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Derivative Instruments (derivative + instruments)

Distribution by Scientific Domains

Business, Economics, Finance and Accounting	100%

Selected Abstracts

MODEL UNCERTAINTY AND ITS IMPACT ON THE PRICING OF DERIVATIVE INSTRUMENTS

MATHEMATICAL FINANCE, Issue 3 2006
Rama Cont
Uncertainty on the choice of an option pricing model can lead to "model risk" in the valuation of portfolios of options. After discussing some properties which a quantitative measure of model uncertainty should verify in order to be useful and relevant in the context of risk management of derivative instruments, we introduce a quantitative framework for measuring model uncertainty in the context of derivative pricing. Two methods are proposed: the first method is based on a coherent risk measure compatible with market prices of derivatives, while the second method is based on a convex risk measure. Our measures of model risk lead to a premium for model uncertainty which is comparable to other risk measures and compatible with observations of market prices of a set of benchmark derivatives. Finally, we discuss some implications for the management of "model risk." [source]

Property Derivatives for Managing European Real-Estate Risk

EUROPEAN FINANCIAL MANAGEMENT, Issue 1 2010
Frank J. Fabozzi
G15; G20 Abstract Although property markets represent a large proportion of total wealth in developed countries, the real-estate derivatives markets are still lagging behind in volume of trading and liquidity. Over the last few years there has been increased activity in developing derivative instruments that can be utilised by asset managers. In this paper, we discuss the problems encountered when using property derivatives for managing European real-estate risk. We also consider a special class of structured interest rate swaps that have embedded real-estate risk and propose a more efficient way to tailor these swaps. [source]

Handling Weather Related Risks Through the Financial Markets: Considerations of Credit Risk, Basis Risk, and Hedging

JOURNAL OF RISK AND INSURANCE, Issue 2 2007
Linda L. Golden
The profits of many businesses are strongly affected by weather related events, and insurance against weather related risks (acts of God) has been a traditional domain for transfer of (certain) of these risks. Recent innovations in the capital market have now provided financial instruments to transfer and hedge some of these risks. Unlike insurance solutions, however, using these financial derivative instruments creates a situation in which the return to the purchaser of the instrument is no longer perfectly correlated with the loss experienced. Such a mismatch creates new risks which must be examined and evaluated as part of ascertaining cost effective risk management plans. Two newly engendered risks, basis risk (the risk created by the fact that the return from the financial derivative is a function of weather at a prespecified geographical location which may not be identical to the location of the firm) and credit risk (the risk that the counterparty to the derivative contract may not perform), are analyzed in this article. Using custom tailored derivatives from the over the counter market can decrease basis risk, but increases credit risk. Using standardized exchange traded derivatives decreases credit risk but increases basis risk. Here also the effectiveness of using hedging methods involving forwards and futures having linear payoffs (linear hedging) and methods using derivatives having nonlinear payoffs such as those involving options (nonlinear hedging) for the purpose of hedging basis risk are examined jointly with credit risk. [source]

MODEL UNCERTAINTY AND ITS IMPACT ON THE PRICING OF DERIVATIVE INSTRUMENTS

Robust estimation of the optimal hedge ratio

THE JOURNAL OF FUTURES MARKETS, Issue 8 2003
Richard D. F. Harris
When using derivative instruments such as futures to hedge a portfolio of risky assets, the primary objective is to estimate the optimal hedge ratio (OHR). When agents have mean-variance utility and the futures price follows a martingale, the OHR is equivalent to the minimum variance hedge ratio,which can be estimated by regressing the spot market return on the futures market return using ordinary least squares. To accommodate time-varying volatility in asset returns, estimators based on rolling windows, GARCH, or EWMA models are commonly employed. However, all of these approaches are based on the sample variance and covariance estimators of returns, which, while consistent irrespective of the underlying distribution of the data, are not in general efficient. In particular, when the distribution of the data is leptokurtic, as is commonly found for short horizon asset returns, these estimators will attach too much weight to extreme observations. This article proposes an alternative to the standard approach to the estimation of the OHR that is robust to the leptokurtosis of returns. We use the robust OHR to construct a dynamic hedging strategy for daily returns on the FTSE100 index using index futures. We estimate the robust OHR using both the rolling window approach and the EWMA approach, and compare our results to those based on the standard rolling window and EWMA estimators. It is shown that the robust OHR yields a hedged portfolio variance that is marginally lower than that based on the standard estimator. Moreover, the variance of the robust OHR is as much as 70% lower than the variance of the standard OHR, substantially reducing the transaction costs that are associated with dynamic hedging strategies. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:799,816, 2003 [source]