Classic option pricing theory values a derivative contract via dynamic replication, and views the derivative as redundant relative to the replicating portfolio. In practice, while dynamic replication proves highly effective in drastically reducing the risk in derivative investments, the...

We solve for the optimal portfolio allocation in a setting where both conditional correlation and theclustering of extreme events are considered. We demonstrate that there is a substantial welfare loss indisregarding tail dependence, even when dynamic conditional correlation has been accounted...

This paper investigates the relationship between upside potential and future hedge fund returns. We measure upside potential based on the maximum monthly returns of hedge funds (MAX) over a fixed time interval, and show that MAX successfully predicts cross-sectional differences in future fund...

This paper investigates hedge funds' exposures to various financial and macroeconomic risk factors through alternative measures of factor betas and examines their performance in predicting the cross-sectional variation in hedge fund returns. Both parametric and nonparametric tests indicate a...

The problem of optimal portfolio choice is solved, in closed form, for an ambiguity averse investor who has access to stock and derivatives markets. The investor can have different levels of uncertainty about models for stock return and its stochastic volatility. Although both types of ambiguity...

This paper uses deep learning to value derivatives. The approach is broadly applicable, and we use a call option on a basket of stocks as an example. We show that the deep learning model is accurate and very fast, capable of producing valuations a million times faster than traditional models. We...

The main goal of this paper is to better understand the behavior of credit spreads in the past and the potential risk of unexpected future credit spread changes. One important consideration to note regarding credit spreads is the fact that bond spreads contain a liquidity premium, which...

This paper proposes a simple technical approach for the analytical derivation of Point-in-Time PD (probability of default) forecasts, with minimal data requirements. The inputs required are the current and future Through-the-Cycle PDs of the obligors, their last known default rates, and a...

In this article we study the widely used in randomized experiments approach of decreasing variance of estimate of average treatment effect (ATE) by estimating ATE on residuals using linear regression, i.e. when we first fit using linear regression on a pooled dataset exploratory...

We explore the cost of implicit leverage associated with an S&P 500 Index futures contract and derive an implied financing rate (the Futures-Implied Rate or FIR), based on a simple model of stock and futures, without any explicit arbitrage or other relationship to market interest rates. We...