6 papers
Identifying and Quantifying Financial Bubbles with the Hyped Log-Periodic Power Law Model
Zheng Cao, Xingran Shao, Yuheng Yan +1
We propose a novel model, the Hyped Log-Periodic Power Law Model (HLPPL), to the problem of quantifying and detecting financial bubbles, an ever-fascinating one for academics and p…
Chain-of-Alpha: Unleashing the Power of Large Language Models for Alpha Mining in Quantitative Trading
Lang Cao
Alpha factor mining is a fundamental task in quantitative trading, aimed at discovering interpretable signals that can predict asset returns beyond systematic market risk. While tr…
The Hype Index: an NLP-driven Measure of Market News Attention
Zheng Cao, Wanchaloem Wunkaew, Helyette Geman
This paper introduces the Hype Index as a novel metric to quantify media attention toward large-cap equities, leveraging advances in Natural Language Processing (NLP) for extractin…
A Hype-Adjusted Probability Measure for NLP Stock Return Forecasting
Zheng Cao, Helyette Geman
This article introduces a Hype-Adjusted Probability Measure in the context of a new Natural Language Processing (NLP) approach for stock return and volatility forecasting. A novel…
Theoretical and Empirical Validation of Heston Model
Zheng Cao, Xinhao Lin
This study focuses on the application of the Heston model to option pricing, employing both theoretical derivations and empirical validations. The Heston model, known for its abili…
Stochastic Calculus for Option Pricing with Convex Duality, Logistic Model, and Numerical Examination
Zheng Cao
This thesis explores the historical progression and theoretical constructs of financial mathematics, with an in-depth exploration of Stochastic Calculus as showcased in the Binomia…