Dynamic Asset Allocation With Ambiguous Return Predictability
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| Author | : Hui Chen |
| Publisher | : |
| Total Pages | : 46 |
| Release | : 2011 |
| Genre | : |
| ISBN | : |
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.
| Author | : Paul Dou |
| Publisher | : |
| Total Pages | : 270 |
| Release | : 2013 |
| Genre | : Asset allocation |
| ISBN | : |
| Author | : Carsten Sørensen |
| Publisher | : |
| Total Pages | : 54 |
| Release | : 2004 |
| Genre | : |
| ISBN | : 9788790705879 |
We derive an explicit solution to the portfolio problem of a power utility investor with preferences for wealth at a nite investment horizon. The investor can invest in assets with return dynamics described as part of a general multivariate model. The modeling framework encompasses discrete-time VAR-models where some of the state-variables (e.g. expected excess returns) may not be directly observable. A realistic multivariate model is estimated and applied to analyze the portfolio implications of investment horizon and return predictability when real interest rates and expected excess returns on stock and bonds are not directly observed but must be estimated as part of the problem faced by the investor. The solution exhibits small variability in portfolio allocations over time compared to the case when excess returns are assumed observable. JEL Classification: G11 Keywords: Portfolio choice, predictability, VAR, unobserved state-variables, hedging demands.
| Author | : Thomas Quistgaard Pedersen |
| Publisher | : |
| Total Pages | : |
| Release | : 2010 |
| Genre | : |
| ISBN | : 9788790117788 |
| Author | : Jean-Guy Simonato |
| Publisher | : |
| Total Pages | : 36 |
| Release | : 2018 |
| Genre | : |
| ISBN | : |
We examine the interplay between event risk, transaction costs and predictability on the dynamic asset allocation of an investor with discrete trading opportunities. The model is calibrated to the U.S. stock market and a Gauss-Hermite quadrature approach is used to solve the investor's dynamic optimization problem. Numerical scenarios are examined to show the impact of event risk on asset allocations, hedging demands, no-trading regions, and certainty equivalent returns. It is found that event risk shrinks hedging demand. Neglecting event risk can also lead to sizeable certainty equivalent return losses.
| Author | : Abraham Lioui |
| Publisher | : |
| Total Pages | : 53 |
| Release | : 2016 |
| Genre | : |
| ISBN | : |
We provide a new portfolio decomposition formula that sheds light on the economics of portfolio choice for investors following the mean-variance (MV) criterion. We show that the number of components of a dynamic portfolio strategy can be reduced to two: the first is preference free and hedges the risk of a discount bond maturing at the investor's horizon while the second hedges the time variation in pseudo relative risk tolerance. Both components entail strong horizon effects in the dynamic asset allocation as a result of time-varying risk tolerance and investment opportunity sets. We also provide closed-form solutions for the optimal portfolio strategy in the presence of market return predictability. The model parameters are estimated over the period 1963 to 2012 for the U.S. market. We show that:(i) intertemporal hedging can be very large, (ii) the MV criterion hugely understates the true extent of risk aversion for high values of the risk aversion parameter, and the more so the shorter the investment horizon and, (iii) the efficient frontiers seem problematic for investment horizons shorter than one year but satisfactory for large horizons. Overall, adopting the MV model leads to acceptable results for medium and long term investors endowed with medium or high risk tolerance, but to very problematic ones otherwise.
| Author | : Kathryn A. Wilkens |
| Publisher | : |
| Total Pages | : 206 |
| Release | : 1998 |
| Genre | : Asset allocation |
| ISBN | : |
| Author | : David A. Hammer |
| Publisher | : |
| Total Pages | : 362 |
| Release | : 1991-04-25 |
| Genre | : Business & Economics |
| ISBN | : |
Includes an examination of traditional asset allocation methods, why they do and do not work, and which elements can be used in overseeing the professional's own portfolio. In addition, the author introduces his own proven method of portfolio management and asset allocation strategies--the ``7-Step System''--using simple statistical techniques to forecast stock, bond, commodity, and money market returns. Free of complex mathematics, charts, graphs, and technical jargon, this is a highly readable guide to getting the most from today's sophisticated investment techniques.
| Author | : Holger Haldenwang |
| Publisher | : European Alliance for Innovation |
| Total Pages | : 639 |
| Release | : 2023-04-14 |
| Genre | : Business & Economics |
| ISBN | : 1631903934 |
The 2022 International Conference on Financial Innovation, FinTech and Information Technology (FFIT 2022), hosted by Shenzhen University of Technology and organized by the Financial Innovation and Fintech Research Center of Shenzhen University of Technology, was held on October 28-30, 2022 in Shenzhen, China. Due to the current COVID-19 pandemic and the strict travelling rules, it is still difficult to take international travel for all our attendees to participate in the conference. Therefore, FFIT 2022 was held as a hybrid event. FFIT 2022 brought together innovative academics and industrial experts in the field of Financial Innovation, Financial Technology and Information Technology to discuss the latest research results in this field.
| Author | : Pierre Collin-Dufresne |
| Publisher | : |
| Total Pages | : 57 |
| Release | : 2015 |
| Genre | : |
| ISBN | : |
We propose a simple approach to dynamic multi-period portfolio choice with transaction costs that is tractable in settings with a large number of securities, realistic return dynamics with multiple risk factors, many predictor variables, and stochastic volatility. We obtain a closed-form solution for an optimal trading rule when the problem is restricted to a broad class of strategies we define as 'linearity generating strategies' (LGS). When restricted to this class, the non-linear dynamic optimization problem reduces to a deterministic linear-quadratic optimization problem in the parameters of the trading strategies. We show that the LGS approach dominates several alternatives in realistic settings, and in particular when the covariance structure and transaction costs are stochastic.
