BZ 2017b

Asset Allocation under Parameter Uncertainty

organized by

Alex Weissensteiner, Free University of Bozen-Bolzano, Italy

venue: Free University of Bolzano - Room F6 University Club

date: Dec 18, 2017

map: see below

Invited speakers

Nicole Branger - University of Muenster

Thomas Dangl - TU Wien

Lorenzo Garlappi - Sauder School of Business

Michael Hanke - University of Liechtenstein

Tim A. Kroencke - University of Basel

Claus Munk - Copenhagen Business School

Rolf Poulsen - University of Copenhagen

Sebastian Stöckl - University of Liechtenstein

Programm

Sunday, Dec 17 come together

19:00 meeting in the lobby of the Hotel Stiegl

19:30 dinner Römerkeller

Monday, Dec 18 scientific program

09:00 - 09:15 Welcome speech by Oswin Maurer (dean of the faculty of economics)

09:15 - 10:00 Parameter Uncertainty, Financial Turbulence and Aggregate Stock Return (S. Stöckl)

10:00 - 10:45 Idiosyncratic Volatility, its Expected Variation, and the Cross-Section of Stock Returns (N. Branger)

10:45 - 11:15 coffee break

11:15 - 12:00 The FOMC Risk Shift (T. Kroencke)

12:00 - 12:45 Risk-minimization in Electricity Markets: Fixed Price, Unknown Consumption (R. Poulsen)

12:45 - 14:15 lunch break

14:15 - 15:00 Comparing Large-Sample Maximum Sharpe Ratios and Incremental Variable Testing (M. Hanke)

15:00 - 15:45 Hedging Recessions (C. Munk)

15:45 - 16:15 coffee break

16:15 - 17:00 Long-Term Asset Allocation under Time-Varying Investment Opportunities: Optimal Portfolios with Parameter and Model Uncertainty (T. Dangl)

17:00 - 17:45 Dynamic Consumption and Portfolio Choice under Model and Parameter Uncertainty: Learning about Return Predictability (L. Garlappi)

17:45 - 18:00 discussion

19:30 dinner Vögele

Abstract of invited talks:

Idiosyncratic Volatility, its Expected Variation, and the Cross-Section of Stock Returns (SSRN)

Nicole Branger, Hendrik Hülsbusch and Frederik Middelhoff

We offer a novel perspective on the negative relation between idiosyncratic volatility (IVOL) and expected returns. We show that the IVOL puzzle is largely driven by a mean-reversion behavior of the stocks' volatilities, which is not captured by a simple historic measure of IVOL. In doing so, we make use of option implied information to extract the expected mean-reversion speed of IVOL in an almost model-free fashion. Together with the current level of IVOL this method allows us to identify stocks' expected IVOL innovations in a very general setting. Under the assumption of IVOL carrying a positive price of risk (Merton (1987)) we resolve the puzzle. In a horse race we show that the mean-reversion speed is superior to the most prominent competing explanations. All our findings are robust to different measures of IVOL and various stock characteristics.

Long-Term Asset Allocation under Time-Varying Investment Opportunities: Optimal Portfolios with Parameter and Model Uncertainty (SSRN)

Thomas Dangl and Alex Weissensteiner

We study the implications of predictability on the optimal asset allocation of ambiguity averse long-term investors. We analyze the term structure of the multivariate risk-return trade-off in a VAR model under full consideration of parameter uncertainty, and we decompose the predictive covariance along different sources of risk/uncertainty. We calibrate the model to real returns of US stocks, US long-term government bonds, cash, real-estate and gold using the term spread and the dividend-price ratio as additional predictive variables. While over short periods the model-implied conditional covariance structure of asset-class returns determines the optimal allocation, we find that over longer horizons the optimal asset allocation is significantly influenced by the covariance structure induced by estimation errors. As a consequence, the ambiguity averse long-term investor tilts her portfolio not simply toward the global minimum-variance portfolio but shrinks portfolio weights toward a seemingly inefficient portfolio which shows maximum robustness against estimation errors. Most interestingly, we find that even though time diversification of stock returns vanishes after consideration of estimation errors, real long-term bond returns are even more affected, making stocks an important asset class for the ambiguity averse long-term investor.

Dynamic Consumption and Portfolio Choice under Model and Parameter Uncertainty: Learning about Return Predictability

Lorenzo Garlappi and Georgios Skoulakis

In this paper we consider the lifetime consumption and portfolio choice of an investor who is uncertain about both the parameters driving asset returns and the model underlying the data generation process. The setting is motivated by the long-standing debate in the empirical asset pricing literature regarding the existence and strength of predictability in asset returns. If returns are predictable, portfolio allocations would crucially depend on the dynamics of the predictor as well as the investment horizon. However, even assuming that the investor is convinced about the existence of predictability, a further issue remains regarding the strength of such predictability. We study this issue by solving the dynamic consumption and portfolio choice problem for a long-lived investor who is uncertain both about the model generating the return data and the values of all of the parameters describing each model. We view these two layers of uncertainty as essential features of virtually any realistic consumption and portfolio choice problems. We show that the dynamics of the learning problem in this relatively simple setting (one risky-asset), is fully described by 8 state variables, rendering the solution numerically challenging. We explore the use of recent techniques in theory of Gaussian Processes to efficiently handle the high dimensionality of the problem.

Comparing Large-Sample Maximum Sharpe Ratios and Incremental Variable Testing (SSRN)

Michael Hanke and Spiridon Penev

Most existing results on the distribution of the maximum Sharpe ratio depend on the assumption of multivariate normal return distributions. We use recent results from the literature to provide an analytical representation of the distribution of the difference between two maximum Sharpe ratios for much less restrictive distributional assumptions, both with and without short sales. Knowing the distribution of the difference enables us to test ex ante whether or not the inclusion of additional variables leads to a significant improvement in the maximum Sharpe ratio. In addition, we characterize the optimal long-only solution and provide conditions for global optimality.

The FOMC Risk Shift (SSRN)

Tim A. Kroencke, Maik Schmeling and Andreas Schrimpf

This paper presents new evidence on channels through which monetary policy affects prices in equity and other asset markets. A large part of U.S. equity price moves around FOMC meetings can be attributed to shocks that are uncorrelated with yield changes but closely linked to changes in investors' risk appetite. These price effects are mirrored by investors' portfolio rebalancing decisions, manifesting themselves via sizeable shifts in fund flows between bonds and equities. All these effects are transitory and largely reversed after about one month. We find evidence that risk appetite shocks are related to changes in uncertainty triggered by FOMC meetings.

Hedging Recessions (SSRN)

Nicole Branger, Linda Sandris Larsen and Claus Munk

Traditional life-cycle models conclude that consumer-investors should be fully invested in stocks when young---in stark contrast to observed stock holdings---and then gradually replace stocks with bonds as retirement is approaching. We show that a careful modeling of business cycle and unemployment risks reduces the early-life stock holdings dramatically, in some situations even to zero in accordance with the wide-spread non-participation in the stock market. The reduction is driven by the relatively high unemployment risk of young adults, the negative influence of unemployment on future salaries, and the business cycle variations in stock prices and unemployment risk that cause human capital to be riskier and more stock-like.

Risk-minimization in Electricity Markets: Fixed Price, Unknown Consumption (Paper)

Martin Jönsson, Rolf Poulsen, Rune Ramsdal Ernstsen, and Anders Skajaa