Functional Data-Driven Quantile Model Averaging with Application to Cryptocurrencies

Given the high volatility and susceptibility to extreme events in the cryptocurrency market, forecasting tail risk is of paramount importance. Value-at-Risk (VaR), a quantile-based risk measure, is widely used for assessing tail risk and is central to monitoring financial market stability. In data-rich environments, functional data from various domains are employed to forecast conditional quantiles. However, the infinite-dimensional nature of functional data introduces uncertainty. This paper ad...