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20 OctTue
  1. arXiv q-fin45

    Research on Conditionally Identifiable Latent Representation Methods for Multivariate Time Series with Structural Dynamics

    The study proposes the Identifiable Variational Dynamic Factor Model (iVDFM) for multivariate time series modeling. The model combines variational inference to provide partial identifiability guarantees within a known fuzzy class range. The model's innovation terms are conditioned on observed auxiliary context and mechanism embeddings, follow a conditional exponential family prior, and are trained by maximizing the ELBO to estimate uncertainty in latent trajectories and predictions. This research has been published in the ProbML 2026 conference proceedings, and the code is open source.

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  2. arXiv q-fin53

    A Study Based on a Sample of U.S. Stocks from 1999 to 2024: Disagreement and Compliance Classification Dynamics Across Different Islamic Finance Screening Rules

    This arXiv paper applies 7 sets of Islamic finance screening rules to a sample of 1.34 million monthly observations of U.S. securities from 1999 to 2024, and backtests and compares them on a unified threshold-anchored scale. The results show that the disagreement across the sets of rules reaches 35.9% across all compliant industry observations, and the disagreement in financial ratio screening alone reaches 47.3%. Under AAOIFI's market value denominator rule, changes in market value alone are sufficient to explain 65.6% of non-compliance events, and half of the denominator-driven non-compliances reverse within 3 months.

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  3. arXiv q-fin55

    Amortized Neural Filtering for Calibrating Posteriors in Statistical Arbitrage

    The paper proposes a Neural Filter Estimator (NFE), trained on simulated paths of mean-reverting processes, that outputs the posterior distribution of the implied state for each spread in the cross-section in a single forward pass, incorporating estimation uncertainty into trading decisions. On simulated paths with known ground truth, the method achieves accuracy comparable to other practical estimators, with its advantage lying in correctly characterizing its own uncertainty.

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19 OctMon
  1. Quantocracy31

    Quantocracy's Latest Quant Research Link Roundup as of October 18, 2026

    Quantocracy has compiled the latest quant research-related links as of October 18, 2026, covering topics including trend following, futures continuous contract construction, in-sample to out-of-sample Sharpe ratio decay, the impact of liquidity on stock returns and option pricing, and cryptocurrency cross-sectional trend factors. One study based on 12 commodity futures found that the expected retention ratio of in-sample Sharpe ratios from a 10-year backtest on new data is 30%.

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16 OctFri
15 OctThu
  1. Quantocracy37

    Quantocracy's latest roundup of quantitative research links as of October 14, 2026.

    Quantocracy released its latest roundup of quantitative research links on October 14, 2026, featuring multiple research pieces and content related to the quantitative field. These include an out-of-sample evaluation study of Hidden Markov Model (HMM) market state identification, an analysis of the impact of complexity on strategy performance, and research on cross-sectional momentum ranking methods. The related research covers backtest results across different sample periods and discussions of strategy logic.

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13 OctTue
  1. Quantocracy32

    Quantocracy Latest Quantitative Research Links Roundup (October 12, 2026)

    Quantocracy compiled recent quantitative content on October 12, 2026, covering an introduction to Quant Observer, a quantitative tools directory platform; a historical effectiveness analysis of excess returns from insider buying; a backtest of volatility clustering effects in S&P 500 constituents from 2006 to 2025; a guide to building a multi-asset, multi-timeframe trading pipeline; and AI answers on the replicability of empirical finance research.

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12 OctMon
  1. Alpha Architect68

    LLM Replication Pipeline Examines 1,328 Top Empirical Finance Papers: Reproducible In-Sample but Substantially Decayed Out-of-Sample

    Alpha Architect interprets Dmitriy Muravyev's 2026 working paper, which uses an in-house LLM replication pipeline to reconstruct the core results of 1,328 papers published in the Journal of Finance, Journal of Financial Economics, and Review of Financial Studies between 2000 and 2020, of which 1,005 were eligible for subsequent out-of-sample testing.

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  2. AQR: Research38

    Misconceptions About Tax-Aware Long-Short Strategies: The Misleading Analogy to Direct Indexing (Part 3)

    AQR has released the third part of its research series on tax-aware long-short (TA LS) strategies, clarifying two common misconceptions. As an active investment strategy, TA LS deliberately retains tracking error to express alpha models and capture excess returns and tax deferral benefits, rather than minimizing tracking error like direct indexing. Portfolio construction for TA LS requires balancing expected returns, risk, costs, and taxes, rather than simply realizing capital losses or deferring capital gains.

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8 OctThu
  1. Quantocracy31

    Quantocracy's Latest Quantitative Research Link Roundup as of October 7, 2026

    Quantocracy has compiled the latest quantitative research-related links as of October 7, 2026, covering an interview with Kris Longmore of Robot Wealth, analysis of multi-asset drift effects around the US election, interpretation of market reactions following earnings releases, and a backtest of the "boiling frog" momentum strategy for the S&P 500 index. Readers can visit Quant Mashup to view the latest link content.

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6 OctTue
  1. vn.py：GitHub Releases43

    vn.py 4.5.0 Released

    vn.py version 4.5.0 has been released. This update includes feature adjustments, performance optimizations, and fixes for multiple issues. Key changes include: vnpy_ctabacktester backtest configurations are now saved grouped by strategy name; vnpy.alpha has been refactored for factor and signal performance analysis with a new vwap matching mode; vnpy_polygon has been renamed to vnpy_massive; and several trading interfaces have updated API versions. The update also fixes issues related to UI sorting, cross-contract indicator calculation, market data processing, and connection timeouts.

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  2. Quantocracy24

    Quantocracy's Roundup of Quantitative Research Links for October 5, 2026

    Quantocracy has compiled recent quantitative research-related links as of October 5, 2026, covering 5 quantitative research pieces on different topics. The content includes a study on the century-long history of meme stocks, methods for constructing statistically valid backtests, market reactions following analyst downgrades, a comparison of 200-day moving average and volatility targeting strategies, and an introduction to the Orthogonal Clustering Risk Parity (OCRP) strategy.

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5 OctMon
  1. Quantpedia62

    A century of meme stock research: identifying speculative characteristics using market data, with a weekly portfolio achieving a five-factor plus momentum alpha of 11.5% annualized

    The SSRN paper "A Century of Meme Stocks and the Price of Coordination" proposes training machine learning models using market and company data to identify meme stocks, extending the traceable "memeness" indicator back to 1926.

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4 OctSun
  1. Quantocracy32

    Quantocracy Latest Quantitative Research Link Roundup for October 3, 2026

    Quantocracy compiled recent links related to quantitative research on October 3, 2026, covering five topics: a backtest of Warren Buffett's contrarian investment advice, the performance of a Nasdaq-100 polynomial regression band strategy, the causes of the asset growth anomaly, a test of the U.S. stock turn-of-the-month effect, and a method for calculating transaction costs in macro trading strategies.

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3 OctSat
  1. Quantocracy35

    Quantocracy Latest Quantitative Research Link Roundup as of October 2, 2026

    Quantocracy has compiled the latest links related to quantitative research as of October 2, 2026, covering a range of quantitative research topics. These include 897,000 tests conducted on approximately 150 types of trading patterns, an analysis of the impact of 13 oil price surges on U.S. stocks since 1970, a study of asset performance during periods of rising bond yields from 1963 to 2026, and research on an attention factor based on the WallStreetBets herding effect and BERT sentiment.

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2 OctFri
1 OctThu
  1. Quantocracy31

    Quantocracy Latest Quantitative Research Link Roundup for September 30, 2026

    Quantocracy released its latest roundup of quantitative research links on September 30, 2026, covering areas such as quantitative strategy replication, machine learning cross-sectional factors, quantitative trading podcast analysis, and correlation and volatility research. This includes the launch of the Quantpedia Awards 2027 competition, a replication of the intraday momentum strategy proposed by Gao et al. in 2018, and a systematic summary of the 335th episode of a quantitative trading podcast.

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28 SeptMon
  1. AQR: Research50

    AQR: Common Misconceptions About Tax-Aware Long-Short Investing (Part 2) — The Misleading Analogy to Direct Indexing

    AQR has published the second installment of its research series on tax-aware long-short (TA LS) investing, clarifying two misconceptions arising from analogies to direct indexing. First, the tax benefits of TA LS come primarily from deferred capital gains rather than active loss harvesting: its loss realization pace is similar to ordinary tax-insensitive strategies, and tax-aware optimization is mainly used to avoid selling positions with existing unrealized gains, especially short-term gains.

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21 SeptMon
28 AugFri
  1. AQR: Research38

    AQR Research: Accessing Liquidity Without Liquidating

    AQR research explores whether tax-aware equity strategies can provide sufficient liquidity without full liquidation, while preserving investment objectives. The study finds that substantial capital can be extracted while maintaining tracking error, leverage, and pre-tax information ratio. The tax-efficient extraction capability of long-short strategies is generally superior to that of direct indexing strategies, and improves with higher strategy tracking error and leverage levels.

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1 JulWed
29 JunMon
  1. Rob Carver：This Blog is Systematic59

    Is Rolling Exponentially Weighted Estimation Better Than Full Sample: A Backtest Examination of Portfolio Optimization Parameters

    The authors use random subsample backtests to examine the effectiveness of exponentially weighted window estimates of the Sharpe ratio for portfolio optimization. They compare the out-of-sample Sharpe ratios of EWM spans of 5, 10, 20, and 30 years against full-sample estimates across various in-sample and out-of-sample periods.

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22 JunMon
8 JunMon
  1. Robot Wealth45

    How Independent Traders Should Allocate Resources for a Triangulated Statistical Arbitrage Business

    This article is the sixth part of a series on statistical arbitrage for independent traders. It explains the three core modules of triangulated statistical arbitrage and their resource allocation priorities. High-quality pair screening is the core foundation: using 24 months of historical data, the top 10% of pairs are screened monthly and divided into 5 quality tiers, with the best tier achieving a Sharpe ratio of 1.6 and the worst only 0.42. The author discloses only the general methodology and does not reveal specific implementation details.

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1 JunMon
  1. Robot Wealth54

    Triangulated statistical arbitrage: how to identify genuine pricing deviations rather than mispricing

    This article is the fifth in a statistical arbitrage series for independent traders, focusing on the triangulated statistical arbitrage method. Using the energy sector spread network as an example, the author explains how to cross-validate multiple overlapping spreads to identify genuinely mispriced individual stocks, rather than treating deviations in a single spread as a direct trading signal.

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22 MayFri
  1. Robot Wealth53

    From Pairs to Portfolios, Part 4: A Triangulated Statistical Arbitrage Approach for Independent Traders

    This article introduces a triangulated statistical arbitrage approach. Using 8 spread groups constructed from 6 energy stocks as an example, the z-score signal of each spread is decomposed into opposite votes for the two individual stocks, which are then aggregated into long-short signals at the individual stock level. This allows direct trading of undervalued or overvalued stocks, replacing the traditional pairs-trading model of hedging both legs simultaneously. The approach can improve capital efficiency, reduce transaction costs, and increase signal utilization, while achieving variance control similar to pairs trading through a long-short basket portfolio. The article will further explain how to evaluate the quality of aggregated signals.

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12 MayTue
10 AprFri
  1. Robot Wealth53

    Trend or No Trend? That's the Wrong Question

    The author argues that mean reversion, trend, and momentum are merely labels for price movements rather than trading edges. A true edge requires first identifying the underlying structural cause and then validating it with data. The article uses three types of mean-reversion scenarios as examples: forced liquidation by leveraged funds, scheduled rebalancing of crypto leveraged tokens, and month-end stock-bond rebalancing by wealth management institutions. All three scenarios involve identifiable trading flows that are insensitive to price.

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24 DecWed