PRICING LOOKBACK OPTION FOR CRYPTOCURRENCY

• Main Author: Tristan, Auliya
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/74542
• Institution: Institut Teknologi Bandung

The derivatives market is a rapidly growing industry that aligns with global economic growth, including options. In addition to vanilla options, exotic options such as lookback options are becoming increasingly attractive to market participants due to their ability to hedge against extreme price movements of assets, such as cryptocurrency. In this final project, the pricing of lookback options for cryptocurrencies is determined using the Monte Carlo method based on three models: Black-Scholes as the benchmark model, Normal Inverse Gaussian (NIG), and Fractional Brownian Motion (FBM). The NIG and FBM models are chosen because they can capture the characteristics of drastic fluctuations in cryptocurrency prices. The antithetic Monte Carlo method is also used to reduce variance with the aim of improving efficiency and precision in price estimation. The approach taken in this final project involves the CCi30 index as the underlying asset to reduce volatility and uses three price monitoring methods, one of which is the window average method that uses the average asset price within a specific time window during the option's term to determine the price. The simulation results show that in general, the Black-Scholes model produces the highest prices for lookback options, followed by the NIG and FBM models, respectively. This is due to the NIG model's better ability to capture kurtosis and skewness, as well as the lower volatility estimation in the FBM model. Furthermore, the prices obtained through the harmonic average method are always lower than the arithmetic and geometric averages.