This paper proposes to extract tail risk from a risk-neutral mean-adjusted expected shortfall of high-frequency stock returns. Risk adjustment is based on a nonparametric estimator of the state price density that does not use option prices and relies solely on a stock index returns. This makes...

We present effective momentum strategies over the liquid equity futures market in India. We evaluate and determine the persistence of the returns at various look-backs ranging from quarterly and weekly to more granular look-backs. We look at a universe of the liquid equity instruments traded...

Guarantees embedded variable annuity contracts exhibit option-like payoff features and the pricing of such instruments naturally leads to risk neutral valuation techniques. This paper considers the pricing of two types of guarantees; namely, the Guaranteed Minimum Maturity Benefit and the...

Investment decisions may be evaluated via several different metrics/criteria, which are functions of a vector of value drivers. The economic significance and the reliability of a metric depend on its compatibility with the Net Present Value (NPV). Traditionally, a metric is said to be...

The Simulation-Based Excess Return Model (SERM) offers a simple, practical decision-making method for underwriting real estate development projects. It addresses the shortcomings of discounted cash flow modeling by taking into account the probabilistic distribution of outcomes and is based on...

This article is concerned with the study of the tail correlation among equity indices by means of dynamic copula functions. The main idea is to consider the impact of the use of copula functions in the accuracy of the model´s parameters and in the computation of Value-at-Risk (VaR). Results...

The Simulation-Based Excess Return Model (SERM) offers a simple, practical decision-making method for underwriting real estate development projects. It addresses the shortcomings of discounted cash flow modeling by taking into account the probabilistic distribution of outcomes and is based on...

Adaptive Polar Sampling (APS) is proposed as a Markov chain Monte Carlomethod for Bayesian analysis of models with ill-behaved posteriordistributions. In order to sample efficiently from such a distribution,a location-scale transformation and a transformation to polarcoordinates are used. After...