Hedging using simulation: a least squares approach

Tebaldi, Claudio

doi:10.1016/j.jedc.2004.07.006

Cited by 10 publications

(1 citation statement)

References 32 publications

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“…Factor hedging is well suited for hedging with general multidimensional models (Chiarella et al, ; Clewlow & Strickland, ) and allows simultaneous hedging of multiple risk factors impacting the entire term structure of the forward curve of commodities, and their derivatives. Theoretical self‐financing replicating hedge strategies are predicated on rebalancing in continuous time (see, e.g., Barrieu & El Karoui, ; Tebaldi, ), while in practice hedges can only be rebalanced discretely—this is another reason why factor hedging is the more suitable approach, as it better caters for the fact that a perfectly self‐financing replicating hedge in continuous time is not implementable in practice.…”

Section: Introductionmentioning

confidence: 99%

Interest rate risk in long‐dated commodity options positions: To hedge or not to hedge?

Cheng

Nikitopoulos

Schlögl

2018

Journal of Futures Markets

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We empirically assess hedging interest rate risk beyond the conventional delta, gamma, and vega hedges in long‐dated crude oil options positions. Using factor hedging in a model featuring stochastic interest rates and stochastic volatility, interest rate hedges consistently provide an improvement beyond delta, gamma, and vega hedges. Under high interest rate volatility and/or when a rolling hedge is used, combining interest rate and delta hedging improves performance by up to four percentage points over the common hedges of gamma and/or vega. Thus, contrary to common practice, hedging interest rate risk should have priority over these “second‐order” hedges.

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Section: Introductionmentioning

confidence: 99%

Interest rate risk in long‐dated commodity options positions: To hedge or not to hedge?

Cheng

Nikitopoulos

Schlögl

2018

Journal of Futures Markets

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B ermudan Options

Kolkiewicz¹

2010

Encyclopedia of Quantitative Finance

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Pricing Bermudan options that depend on multiple assets is a challenging computational problem. Algorithms based on a discretization of the state space typically suffer from the “curse of dimensionality”, meaning that the computational effort grows exponentially with the number of state variables. Regression‐based methods address this problem first by simulating trajectories of the underlying process and then by estimating continuation values through the regression of option values at the next time step on a set of regressors that depend on the current state. In principle, these methods can be applied to any situation where trajectories of the underlying process can be simulated, since no other information about the process is required. In particular, they can be applied to path‐dependent options.

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A Defaultable Financial Market with Complete Information

Raju

2015

Lecture Notes in Electrical Engineering

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Hedging using simulation: a least squares approach

Cited by 10 publications

References 32 publications

Interest rate risk in long‐dated commodity options positions: To hedge or not to hedge?

Interest rate risk in long‐dated commodity options positions: To hedge or not to hedge?

B ermudan Options

A Defaultable Financial Market with Complete Information

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