Search Results for author: Carmine Ventre

Found 12 papers, 0 papers with code

Bitcoin's Edge: Embedded Sentiment in Blockchain Transactional Data

no code implementations18 Apr 2025 Charalampos Kleitsikas, Nikolaos Korfiatis, Stefanos Leonardos, Carmine Ventre

Using a variety of Machine Learning techniques, we showcase for the first time the predictive power of blockchain-embedded sentiment in forecasting cryptocurrency price movements on the Bitcoin and Ethereum blockchains.

Sentiment Analysis

Scalable Signature-Based Distribution Regression via Reference Sets

no code implementations11 Oct 2024 Andrew Alden, Carmine Ventre, Blanka Horvath

Distribution Regression (DR) on stochastic processes describes the learning task of regression on collections of time series.

regression

A Financial Time Series Denoiser Based on Diffusion Model

no code implementations2 Sep 2024 Zhuohan Wang, Carmine Ventre

Finally, we show that by using classifiers trained on denoised time series, we can recognize the noising state of the market and obtain excess return.

Decision Making Time Series

An Empirical Analysis on Financial Markets: Insights from the Application of Statistical Physics

no code implementations28 Aug 2023 Haochen Li, Yi Cao, Maria Polukarov, Carmine Ventre

In this study, we introduce a physical model inspired by statistical physics for predicting price volatility and expected returns by leveraging Level 3 order book data.

Detecting Financial Market Manipulation with Statistical Physics Tools

no code implementations16 Aug 2023 Haochen Li, Maria Polukarova, Carmine Ventre

We take inspiration from statistical physics to develop a novel conceptual framework for the analysis of financial markets.

Anomaly Detection

A new encoding of implied volatility surfaces for their synthetic generation

no code implementations23 Nov 2022 Zheng Gong, Wojciech Frys, Renzo Tiranti, Carmine Ventre, John O'Hara, Yingbo Bai

In financial terms, an implied volatility surface can be described by its term structure, its skewness and its overall volatility level.

Management

Error in the Euclidean Preference Model

no code implementations17 Aug 2022 Luke Thorburn, Maria Polukarov, Carmine Ventre

Spatial models of preference, in the form of vector embeddings, are learned by many deep learning and multiagent systems, including recommender systems.

model Recommendation Systems

Denoised Labels for Financial Time-Series Data via Self-Supervised Learning

no code implementations19 Dec 2021 Yanqing Ma, Carmine Ventre, Maria Polukarov

Its convenience led to an exponentially increasing amount of financial data, which is however hard to use for the prediction of future prices, due to the low signal-to-noise ratio and the non-stationarity of financial time series.

Denoising Image Classification +3

The Efficient Hedging Frontier with Deep Neural Networks

no code implementations12 Apr 2021 Zheng Gong, Carmine Ventre, John O'Hara

The trade off between risks and returns gives rise to multi-criteria optimisation problems that are well understood in finance, efficient frontiers being the tool to navigate their set of optimal solutions.

Navigate

Cryptocurrency Trading: A Comprehensive Survey

no code implementations25 Mar 2020 Fan Fang, Carmine Ventre, Michail Basios, Leslie Kanthan, Lingbo Li, David Martinez-Regoband, Fan Wu

This paper provides a comprehensive survey of cryptocurrency trading research, by covering 146 research papers on various aspects of cryptocurrency trading (e. g., cryptocurrency trading systems, bubble and extreme conditions, prediction of volatility and return, crypto-assets portfolio construction and crypto-assets, technical trading and others).

Management Survey

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