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Author: Ingmar Nolte
Publisher:
ISBN:
Category :
Languages : en
Pages : 49
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Book Description
In previous studies, high-frequency data has been used to improve portfolio allocation by estimating the full realized covariance matrix. In this paper, we show that strategies using high-frequency data for measuring and forecasting univariate realized volatility alone can already generate statistically significant and economically tangible benefits compared to low-frequency strategies. Most importantly, however, high-frequency data also allow us to separate realized volatility into different components and construct realized higher moments. Strategies using upside and downside volatility components as well as realized skewness are shown to reveal additional information and deliver incremental economic benefits over strategies using total realized volatility alone.
Author: Ingmar Nolte
Publisher:
ISBN:
Category :
Languages : en
Pages : 49
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Book Description
In previous studies, high-frequency data has been used to improve portfolio allocation by estimating the full realized covariance matrix. In this paper, we show that strategies using high-frequency data for measuring and forecasting univariate realized volatility alone can already generate statistically significant and economically tangible benefits compared to low-frequency strategies. Most importantly, however, high-frequency data also allow us to separate realized volatility into different components and construct realized higher moments. Strategies using upside and downside volatility components as well as realized skewness are shown to reveal additional information and deliver incremental economic benefits over strategies using total realized volatility alone.
Author: Qianqiu Liu
Publisher:
ISBN:
Category :
Languages : en
Pages : 34
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Book Description
We examine how the use of high-frequency data impacts the portfolio optimization decision. Prior research has documented that an estimate of realized volatility is more precise when based upon intraday returns rather than daily returns. Using the framework of a professional investment manager who wishes to track the Samp;P 500 with the 30 DJIA stocks, we find that the benefits of using high-frequency data depend upon the rebalancing frequency and estimation horizon. If the portfolio is rebalanced monthly and the manager has access to at least the previous 12 months of data, daily data has the potential to perform as well as high-frequency data. However, substantial improvements in the portfolio optimization decision from high-frequency data are realized if the manager rebalances daily or has less than a six-month estimation window. These findings are robust to transaction costs.
Author: Nikolaus Hautsch
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Rana Das
Publisher: Ocleno
ISBN:
Category : Business & Economics
Languages : en
Pages : 29
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Book Description
Dive into the intricate world of finance with 'Unlock the Secrets of Financial Markets: A Comprehensive Guide to Analysis and Trends.' From traditional fundamental analysis to groundbreaking innovations like decentralized finance and artificial intelligence, this book offers a comprehensive exploration of the principles, methodologies, and emerging trends shaping today's financial landscape. Whether you're a seasoned investor or just starting your journey, this guide equips you with the knowledge and insights needed to navigate the complexities of financial markets and seize opportunities in an ever-changing environment. Discover the secrets to success in finance and unlock your full potential as an investor with this essential resource.
Author: Söhnke M. Bartram
Publisher: CFA Institute Research Foundation
ISBN: 195292703X
Category : Business & Economics
Languages : en
Pages : 95
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Book Description
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.
Author: John Y. Campbell
Publisher: OUP Oxford
ISBN: 019160691X
Category : Business & Economics
Languages : en
Pages : 272
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Book Description
Academic finance has had a remarkable impact on many financial services. Yet long-term investors have received curiously little guidance from academic financial economists. Mean-variance analysis, developed almost fifty years ago, has provided a basic paradigm for portfolio choice. This approach usefully emphasizes the ability of diversification to reduce risk, but it ignores several critically important factors. Most notably, the analysis is static; it assumes that investors care only about risks to wealth one period ahead. However, many investors—-both individuals and institutions such as charitable foundations or universities—-seek to finance a stream of consumption over a long lifetime. In addition, mean-variance analysis treats financial wealth in isolation from income. Long-term investors typically receive a stream of income and use it, along with financial wealth, to support their consumption. At the theoretical level, it is well understood that the solution to a long-term portfolio choice problem can be very different from the solution to a short-term problem. Long-term investors care about intertemporal shocks to investment opportunities and labor income as well as shocks to wealth itself, and they may use financial assets to hedge their intertemporal risks. This should be important in practice because there is a great deal of empirical evidence that investment opportunities—-both interest rates and risk premia on bonds and stocks—-vary through time. Yet this insight has had little influence on investment practice because it is hard to solve for optimal portfolios in intertemporal models. This book seeks to develop the intertemporal approach into an empirical paradigm that can compete with the standard mean-variance analysis. The book shows that long-term inflation-indexed bonds are the riskless asset for long-term investors, it explains the conditions under which stocks are safer assets for long-term than for short-term investors, and it shows how labor income influences portfolio choice. These results shed new light on the rules of thumb used by financial planners. The book explains recent advances in both analytical and numerical methods, and shows how they can be used to understand the portfolio choice problems of long-term investors.
Author: Vasant Naik
Publisher: CFA Institute Research Foundation
ISBN: 1944960155
Category : Business & Economics
Languages : en
Pages : 192
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Book Description
Author: Yacine Aït-Sahalia
Publisher: Princeton University Press
ISBN: 0691161437
Category : Business & Economics
Languages : en
Pages : 683
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Book Description
A comprehensive introduction to the statistical and econometric methods for analyzing high-frequency financial data High-frequency trading is an algorithm-based computerized trading practice that allows firms to trade stocks in milliseconds. Over the last fifteen years, the use of statistical and econometric methods for analyzing high-frequency financial data has grown exponentially. This growth has been driven by the increasing availability of such data, the technological advancements that make high-frequency trading strategies possible, and the need of practitioners to analyze these data. This comprehensive book introduces readers to these emerging methods and tools of analysis. Yacine Aït-Sahalia and Jean Jacod cover the mathematical foundations of stochastic processes, describe the primary characteristics of high-frequency financial data, and present the asymptotic concepts that their analysis relies on. Aït-Sahalia and Jacod also deal with estimation of the volatility portion of the model, including methods that are robust to market microstructure noise, and address estimation and testing questions involving the jump part of the model. As they demonstrate, the practical importance and relevance of jumps in financial data are universally recognized, but only recently have econometric methods become available to rigorously analyze jump processes. Aït-Sahalia and Jacod approach high-frequency econometrics with a distinct focus on the financial side of matters while maintaining technical rigor, which makes this book invaluable to researchers and practitioners alike.
Author: Wayne Ferson
Publisher: MIT Press
ISBN: 0262039370
Category : Business & Economics
Languages : en
Pages : 497
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Book Description
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.
Author: Greg N. Gregoriou
Publisher: Academic Press
ISBN: 0128023627
Category : Business & Economics
Languages : en
Pages : 495
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Book Description
This comprehensive examination of high frequency trading looks beyond mathematical models, which are the subject of most HFT books, to the mechanics of the marketplace. In 25 chapters, researchers probe the intricate nature of high frequency market dynamics, market structure, back-office processes, and regulation. They look deeply into computing infrastructure, describing data sources, formats, and required processing rates as well as software architecture and current technologies. They also create contexts, explaining the historical rise of automated trading systems, corresponding technological advances in hardware and software, and the evolution of the trading landscape. Developed for students and professionals who want more than discussions on the econometrics of the modelling process, The Handbook of High Frequency Trading explains the entirety of this controversial trading strategy. Answers all questions about high frequency trading without being limited to mathematical modelling Illuminates market dynamics, processes, and regulations Explains how high frequency trading evolved and predicts its future developments
