It Only Takes a Few Moments to Hedge

Barletta, Andrea; Magistris, Paolo Santucci de; Sloth, David

doi:10.2139/ssrn.3086538

Cited by 2 publications

(3 citation statements)

References 44 publications

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“…Figure 3 compares the behavior of the monthly average of 1 month S&P 500 option prices over different forward moneyness. Consistent with Barletta et al (2017), the ITM options exhibit non-stationary behavior whereas the OTM options are stationary.…”

Section: Data Descriptionmentioning

confidence: 66%

Universal Arbitrage-Free Estimation of State Price Density

Newton

2020

JOD

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Given the valuable information content of Arrow-Debreu prices, the recovery of a well behaved state price density is of considerable importance. However, this is a non-trivial task due to data limitation and the complex arbitrage-free constraints. In this paper, we develop a more effective linear programming support vector machine (SVM) estimator for state price density which incorporates no-arbitrage restrictions and bid-ask spread. This method does not depend on a particular approximation function and framework and is, therefore, universally applicable.In a parallel empirical study, we apply the method to options on the S&P 500, showing it to be accurate and smooth.

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Section: Data Descriptionmentioning

confidence: 66%

Universal Arbitrage-Free Estimation of State Price Density

Newton

2020

JOD

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“…The optimization problem (12) is solved resorting to the MATLAB built-in function fmincon. The formula to compute the delta, the gamma and the vega implied by estimates of the RND obtained by (12) is provided in Barletta et al (2018).…”

Section: Option Pricing With Orthogonal Polynomial Expansionsmentioning

confidence: 99%

“…The estimated RND can be exported as a MATLAB function handle and used for extracting useful information for risk management such as the higher moments or quantiles like the VaR under the risk-neutral measure, see Aït-Sahalia and Lo (2000) and . Finally, based on the estimated RND, delta, gamma and vega hedge ratios can be computed non-parametrically following the methodology outlined in Barletta et al (2018) and adopted for hedging purposes, see Figure 5.…”

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confidence: 99%

Analyzing the Risks Embedded in Option Prices with rndfittool

Barletta

Magistris

2018

Risks

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This paper introduces a new computational tool for the analysis of the risks embedded in a set of prices of European-style options. The software enables the estimation of the risk-neutral density (RND) from the observed option prices by means of orthogonal polynomial expansions. Orthogonal polynomials offer a viable alternative to more standard techniques based on interpolation and estimation of the second-order derivatives of option prices. The app rndfittool is available on GitHub and its usage is illustrated with examples based on real data.

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It Only Takes a Few Moments to Hedge

Cited by 2 publications

References 44 publications

Universal Arbitrage-Free Estimation of State Price Density

Universal Arbitrage-Free Estimation of State Price Density

Analyzing the Risks Embedded in Option Prices with rndfittool

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