Hedging via Perpetual Derivatives: Trinomial Option Pricing and Implied Parameter Surface Analysis

We introduce a fairly general, recombining trinomial tree model in the natural world. Market completeness is ensured by considering a market consisting of two risky assets, a riskless asset and a European option. The two risky assets consist of a stock and a perpetual derivative of that stock. The option has the stock and its derivative as its underlying. Using a replicating portfolio, we develop prices for European options and generate the unique relationships between the risk-neutral and real-world parameters of the model. We discuss calibration of the model to empirical data in the cases in which the risky asset returns are treated as either arithmetic or logarithmic. From historical price and call option data for select large cap stocks, we develop implied parameter surfaces for the real-world parameters in the model.

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Publication Details

Journal
Journal of risk and financial management
Published
2025-04-02
DOI
https://doi.org/10.3390/jrfm18040192
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
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article

Hedging via Perpetual Derivatives: Trinomial Option Pricing and Implied Parameter Surface Analysis

Svetlozar T. Rachev, W. Brent Lindquist, Jagdish Gnawali
Journal of risk and financial management
Stochastic processes and financial applications
article

Hedging via Perpetual Derivatives: Trinomial Option Pricing and Implied Parameter Surface Analysis

Svetlozar T. Rachev, W. Brent Lindquist, Jagdish Gnawali
article en

Abstract

We introduce a fairly general, recombining trinomial tree model in the natural world. Market completeness is ensured by considering a market consisting of two risky assets, a riskless asset and a European option. The two risky assets consist of a stock and a perpetual derivative of that stock. The option has the stock and its derivative as its underlying. Using a replicating portfolio, we develop prices for European options and generate the unique relationships between the risk-neutral and real-world parameters of the model. We discuss calibration of the model to empirical data in the cases in which the risky asset returns are treated as either arithmetic or logarithmic. From historical price and call option data for select large cap stocks, we develop implied parameter surfaces for the real-world parameters in the model.

Journal of risk and financial managementVol. 18(4)
Texas Tech University (US)
Openalex Percentile: Top 91%
Stochastic processes and financial applications
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