Stochastic linear programming is a suitable numerical approach for solving practical asset-liability
management problems. In this paper, we consider a multi-stage setting under time-…

We compare risk-neutral densities from equity index options across several countries during
the early phase of the COVID-19 pandemic. The initial reaction in all analyzed markets was …

Many numerical optimization methods use scenario trees as a discrete approximation for
the true (multi-dimensional) probability distributions of the problem’s random variables. …

We consider optimal consumption and (strategic) asset allocation of an investor with
uncertain lifetime. The problem is solved using a multi-stage stochastic linear programming (SLP) …

Since its announcement made on September 6, 2011, the Swiss National Bank (SNB) has
been pursuing the goal of a minimum EUR/CHF exchange rate of 1.20, promising to intervene …

Diversified banks (ie financial conglomerates) trade often at a discount compared to matched
portfolios of specialized stand-alone banks. The existing research explains this evidence …

Most portfolio selection rules based on the sample mean and covariance matrix perform poorly
out-of-sample. Moreover, there is a growing body of evidence that such optimization rules …

Betting quotes provide valuable information on market-implied probabilities for outcomes of
events such as elections or referendums, which may have an impact on exchange rates. We …

Many optimization-based portfolio rules fail to beat the simple 1/N rule out-of-sample because
of parameter uncertainty. In this paper we suggest a grouping strategy in which we first …

We study the implications of predictability on the optimal asset allocation of ambiguity-averse
long-term investors and analyze the term structure of the multivariate risk–return trade-off …