9 citations · 9 across the 4 of their papers we have counts for
4 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…
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…
A Sentiment Analysis Approach to the Prediction of Market Volatility
Justina Deveikyte, Helyette Geman, Carlo Piccari +1
Prediction and quantification of future volatility and returns play an important role in financial modelling, both in portfolio optimization and risk management. Natural language p…