Price discovery in the cryptocurrency option market: A univariate GARCH approach

Abstract

In this paper, two univariate generalised autoregressive conditional heteroskedasticity (GARCH) option pricing models are applied to Bitcoin and the Cryptocurrency Index (CRIX). The first model is symmetric and the other takes asymmetric effects into account. Furthermore, the accuracy of the GARCH option pricing model applied to Bitcoin is tested. Empirical results indicate that asymmetry is not an important factor to consider when pricing options on Bitcoin or CRIX, this is consistent with findings in the literature. In addition, the GARCH option pricing model provides realistic price discovery within the bid-ask spreads suggested by the market.

Intensification Dimension of Prices Cryptocurrency with Hamiltonian Quantum Mechanics

“…Alfeus & Kannan [8] found the existence of modeling crypto asset prices in the 30 Largest Cryptocurrency Market Cap Index (CCI30) with the Price Lookback Option method and the Normal Inverse Gaussian (NIG) distribution from a Monte-Carlo perspective that crypto asset prices are much lower from the results of consideration of option pricing decisions. Furthermore, it was discovered that price optimization in real-time can change prices with a degree of freedom in making decisions from option prices and is capable of making investor expectations depreciate due to the influence of a decentralized disequilibrium system from the market price of CCs with the risk effect of common currency indices such as fiat USD [9][10][11][12][13].…”