant communications, spawning a great deal of research in empirical finance and time series econometrics. Providing an overview of the most recent advances, Handbook of Volatility Models and Their Applications explores key concepts and topics essential for modeling the volatility of financial time series, both univariate and multivariate, parametric and non-parametric, high-frequency and low-frequency. Featuring contributions from international experts in the field, the book features numerous examples and applications from real-world projects and cutting-edge research, showing step by step how to use various methods accurately and efficiently when assessing volatility rates. Following a comprehensive introduction to the topic, readers are provided with three distinct sections that unify the statistical and practical aspects of volatility: Autoregressive Conditional Heteroskedasticity and Stochastic Volatility presents ARCH and stochastic volatility models, with a focus on recent research topics including mean, volatility, and skewness spillovers in equity markets Other Models and Methods presents alternative approaches, such as multiplicative error models, nonparametric and semi-parametric models, and copula-based models of (co)volatilities Realized Volatility explores issues of the measurement of volatility by realized variances and covariances, guiding readers on how to successfully model and forecast these measures Handbook of Volatility Models and Their Applications is an essential reference for academics and practitioners in finance, business, and econometrics who work with volatility models in their everyday work. The book also serves as a supplement for courses on risk management and volatility at the upper-undergraduate and graduate levels.