Quant LetterNo. 19
78 items across 10 sections, as sent to readers on 4 October 2023. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
18 items
Clustering and deep reinforcement learning for multi-period trading: The study introduces a new trading strategy that merges reinforcement learning and clustering techniques for portfolio management in multi-period trading, showing better results than traditional portfolio management methods.
5 sharesSource ↗
The paper explores the use of Wasserstein k-means clustering on multidimensional time series data for automated regime detection, proving its effectiveness in identifying different market regimes in real financial time series.
5 shares4 citations todaySource ↗
The bibliometric review studies the research on early warning systems in finance, emphasizing the shift towards machine learning methods and the importance of using both macroeconomic and microeconomic data for better predictive accuracy.
4 shares17 citations todaySource ↗
The research expands the hedging of European options to cover multiple short maturities, using a set of shorter-term options to calculate the hedging error, and compares the Black-Scholes and Merton Jump Diffusion models' performance.
8 shares1 citation todaySource ↗
The Average Oracle, a fast covariance filtering method, outperforms complex methods, yielding superior Sharpe ratios in large-scale experiments.
4 shares6 citations todaySource ↗
LSTM Stock Return Prediction: NoxTrader, a tool for portfolio construction and trading execution, uses time-series analysis of historical data to generate profitable stock market outcomes.
4 sharesSource ↗
A new model combining macroeconomic indicators, stock technical indicators, and Baidu search indices significantly improves stock volatility prediction, reducing error from 1.00 to 0.86.
4 shares2 citations todaySource ↗
A new model-free bond portfolio selection method helps financial institutions hedge against interest rate risk, maximizing worst-case equity and outperforming existing methods.
3 shares1 citation todaySource ↗
The Linear Regression method is suggested for handling missing data in the Burundian sovereign bond market, aiding in the development of financial products and trading strategies in Burundi.
3 sharesSource ↗
The paper introduces a new data-driven method using a Transformer-based Multivariate Time Series Classifier to enhance decision making in Venture Capital and Growth Capital investments by predicting the success of potential investment targets.
4 sharesSource ↗
The study investigates the application of Large Language Models in analyzing qualitative interview data, warning about possible biases and recommending the use of simpler supervised models trained on high-quality human annotations to reduce measurement error and bias.
2 shares78 citations todaySource ↗
Insights and Strategies: The article suggests a method to evaluate the financial stability of virtual asset service providers using data from crypto wallets, balance sheets, and regulatory bodies, emphasizing the importance of regular audits for crypto assets.
6 shares8 citations todaySource ↗
The research introduces a hybrid method for predicting the volatility and risk of financial tools by merging GARCH time series models with deep learning neural networks, finding that while this approach improves volatility predictions, it doesn't necessarily enhance Value-at-Risk and Expected Shortfall forecasts.
5 shares8 citations todaySource ↗
The article explores deep learning models for financial forecasting, discussing their structures, uses, pros and cons, and potential future research areas.
86 sharesSource ↗
The article introduces an improved multilevel Monte Carlo method for estimating solutions to a stochastic differential equation, using a numerical smoothing technique to enhance convergence, complexity, and robustness.
37 shares2 citations todaySource ↗
The paper questions the standard approach to achieving constant equilibrium in macroeconomic models, suggesting a new method that allows simultaneous adjustment of prices, policy, and population distribution.
40 shares1 citation todaySource ↗
Online reputation of employers, especially smaller and less established firms, significantly influences their ability to attract employees, according to a study using Glassdoor.com and Dice.com data.
27 shares1 citation todaySource ↗
A proposed reverse stress testing framework using a compound Poisson process allows for the examination of hypothetical scenarios and the comparison of stress effects on process dynamics.
24 shares8 citations todaySource ↗
Working papers in finance and economics from SSRN.
21 items
The research uses machine learning and Kalman filtering to improve pair trading strategies, increasing efficiency and returns.
4 sharesSource ↗
The study suggests that the influence of CEOs on their firms' performance, known as the CEO effect, is not significant, based on machine learning models and predictive analytics.
3 shares3 citations todaySource ↗
The paper expands the method of hedging European options to include options over multiple short maturities, comparing the Black-Scholes and Merton Jump Diffusion models.
2 sharesSource ↗
The Wasserstein k-means clustering algorithm effectively identifies regimes in synthetic one-dimensional time series data, with a proposed extension to multidimensional data.
2 sharesSource ↗
Research shows that mutual funds managed by 'attractive' managers attract more investments from retail investors, despite no evidence of better fund performance.
26 sharesSource ↗
A study warns that increasing interest rates could cause significant losses for U.S. banks, particularly those with low capital and high uninsured leverage, potentially leading to bank runs.
132,106 sharesSource ↗
The use of derivatives in UK pension schemes is questioned due to their potential to exacerbate losses in worst-case scenarios, raising systemic risk concerns.
2 sharesSource ↗
A study on the Chinese stock market finds that premiums for joint lower-tail risk of liquidity and investor sentiment significantly affect future stock returns.
2 sharesSource ↗
Market Risk Backtesting: The article presents LIGHT Benchmark, a tool for comparing market risk models, including a scoring system for evaluating Value at Risk and Expected Shortfall models.
4 shares1 citation todaySource ↗
The research highlights the significance of measuring risk-adjusted returns in investments and trading, providing insights for strategy optimization and understanding risk-return dynamics.
20 shares4 citations todaySource ↗
Large language models like ChatGPT can generate profitable trading signals from news sentiment, but backtesting can yield biased results due to overlapping periods.
5 sharesSource ↗
The study criticizes inconsistent methodologies in corporate bond factors literature, suggesting a robust factor construction and a clean database for corporate bond returns.
20 shares16 citations todaySource ↗
The XGBoost machine learning model is found to be highly accurate and efficient in empirical asset pricing, with improved performance through feature reduction and shorter time observations.
3 sharesSource ↗
A hybrid approach combining GARCH time series models with deep learning neural networks is proposed for forecasting financial volatility and risk, tested on S&P 500, gold, and Bitcoin prices.
2 sharesSource ↗
Hedge fund option usage impacts skewness risk premium in individual stock options, with stocks having more hedge fund holders using the long naked put strategy showing more positive returns.
3 sharesSource ↗
Modern asset pricing models suggest that statistical arbitrageurs create inelastic market demand for assets, a contrast to classical models where they create elastic demand.
233 sharesSource ↗
CARA investors keep a steady trading speed in a market with partially predictable returns and costly trading, optimizing both trading speed and portfolio for a frictionless market.
361 sharesSource ↗
Stock returns are negatively affected by liquidity volatility across international markets, with high liquidity volatility leading to significant liquidity decreases and lower average returns.
2 sharesSource ↗
Four models - HAR, realised GARCH, RECH, and RFSV - each have unique strengths in forecasting realised volatility in emerging markets, with HAR capturing long-term volatility patterns and realised GARCH capturing volatility clustering and persistence.
3 shares13 citations todaySource ↗
Volatility and Correlation in Portfolio Optimization: A proposed model allowing for constant elasticity of volatility and correlation proves significant for pricing and portfolio optimization, offering straightforward solutions for allocations and value functions.
2 sharesSource ↗
A study finds a direct correlation between Chinese mutual funds' political ties and their investment choices, with these influences decreasing after the 2012 anti-corruption campaign, implying such campaigns can improve market fairness.
3 shares7 citations todaySource ↗
Papers that shipped their code, from the Papers with Code feed (2023-25).
4 items
The article presents a system that simultaneously improves distributed execution and gradient checkpointing plans.
34,516 shares
Adaptive Radial Basis Functions for Neural Fields Representation: The article highlights the limitations of fixed spatial positions of neural features on grid nodes in adapting to target signals.
126 shares
Logic Function Regression with Transformers: The article presents Boolformer, a novel Transformer architecture designed for symbolic regression of Boolean functions.
102 shares
Fine-tuning Language Models for Intelligent Legal Services: The article introduces DISCLawLLM, a smart legal system that utilizes large language models to offer diverse legal services.
92 shares
Repositories the letter featured.
8 items
The software compiles a thorough list of resources for SelfSupervised Learning in Time Series.
98 shares
The software offers techniques to replicate strategies from EP Chan's book on algorithmic trading.
72 shares
The software concentrates on calculating the leadlag parameter from nonsynchronous data.
83 shares
The software explores the application of various deep learning models for limit order book.
37 shares
The software shares a curated list of resources on AI for Time Series from leading AI conferences and journals.
655 shares
The software explains how hackers can exploit language models.
806 shares
The software promotes a Discord server for discussing applications of advanced language models.
1,280 shares
The promotes presents OpenMMLab's innovative creation toolbox with user-friendly APIs and diffusion models.
5,790 shares
Industry news: funds, hiring, markets and regulation.
7 items
The DMASwap strategy, allowing Chinese hedge fund managers to circumvent regulatory borrowing limits, is yielding substantial returns in the struggling Chinese stock markets, according to Bloomberg.
3 shares
Bloomberg has launched Bridge AXE, a tool that allows participants to anonymously post and identify trading interests using existing liquidity discovery tools.
3 shares
Salmaan Jaffery anticipates a significant increase in hedge funds at Dubai International Financial Centre.
2 shares
A special report by IPE suggests that AI could dramatically transform the investment management industry.
2 shares
Su Zhu, co-founder of the unsuccessful crypto hedge fund Three Arrows Capital, has been imprisoned in Singapore for failing to cooperate with investigators.
2 shares
Abu Dhabi's private non-oil economy has grown by 12% annually due to hedge funds, reaching a record AED154bn ($41.9bn).
2 shares
Michael Turner, the CEO of Man Group's solutions business, has left the company after 16 years.
1 shares
Episodes on markets, quant methods and economics.
3 items
Jason Halliwell discusses equity perspectives, the effectiveness of systematic macro approaches, and value investing in a Masterworks-sponsored podcast.
6 shares
Dan Ferris shares his views on the current financial situation, monetary policy history, and investment strategies, warning of a potential massive financial bubble.
10 shares
Dr. Matthias Arnsdorf talks about capital valuation adjustments and the significance of communication skills in quantitative finance on the QuantSpeak podcast.
5 shares
Posts from quant and economics blogs and newsletters.
2 items
ETS Asset Management Factory is using AI to improve risk assessment in their Alternative DataDriven Investment strategy.
6 shares
Quantifiedstrategies.com presents the LumberGold Ratio Trading Strategy for stocks and bonds, including backtest performance and rules.
4 shares
Talks, lectures and tutorials.
4 items
ML Augmented Taylor Rule: A new model for predicting the Federal funds rate has been developed, significantly outperforming the traditional Taylor rule model and offering potential applications in asset pricing and investing.
5 shares
Sendhil Mullainathan and Sharad Goel: The ABFR Webinar, discussing AI and big data's role in economics and finance, is set to take place on September 28, 2023.
1 shares
Two Sigma is offering internships to PhD students, giving them practical experience and insight into a career in quantitative research.
4 shares
How and Why: Despite layoffs, companies continue to recruit as they adapt to market changes, cutting costs in some sectors while expanding others.
7 shares
Posts from quant researchers on X.
4 items
Apologies, but the provided texts do not contain enough information to generate a summary for each article.
1 shares
Zhang's research paper determines the value of equity factors by evaluating the long-term reversal spread, finding positive returns only when the spread surpasses the historical median.
0 shares
The latest WizardCoder 34B, built on Code Llama, surpasses GPT4, ChatGPT3.5, and Claude2 in performance on HumanEval, achieving a 73.2% pass rate.
0 shares
The article explores the role of technology in facilitating innovative methods of creation.
0 shares
Threads from r/quant, r/algotrading and friends.
7 items