This thesis focuses on the joint calibration of the S&P 500 and the VIX indexes. These are respectively the main equity index worldwide and its volatility index. The VIX index, often referred to as the "fear gauge", measures the market’s expectation of future volatility, while the S&P 500 index is a widely followed benchmark of U.S. equity market performance. The primary aim of this research is to develop a robust joint calibration framework that accurately captures the dynamics of both indexes. The need for a single model to calibrate both indexes arises from the fact that the VIX index is constructed from options on the S&P 500 index, making the two indexes inevitably linked. The model that will be discussed throughout the following lines is the quintic Ornstein-Uhlenbeck volatility model, introduced by Jaber et al. (2022b). It belongs to the class of stochastic volatility models, where the volatility is represented as a fifth-degree polynomial of a Ornstein-Uhlenbeck process, hence the model’s name. By exploiting a well-known expression for the VIX index in continuous time, it is possible to derive an analytical formula to price options having the VIX index as the underlying. Additionally, a Monte Carlo technique is employed to simulate the S&P 500 index for pricing purposes. This work compares the Euler scheme and the Turbocharging scheme, from the paper of McCrickerd and Pakkanen (2018), for simulating S&P 500 index paths, focusing on option prices, implied volatilities, computational times, and stability. It also conducts a stability analysis of S&P 500-VIX joint calibration using Bloomberg market data from March and April 2024, examining the evolution of model parameters. Additionally, the project simplifies the modeling of the forward variance curve, with respect to the one proposed in Jaber et al. (2022b), by using piece-wise constant interpolation.
Questa tesi si concentra sulla calibrazione congiunta degli indici S&P 500 e VIX. Questi sono rispettivamente il principale indice azionario mondiale e il suo indice di volatilità. L’indice VIX, spesso chiamato il "fear gauge", misura le aspettative del mercato riguardo alla volatilità futura, mentre l’indice S&P 500 è un punto di riferimento ampiamente seguito per la performance del mercato azionario statunitense. L’obiettivo principale di questa ricerca è sviluppare un quadro di calibrazione congiunta robusto che catturi accuratamente le dinamiche di entrambi gli indici. La necessità di un singolo modello per calibrare entrambi gli indici nasce dal fatto che l’indice VIX è costruito a partire dalle opzioni sull’indice S&P 500, rendendo i due indici inevitabilmente collegati. Il modello che sarà discusso nelle righe seguenti è il modello quintic Ornstein-Uhlenbeck volatility, introdotto in Jaber et al. (2022b). Appartiene alla classe dei modelli di volatilità stocastica, dove la volatilità è rappresentata come un polinomio di quinto grado di un processo di Ornstein-Uhlenbeck, da cui il nome del modello. Sfruttando un’espressione ben nota per l’indice VIX in tempo continuo, è possibile derivare una formula analitica per valutare le opzioni aventi come sottostante l’indice VIX. Inoltre, viene impiegata una tecnica Monte Carlo per simulare l’indice S&P 500. Questo progetto confronta lo schema di Eulero e lo schema Turbocharging, descritto in McCrickerd and Pakkanen (2018), per la simulazione dell’indice S&P 500, concentrandosi su prezzi delle opzioni, volatilità implicite, tempi di calcolo e stabilità. Inoltre, viene condotta un’analisi della stabilità della calibrazione congiunta S&P 500-VIX utilizzando dati di mercato di Bloomberg di marzo e aprile 2024, esaminando l’evoluzione dei parametri del modello. Infine, il progetto semplifica la modellazione della curva di varianza futura, rispetto a quella proposta in Jaber et al. (2022b), utilizzando l’interpolazione costante a tratti.
Quintic Ornstein-Uhlenbeck Volatility Model
Nocchi, Fabio
2023/2024
Abstract
This thesis focuses on the joint calibration of the S&P 500 and the VIX indexes. These are respectively the main equity index worldwide and its volatility index. The VIX index, often referred to as the "fear gauge", measures the market’s expectation of future volatility, while the S&P 500 index is a widely followed benchmark of U.S. equity market performance. The primary aim of this research is to develop a robust joint calibration framework that accurately captures the dynamics of both indexes. The need for a single model to calibrate both indexes arises from the fact that the VIX index is constructed from options on the S&P 500 index, making the two indexes inevitably linked. The model that will be discussed throughout the following lines is the quintic Ornstein-Uhlenbeck volatility model, introduced by Jaber et al. (2022b). It belongs to the class of stochastic volatility models, where the volatility is represented as a fifth-degree polynomial of a Ornstein-Uhlenbeck process, hence the model’s name. By exploiting a well-known expression for the VIX index in continuous time, it is possible to derive an analytical formula to price options having the VIX index as the underlying. Additionally, a Monte Carlo technique is employed to simulate the S&P 500 index for pricing purposes. This work compares the Euler scheme and the Turbocharging scheme, from the paper of McCrickerd and Pakkanen (2018), for simulating S&P 500 index paths, focusing on option prices, implied volatilities, computational times, and stability. It also conducts a stability analysis of S&P 500-VIX joint calibration using Bloomberg market data from March and April 2024, examining the evolution of model parameters. Additionally, the project simplifies the modeling of the forward variance curve, with respect to the one proposed in Jaber et al. (2022b), by using piece-wise constant interpolation.File | Dimensione | Formato | |
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2024_07_Nocchi.pdf
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https://hdl.handle.net/10589/223839