Hedge funds offer desirable risk-return profiles; but we also find high management fees, lack of transparency and worse, very limited liquidity (they are often closed to new investors and disinvestment fees can be prohibitive). This creates an incentive to replicate the attractive features of...

The recent crisis made it evident that replicating the performance of a benchmark is not a sufficient goal to meet the expectations of usually risk-averse investors. The manager should also consider that the investor are seeking for a downside protection when the benchmark performs poorly and...

This paper aims at providing macroeconomists with a detailed exposition of the New Keynesian DSGE model. Both the sticky price version and the sticky information variant are derived mathematically. Moreover, we simulate the models, also including lagged terms in the sticky price version, and...

Using equations that arise in quantum mechanics, this paper describes a way to more accurately and efficiently represent non-Gaussian return distributions than the standard method of invoking skewness and kurtosis. Then, it provides a new single intuitive number, defined here as the “crash...

We study an optimization-based approach to construct a mean-reverting portfolio of assets. Our objectives are threefold: (1) design a portfolio that is well-represented by an Ornstein-Uhlenbeck process with parameters estimated by maximum likelihood, (2) select portfolios with desirable...

We estimate a small-scale macroeconomic model for Japan by taking into account the nonlinearity stemming from the zero lower bound (ZLB) of the nominal interest rate. To this end, we apply the Sequential Monte Carlo Squared method to the case of Japan, where the ZLB has constrained the country's...

In this paper, I show how gradient-based optimization methods can be used to estimate stochastic dynamic models in economics. By extending the state space to include all model parameters, I show that we need to solve the model only once to do structural estimation. Parameters are then estimated...

Estimation and modelling problems as they arise in many fields often turn out to be intractable by standard numerical methods. One way to deal with such a situation consists in simplifying models and procedures. However, the solutions to these simplified problems might not be satisfying. A...

The evaluation of quantiles (or VaR, Value at Risk) and that of CVaR, Conditional Value at Risk in risk management (or mean excess in actuarial sciences) is a very crucial point in the decision processes. Indeed, there are often great difficulties (or impossibilities) in finding the kind of...

Should long-term investors account for time-variation in model parameters? We develop a time-varying Vector Autoregressive model that can handle time-variation in intercepts, slopes, volatility and correlation, the leverage effect in volatility and fat tails. Long-term investors should take...