Download or read book Model Uncertainty Ambiguity Premium and Optimal Asset Allocation written by Yuhong Xu and published by . This book was released on 2016 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper I investigate financial markets with drift and volatility uncertainties. Appropriate definitions of arbitrage for super and sub-hedging strategies are presented such that the super and sub-hedging prices are reasonable. Especially the condition of arbitrage for sub-hedging strategy fills the gap of the theory of arbitrage under model uncertainty. The Profit&Loss (P&L for short) of super(sub)-hedging is derived to be in fact the penalty term K with finite-variance arising in the super(sub)-hedging strategy. The ask-bid spread is hence an accumulation of the superhedging P&L and the subhedging P&L.Asset allocation under constant absolute risk aversion (CARA) utility is investigated with ambiguous volatility and subjective risk premium. I show that ambiguity aversion of a rational individual decreases her market participation. The aggregate premium is computed explicitly which is decomposed into three parts. Opposite signs between the rates of ambiguity premium and risk premium demonstrate that a decrease in ambiguity premium on volatility gives rise to an increase in risk premium.Kelly criterion for the wealth process to reach a goal is also studied under such ambiguous market. Ambiguity of stock appreciation rate results in investors' withdraw from markets whereas in a single-priced market, investors always trade with the market if no short-sale constraints and no transaction cost.
Download or read book Optimal Portfolios Under Time Varying Investment Opportunities Parameter Uncertainty and Ambiguity Aversion written by Thomas Dangl and published by . This book was released on 2018 with total page 51 pages. Available in PDF, EPUB and Kindle. Book excerpt: We study the implications of predictability on the optimal asset allocation of ambiguity-averse long-term investors and analyze the term structure of the multivariate risk-return trade-off considering parameter uncertainty. We calibrate the model to real returns of US stocks, long-term bonds, cash, real estate, and gold using the term spread and the dividend-price ratio as additional predictive variables, and we show that over long horizons the optimal asset allocation is significantly influenced by the covariance structure induced by estimation errors. The ambiguity-averse long-term investor optimally tilts her portfolio toward a seemingly inefficient portfolio, which shows maximum robustness against estimation errors.
Download or read book Model Uncertainty Ambiguity Aversion and Market Participation written by David Hirshleifer and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ambiguity aversion alone does not explain the market nonparticipation puzzle. We show that in a rational expectations equilibrium model with a fund offering the risk-adjusted market portfolio (RAMP), ambiguity averse investors hold the fund and an information-based portfolio, and thus participate in all asset markets, directly or indirectly. This result follows from a new separation theorem which states that an investor's equilibrium portfolio can be decomposed into components, each matching the optimal portfolio based on only one information source (price versus private signal). Asset risk premia satisfy the CAPM with the fund as the pricing portfolio.
Download or read book A Shrinkage Approach to Model Uncertainty and Asset Allocation written by and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This article takes a shrinkage approach to examine the empirical implications of aversion to model uncertainty. The shrinkage approach explicitly shows how predictive distributions incorporate data and prior beliefs. It enables us to solve the optimal portfolios for uncertainty-averse investors. Aversion to uncertainty about the capital asset pricing model leads investors to hold a portfolio that is not mean-variance efficient for any predictive distribution. However, mean-variance efficient portfolios corresponding to extremely strong beliefs in the Fama-French model are approximately optimal for uncertainty-averse investors. The empirical Bayes approach does not result in optimal portfolios for investors who are averse to model uncertainty.
Download or read book Dynamic Asset Allocation with Ambiguous Return Predictability written by Hui Chen and published by . This book was released on 2011 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: We study an investor's optimal consumption and portfolio choice problem when he is confronted with two possibly misspecified submodels of stock returns: one with IID returns and the other with predictability. We adopt a generalized recursive ambiguity model to accommodate the investor's aversion to model uncertainty. The investor deals with specification doubts by slanting his beliefs about submodels of returns pessimistically, causing his investment strategy to be more conservative than the Bayesian strategy. This effect is especially strong when the submodel with a low Bayesian probability delivers a much smaller continuation value. Unlike in the Bayesian framework, the hedging demand against model uncertainty may cause the investor's stock allocation to decrease sharply given a small doubt of return predictability, even though the predictive variable is large. Adopting the Bayesian strategy can lead to sizable welfare costs for an ambiguity-averse investor, especially when he has a strong prior of return predictability.
Download or read book When Uncertainty and Volatility Are Disconnected written by Yacine Aït-Sahalia and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We analyze an environment where the uncertainty in the equity market return and its volatility are both stochastic, and may be potentially disconnected. We solve a representative investor's optimal asset allocation and derive the resulting conditional equity premium and risk-free rate in equilibrium. Our empirical analysis shows that the equity premium appears to be earned for facing uncertainty, especially high uncertainty that is disconnected from lower volatility, rather than for facing volatility as traditionally assumed. Incorporating the possibility of a disconnect between volatility and uncertainty significantly improves portfolio performance, over and above the performance obtained by conditioning on volatility only.
Download or read book Ambiguity Aversion and Portfolio Efficiency Tests written by Valery Polkovnichenko and published by . This book was released on 2019 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: Testing portfolio alpha against a linear factor model can be interpreted as a mean-variance efficiency test of the optimal portfolio of factors. For ambiguity neutral investor, adding active portfolio with statistically significant alpha always implies efficiency gain relative to the optimal portfolio of factors. In contrast, for ambiguity averse investor, the efficiency gain must be above a threshold which depends on the uncertainty about the factors' and active portfolio's expected returns. Building on the theoretical framework developed in Garlappi, Uppal and Wang (2007), we propose a new method to test portfolio efficiency relative to a factor model by using asset exclusion conditions from the optimal portfolio of the ambiguity averse investor. The asset exclusion threshold is an F-statistic that is non-redundant with significance of alpha under the ambiguity-neutral test. Active portfolios with statistically significant alpha but weak efficiency gain may be excluded from the optimal portfolio. We apply this criterion empirically to screen active portfolios ("anomalies'') and find that some anomalies do not pass our exclusion test under statistically reasonable ambiguity about their expected return.
Download or read book Optimal Portfolio Rule written by Hyunjong Jin and published by . This book was released on 2012 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: The classical mean-variance model, proposed by Harry Markowitz in 1952, has been one of the most powerful tools in the field of portfolio optimization. In this model, parameters are estimated by their sample counterparts. However, this leads to estimation risk, which the model completely ignores. In addition, the mean-variance model fails to incorporate behavioral aspects of investment decisions. To remedy the problem, the notion of ambiguity aversion has been addressed by several papers where investors acknowledge uncertainty in the estimation of mean returns. We extend the idea to the variances and correlation coefficient of the portfolio, and study their impact. The performance of the portfolio is measured in terms of its Sharpe ratio. We consider different cases where one parameter is assumed to be perfectly estimated by the sample counterpart whereas the other parameters introduce ambiguity, and vice versa, and investigate which parameter has what impact on the performance of the portfolio.
Download or read book Optimal Consumption and Portfolio Choice with Ambiguity written by Qian Lin and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider optimal consumption and portfolio choice in the presence of Knightian uncertainty in continuous-time. We embed the problem into the new framework of stochastic calculus for such settings, dealing in particular with the issue of non-equivalent multiple priors. We solve the problem completely by identifying the worst-case measure. Our setup also allows to consider interest rate uncertainty; we show that under some robust parameter constellations, the investor optimally puts all his wealth into the asset market, and does not save or borrow at all.
Download or read book Ambiguity Matters If You Invest in Many Assets written by Yuki Shigeta and published by . This book was released on 2019 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study examines the practical performance of the multiple priors optimal portfolio based on the mean-variance preference. The multiple priors optimal portfolio is designed to be robust to model uncertainty, also known as ambiguity. A back test finds two properties: the multiple priors optimal portfolio tends to be efficient when the number of assets is large and it has fewer turnovers than the mean-variance-efficient portfolios. Furthermore, the presented simulation shows that the multiple priors optimal portfolio outperforms the others when the number of assets is large and number of observations to form a portfolio is small.
Download or read book Asset Pricing and Portfolio Performance written by Robert A. Korajczyk and published by . This book was released on 1999 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive reference work presenting an original framework for evaluating observed differences in returns across assets.
Download or read book Modeling Uncertainty as Ambiguity written by Cosmin L. Ilut and published by . This book was released on 2022 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We survey literature on ambiguity with an emphasis on recent applications in macroeconomics and finance. Like risk, ambiguity leads to cautious behavior and uncertainty premia in asset markets. Unlike risk, ambiguity can generate first order welfare losses. As a result, precautionary behavior and ambiguity premia obtain even when agents have linear utility and are reflected in linear approximations to model dynamics. Quantitative work exploits this insight to estimate models that jointly match the dynamics of asset prices and macro aggregates. In micro data, inertia and inaction due to ambiguity help understand patterns such as non-participation in asset markets, price rigidities and simple contracts. Learning under ambiguity generates asymmetric responses to news that help connect higher moments in micro and macro data. Survey evidence is increasingly used to provide direct evidence on ambiguity averse behavior, as well as to discipline quantitative models.
Download or read book Intuitive Ambiguity Management written by Hakan Kaya and published by . This book was released on 2016 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper is about the issue of input parameter uncertainty in portfolio optimization in a discrete setting with finite states (such as the case in a world with different macroeconomic regimes). In such a setting, being unable to assign reliable point estimates to the probabilities (or frequencies) of the states creates the ambiguity. We first describe how this ambiguity can be modeled probabilistically. Then, we show how this added uncertainty can be dealt with in optimal asset allocation problems. In simple-yet-realistic example applications we demonstrate that without sacrificing much of the upside, ambiguity managed portfolios enhance the uniformity of returns across different states when compared to portfolios constructed by traditional methods. We stress that a key advice from these methods builds the case for insurance-like and potentially negative yielding investments such as bonds and commodities so as to hedge the unforeseeable macro uncertainties for a smoother portfolio performance. Finally, we offer a variety of problem domains in which ambiguity management can be nested including macroeconomic scenario based asset allocation, investing with regime switching models, momentum investing, and risk-based investing.
Download or read book Efficient Asset Management written by Richard O. Michaud and published by Oxford University Press. This book was released on 2008-03-03 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: In spite of theoretical benefits, Markowitz mean-variance (MV) optimized portfolios often fail to meet practical investment goals of marketability, usability, and performance, prompting many investors to seek simpler alternatives. Financial experts Richard and Robert Michaud demonstrate that the limitations of MV optimization are not the result of conceptual flaws in Markowitz theory but unrealistic representation of investment information. What is missing is a realistic treatment of estimation error in the optimization and rebalancing process. The text provides a non-technical review of classical Markowitz optimization and traditional objections. The authors demonstrate that in practice the single most important limitation of MV optimization is oversensitivity to estimation error. Portfolio optimization requires a modern statistical perspective. Efficient Asset Management, Second Edition uses Monte Carlo resampling to address information uncertainty and define Resampled Efficiency (RE) technology. RE optimized portfolios represent a new definition of portfolio optimality that is more investment intuitive, robust, and provably investment effective. RE rebalancing provides the first rigorous portfolio trading, monitoring, and asset importance rules, avoiding widespread ad hoc methods in current practice. The Second Edition resolves several open issues and misunderstandings that have emerged since the original edition. The new edition includes new proofs of effectiveness, substantial revisions of statistical estimation, extensive discussion of long-short optimization, and new tools for dealing with estimation error in applications and enhancing computational efficiency. RE optimization is shown to be a Bayesian-based generalization and enhancement of Markowitz's solution. RE technology corrects many current practices that may adversely impact the investment value of trillions of dollars under current asset management. RE optimization technology may also be useful in other financial optimizations and more generally in multivariate estimation contexts of information uncertainty with Bayesian linear constraints. Michaud and Michaud's new book includes numerous additional proposals to enhance investment value including Stein and Bayesian methods for improved input estimation, the use of portfolio priors, and an economic perspective for asset-liability optimization. Applications include investment policy, asset allocation, and equity portfolio optimization. A simple global asset allocation problem illustrates portfolio optimization techniques. A final chapter includes practical advice for avoiding simple portfolio design errors. With its important implications for investment practice, Efficient Asset Management 's highly intuitive yet rigorous approach to defining optimal portfolios will appeal to investment management executives, consultants, brokers, and anyone seeking to stay abreast of current investment technology. Through practical examples and illustrations, Michaud and Michaud update the practice of optimization for modern investment management.
Download or read book Model Misspecification and Under Diversification written by Tan Wang and published by . This book was released on 2009 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we develop a model of intertemporal portfolio choice where an investor accounts explicitly for the possibility of model misspecification. This work is motivated by the difficulty in estimating precisely the probability law for asset returns. Our contribution is to develop a framework that allows for ambiguity about the joint distribution of returns for all stocks being considered for the portfolio, and also for different levels of ambiguity for the marginal distribution of returns for any subset of these stocks. We then use this framework to derive in closed-form the optimal portfolio weights of an investor who accounts for model misspecification. We illustrate the model by calibrating it to data on international equity returns. The calibration shows that when the overall ambiguity about the joint distribution of returns is high, then small differences in ambiguity for the marginal return distribution will result in a portfolio that is significantly under-diversified relative to the standard mean-variance portfolio. Keywords :Portfolio choice,uncertainty,ambiguity,robust control.
Download or read book Strategic Asset Allocation for Long Term Investors written by Roy P. M. M. Hoevenaars and published by . This book was released on 2013 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: We study the effect of parameter uncertainty on the long-run risk for three asset classes: stocks, bills and bonds. We model return dynamics as a Bayesian vector autoregression. With an uninformative prior we find that parameter uncertainty raises the annualised long-run volatilities of all three asset classes proportionally with the same factor relative to estimates that are conditional on ML parameter estimates. Correlations among returns appear robust against parameter uncertainty. As a result the effect of the investment horizon on optimal asset allocations is much weaker compared to models in which only equity returns are subject to parameter uncertainty. While equity is more volatile, the same holds for the other asset classes. Results are sensitive to alternative informative priors, but generally the term structure of risk for stocks and bonds are relatively flat for investment horizons up to 15 years.
Download or read book Strategic Asset Allocation written by John Y. Campbell and published by OUP Oxford. This book was released on 2002-01-03 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
