Reinforcement Learning for Hedging
The article introduces a novel application of reinforcement learning for efficiently managing a portfolio of over-the-counter derivatives, independent of any model.
91 sharesSource ↗
Quant LetterNo. 116
October 2025, Week 4
10 items across 1 sections, as sent to readers on 24 October 2025. Paper titles open their ML-Quant page; ↗ goes to the source.
- Items
- 10
- Papers
- 10
- Sections
- 1
- Issue
- No. 116
RePEc
Economics working papers from RePEc's NEP field reports.
10 items
Historical Trending10
HighFrequency Trading Impact
The paper discusses the effects of high-frequency trading on market factors like volatility, transaction costs, and liquidity, indicating varied opinions in the financial sector.
90 sharesSource ↗
International Arbitrage for Stocks
The study suggests a new strategy for high-frequency arbitrage on international cross-listed stocks, exploiting price discrepancies.
28 sharesSource ↗
Nowcasting NZ GDP with ML
The paper reveals that machine learning algorithms are more effective than traditional statistical models in predicting real GDP growth in New Zealand.
175 sharesSource ↗
Predicting Vehicle Wait Times at Borders
The study explores new data sources and machine learning techniques to forecast short-term wait times at a US-Mexico border crossing, emphasizing the difficulties of high data variability.
25 sharesSource ↗
Risk Factor Validation
The research disputes the Fama and French three factor model, stating that size and value mimicking factors should not be seen as systematic risk factors.
30 sharesSource ↗
Cost Estimation with ML
The article introduces a machine learning method for predicting software costs early in a project with high accuracy.
42 sharesSource ↗
Intraday Volatility Prediction
The paper reveals that range-based volatility forecasting and asymmetric GARCH models are most effective for the Indian stock market, particularly the GKYZ volatility estimator.
18 sharesSource ↗
Bank Failure Prediction
The study uses machine learning survival models to predict US bank failures, offering insights to enhance risk management in the banking sector.
17 sharesSource ↗
Brazilian ML Portfolios
The research investigates the use of machine learning to predict stock returns in Brazil, showing that an Equal Risk Contribution approach greatly enhances risk-adjusted returns.
16 sharesSource ↗