An intensive and still growing body of research focuses on estimating a portfolio’s Value-at-Risk.Depending on both the degree of non-linearity of the instruments comprised in the portfolio and thewillingness to make restrictive assumptions on the underlying statistical distributions, a...

This paper develops a new methodology for simulating fixed-income return distributions. It is shown that a traditional factor risk model, when augmented with reference returns, is capable of generating visually consistent return distributions for a broad range of fixed income instruments such as...

In this paper, expected utility, defined by a Taylor series expansion around expected wealth, is maximized. The coefficient of relative risk aversion (CRRA) that is commensurate with a 100% investment in the risky asset is simulated. The following parameters are varied: the riskless return, the...

In recent years both equity and bond markets have been afflicted by high volatility. In order to build up a conservative portfolio several models may be used, such as minimum variance portfolio or equally weighted portfolio. In 2008/09 another way to deal with diversification came up, that is...

Faber's 'A Quantitative Approach to Tactical Asset Allocation' (2009) proposes the use of a very simple trading rule to improve the risk-adjusted returns across various asset classes. The purpose of this paper is to present an alternative and simple quantitative risk based portfolio management...

In this study, we investigate the attenuation of idiosyncratic risk and corresponding benefits of diversification for equally weighted and market capitalization weighted portfolios in the UK Equity Market over 2002 - 2012. We analyze the absolute benefits of risk reduction by testing the...

In this paper we show how risk-averse reinforcement learning can be used to hedge options. We apply a state-of-the-art risk-averse algorithm: Trust Region Volatility Optimization (TRVO) to a vanilla option hedging environment, considering realistic factors such as discrete time and transaction...

Historical VaR, CVaR and ES (Expected Shortfall) to LIQUIDATION Software is a model characterized by its straightforwardness, allowing regulators measure risk using a standard database of primitive factors and portfolio positions only, leaving little error margin in comparing market risk for...

Sophisticated algorithmic techniques are complementing human judgement across the fund industry. Whatever the type of rebalancing that occurs in the course of a longer horizon, it probably violates the buy-and-hold assumption. In this article, we develop the methodology to predict, dissect and...