We introduce an ensemble learning method based on Gaussian Process Regression (GPR) for predicting conditional expected stock returns given stock-level and macro-economic information. Our ensemble learning approach significantly reduces the computational complexity inherent in GPR inference and...

We introduce a new class of momentum strategies, the risk-adjusted time series momentum (RAMOM) strategies, which are based on averages of past futures returns, normalized by their volatility. We test these strategies on a universe of 64 liquid futures contracts and show that RAMOM strategies...

While CBOE's VIX index is widely acknowledged as a broad-based investor “fear gauge” for its strong inverse relationship with major equity indexes, one cannot necessarily expect it to translate to the level of future turbulence or investor risk aversion in fixed-income markets. Indeed,...

Estimates of agents' risk aversion differ between market studies and experimental studies. We demonstrate that the estimates can be reconciled through consistent treatment of agents' tendency for narrow framing, regarding integration of background wealth as well as across risky outcomes: Risk...

Monetary risk measures classify a financial position by the minimal amount of external capital that must be added to the position to make it acceptable.We propose a new concept: intrinsic risk measures. The definition via external capital is avoided and only internal resources appear. An...

We solve the problems of mean-variance hedging (MVH) and mean-variance portfolio selection (MVPS) under restricted information. We work in a setting where the underlying price process S is a semimartingale, but not adapted to the filtration G which models the information available for...

We study mean-variance hedging under portfolio constraints in a general semimartingale model. The constraints are formulated via predictable correspondences, meaning that the trading strategy is restricted to lie in a closed convex set which may depend on the state and time in a predictable way....

We solve the problem of mean-variance hedging for general semimartingale models via stochastic control methods. After proving that the value process of the associated stochastic control problem has a quadratic structure, we characterise its three coefficient processes as solutions of...

We show that in a consumption-based asset-pricing model with hyperbolic discounting leading to dynamically inconsistent time preferences value premium increases nonlin-early with the degree of discounting and thus affects cross section of returns. To test our model empirically, we relate the...

This paper develops an optimal trading strategy explicitly linked to an agent's preferences and assessment of the distribution of asset returns. The price of this strategy is a portfolio of implied moments, and its expected excess returns naturally accommodate compensation for higher-order...