In financial risk management, Value at Risk (VaR) is widely used to estimate potential
portfolio losses. VaR's limitation is its inability to account for the magnitude of losses beyond …

In this paper, we explore the modified Greenwood statistic, which, in contrast to the classical
Greenwood statistic, is properly defined for random samples from any distribution. The …

Motivated by the empirical power law of the distributions of credits (eg, the number of" likes")
of viral posts in social media, we introduce the high-dimensional tail index regression and …

This paper introduces a flexible framework for the estimation of the conditional tail index of
heavy tailed distributions. In this framework, the tail index is computed from an auxiliary …

We develop new tests for predictability, based on the Lagrange Multiplier [LM] principle, in
the context of quantile regression [QR] models which allow for persistent and endogenous …

This thesis focuses on the modification of the classical Black-Scholes equation by
introducing fractional derivatives instead of the usual integer order derivatives. The project …

We develop new tests for predictability, based on the Lagrange Multiplier [LM] principle, in
the context of quantile regression [QR] models which allow for persistent and endogenous …

This paper aims to describe tail risk dynamics in the US equity market and put it in context of
ESG practices. By estimating a firm-specific conditional tail index, the paper looks at the …

머신러닝 트레이딩 시스템을 설계할 때 필수적인 과정 중 하나는 과거 주가 데이터를 사용하여
학습 모형을 구축하는 것이다. 하지만 금융시장이라는 환경의 특성상 대량의 주가 데이터를 …

This paper introduces a flexible framework for the estimation of the conditional tail index of
heavy tailed distributions. In this framework, the tail index is computed from an auxiliary …