Enhancing OHLC Data with Timing Features: A Machine Learning Evaluation
Fuente:
arXiv
Enregistré dans:
| Auteur principal: | Tepelyan, Ruslan |
|---|---|
| Format: | Preprint |
| Publié: |
2025
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
Transformers Beyond Order: A Chaos-Markov-Gaussian Framework for Short-Term Sentiment Forecasting of Any Financial OHLC timeseries Data
par: Pathan, Arif
Publié: (2025)
par: Pathan, Arif
Publié: (2025)
Efficient Multivariate Kelly Optimization Reveals Sigmoidal Scaling Laws
par: Tepelyan, Ruslan, et autres
Publié: (2026)
par: Tepelyan, Ruslan, et autres
Publié: (2026)
Machine Learning Methods for Pricing Financial Derivatives
par: Fan, Lei, et autres
Publié: (2024)
par: Fan, Lei, et autres
Publié: (2024)
Forecasting Intraday Volume in Equity Markets with Machine Learning
par: Cucuringu, Mihai, et autres
Publié: (2025)
par: Cucuringu, Mihai, et autres
Publié: (2025)
Exploiting Distributional Value Functions for Financial Market Valuation, Enhanced Feature Creation and Improvement of Trading Algorithms
par: Grab, Colin D.
Publié: (2024)
par: Grab, Colin D.
Publié: (2024)
Causal Discovery in Financial Markets: A Framework for Nonstationary Time-Series Data
par: Sadeghi, Agathe, et autres
Publié: (2023)
par: Sadeghi, Agathe, et autres
Publié: (2023)
From Factor Models to Deep Learning: Machine Learning in Reshaping Empirical Asset Pricing
par: Ye, Junyi, et autres
Publié: (2024)
par: Ye, Junyi, et autres
Publié: (2024)
HARd to Beat: The Overlooked Impact of Rolling Windows in the Era of Machine Learning
par: Audrino, Francesco, et autres
Publié: (2024)
par: Audrino, Francesco, et autres
Publié: (2024)
Ultimate Forward Rate Prediction and its Application to Bond Yield Forecasting: A Machine Learning Perspective
par: Du, Jiawei, et autres
Publié: (2025)
par: Du, Jiawei, et autres
Publié: (2025)
Enhancing Cryptocurrency Sentiment Analysis with Multimodal Features
par: Liu, Chenghao, et autres
Publié: (2025)
par: Liu, Chenghao, et autres
Publié: (2025)
Time-Series K-means in Causal Inference and Mechanism Clustering for Financial Data
par: Xiao, Minheng
Publié: (2022)
par: Xiao, Minheng
Publié: (2022)
Higher Order Transformers: Enhancing Stock Movement Prediction On Multimodal Time-Series Data
par: Omranpour, Soroush, et autres
Publié: (2024)
par: Omranpour, Soroush, et autres
Publié: (2024)
Interpretable Machine Learning Models for Predicting the Next Targets of Activist Funds
par: Kim, Minwu, et autres
Publié: (2024)
par: Kim, Minwu, et autres
Publié: (2024)
Multi-Agent Stock Prediction Systems: Machine Learning Models, Simulations, and Real-Time Trading Strategies
par: Dave, Daksh, et autres
Publié: (2025)
par: Dave, Daksh, et autres
Publié: (2025)
Time-aware Metapath Feature Augmentation for Ponzi Detection in Ethereum
par: Jin, Chengxiang, et autres
Publié: (2022)
par: Jin, Chengxiang, et autres
Publié: (2022)
Financial Time-Series Forecasting: Towards Synergizing Performance And Interpretability Within a Hybrid Machine Learning Approach
par: Liu, Shun, et autres
Publié: (2023)
par: Liu, Shun, et autres
Publié: (2023)
Time-Varying Factor-Augmented Models for Volatility Forecasting
par: Zhang, Duo, et autres
Publié: (2025)
par: Zhang, Duo, et autres
Publié: (2025)
The Theory of Intrinsic Time: A Primer
par: Glattfelder, James B., et autres
Publié: (2024)
par: Glattfelder, James B., et autres
Publié: (2024)
Enhancing Black-Scholes Delta Hedging via Deep Learning
par: Qiao, Chunhui, et autres
Publié: (2024)
par: Qiao, Chunhui, et autres
Publié: (2024)
Evaluating Transfer Learning Methods on Real-World Data Streams: A Case Study in Financial Fraud Detection
par: Pereira, Ricardo Ribeiro, et autres
Publié: (2025)
par: Pereira, Ricardo Ribeiro, et autres
Publié: (2025)
Distributions of Historic Market Data -- Relaxation and Correlations
par: Moghaddam, M. Dashti, et autres
Publié: (2019)
par: Moghaddam, M. Dashti, et autres
Publié: (2019)
Investigating Conditional Restricted Boltzmann Machines in Regime Detection
par: Rentala, Siddhartha Srinivas
Publié: (2025)
par: Rentala, Siddhartha Srinivas
Publié: (2025)
FNSPID: A Comprehensive Financial News Dataset in Time Series
par: Dong, Zihan, et autres
Publié: (2024)
par: Dong, Zihan, et autres
Publié: (2024)
Model-Free Deep Hedging with Transaction Costs and Light Data Requirements
par: Brugière, Pierre, et autres
Publié: (2025)
par: Brugière, Pierre, et autres
Publié: (2025)
Forecasting Volatility with Machine Learning and Rough Volatility: Example from the Crypto-Winter
par: Tang, Siu Hin, et autres
Publié: (2023)
par: Tang, Siu Hin, et autres
Publié: (2023)
Forecasting the Evolving Composition of Inbound Tourism Demand: A Bayesian Compositional Time Series Approach Using Platform Booking Data
par: Katz, Harrison
Publié: (2026)
par: Katz, Harrison
Publié: (2026)
The Shape of Markets: Machine learning modeling and Prediction Using 2-Manifold Geometries
par: Papaioannou, Panagiotis G., et autres
Publié: (2025)
par: Papaioannou, Panagiotis G., et autres
Publié: (2025)
Algorithmic Monitoring: Measuring Market Stress with Machine Learning
par: Schmitt, Marc
Publié: (2026)
par: Schmitt, Marc
Publié: (2026)
Enhancing Regime Shift Detection Using Unstructured Data: A Study on the Treasury Market
par: Yi, Mingxuan, et autres
Publié: (2026)
par: Yi, Mingxuan, et autres
Publié: (2026)
Trends and Reversion in Financial Markets on Time Scales from Minutes to Decades
par: Safari, Sara A., et autres
Publié: (2025)
par: Safari, Sara A., et autres
Publié: (2025)
Modeling of Measurement Error in Financial Returns Data
par: Jasra, Ajay, et autres
Publié: (2024)
par: Jasra, Ajay, et autres
Publié: (2024)
Behavioral Machine Learning? Regularization and Forecast Bias
par: Frank, Murray Z., et autres
Publié: (2023)
par: Frank, Murray Z., et autres
Publié: (2023)
Bitcoin Forecasting with Classical Time Series Models on Prices and Volatility
par: Kareem, Anmar, et autres
Publié: (2025)
par: Kareem, Anmar, et autres
Publié: (2025)
PolyModel for Hedge Funds' Portfolio Construction Using Machine Learning
par: Zhao, Siqiao, et autres
Publié: (2024)
par: Zhao, Siqiao, et autres
Publié: (2024)
A Decision Support System for Stock Selection and Asset Allocation Based on Fundamental Data Analysis
par: Abrishami, Ali, et autres
Publié: (2024)
par: Abrishami, Ali, et autres
Publié: (2024)
PriceSeer: Evaluating Large Language Models in Real-Time Stock Prediction
par: Liang, Bohan, et autres
Publié: (2025)
par: Liang, Bohan, et autres
Publié: (2025)
A Deep Learning Approach for Trading Factor Residuals
par: Long, Wo, et autres
Publié: (2024)
par: Long, Wo, et autres
Publié: (2024)
Assets Forecasting with Feature Engineering and Transformation Methods for LightGBM
par: Bisdoulis, Konstantinos-Leonidas
Publié: (2024)
par: Bisdoulis, Konstantinos-Leonidas
Publié: (2024)
AI-Enhanced Factor Analysis for Predicting S&P 500 Stock Dynamics
par: Gu, Jiajun, et autres
Publié: (2024)
par: Gu, Jiajun, et autres
Publié: (2024)
Evaluating the resilience of ESG investments in European Markets during turmoil periods
par: Iannone, Barbara, et autres
Publié: (2025)
par: Iannone, Barbara, et autres
Publié: (2025)
Documents similaires
-
Transformers Beyond Order: A Chaos-Markov-Gaussian Framework for Short-Term Sentiment Forecasting of Any Financial OHLC timeseries Data
par: Pathan, Arif
Publié: (2025) -
Efficient Multivariate Kelly Optimization Reveals Sigmoidal Scaling Laws
par: Tepelyan, Ruslan, et autres
Publié: (2026) -
Machine Learning Methods for Pricing Financial Derivatives
par: Fan, Lei, et autres
Publié: (2024) -
Forecasting Intraday Volume in Equity Markets with Machine Learning
par: Cucuringu, Mihai, et autres
Publié: (2025) -
Exploiting Distributional Value Functions for Financial Market Valuation, Enhanced Feature Creation and Improvement of Trading Algorithms
par: Grab, Colin D.
Publié: (2024)