My research interests include theoretical and empirical asset pricing, dynamic portfolio choice, model and parameter uncertainty, robustness, liquidity, and financial mathematics.


 Parameter Uncertainty: The Missing Piece of the Liquidity Premium Puzzle?

I analyze a dynamic investment problem with stochastic transaction cost and parameter uncertainty. I solve the problem numerically and obtain the optimal consumption and investment policy and the least-favorable transaction cost process. Using reasonable parameter values, I confirm the liquidity premium puzzle, i.e., the representative agent model (without robustness) produces a liquidity premium which is by a magnitude lower than the empirically observed value. I show that my model with robust investors generates an additional liquidity premium component of 0.05%-0.10% (depending on the level of robustness) for the first 1% proportional transaction cost, and thus it provides a partial explanation to the liquidity premium puzzle. Additionally, I provide a novel non-recursive representation of discrete-time robust dynamic asset allocation problems with transaction cost, and I develop a numerical technique to efficiently solve such investment problems.

Robust Pricing of Fixed Income Securities (with Frank de Jong and Bas J.M. Werker)

We analyze a dynamic investment problem with interest rate risk and ambiguity. After deriving the optimal terminal wealth and investment policy, we expand our model into a robust general equilibrium model and calibrate it to U.S. data. We confirm the bond premium puzzle, i.e., we need an unreasonably high relative risk-aversion parameter to explain excess returns on long-term bonds. Our model with robust investors reduces this risk-aversion parameter substantially: a relative risk aversion of less than four suffices to match market data. Additionally we provide a novel formulation of robust dynamic investment problems together with an alternative solution technique: the robust version of the martingale method.

Dynamic Asset Liability Management under Model Uncertainty (with Frank de Jong and Bas J.M. Werker)

We analyze a dynamic Asset Liability Management problem with model uncertainty in a complete market. The fund manager acts in the best interest of the pension holders by maximizing the expected utility derived from the terminal funding ratio. We solve the robust multi-period Asset Liability Management problem in closed form, and identify two constituents of the optimal portfolio: the myopic demand, and the liability hedge demand. We fi.nd that even though the investment opportunity set is stochastic, the investor does not have intertemporal hedging demand. We also fi.nd that model uncertainty induces a more conservative investment policy regardless of the risk attitude of the fund manager, i.e., a robust investment strategy corresponds to risk exposures which provide a much stronger liability hedge.


 Robustness for Asset-Liability Management of Pension Funds (With Frank de Jong and Bas J.M. Werker, Netspar Survey Paper 47, October 2016)

This paper by Ferenc Horvath, Frank de Jong, and Bas J.M. Werker (all Tilburg University) discusses the effects of uncertainty on optimal investment decisions and on optimal asset-liability management by institutional investors, especially pension funds, by surveying the most recent literature on robust dynamic asset allocation with an emphasis on the asset-liability management of pension funds. The authors also provide several policy recommendations.

Tőkeáttétel-ciklusok (Leverage Cycles, in Hungarian) (with Edina Berlinger and Ágnes Vidovics-Dancs, Hitelintézeti Szemle (Journal of Banking, in Hungarian), Vol. 11, No. 1, pp. 1-23, 2012)

There are several indices to measure the leverage of different sectors such as households, firms, government or banking system. Examining the historic trends of these indices reveals that in booms economic actors tend to enhance their leverage while in crisis periods they deleverage their positions consciously or intuitively. Since yield multiplies, high leverage is a profitable strategy when economy does well. Nevertheless, higher yield means higher risk, as leverage magnifies negative shocks as well. In this paper, after introducing the basic concepts, we summarize the empirical evidences for the existence of leverage cycles, then we examine the rational and less rational reasons of this phenomenon. Finally, we analyze the consequences and the role of regulators.