Pricing Embedded Options Using Fast Fourier Transform to Compare Variance Gamma and Black-Scholes-Merton Model Efficiency
Volume 9, Issue 2, 2025, Pages 54-69
https://doi.org/10.61186/ijf.2024.424421.1439
Alireza Barati, Maryam Khalili Araghi
Abstract Embedded options are virtually new instruments identical to options in many aspects except their non-tradable nature. Testing the efficiency of the Variance Gamma and Black-Scholes-Merton model on these instruments would provide a vision of transitioning from the classical model with its deficiency to more intricate models. Considering the complicated nature of the Variance Gamma stochastic process to price options, the Fast Fourier Transform (FFT) method is used in conjunction with the Nelder-Mead Simplex method to calibrate models. This research uses the Fast Fourier Transform (FFT) to price four embedded options with the ticker symbols Hefars912, Heghadir912, Heksho208, and Hetrol911 under the two models. The result approves that the Variance Gamma process is more efficient than the Black-Scholes-Merton model in pricing embedded options. Consequently, the variance gamma process would generate fewer errors in pricing those options that can be used in a practical sense.
Applying black- Scholes model to breakdown beta: growth options and the risk of beta miscalculation
Volume 3, Issue 4, Autumn 2019, Pages 1-22
https://doi.org/10.22034/ijf.2020.213958.1102
Amin Babaei Falah, Maryam Khalili Araghi, Hashem Nikoomaram
Abstract When evaluating companies and investment plans, most analysts use a discount rate that is derived from CAPM models. The beta in these models usually represent risks and opportunities of the relative industry, with almost no attention to the risks that are already included in the beta. This ignorance in risk measurement could ultimately impair shareholders value. What makes things critical is that by adjusting risks and opportunities in beta, the result of investment plans and company valuation could be much different. In this paper we use 1 to 10 years of monthly return data for all industries of Tehran Stock Exchange and Iran Fara Bourse and suggest an adjusted beta for each industry which is stripped of the dazzling effects of the debts and growth opportunities. We separately account for breaking down beta into beta of growth opportunities and beta of existing assets for each industry in various timelines between 1 to 10 years. Our results showed that the beta of growth opportunities is bigger than the beta of assets for almost all industries. The mentioned betas can make a big difference in cost of capital and we suggest using them when evaluating investment plans, development plans, valuation of companies and even start-ups.