This study examines the use of Filtered Historical Simulation (FHS) to estimate tail risk in cryptocurrency markets for the optimization of robustness in this area under model misspecification. An ARMA-GARCH model is employed on the daily returns on Binance Coin and Litecoin in order to compare...

Credit risk is one of the most significant risks for banks, with the probability of default (PD) playing a central role in risk management. Logistic regression models are widely used to estimate PDs based on historical default data and firm characteristics. However, such models rely on...

Understanding the density of possible prices in one-minute intervals provides traders, investors, and financial institutions with the data necessary for making informed decisions, managing risk, optimizing trading strategies, and enhancing the overall efficiency of the cryptocurrency market....