(Fuente: *Rising demand for hedges**, Flows & Liquidity, February 24 2012.*

Posted on 28 febrero 2012.

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Posted on 21 enero 2012.

**A dynamic default correlation model (2008)**

We develop a dynamic model of default that matches single-name CDS spreads by construction and can be calibrated to standard CDO tranche spreads. We assume that single-name default intensities have a one-factor structure with an unobservable systematic factor. Our model formalizes an intuitive idea: while the current level of spreads is determined by the distribution of default times, spread volatility is determined by the process of resolution of uncertainty about default times. We model resolution of uncertainty as learning about the unobservable systematic factor. Our model is computationally tractable and has the appealing property that the learning process can be specified to match empirically observed spread volatility with no affect on the model-implied spread levels

Link al Paper

**Commodity Futures and Inflation (2008)**

In this paper, we present some empirical evidence on the connection between commodities and inflation. Using historical prices on twenty commodity futures covering a period from 1988 to early 2008, we estimate correlations between futures returns and several inflation measures. We find that most commodity futures exhibit very weak correlation with several core inflation measures. Energy commodities have somewhat higher correlation with the total Consumer Price Index (CPI), which is due to the effect of volatile energy prices on the CPI level. We conclude that the average correlation between various commodities and overall price inflation is very low.

Link al Paper

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*Estos papers fueron escritos por Leonid Kogan de MIT*

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Posted on 20 enero 2012.

*FT Alphaville* tiene una muy buena serie de *posts* sobre un método (una subasta) por el cual se obtiene el monto definitivo que paga un CDS (si un evento de default ocurre).

To the extent that CDS are used to hedge, rather than speculate, the outcomes of these auctions will dictate

how effective the hedge has been.In this series, FT Alphaville looks at why the auction process was put in place, how it works, and why it

maybe biased — while discussing some rather curious cases along the way.

Aquí están los links los tres *posts*.

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Posted on 11 octubre 2011.

Tal vez es una serie de *post* más para **finanzas 301**, pero los ultimos 3 *post* de *Quantivity* hacen un buen capitulo de *Hedging*.

*“The root challenge of two current equity risk and alpha projects boil down to hedging using non-underlying instruments, known as proxy hedging or cross hedging.”*

Empirical Quantiles and Proxy Selection

*“(…)how to choose an appropriate hedge instrument, especially amongst several alternatives.”*

Empirical Copulas and Hedge Basis Risk

*“Of particular interest is understanding the dynamics of basis risk under extreme scenarios (both up and down), which are driven by time-varying stochastic joint covariation.”*

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Posted on 28 marzo 2011.

**An Empirical Analysis of Dynamic Multiscale Hedging using Wavelet Decomposition**

Abstract

This paper investigates the hedging effectiveness of a dynamic moving window OLS hedging model, formed using wavelet decomposed time-series. The wavelet transform is applied to calculate the appropriate dynamic minimum-variance hedge ratio for various hedging horizons for a number of assets. The effectiveness of the dynamic multiscale hedging strategy is then tested, both in- and out-of-sample, using standard variance reduction and expanded to include a downside risk metric, the time horizon dependent Value-at-Risk. Measured using variance reduction, the effectiveness converges to one at longer scales, while a measure of VaR reduction indicates a portion of residual risk remains at all scales. Analysis of the hedge portfolio distributions indicate that this unhedged tail risk is related to excess portfolio kurtosis found at all scales.

Link al Paper

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Posted on 26 octubre 2010.

**Abstract**

This paper presents hedging strategies for European and exotic options in a Lévy market. By applying Taylor’s theorem, dynamic hedging portfolios are constructed under different market assumptions, such as the existence of power jump assets or moment swaps. In the case of European options or baskets of European options, static hedging is implemented. It is shown that perfect hedging can be achieved. Delta and gamma hedging strategies are extended to higher moment hedging by investing in other traded derivatives depending on the same underlying asset. This development is of practical importance as such other derivatives might be readily available. Moment swaps or power jump assets are not typically liquidly traded. It is shown how minimal variance portfolios can be used to hedge the higher order terms in a Taylor expansion of the pricing function, investing only in a risk-free bank account, the underlying asset, and potentially variance swaps. The numerical algorithms and performance of the hedging strategies are presented, showing the practical utility of the derived results.

Link al Paper

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