Separating Ads from E-commerce
Ecommerce platforms merging advertising and marketplace roles can disadvantage consumers by lacking effective targeting, ultimately harming societal welfare.
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Quant LetterNo. 127
52 items across 8 sections, as sent to readers on 12 February 2026. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
2 items
Ecommerce platforms merging advertising and marketplace roles can disadvantage consumers by lacking effective targeting, ultimately harming societal welfare.
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Including discounted sales of soon-to-expire perishables in demand forecasts leads to underestimating demand, highlighting the need for better forecasting to reduce inventory waste in grocery stores.
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Economics working papers from RePEc's NEP field reports.
10 items
The study finds that machine learning can better predict VIX by highlighting economic indicators like jobless claims as key factors in market volatility forecasts.
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This research examines how individual stocks shape trends on the Pakistan Stock Exchange and suggests a machine learning-based optimal portfolio allocation strategy.
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The study introduces an Adaptive Trading System designed for emerging market portfolios to mitigate losses during downturns and curb capital outflows in crises.
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This paper presents a new method for optimizing risk parity portfolios, aiming to lower sensitivity to market volatility and boost risk-adjusted returns in challenging times.
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In the European banking sector, traditional machine learning models outperform deep learning in predicting stock price movements, revealing potential issues with advanced models' data requirements.
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Sharpe Ratio trading strategies outperform buy-and-hold methods, aligning with the Adaptive Market Hypothesis due to performance fluctuations across global markets.
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Accurate assessment of news sentiment affects stock return volatility, with GPT-4 outperforming RavenPack in analyzing the Dow Jones index.
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A novel machine learning method shows superior accuracy and flexibility in financial modeling of complex time series data during the COVID-19 pandemic.
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Two new deep learning frameworks enhance the estimation of Value at Risk and Expected Shortfall, improving risk management for financial institutions.
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Macroeconomic expectation disagreements significantly affect financial risk premia, especially in small-cap stocks and low profitability when consumption and productivity forecasts diverge.
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Papers that shipped their code, from the Papers with Code feed (2023-25).
10 items
Sparse Agentic Intelligence: Step 3.5 Flash is an AI model designed for advanced intelligence using efficient parameters and attention mechanisms.
1,238 shares
Autonomous Discovery System: InternAgent1.5 is a system that integrates computational modeling with experimental research for autonomous scientific discovery.
866 shares
GUI Agents for Visual States: Code2World enables autonomous GUI agents to predict visual outcomes by generating renderable code, improving navigation.
133 shares
Evolving RL Agents: SkillRL enhances large language models by enabling skill discovery and policy evolution while conserving computational resources.
92 shares
Unified Audio Model: Researchers developed ReasoningCodec for improved audio processing and UniAudio 2.0, a strong model for various audio tasks using a large dataset.
60 shares
Improving Agents with Weak Checkpoints: WMSS boosts large language models by using weak checkpoints to close learning gaps for better results.
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Advancing RL in Synthetic Environments: Large language models in synthetic settings exceed traditional models in adapting to new situations.
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Model Compression via Knapsack Optimization: ROCKET introduces an efficient model compression technique that treats the process like solving a knapsack problem.
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Enhanced Block-Sparse Attention for LLMs: Prism enhances long-context LLM performance by optimizing which blocks to select in blocksparse attention.
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Benchmarking Language Agents in Extreme Contexts: LOCAbench is a benchmark designed to evaluate language agents handling long-context tasks.
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Repositories the letter featured.
7 items
A new framework gathers and analyzes data from prediction markets, featuring extensive datasets from Polymarket and Kalshi.
693 shares
The TradingView Screener API offers comprehensive access to various financial data including stocks, crypto, forex, bonds, and futures.
718 shares
AKQuant is an open-source research and trading framework built with Rust and Python for high performance.
76 shares
An AI-driven terminal, akin to Bloomberg, uses Redis and AlphaVantage data for efficient simulations while minimizing API calls.
688 shares
A curated resource collection for stock traders, including essential tools, websites, and books.
436 shares
A new AI assistant prioritizes user privacy by working silently without drawing attention during meetings and conversations.
389 shares
A smart LLM router reduces costs by overseeing different AI models and enabling micropayments for efficient use.
576 shares
Episodes on markets, quant methods and economics.
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Rob Carver emphasizes the importance of risk management and disciplined investment strategies in navigating current commodity market volatility.
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Ian Harnett examines the transition from disinflation to persistent inflation and its potential impact on the economy and the dollar before the midterms.
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Dan Rasmussen and D.A. Wallach analyze the rise in biotech, China's market trends, and how technology influences productivity and valuations globally.
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A repeat discussion with Dan Rasmussen and D.A. Wallach covers the biotech boom, the growth of China's market, and valuation methods, including U.S. and Japanese stock insights.
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David Dziekanski discusses how return stacking can turn leverage into a sustainable investment strategy in an interview by Quantify Funds.
6 shares
Ted Oakley talks about managing investment risks during inflation by separating base and investment capital in unpredictable markets.
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Vanguard's Economic Insights: Joe Davis highlights Vanguard's rich history, its strong research team, and how AI may influence investment strategies and market trends.
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Gold vs. Silver: Natasha Kaneva and Greg Shearer examine the recent fluctuations in gold and silver markets, noting their unique functions in investment portfolios.
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Navigating Energy Risks: John Love discusses how geopolitical factors and supply changes are influencing commodities, urging a focus on specific exposures instead of broad market indexes.
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Sean McGould explores a multi-strategy investment approach, addressing the effects of macroeconomic trends, including AI and market volatility.
4 shares
Posts from quant and economics blogs and newsletters.
10 items
An options-selling strategy suffered major losses from volatility linked to the Indian budget and a US-India trade deal, erasing months of gains.
4 shares
After ten months, a delta-hedged short strangle system ended up at breakeven due to small profits being outweighed by a large loss.
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Brokers and exchanges thrived during market volatility, highlighting the risks of depending on options-selling for steady income.
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The Thanksgiving Turkey chart demonstrates black swan events in trading, showing how unpredictable market outcomes can be.
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The article discusses the reality of options trading, where strategies can backfire and lead to significant losses in volatile markets.
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A delta-hedged short strangle strategy made profits for six months before losing significantly due to market volatility.
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Small, steady gains were erased by a major loss, leaving the strategy just breaking even after ten months.
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The article emphasizes the risks of selling options for income, noting that unexpected events can greatly affect results.
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A profit and loss chart shows a trend of minor losses followed by a large setback in trading performance.
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Overall, brokers, exchanges, and the government seem to gain more from these trading strategies than the individual traders.
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Posts from quant researchers on X.
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The article explains that as AI technology advances, the emphasis in software development is moving from quick coding to creating customized software designs tailored to individual needs.
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Threads from r/quant, r/algotrading and friends.
2 items
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