The optimal use of return predictability : an empirical study

In this paper we study the economic value and statistical significance of asset return predictability, based on a wide range of commonly used predictive variables. We assess the performance of dynamic, unconditionally efficient strategies, first studied by Hansen and Richard (1987) and Ferson and Siegel (2001), using a test that has both an intuitive economic interpretation and known statistical properties. We find that using the lagged term spread, credit spread, and inflation significantly improves the risk-return trade-off. Our strategies consistently outperform efficient buy-and-hold strategies, both in and out of sample, and they also incur lower transactions costs than traditional conditionally efficient strategies

Zap Q-Learning for Optimal Stopping Time Problems

The objective in this paper is to obtain fast converging reinforcement learning algorithms to approximate solutions to the problem of discounted cost optimal stopping in an irreducible, uniformly ergodic Markov chain, evolving on a compact subset of $\mathbb{R}^n$. We build on the dynamic programming approach taken by Tsitsikilis and Van Roy, wherein they propose a Q-learning algorithm to estimate the optimal state-action value function, which then defines an optimal stopping rule. We provide insights as to why the convergence rate of this algorithm can be slow, and propose a fast-converging alternative, the "Zap-Q-learning" algorithm, designed to achieve optimal rate of convergence. For the first time, we prove the convergence of the Zap-Q-learning algorithm under the assumption of linear function approximation setting. We use ODE analysis for the proof, and the optimal asymptotic variance property of the algorithm is reflected via fast convergence in a finance example

An examination of the benefits of dynamic trading strategies in U.K. closed-end funds

We examine the after-cost out-of-sample performance of the unconditional mean-variance (UMV) strategy in the presence of conditioning information (Ferson and Siegel(2001)) using portfolios of U.K. equity closed-end funds. We find that the performance of the UMV strategy significantly improves when using lagged information variables with the highest persistence (first-order autocorrelation) levels and reduces turnover. This strategy is able to outperform alternative dynamic trading strategies and performs well across different subperiods. At low levels of trading costs, the UMV strategy is able to deliver significant value added to investors

On the modulation of low frequency Quasi-Periodic Oscillations in black-hole transients

We studied the properties of the low-frequency quasi-periodic oscillations detected in a sample of six black hole candidates (XTE J1550-564, H 1743-322, XTE J1859+226, 4U 1630-47,GX 339-4, XTE J1650-500) observed by the Rossi XTE satellite. We analyzed the relation between the full width half maximum and the frequency of all the narrow peaks detected in power density spectra where a type-C QPO is observed. Our goal was to understand the nature of the modulation of the signal by comparing the properties of different harmonic peaks in the power density spectrum. We find that for the sources in our sample the width of the fundamental and of the first harmonic are compatible with a frequency modulation, while that of the sub-harmonic is independent of frequency, possibly indicating the presence of an additional modulation in amplitude. We compare our results with those obtained earlier from GRS 1915+105 and XTE J1550-564.Comment: 8 pages, 3 figures, accepted for publication in Monthly Notices of the Royal Astronomical Society Main Journa