"A detailed, expert-driven guide to today's major financial point of interest The xVA Challenge: Counterparty Credit Risk, Funding, Collateral, and Capital is a practical guide from one of the leading and most influential credit practitioners, Jon Gregory. Focusing on practical methods, this...

Growing experimental evidence suggests that loss aversion plays an important role in asset allocation decisions. We study the asset allocation of a linear loss-averse (LA) investor and compare the optimal LA portfolio to the more traditional optimal mean-variance (MV) and conditional...

The objective of this paper is to combine a real options framework with portfolio optimization techniques and to apply this new framework to investments in the electricity sector. In particular, a real options model is used to assess the adoption decision of particular technologies under...

Market liquidity is the ease of trading an asset. Its risk is the potential loss, because a security can only be traded at high or prohibitive costs. While the omnipresence and importance of market liquidity is widely acknowledged, it has long remained a more or less elusive concept. Treatment...

We integrate liquidity risk measured by the weighted spread into a Value-at-Risk (VaR) framework. The weighted spread measure extracts liquidity costs by order size from the limit order book. We show that it is precise from a risk perspective in a wide range of clearly defined situations. Using...

This paper focuses on two methods for optimum portfolio selection. We compare Mean-Variance method with Mean-VaR method by the means of investment simulation, based on Czech financial market data from turbulent market periods of the year 2007 and the year 2008. We compare both strategies, basing...

We characterize the investor’s optimal portfolio allocation subject to a budget constraint and a probabilistic VaR constraint in complete markets environments with a finite number of states. The set of feasible portfolios might no longer be connected or convex, while the number of local optima...