Multi-stage real option evaluation with double barrier under stochastic volatility and interest rate

2022 ◽  
Author(s):  
Michele Bufalo ◽  
Antonio Di Bari ◽  
Giovanni Villani
Keyword(s):  
Interest Rate ◽  
Stochastic Volatility ◽  
Real Option ◽  
Double Barrier ◽  
Multi Stage

scholarly journals Real Option Valuation with Stochastic Interest Rate and Stochastic Volatility

Matematika ◽  
2019 ◽  
Vol 18 (2) ◽  
Author(s):  
Ramdhan Fazrianto Suwarman
Keyword(s):  
Interest Rate ◽  
Real Options ◽  
Stochastic Volatility ◽  
North Sea ◽  
Real Option ◽  
Oil Field ◽  
Stochastic Interest Rate ◽  
Option Valuation ◽  
Real Option Valuation ◽  
Stochastic Interest

Abstract. Real options are one of the most interesting research topics in Finance since 1977 Stewart C. Myers from MIT Sloan School of Management published his pioneering article on this subject in the Journal of Financial Economics. Real options are techniques for supporting capital budgeting decisions that adapt techniques developed for financial securities options. The purpose of using this real option is to capture the options contained in projects that cannot be captured by the discounted cash flow model which operates as a basic framework for almost all financial analyzes. The process of valuing real options will be complemented by the stochastic interest rate and stochastic volatility to better capture the flexibility and volatility of the existing economic and financial situation. The valuation will use a Monte Carlo simulation with the MATLAB programming language on crude oil data from the North Sea oil field. Data were obtained from the thesis of Charlie Grafström and Leo Lundquist with the title "Real Option Valuation vs. DCF Evaluation – An Application to a North Sea oilfield".Keyword: real options, stochastic interest rate model, stochastic volatility model, simulation

PRICING VARIANCE SWAPS UNDER DOUBLE HESTON STOCHASTIC VOLATILITY MODEL WITH STOCHASTIC INTEREST RATE

2021 ◽  
pp. 1-17
Author(s):  
Huojun Wu ◽  
Zhaoli Jia ◽  
Shuquan Yang ◽  
Ce Liu
Keyword(s):  
Interest Rate ◽  
Closed Form ◽  
Stochastic Volatility ◽  
Stochastic Volatility Model ◽  
Characteristic Functions ◽  
Stochastic Interest Rate ◽  
Modeling Framework ◽  
Variance Swaps ◽  
Volatility Model ◽  
Stochastic Interest

In this paper, we discuss the problem of pricing discretely sampled variance swaps under a hybrid stochastic model. Our modeling framework is a combination with a double Heston stochastic volatility model and a Cox–Ingersoll–Ross stochastic interest rate process. Due to the application of the T-forward measure with the stochastic interest process, we can only obtain an efficient semi-closed form of pricing formula for variance swaps instead of a closed-form solution based on the derivation of characteristic functions. The practicality of this hybrid model is demonstrated by numerical simulations.

scholarly journals Time-Consistent Investment and Reinsurance Strategies for Mean-Variance Insurers under Stochastic Interest Rate and Stochastic Volatility

Mathematics ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 2183
Author(s):  
Jiaqi Zhu ◽  
Shenghong Li
Keyword(s):  
Interest Rate ◽  
Stochastic Volatility ◽  
Financial Market ◽  
Equilibrium Strategy ◽  
Stochastic Interest Rate ◽  
Programming Approach ◽  
Model Parameters ◽  
Stochastic Interest ◽  
The Impact ◽  
Mean Variance

This paper studies the time-consistent optimal investment and reinsurance problem for mean-variance insurers when considering both stochastic interest rate and stochastic volatility in the financial market. The insurers are allowed to transfer insurance risk by proportional reinsurance or acquiring new business, and the jump-diffusion process models the surplus process. The financial market consists of a risk-free asset, a bond, and a stock modelled by Heston’s stochastic volatility model. Interest rate in the market is modelled by the Vasicek model. By using extended dynamic programming approach, we explicitly derive equilibrium reinsurance-investment strategies and value functions. In addition, we provide and prove a verification theorem and then prove the solution we get satisfies it. Moreover, sensitive analysis is given to show the impact of several model parameters on equilibrium strategy and the efficient frontier.

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