Financial markets can be regarded as a complex system. In recent years, financial markets experienced several global crisis and structural changes due to greater interdependence among banks and other agents, new technologies, financial innovations and deregulation, and increasing availability of financial information. Although it is arguable that financial crisis are typical emergent phenomena of a complex system such as the financial system, over the past two decades we witnessed an increasing level of systemic risk, alongside a much higher frequency of episodes of turbulence. These stylized facts are quite apparent analyzing the frequency of exceptional volatility spikes, the intensity of the tail dependence among financial assets, the entropy level, and the degree of interdependence among agents. There are a number of reasons behind that, including decision models commonly used in financial markets. Among them, there are many organizational processes and decision models commonly used by policy makers, regulators, and single firms when approaching risk management and managers’ incentives. Even if financial markets are structurally prone to crashes and panics due to their complex nature, improving current policies and decision models explicitly recognizing their complexity, i.e. «thinking in systems », might strengthen the capacity to cope with financial crisis, thus reducing systemic risk.
The purpose of this paper is to compare ex ante value-at-risk (VaR) estimation produced by two risk models: historical simulation and Monte Carlo filtered bootstrap. We perform three tests: unconditional coverage, independence and conditional coverage. We present results on both VaR1% and VaR5% on a one-day horizon for the following indexes: S&P 500, Topix, Dax, […]
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 that improves the risk-adjusted portfolio returns across various asset classes. This […]
A pioneering reference essential in any financial library, the Encyclopedia of Alternative Investments is the most authoritative source on alternative investments for students, researchers, and practitioners in this area. Containing 545 entries, the encyclopedia focuses on hedge funds, managed futures, commodities, and venture capital. It features contributions from well-known, respected academics and professionals from around […]
This book comprises an edited series of papers about risk management and the latest developments in the field. Covering topics such as Stochastic Volatility, Risk Dynamics, Weather Derivatives and Portfolio Diversification, this book will have broad international appeal. It is highly relevany for optimal portfolio allocation for both private and institutional investors worldwide.
This significant new book addresses the important issue of diversification in an age where it is vital to reduce volatility on investments. Properly applied portfolio management can lead to greater gains. The expert authors guide investors through international portfolio diversification, make clear how to help improve the efficiency of their investments, and explain how international […]
We present a multi-period risk model to measure portfolio risk that integrates market risk, credit risk and, in a simplified way, liquidity risk. Thus, it overcomes the major limitation currently shared by many risk models that are unable to give a complete picture of all portfolio risks according to a single, coherent framework. The model […]
Recently in the asset management community, there has been a lot of attention given to techniques for estimating risk indicators. The authors’ focus is on the use of risk indicators, that is, they concentrate on risk policies rather than on estimation techniques. The aim of this paper is to assess, from an empirical point of […]
In the investment community, tracking error is often regarded as the single most important risk measure, and many active asset management companies use tracking error as a basis for keeping a portfolio’s relative risk under control. Recently, the investment community has become aware of some shortfalls of tracking error. One of the main pitfalls is […]
We propose filtering historical simulation by GARCH processes to model the future distribution of assets and swap values. Options’ price changes are computed by full reevaluation on the changing prices of underlying assets. Our methodology takes implicitly into account assets’ correlations without restricting their values over time or computing them explicitly. VaR values for portfolios […]