| The Uncorrelated Attraction of Cat BondsCatastrophe bonds had a banner year in 2012 in terms of issuance, but they also present investors with a unique market paradigm and whole new set of risks to consider. |
|
| The Application of Numeraire Portfolio in PensionsUTS Sydney professor Eckhard Platen says his Benchmark Approach addresses problems posed by long-term contracts. |
|
| ETFs and Market CorrelationsIs the growing exchange-trade fund market exacerbating market correlations? It is an open question that could have far-reaching ramifications. |
|
| Risk Budgeting in the Investment Process: A Framework for ImplementationAs risk management becomes increasingly important, more and more institutional investors are adding a risk budgeting process to their investment decision-making. |
|
| A Simple Solution for Tail RiskThomas Philips of asset manager Fischer Francis Trees and Watts says a simple enhancement to the mean-variance paradigm allows for the inclusion of tail risk. |
|
| Value-at-Risk: Evolution, Deficiencies and AlternativesIn 1988, with increasing stock market activity, JP Morgan saw the motivation to develop an all-in-one solution -- a sole number that can cover financial risk in its whole complexity, yet is easy to interpret. |
|
| Alpha Generation and Risk Smoothing Using Volatility of VolatilityWhether or not you believe in the efficient market hypothesis, it is difficult to predict market returns, whereas market volatility is clearly forecastable |
|
| Leveraged ETFs: All You Wanted to Know but Were Afraid to AskLeveraged exchange-traded funds present a variety or risks, particularly for buy-and-hold investors. To manage these risks effectively, investors must understand the impact of different factors – including compounding, daily balancing and volatility – on returns. |
|
| How to Estimate and Calibrate Analytical VaR for Interest Rate RiskSince analytical value-at-risk (VaR) is easier to understand and to apply than Monte Carlo VaR, the hunt for analytical VaR methodologies is worthwhile, particularly if they can compete with the complexities of Monte Carlo modeling.This article demonstrates how analytical interest rate risk VaR can be estimated using principal component analysis (PCA). |
|
| To VaR Is HumanRisk management is relatively simple in its essence: What is the probability of an event occurring, and, if it happens, how badly will it hurt? However, if we consider how we estimate probabilities and losses, the answers to these seemingly simple questions become complicated very quickly. |
|
| The US Housing Crash: Model or Management Failure?Executives who were quick to blame “faulty” risk models for their inability to predict the real estate downturn need to take a closer look in the mirror. Many factors have contributed to the recent financial crisis. |
|
| Transition Matrices: Filling a Risk Management GapThe recent financial crisis underlined the inadequacy of existing models in the face of changing market conditions; many managers found that the models they were using weren't varying with the evolving conditions and that the gaps they saw could be reduced if market and economic conditions were somehow integrated in the models. |
|
| A Model DefenseThere's one area where quants have an edge over legislators, regulators and financial executives: they remember. They embed their lessons in equations and computer code. |
|
| The March Toward a Consolidated Risk Statement Today, a confluence of technologies has the potential to bring transparency to the arithmetic of uncertain quantities -- i.e., probability distributions -- with beneficial consequences for numerous industries. |
|
| Market Turbulence Raises Questions About Future of Risk ModelsOne of the strengths of risk models is supposed to be their ability to use a limited range of parameters to predict events. However, the reliability of these mathematically-driven models has been called into question by the subprime turmoil, and regulators are now eager to rationalize models and to develop stronger risk management policies. |
|