Challenges of Calibrating ABMs
Discusses challenges and solutions in constructing agent-based models for complex systems.
4 shares8 citations todaySource ↗
Quant LetterNo. 6
107 items across 11 sections, as sent to readers on 5 July 2023. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
14 items
Discusses challenges and solutions in constructing agent-based models for complex systems.
4 shares8 citations todaySource ↗
Triangle fees decrease with trade size, improving accuracy and revenue for AMMs.
4 shares1 citation todaySource ↗
A new framework is proposed as an alternative to the Heath-Jarrow-Morton model for discount models.
2 shares2 citations todaySource ↗
Robust mean-variance optimization in portfolio selection shows promising results in the US stock market using a Wasserstein ball.
2 sharesSource ↗
Decentralized exchanges can improve liquidity and reduce slippage for small trades through repositioning.
5 shares15 citations todaySource ↗
External factors like macroeconomic reports and stock indices impact the activity patterns of cryptocurrencies like bitcoin and ether.
3 shares14 citations todaySource ↗
Different store formats have varying price rigidity, affecting the interpretation of price cuts and sale prices.
2 shares1 citation todaySource ↗
Agents' accuracy in decision-making can cause instability in certain games, and the stability of best-response dynamics depends on the learning barrier.
2 shares2 citations todaySource ↗
ChatGPT predicts stock market returns using sentiment analysis, outperforming traditional methods.
82 shares403 citations todaySource ↗
PELVE converts VaR to ES and provides insights on distribution models for insurance.
25 shares2 citations todaySource ↗
Neural networks can identify model-free static arbitrage opportunities in financial markets with many traded securities, offering tractability and effectiveness.
7 shares3 citations todaySource ↗
Firm growth rates are correlated through a common factor, but supply chain-linked firms have a stronger correlation, allowing for reconstruction of the supply chain network using Gaussian Markov Models.
16 shares6 citations todaySource ↗
The Orthogonal Chebyshev Sliding Technique reduces computational costs for calculating ES values in FRTB-IMA for equity autocallable portfolios, improving efficiency.
8 shares1 citation todaySource ↗
Bounded regret can be achieved in recommender systems modeled as linear contextual bandits, even without exact knowledge of the linear model, using Synthetic Control Methods.
7 shares2 citations todaySource ↗
Working papers in finance and economics from SSRN.
19 items
Machine learning used to analyze hedge fund strategies and performance, emphasizing accurate fund classification.
5 sharesSource ↗
Companies with high sales backlogs use fewer FX derivatives for hedging, suggesting positive future sales and profitability.
4 sharesSource ↗
Implied volatility measures derived for individual equity options at 1-minute intervals, confirming negative link between stock returns and volatility.
3 sharesSource ↗
Portfolio Entropy outperforms benchmark portfolios in long-term asset allocation using ETFs, based on maximum entropy principle.
6 sharesSource ↗
Constant Leverage strategy improves performance of momentum portfolios by addressing biases, transaction costs, and compensation mechanisms.
3 sharesSource ↗
Stablecoin issuers face risk due to illiquid assets and fixed redemption values, worsened by efficient arbitrage.
240 sharesSource ↗
XPER method breaks down machine learning model performance to identify impactful features.
371 sharesSource ↗
Supplier diversification is linked to major corporate customers, influenced by agency risk, monitoring, and demand.
14 sharesSource ↗
Blockchain-based decentralized governance with a token leads to greater user surplus than centralized governance.
141 sharesSource ↗
Bitcoin and ether derivatives markets are becoming more efficient, especially for longer-dated options.
4 shares1 citation todaySource ↗
A new model analyzes the impact of informed order flows on price impacts and generates fire sales.
14 sharesSource ↗
Portfolio trading benefits bond market liquidity, but may be costly during market downturns.
5 shares4 citations todaySource ↗
Machine learning techniques show consistent predictability in intraday stock returns, with nonlinear models performing better than linear models.
4 shares1 citation todaySource ↗
A tick size change in Korea increased short selling for certain stocks, but had no significant effect on others.
3 sharesSource ↗
CPO is a machine learning method that beats traditional optimization in adapting to market conditions.
1,678 sharesSource ↗
Factor investing benefits from timeseries predictability, with managed market portfolios generating strong alphas.
513 sharesSource ↗
Corporate bond portfolio trading is boosted by inventory hedging, benefiting liquidity and transaction costs.
161 sharesSource ↗
Portfolio transparency enhances investment efficiency but doesn't reduce manipulation by mutual funds.
119 sharesSource ↗
Insurance companies contribute to economic downturns by spreading liquidity shocks, leading to low GDP and high unemployment.
239 sharesSource ↗
Economics working papers from RePEc's NEP field reports.
19 items
A Cointegration Approach: Examines relationship between stock and VIX futures, proposes hedging strategy.
38 sharesSource ↗
Improving Entry and Exit Timing: Technical analysis and sentiment measures can outperform buy and hold strategy.
31 sharesSource ↗
Machine learning algorithms developed for intraday trading of cryptocurrencies.
26 sharesSource ↗
Investigates volatility changes in stock markets during and after COVID-19 pandemic.
22 sharesSource ↗
Stock volatility affects trend-following profits, signal volatility is important.
18 sharesSource ↗
Machine learning used to improve insolvency risk rating for banks in Brazil.
27 sharesSource ↗
Machine learning identifies main factors contributing to bank default in the US.
21 sharesSource ↗
Continual learning explored in quantum machine learning to prevent catastrophic forgetting.
20 sharesSource ↗
Neural network with selective option improves interpretability in credit risk assessment.
19 sharesSource ↗
Study tests sentiment analysis and machine learning to predict exchange rates and commodity prices.
31 sharesSource ↗
Research finds top machine learning algorithm for assessing risk in post-pandemic cryptocurrency investments.
27 sharesSource ↗
Machine learning has limited ability to predict European stock market returns.
25 sharesSource ↗
The article examines current research in quantitative finance and highlights important areas and new topics.
25 sharesSource ↗
The study compares the accuracy of GMDH neural network with traditional methods in predicting the US REIT market, finding GMDH to be highly accurate.
20 sharesSource ↗
Forex traders' biases cause market volatility, study shows.
25 sharesSource ↗
Investor sentiment impacts stock volatility in China.
22 sharesSource ↗
Earnings volatility reduces stock price response to information.
19 sharesSource ↗
Global liquidity boosts housing prices more in developing economies than advanced ones.
17 sharesSource ↗
A study evaluates interpretability techniques for understanding a neural network's use in credit risk management.
2 sharesSource ↗
Papers that shipped their code, from the Papers with Code feed (2023-25).
8 items
Finetuning on instruction data is a good method for implementing chat language models.
1,404 shares
Breaking Linear Presentation of Notebooks: StickyLand is a notebook extension that helps users organize their code in flexible ways.
401 shares
Open-Source Legal Language Model with Knowledge Bases: A self-attention method is suggested to improve large models' problem-solving abilities and handle errors in reference data.
326 shares
ABSA has seven subtasks, but their interactions have not been adequately studied.
206 shares
Anytoany voice conversion transforms speech into a different voice using a few examples.
158 shares
The SAM model by Meta AI Research has impressive generalization and zero-shot capabilities with extensive training data.
82 shares
ReProver is a prover that uses retrieval to select premises from a large math library.
76 shares
This article is the first comprehensive literature review of open vocabulary learning.
64 shares
Repositories the letter featured.
6 items
Presents a framework for machine learning with time series data.
433 shares
Shapash is a user-friendly tool that improves the interpretability and reliability of machine learning models.
2,346 shares
Code for the process of preparing tables for machine learning tasks.
2,346 shares
Insights into the steps involved in preparing tables for machine learning applications are provided in this article.
755 shares
CS Community Papers: Recommendations for computer science papers to read and discuss in the community.
3,030 shares
Industry news: funds, hiring, markets and regulation.
8 items
Machine learning is revolutionizing quantitative trading.
14 shares
Hesitation Hinders Success: The problems in the American quant market are analyzed.
2 shares
AI enhances the performance of a quant firm in experiments.
2 shares
The Beneish MScore Examined: The Beneish M-Score is investigated as a means to identify financial fraud.
2 shares
Empowering the Future of Finance with Cutting-Edge Tech: FinGPT, an advanced technology, is shaping the future of finance.
2 shares
EPS is being questioned as the best measure for investment success: There are doubts about whether earnings per share (EPS) is the most reliable metric for determining investment success.
2 shares
A prominent tech manager in Singapore is leaving the finance industry: A well-known technology manager in Singapore is stepping away from the finance sector.
2 shares
The Financial Times provides news and analysis on global business: The Financial Times is a trusted source for news and analysis on international business matters.
0 shares
Episodes on markets, quant methods and economics.
9 items
Will McBride and Dmitry Pargaminik discuss implied volatility and option pricing.
9 shares
Judd Arnold shares his skeptical investment strategy in the energy market.
8 shares
Sean McGould talks about the hedge fund industry's evolution and the importance of accounting knowledge in investing.
7 shares
Wall Street to Social Media Transitions: Olivia Voznenko discusses her flexible trading approach, gender in the industry, and the impact of social media on trading strategies.
6 shares
What You Need to Know: AI is impacting the stock market, article explains how.
6 shares
Pros & Cons: CEO of TOGGLE AI talks about AI's influence on thematic trading and stock picking.
6 shares
Insights from Ilana Weinstein: Interview with executive search firm founder on market trends and hedge funds.
4 shares
Shattering Overconfidence: Article questions investing assumptions and discusses randomness and data.
4 shares
Exploring Applications: Author explores using Generative AI, like ChatGPT, in investment processes.
4 shares
Posts from quant and economics blogs and newsletters.
5 items
Exploring connections between different currencies in the Forex market.
2 shares
Article discusses how macroeconomic factors affect equity trend following strategies.
4 shares
Guide on implementing and testing profitable cryptocurrency arbitrage strategy.
4 shares
Fed Reserve & Debt Ceiling: Examining the Federal Reserve's role in managing the debt ceiling.
3 shares
Introducing a comprehensive approach to measure climate-related risks on investment portfolios.
2 shares
Talks, lectures and tutorials.
2 items
The MLI program enhances knowledge and careers in machine learning.
1 shares
Posts from quant researchers on X.
9 items
The tweet talks about how statistical arbitrage has evolved with the use of alternative data and shorter holding periods.
5 shares
This tweet reviews academic research on currency risk premia, looking at multihorizon results and the bond-currency relationship.
4 shares
The tweet explores low volatility investing, discussing selection vs allocation effects, pandemic performance, and currency in global low vol portfolios.
3 shares
A paper suggests that machine learning can predict private equity fund performance by analyzing fundraising prospectuses and comparing limited partners to unlimited machines.
2 shares
The Worst Metric: MAPE is not a good metric for forecasting, use other metrics instead.
1 shares
Florin Court's markets have more independent bets than traditional CTA universes.
1 shares
University of Michigan survey shows lower inflation expectations in June.
0 shares
ML predicts sector ETF returns by combining price and economic data.
0 shares
Dimensionality Reduction Technique: Feature clustering is a new technique for reducing dimensions in datasets.
0 shares
Threads from r/quant, r/algotrading and friends.
8 items
85 shares
72 shares
11 shares