We introduce a simple approach to managing portfolio interest rate risk that is consistent and performs well across different interest rate regimes, including when interest rates are low or even negative. Inspired by Black (1995), this approach uses a novel inverse-call transformation...

We study the out-of-sample and post-publication return-predictability of 97 variables that academic studies show to predict cross-sectional stock returns. Portfolio returns are 26% lower out-of-sample and 58% lower post-publication. The out-of-sample decline is an upper bound estimate of data...

Exercises and case studies for a rigorous approach to risk- and portfolio-management. This booklet stems from the review sessions of the six-day ARPM bootcamp.Contents include:Advanced multivariate statistics; copula-marginal decompositionAnnualization/projection (FFT, cumulants,...

With the exception of naive methods for portfolio selection, such as the equal weighted approaches, all other methods of portfolio allocation are more or less sensitive to the quality of the inputs considered in constructing the models and risk measures utilised in the allocation framework. The...

We provide a model-free framework for studying the dynamics of the state vector and its risk prices. Specifically, we derive a frequency domain decomposition of the unconditional asset return premium in a general setting with a log-affine stochastic discount factor (SDF). Importantly, we show...

To study the characteristics-sorted factor model in asset pricing, we develop a bottom-up approach with state-of-the-art deep learning optimization. With an economic objective to minimize pricing errors, we train a non-reduced-form neural network using firm characteristics [inputs], and generate...

We analyze the economic benefits of several covariance estimation approaches on a tactical asset-allocation problem in the presence of high-frequency return data. Our analysis confirms that the use of robust-to-noise and asynchronicity estimators not only gives statistically more accurate...

The Entropy Pooling approach is a versatile theoretical framework to process market views and generalized stress-tests into an optimal "posterior" market distribution, which is then used for risk management and portfolio management. Entropy Pooling can be implemented non-parametrically or...

A value investing strategy consists of purchasing stocks relatively undervalued to their fundamental values and selling those relatively overvalued. Finding this kind of companies has been one of the most challenging goals for investors throughout the history. The main objective of this paper is...

The return dynamics of Argentina's main stock index, the SP Mer.Val., show a high level of volatility, signaling a higher degree of downside risk. To hedge against that specific risk, investors could buy put options. However, the Argentinean capital market slacks variety of hedging contracts....