A New Tight and General Bound on Return Predictability PDF Download
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Author: Valerio Potì
Publisher:
ISBN:
Category :
Languages : en
Pages : 18
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Book Description
We propose a novel upper bound on the predictability of asset returns. This bound is tighter than the bound proposed by Ross (2005) because it takes into account not only the volatility of the pricing kernel but also the correlation between the pricing kernel and trading strategies that exploit predictability. It is also at least as tight as the bound proposed by Huang et al (2017). We apply our bound to study the predictability of returns on currencies of emerging and developed economies from 1994 to 2016. We find evidence of return predictability in excess of the bound, especially for emerging markets currencies. This implies either market inefficiency or, alternatively, that investors either can become very risk-averse or price currencies using a model radically different from the CAPM. In contrast, the evidence of excess-predictability is much weaker under the wider bound proposed by Ross (2005).
Author: Valerio Potì
Publisher:
ISBN:
Category :
Languages : en
Pages : 18
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Book Description
We propose a novel upper bound on the predictability of asset returns. This bound is tighter than the bound proposed by Ross (2005) because it takes into account not only the volatility of the pricing kernel but also the correlation between the pricing kernel and trading strategies that exploit predictability. It is also at least as tight as the bound proposed by Huang et al (2017). We apply our bound to study the predictability of returns on currencies of emerging and developed economies from 1994 to 2016. We find evidence of return predictability in excess of the bound, especially for emerging markets currencies. This implies either market inefficiency or, alternatively, that investors either can become very risk-averse or price currencies using a model radically different from the CAPM. In contrast, the evidence of excess-predictability is much weaker under the wider bound proposed by Ross (2005).
Author: Dashan Huang
Publisher:
ISBN:
Category :
Languages : en
Pages : 46
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Book Description
Can the degree of predictability found in the data be explained by existing asset pricing models? We provide two theoretical upper bounds on the R-squares of predictive regressions. Using data on the market and component portfolios, we find that the empirical R-squares are significantly greater than the theoretical upper bounds. Our results suggest that the most promising direction for future research should aim to identify new state variables that are highly correlated with stock returns, instead of seeking more elaborate stochastic discount factors.
Author: Zongwu Cai
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Nicolo Cesa-Bianchi
Publisher: Cambridge University Press
ISBN: 113945482X
Category : Computers
Languages : en
Pages : 4
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Book Description
This important text and reference for researchers and students in machine learning, game theory, statistics and information theory offers a comprehensive treatment of the problem of predicting individual sequences. Unlike standard statistical approaches to forecasting, prediction of individual sequences does not impose any probabilistic assumption on the data-generating mechanism. Yet, prediction algorithms can be constructed that work well for all possible sequences, in the sense that their performance is always nearly as good as the best forecasting strategy in a given reference class. The central theme is the model of prediction using expert advice, a general framework within which many related problems can be cast and discussed. Repeated game playing, adaptive data compression, sequential investment in the stock market, sequential pattern analysis, and several other problems are viewed as instances of the experts' framework and analyzed from a common nonstochastic standpoint that often reveals new and intriguing connections.
Author: Roman Vershynin
Publisher: Cambridge University Press
ISBN: 1108415199
Category : Business & Economics
Languages : en
Pages : 299
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Book Description
An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.
Author: Cynthia Dwork
Publisher:
ISBN: 9781601988188
Category : Computers
Languages : en
Pages : 286
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Book Description
The problem of privacy-preserving data analysis has a long history spanning multiple disciplines. As electronic data about individuals becomes increasingly detailed, and as technology enables ever more powerful collection and curation of these data, the need increases for a robust, meaningful, and mathematically rigorous definition of privacy, together with a computationally rich class of algorithms that satisfy this definition. Differential Privacy is such a definition. The Algorithmic Foundations of Differential Privacy starts out by motivating and discussing the meaning of differential privacy, and proceeds to explore the fundamental techniques for achieving differential privacy, and the application of these techniques in creative combinations, using the query-release problem as an ongoing example. A key point is that, by rethinking the computational goal, one can often obtain far better results than would be achieved by methodically replacing each step of a non-private computation with a differentially private implementation. Despite some powerful computational results, there are still fundamental limitations. Virtually all the algorithms discussed herein maintain differential privacy against adversaries of arbitrary computational power -- certain algorithms are computationally intensive, others are efficient. Computational complexity for the adversary and the algorithm are both discussed. The monograph then turns from fundamentals to applications other than query-release, discussing differentially private methods for mechanism design and machine learning. The vast majority of the literature on differentially private algorithms considers a single, static, database that is subject to many analyses. Differential privacy in other models, including distributed databases and computations on data streams, is discussed. The Algorithmic Foundations of Differential Privacy is meant as a thorough introduction to the problems and techniques of differential privacy, and is an invaluable reference for anyone with an interest in the topic.
Author: Mr.Eugenio M Cerutti
Publisher: International Monetary Fund
ISBN: 1484395212
Category : Business & Economics
Languages : en
Pages : 36
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Book Description
For about three decades until the Global Financial Crisis (GFC), Covered Interest Parity (CIP) appeared to hold quite closely—even as a broad macroeconomic relationship applying to daily or weekly data. Not only have CIP deviations significantly increased since the GFC, but potential macrofinancial drivers of the variation in CIP deviations have also become significant. The variation in CIP deviations seems to be associated with multiple factors, not only regulatory changes. Most of these do not display a uniform importance across currency pairs and time, and some are associated with possible temporary considerations (such as asynchronous monetary policy cycles).
Author: Andrew W. Lo
Publisher: Princeton University Press
ISBN: 1400829097
Category : Business & Economics
Languages : en
Pages : 449
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Book Description
For over half a century, financial experts have regarded the movements of markets as a random walk--unpredictable meanderings akin to a drunkard's unsteady gait--and this hypothesis has become a cornerstone of modern financial economics and many investment strategies. Here Andrew W. Lo and A. Craig MacKinlay put the Random Walk Hypothesis to the test. In this volume, which elegantly integrates their most important articles, Lo and MacKinlay find that markets are not completely random after all, and that predictable components do exist in recent stock and bond returns. Their book provides a state-of-the-art account of the techniques for detecting predictabilities and evaluating their statistical and economic significance, and offers a tantalizing glimpse into the financial technologies of the future. The articles track the exciting course of Lo and MacKinlay's research on the predictability of stock prices from their early work on rejecting random walks in short-horizon returns to their analysis of long-term memory in stock market prices. A particular highlight is their now-famous inquiry into the pitfalls of "data-snooping biases" that have arisen from the widespread use of the same historical databases for discovering anomalies and developing seemingly profitable investment strategies. This book invites scholars to reconsider the Random Walk Hypothesis, and, by carefully documenting the presence of predictable components in the stock market, also directs investment professionals toward superior long-term investment returns through disciplined active investment management.
Author: Sanjeev Arora
Publisher: Cambridge University Press
ISBN: 0521424267
Category : Computers
Languages : en
Pages : 609
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Book Description
New and classical results in computational complexity, including interactive proofs, PCP, derandomization, and quantum computation. Ideal for graduate students.
Author: Robert Skidelsky
Publisher: PublicAffairs
ISBN: 1610390032
Category : Business & Economics
Languages : en
Pages : 258
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Book Description
In the debris of the financial crash of 2008, the principles of John Maynard Keynes -- that economic storms are a normal part of the market system, that governments need to step in and use fiscal ammunition to prevent these storms from becoming depressions, and that societies that value the pursuit of money should reprioritize -- are more pertinent and applicable than ever. In Keynes: The Return of the Master, Robert Skidelsky brilliantly synthesizes Keynes career and life, and offers nervous capitalists a positive answer to the question we now face: When unbridled capitalism falters, is there an alternative?
