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5 papers · 1 filter
Sentiment trading with large language models
Kemal Kirtac, Guido Germano
We investigate the efficacy of large language models (LLMs) in sentiment analysis of U.S. financial news and their potential in predicting stock market returns. We analyze a datase…
Pricing methods for -quantile and perpetual early exercise options based on Spitzer identities
Carolyn E. Phelan, Daniele Marazzina, Guido Germano
We present new numerical schemes for pricing perpetual Bermudan and American options as well as -quantile options. This includes a new direct calculation of the optimal exercise…
Hilbert transform, spectral filters and option pricing
Carolyn E. Phelan, Daniele Marazzina, Gianluca Fusai +1
We show how spectral filters can improve the convergence of numerical schemes which use discrete Hilbert transforms based on a sinc function expansion, and thus ultimately on the f…
Anomalous volatility scaling in high frequency financial data
Noemi Nava, T. Di Matteo, Tomaso Aste
Volatility of intra-day stock market indices computed at various time horizons exhibits a scaling behaviour that differs from what would be expected from fractional Brownian motion…
Measures of Causality in Complex Datasets with application to financial data
Anna Zaremba, Tomaso Aste
This article investigates the causality structure of financial time series. We concentrate on three main approaches to measuring causality: linear Granger causality, kernel general…