Partial-Information Markets & Divergent Beliefs
Shows how a mathematical model explains why prices and trader biases converge as traders get more information, and gives the best way to combine expert opinions to hunt for arbitrage.
5 sharesSource ↗
Quant LetterNo. 118
101 items across 9 sections, as sent to readers on 4 November 2025. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
10 items
Shows how a mathematical model explains why prices and trader biases converge as traders get more information, and gives the best way to combine expert opinions to hunt for arbitrage.
5 sharesSource ↗
Presents a simple, interpretable rule-based correction layer that detects and explains shifts in credit-risk scores, validated on 2008 mortgage data.
4 sharesSource ↗
- Excess Growth - Excess Rate - Growth Excess - Surplus Growth - Overgrowth - Growth Surplus Recommended: Excess Growth (keeps meaning but is more concise).: The paper proves that a central portfolio metric—the excess growth rate—can be exactly described using basic information‑theory ideas and a few natural axioms. In short, it shows that the extra growth a portfolio achieves is essentially an information quantity, so portfolio performance can be understood like information gain.
4 shares1 citation todaySource ↗
Lays out data economics: why data is special, documents AI training-data deals, proposes a hierarchy of data units, and lists key research questions.
22 shares3 citations todaySource ↗
Models a central bank that maximizes a quantile (not expected) utility, linking hawkish/dovish leanings to that quantile and finding the Fed is mostly dovish.
14 sharesSource ↗
Shows a perfectly informed but slow trader has a single optimal waiting time between trades set by execution costs and the price path's roughness (Hurst/fractal), supported by theory and data.
9 sharesSource ↗
Machine learning on incomplete ESSER plans estimates U.S. school districts spent about $2.2 billion on high‑dosage tutoring during COVID.
8 sharesSource ↗
Whether automation raises or lowers inequality depends on how workers’ skills relate to each other and to the technology, and the effect can reverse as the technology improves.
6 shares2 citations todaySource ↗
Liquid Private‑Equity Replication: Introduces PEARL, an AI method that reconstructs private‑equity returns from liquid assets using timing and leverage adjustments to better match quarterly PE benchmarks.
4 sharesSource ↗
Following the same workers over time reveals separate effects of immigration on wages, employment, and occupational upgrading that repeated cross‑section studies miss.
3 shares2 citations todaySource ↗
Economics working papers from RePEc's NEP field reports.
30 items
Used ML and copula models to see how KSE‑30 stocks move with the market, forecast volatility, and build a lower‑volatility portfolio.
10 sharesSource ↗
Built and back‑tested an ARMA‑GARCH automated trading system to protect emerging‑market portfolios during crises and reduce capital flight.
9 sharesSource ↗
Proposed a risk‑parity method using expected shortfall with regime‑switching, fat‑tailed returns to lower turnover and improve crisis performance.
9 sharesSource ↗
Found Sharpe‑ratio minima/maxima trading strategies beat buy‑and‑hold across global indices (1998–2023), supporting adaptive investing.
8 sharesSource ↗
Disagreement about future consumption explains market-wide returns, while disagreement about productivity mainly raises risk premia for small, low-profit firms.
5 sharesSource ↗
Derives closed-form rules for how a target‑benefit pension should invest and set benefits when returns have continuous and sudden (jump) risks.
5 sharesSource ↗
Introduces a rolling DEA with linked decision units and Whale Optimization to find firms and trading strategies that stay efficient over time.
5 sharesSource ↗
Allowing optimal early exercise changes the expected raw and delta‑hedged returns of American puts, altering some option‑anomaly results versus European puts.
4 sharesSource ↗
Defines a “sustainable return” (a withdrawal rate that preserves real capital) and shows that return order and reinvestment matter more than average returns for long-term outcomes.
4 sharesSource ↗
For Dow firms (2019–2023), news sentiment—especially when labeled by GPT‑4—strongly predicts intraday stock volatility.
6 sharesSource ↗
JPlus is a gamified app that helps journalists collect emotionally labeled speech, boosting emotion-recognition models and user motivation.
4 sharesSource ↗
Companies facing tougher product-market competition, especially with high earnings volatility, are more likely to adopt zero‑leverage (no-debt) policies.
4 sharesSource ↗
Proposes a new mixture-based autoregressive model that better captures complex financial time series and performs well during COVID-19.
6 sharesSource ↗
Develops two deep-learning frameworks (expectile and spline-quantile) plus a model-combination method to more accurately estimate Value-at-Risk and Expected Shortfall.
6 sharesSource ↗
Shows housing-price shocks transmit more strongly in the tails; the US is the main transmitter, and US interest rates strongly predict spillovers.
5 sharesSource ↗
Finds long-maturity Treasury futures volatility—especially the 10‑year—improves forecasts of Chinese stock volatility; SPCA and lasso beat HAR benchmarks and help investor returns.
5 sharesSource ↗
SVM vs BERT vs GPT-3.5: Compares SVM, SPECTER, BERT, and GPT-3.5 for classifying abstracts: BERT performs best overall, while GPT-3.5 gives mixed results, especially with little data.
4 sharesSource ↗
Study: Spanish-speaking anti-abortion Twitter accounts are mostly male, use hateful/negative messages, tied to religion/politics, and connect extreme-right voices.
4 sharesSource ↗
Review: Predicting demand for new fashion items is hard (changing tastes, seasonality, social media), but machine learning—especially deep learning and ensemble methods—can improve accuracy.
4 sharesSource ↗
LSTM vs SVM: Comparison: During crises, LSTM (deep learning) predicts oil prices much better for mid-to-long-term horizons, while SVM performs poorly.
4 sharesSource ↗
Machine learning with dynamic nonlinear models and weekly jobless claims predicts daily VIX (market volatility) more accurately, helping forecasts and trading.
12 sharesSource ↗
DL vs Traditional: For ten large Eurozone banks, traditional ML (XGBoost, logistic regression) outperformed LSTM/BiLSTM for daily stock direction—likely due to too little data for deep learning.
7 sharesSource ↗
The WNSS didn’t fit EU online gig workers; a simpler 12-item scale with three factors (survival, social contribution, competence) describes their needs better.
2 sharesSource ↗
AI methods (predictive analytics, reinforcement learning, anomaly detection) can automate and improve cloud resource management for more efficient DevOps.
2 sharesSource ↗
Using 2019 Eurobarometer data, the paper profiles young informal workers in the EU27—their share, activities, sectors, and reasons—providing a pre-pandemic baseline.
2 sharesSource ↗
AIpowered e‑government can boost citizen participation but needs tech access, digital skills, trust, and good laws.
2 sharesSource ↗
Online dark patterns trick small investors; the paper calls for behavioral-science and AI-backed rules to stop them.
1 sharesSource ↗
Bank performance depends on many factors, and COVID-19, digitalization, AI, and FinTechs are new major challenges.
1 sharesSource ↗
Companies with strong AI infrastructure perform better, helped by a data-driven culture that also supports sustainability.
1 sharesSource ↗
Social-media ML shows clear, coordinated climate messaging across topics and policy levels is essential to reach net‑zero.
1 sharesSource ↗
The general machine-learning papers the letter carried in 2023-25.
7 items
STRING — a compact, translation-invariant position encoding that generalizes rotary encodings to any number of dimensions to boost vision and robotics models.
23 shares20 citations todaySource ↗
RAC turns prediction sets into decision rules that provably maximize utility while keeping risk below a user-specified threshold.
23 shares46 citations todaySource ↗
Panoptic Segmentation & Grounded Captions: COCONut-PanCap — a COCO-based dataset adding panoptic masks and dense region-level captions to improve vision–language understanding and generation.
15 shares14 citations todaySource ↗
Prostate DCE MRI GAN: AAD-DCE: an attention-based GAN that uses multiple MRI inputs to synthesize early and late DCE-MRI, reducing toxic contrast-agent use and outperforming prior methods.
6 shares2 citations todaySource ↗
Open-Vocabulary 3D Segmentation: Mosaic3D-5.6M: an automated pipeline and 3D mask–text dataset used to train Mosaic3D, achieving state-of-the-art open-vocabulary 3D semantic and instance segmentation.
6 shares24 citations todaySource ↗
OJN-Pass-EPV: a new benchmark and U-Net EPV model (predicting ball height and pass risk/reward) that correctly identifies the higher-value game state about 78% of the time.
5 shares2 citations todaySource ↗
Generative Model for Crystal Discovery: OMatG: a generative framework using stochastic interpolants and symmetry-aware (equivariant) crystal representations to design stable inorganic crystals, setting a new state of the art.
3 shares30 citations todaySource ↗
Papers that shipped their code, from the Papers with Code feed (2023-25).
4 items
Hybrid Linear Attention: Kimi Linear: a new hybrid linear‑attention model that beats full attention while using far less memory, decoding much faster, and with code and checkpoints open‑sourced.
500 shares
Switching RL fine‑tuning from BF16 to FP16: fixes numerical mismatches between training and inference, making training more stable and faster.
88 shares
Long‑Horizon Agent Benchmark: Toolathlon — a benchmark across 32 apps and 604 tools that tests agents on long, realistic workflows and shows current models often fail to complete them.
33 shares
CALM — a method that compresses multiple tokens into one continuous vector and predicts those vectors instead of tokens, cutting generation steps and making generation much faster.
19 shares
Repositories the letter featured.
10 items
Curated study materials and tools to help people prepare for quant and software-engineering jobs at trading firms, HFTs, and hedge funds.
1,333 shares
A ranked list of the best machine-learning libraries available in Rust, comparing their strengths.
437 shares
NOFX proposes a next-generation, AI-powered trading operating system to automate and optimize trading workflows.
6,031 shares
An AI paper-trading project (inspired by nof1 Alpha Arena) that uses cctx to fetch market quotes for simulated trading.
346 shares
NeurIPS25 demo DeepFund Pilot showcasing deep-learning tools to help evaluate and manage fund investments.
208 shares
TOON — a compact JSON-like prompt format that roughly halves token use and includes spec, benchmarks, and reference code.
8,024 shares
Guide — explains how online assessments and interviews work and how to prepare for them.
2,228 shares
Cmux — runs multiple coding-agent CLIs (Claude, Codex, Gemini, etc.) in parallel so you can handle many tasks at once.
398 shares
Industry news: funds, hiring, markets and regulation.
13 items
Winton, a UK quantitative firm, entered the US mutual fund market by becoming adviser to the Altegris Futures Evolution Strategy Fund.
5 shares
Bain Capital bought a minority stake in Montreal’s Innocap to tap growing institutional demand for separately managed accounts.
3 shares
Hedge funds sharply reduced short bets on Brent crude after US sanctions on Russia’s top oil companies triggered a large, record unwind.
3 shares
Millennium Management is raising $5 billion to start a new private‑markets fund, moving beyond its usual liquid strategies.
2 shares
People and companies are returning to banks, but they’re using them in new, different ways than before.
2 shares
Ananym Capital urges LKQ to sell its European unit to raise cash for big share buybacks.
1 shares
Goldman says surprise strong earnings at five big tech firms forced hedge funds to buy back shares and cover shorts.
1 shares
UBS is proceeding with the sale of its O’Connor hedge fund unit to US brokerage Cantor Fitzgerald.
1 shares
Macquarie’s Melbourne Cup predictions narrowly picked the winner — it was right by a nose.
0 shares
AI Cuts: Citi published a compendium of AI use cases — a short guide to how AI can be applied in finance.
0 shares
Episodes on markets, quant methods and economics.
10 items
Kathryn Kaminski: Managed futures had a big recent drawdown, but they still diversify portfolios and patient investors may be rewarded over time.
7 shares
Market Chameleon guests: A credit put spread is shown as a way to limit downside risk, manage volatility, and earn steady income.
5 shares
Tim Lintern (J.P. Morgan): The 30th Long‑Term Capital Market Assumptions give long‑run forecasts that help shape strategic asset allocation.
5 shares
Researchers: VortexNet, a neural network inspired by whirlpool fluid dynamics, aims to fix vanishing gradients and better handle long‑range dependencies.
4 shares
Ipek Ozil & Khagendra Gupta: Recent and upcoming central bank actions are changing interest‑rate derivative pricing and market behavior.
4 shares
Lara Edmonstone‑West: DB pension schemes should prioritize buy‑ins or buyouts to guarantee members’ pensions instead of trying to extract surpluses.
3 shares
JPMorgan strategists: A review of recent market moves and what they mean for risks and opportunities in emerging‑market fixed‑income.
3 shares
Analysts on China LNG: China’s LNG demand will peak around 2032, and growing infrastructure could let it become a major global LNG trader.
3 shares
Alex Temiz: Practical lessons on disciplined short selling, trading psychology, and the habits needed to survive as a trader.
3 shares
Tony Yoseloff: How to invest across different market cycles and where to find opportunity in alternative assets.
3 shares
Posts from quant and economics blogs and newsletters.
10 items
Quant finance used to be concentrated in big global centers like New York and London.
7 shares
Modern risk management grew out of work by a small group of New York quants between 1987 and 1993.
4 shares
A prediction market shows the NYC mayoral race as basically decided, and Bill Ackman objects to that signal.
3 shares
Critics warn Polymarket’s high odds for Zohran Mamdani can be pushed by small bets and might mislead.
3 shares
Observers question why anyone would buy Mamdani at 95% on Polymarket, suggesting the price could be manipulated.
3 shares
Uses a neural net to tune a trading indicator on 10‑minute EUR/USD and shows preliminary results.
2 shares
Follow‑up with additional neural‑net indicator tests and a discussion of what those results mean for trading.
2 shares
Outlines three long‑term trading strategies designed to reduce drawdowns and capture more bull‑market gains.
2 shares
NYT piece on how technology and regulations like Dodd‑Frank have transformed trading on Wall Street.
2 shares
Threads from r/quant, r/algotrading and friends.
7 items
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