ML and Kalman Filter for Pair Trading
The research uses machine learning and Kalman filtering to improve pair trading strategies, leading to better returns.
4 sharesSource ↗
Quant LetterNo. 18
October 2023, Week 1
10 items across 1 sections, as sent to readers on 4 October 2023. Paper titles open their ML-Quant page; ↗ goes to the source.
- Items
- 10
- Papers
- 10
- Sections
- 1
- Issue
- No. 18
SSRN
Working papers in finance and economics from SSRN.
10 items
Quantitative10
CEO Effect Revisited with ML
The study suggests that the influence of CEOs on their companies' performance, or the CEO effect, is not significant, based on machine learning and predictive analytics.
3 shares3 citations todaySource ↗
ML for Designing Bcc High Entropy Alloys
The research discovers eight new alloys for hydrogen storage, one of which can store more hydrogen at room temperature than existing options.
5 sharesSource ↗
Multi-period Static Hedging of Options
The paper explores hedging European options over multiple short maturities, comparing the Black-Scholes and Merton Jump Diffusion models.
2 sharesSource ↗
Dynamic Volatility Regulation of Financial Institutions
The study presents a model that dynamically updates asset risk for financial institutions, revealing different credit risk dynamics for regulated and unregulated firms.
2 sharesSource ↗
Global Evidence on Law Firm Expertise and Venture Capital Investments
Top law firms' involvement in venture capital deals leads to lower failure rates, more investment capital, higher valuations, and a greater chance of successful exits via IPOs or acquisitions.
3 sharesSource ↗
Local-Currency Bond Markets in Emerging Economies and Foreign Investors
When global risk aversion rises, foreign mutual funds increase net sales of Indonesian Rupiah bonds, causing the IDR to depreciate against the US dollar and increasing bond market volatility.
3 sharesSource ↗
Multidimensional Time Series Data: Automated Regime Detection
Automated Regime Detection: The Wasserstein k-means clustering algorithm effectively identifies regimes in synthetic one-dimensional time series data, and its use in multidimensional data is proposed via the sliced Wasserstein k-means method.
2 sharesSource ↗
Tax Volatility and Advance Tax Payment
Using the current year as the estimation base and increasing the frequency of advance corporate income tax payments can decrease tax volatility and reduce outstanding tax liability.
2 shares1 citation todaySource ↗
Univariate vs Multivariate Models for Forecasting Crude Oil Basis Volatility
Simple univariate models are more effective than multivariate models in predicting the volatility of oil futures basis, resulting in higher Sharpe ratios and better forecasting accuracy.
2 sharesSource ↗