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20 OctTue
  1. arXiv q-fin38

    How to Distinguish Liquidity-Constrained Default from Strategic Default Using Deep Learning

    Researchers used proprietary panel data of commercial mortgages from 1998 to 2021 and adopted deep neural networks (DNN) to distinguish liquidity-constrained default from strategic default. The study found that, under delinquency conditions, property net operating income (NOI) has a more significant impact on default rates than loan-to-value ratio (LTV), and the threshold for dividing the two types of defaults remained stable during the 2008 financial crisis and the 2020-2021 COVID-19 commercial real estate shock.

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  3. arXiv q-fin53

    Research on Inferring Implied Risk-Neutral Density from Irregular Option Quotes

    Published at ICAIF 2026, this study finds that accurate option prices do not necessarily mean accurate recovery of the underlying risk-neutral density. By comparing synthetic simulation benchmarks with out-of-sample NIFTY option benchmarks, the research reveals that the two-component lognormal mixture model demonstrates overall pricing performance on synthetic benchmarks.

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  4. arXiv q-fin34

    Certifiable Neural Operators for Simultaneously Solving Infinitely Many Convex Programs: Logarithmic Rank and Linear Complexity

    This arXiv paper proposes proximal equilibrium operators (PEOs), constructed via finite-dimensional deep equilibrium layers, that can solve a family of convex optimization problems on separable Hilbert spaces. The paper proves that when input loss functions lie in a suitable infinite-dimensional set, PEOs can uniformly approximate corresponding solutions to arbitrary precision, with rank and width growing only logarithmically with the inverse of approximation error, and depth growing linearly. The related theory and trainability have been validated across three application domains: nonlinear PDEs, stochastic optimal control, and financial portfolio optimization and hedging.

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19 OctMon
  1. Quantpedia64

    Study Finds Classic Bitcoin Price Cycle Indicators Gradually Losing Effectiveness, While Halving Clock Remains Stable

    Quantpedia analyzes a paper by Josh Molnar published on SSRN, noting that classic Bitcoin cycle signals such as MVRV, Mayer Multiple, and Pi Cycle Top are gradually losing effectiveness as price volatility narrows. The three mature cycle peaks occurred 525, 546, and 534 days after their respective halvings.

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  2. arXiv q-fin23

    Board Gender Diversity and Emissions Performance: Findings from Panel Regression, Machine Learning, and Explainable AI

    A study of European firms from 2016 to 2022, combining panel regression, machine learning, and explainable AI methods, finds a nonlinear relationship between board gender diversity and emissions performance: emissions performance begins to improve significantly when female director representation reaches a minimum threshold of approximately 22%, and further increases in female representation beyond an optimal level of approximately 35% do not yield additional emissions performance gains.

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  3. arXiv q-fin33

    Power-Law Relationship Between Skew and Curvature in Stochastic Volatility Models with Infinite Variation Lévy Jumps

    This paper focuses on the impact of hybrid dynamics (rough volatility and infinite variation Lévy processes) on the implied volatility skew and curvature of at-the-money options. By analyzing the leading terms of their short-time expansions, the origin mechanism of the power-law behavior of skew and curvature can be determined from the hybrid dynamics model. The paper confirms that hybrid models also produce power-law relationships, and the relevant conclusions are crucial for model design and calibration. Numerical evidence for the rough Heston model with CGMY Lévy jumps is also provided.

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  4. arXiv q-fin49

    How Language Model Agents Are Reshaping Price Competition

    Research shows that large language model pricing agents can deviate from the repeated Bertrand competition benchmark where prices converge to marginal costs in homogeneous goods markets, with their performance depending on deployment decisions. Whether LLM pricing agents can maintain prices above marginal costs in self-play is directly related to deployment choices: whether they set prices period-by-period based directly on raw market history including competitor prices, or periodically output probability distributions based on summaries of their own profit history.

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  5. arXiv q-fin47

    AI Agents in Automated Markets

    The research team built behavioral models for three types of trading agents—rational arbitrageurs, manipulators, and retail momentum followers—based on reinforcement learning, and conducted a pilot study on hourly cryptocurrency data (AAVE, ETC, SUI). The results show that the behavioral characteristics of different agents have differentiated impacts on market pressure, liquidity, volatility, and risk-adjusted returns. The research conclusions support formulating differentiated regulatory rules for different behavioral types, rather than uniformly restricting volatility or turnover rates.

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  6. arXiv q-fin44

    OrderFlowDiT: A Transport-Regularized Diffusion Transformer for Probabilistic Limit Order Supply Prediction

    Researchers propose OrderFlowDiT, a conditional diffusion Transformer trained with an unbalanced optimal transport (UOT) auxiliary loss, to predict the conditional distribution of limit order submissions over the next five minutes. Across 1,950 validation conditions covering 30 U.S. stocks, adding UOT reduces the full-field transport cost by 45.8% and the transport energy score by 26.1% compared with training using only mean squared error, with improvements in both metrics for every stock.

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  7. arXiv q-fin43

    From Alpha to Execution: Trading Horizon, Market Regimes, and Execution Schedules under Concave Impact and Hurst Scaling

    This study analyzes trade execution under concave power-law impact and Hurst-scaled price fluctuations. It determines the optimal execution horizon by maximizing the Sharpe ratio of realized trading P&L and identifies conditions for an interior optimum. The derived execution schedule can reduce envelope costs by 10-17% compared to a TWAP schedule over the same duration. The results are published on arXiv.

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  8. arXiv q-fin47

    Study on the Impact of Shared Action Ordering on Executed Credit for LLM Borrowers in a Simulated Lending Market

    An experiment on a simulated collateralized lending market shows that shared action ordering significantly affects the scale of executed credit for LLM borrowers. The experiment set up 12 ordinary order markets and 12 balanced order markets, using an exact randomization test to obtain a two-sided p-value of 2/8100, with a credit difference of 1.12 units of initial unused reference borrowing capacity between leverage-prioritized and deleveraging-prioritized ordinary order markets. No liquidations or actual bad debts occurred in all 24 markets; under the fixed-price 30% shock benchmark, most write-offs came from collateral consumed by liquidation bonuses.

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  9. arXiv q-fin37

    Merton Consumption-Investment Problem under Different Stochastic Integral Conventions

    This study examines the Merton consumption-investment problem under the Itô, Stratonovich, and Hänggi-Klimontovich conventions, corresponding to stochastic integral convention parameter α = 0, 1/2, and 1, respectively. The study finds that if the drift term is transformed synchronously, the optimal investment strategy is unaffected by the choice of convention; if the drift coefficient value is fixed, the investor's opportunity set will change. Under logarithmic utility, consumption decisions are unaffected, but the optimal portfolio weights shift, and the stochastic integral convention cannot be identified using return data alone.

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  11. arXiv q-fin46

    Cross-Product Modeling in Continuous Intraday Electricity Markets Based on Hawkes Processes

    This paper proposes a multivariate state-dependent Hawkes process (SDHP) to model cross-product liquidity dynamics between quarter-hourly and hourly contracts in the Dutch EPEX SPOT continuous intraday market. The model is calibrated using Level 3 order book data from the first month of each quarter in 2024, dividing trading sessions into normal and stress states. The study finds that approximately 95% of orders are driven by their own order flow, with cross-excitation primarily flowing from quarter-hourly contracts to hourly contracts, and this dominance significantly weakens in stress states.

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  12. arXiv q-fin55

    Portfolio Arbitrage in Prediction Markets: Empirical Analysis Based on the Polymarket Order Book

    This study proposes a framework for identifying and quantifying arbitrage opportunities between logically related prediction market contracts, demonstrating that arbitrage exists when prices fall outside the convex hull of feasible return vectors, and solving for the optimal arbitrage portfolio via integer programming. The study recovered 1.9 million logical relationships through semantic analysis of platform metadata and settlement rules, constructing a constraint system covering more than 255,000 contracts.

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  13. arXiv q-fin51

    arXiv Paper: Basis-Only Funding Rates Cannot Achieve Dividend Fairness — Settlement Design for Crypto-Equity Perpetuals

    This 16-page paper, accepted by MARBLE 2026, argues that crypto-exchange stock-like perpetual contracts calculate funding rates from the real-time basis and cannot replicate shareholder dividend cash flows for traders entering or exiting at arbitrary times. The authors derive a fair funding-rate identity, convert point-in-time fairness into an optimal stopping condition, and use measure theory to show that predictable dividends are atomic events. Absolutely continuous funding-rate paths cannot replicate this atom over a holding interval and must be matched with discrete event credits.

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  14. arXiv q-fin36

    Sanctions in a Multipolar World: The Role of Neutral Third Parties

    The paper constructs a three-party theoretical model of trade sanctions involving the sanctioning party, the target party, and a neutral third party, deriving three core conclusions: alliance members typically set different tariffs under Stackelberg timing or imperfect transfer payments; as sanctions tighten, the sanctioning party's welfare may exceed the optimal level under unilateral terms of trade; and when the sanctioning party and the target party compete for the support of a neutral third party, the feasible range of sanctions targets can be clearly defined. The model is applied to a calibrated analysis of sanctions on Russian crude oil, showing that if China and India take unilateral action or the sanctioning alliance offers better terms, the effectiveness of sanctions can increase by approximately 70%.

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  15. arXiv q-fin55

    arXiv Paper: Weak-Form Efficiency Tests of the Full-History Market Capitalization Distribution of Crypto Assets

    Antonis Ballis and Christos Ioannidis released a working paper on arXiv, using a sample of all 8,970 crypto assets and 690 weekly cross-sections from 2013 to 2026 to directly observe asset entry, exit, and survival, and to test the weak-form efficiency symmetry constraints of the Markov chain for the crypto asset market capitalization distribution.

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  16. arXiv q-fin35

    Pricing Generalized Discrete Swaps under Multi-Asset Stochastic Volatility Models

    This paper proposes a generalized variance framework based on the determinant of the instantaneous covariance matrix of asset log returns for pricing multi-asset discrete swaps, which captures the joint discreteness of multivariate asset returns while accounting for their dependence structure. The framework is constructed under Heston and Barndorff-Nielsen-Shephard (BNS) stochastic volatility models, deriving analytical pricing expressions for the three-asset Heston model and tractable approximations for the corresponding BNS model.

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  17. Bank for International Settlements BIS: Research papers54

    BIS Working Paper: Competition Channels for Cross-Border Payments — Banks, Fintechs, and Stablecoins

    The Bank for International Settlements released Working Paper No. 1385, which compares the total costs of three cross-border payment channels: traditional correspondent banking and SWIFT-based bank transfers, fintech remittance operators such as Wise and Remitly, and stablecoin transfers. The study combines intraday fintech pricing, World Bank remittance data, bank transfer transactions, and crypto market data to construct comparable cost indicators across currencies and remittance sizes, distinguishing between foreign exchange markups and explicit fees.

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  19. Bank for International Settlements BIS: Research papers48

    Analysis of Inflation Impact After the Iran Conflict

    The Bank for International Settlements (BIS) released a research paper assessing the impact of the Iran conflict on inflation in the euro area, the United Kingdom, and the United States. As of May 2026, the conflict is expected to push up inflation in these regions by a combined 1.5 to 2 percentage points in 2026 and 2027, with rising inflation expectations potentially contributing an additional 0.3 to 0.4 percentage points. The scale and duration of this inflation shock are smaller than those of the 2021-2024 inflation crisis, and long-term inflation expectations remain broadly stable.

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  20. Bank for International Settlements BIS: Research papers28

    BIS Releases Research Papers for the 25th Annual Conference

    The Bank for International Settlements (BIS) has released research papers from its 25th Annual Conference, held on June 26, 2026, in Basel, Switzerland, under the theme 'Central Banking and Macro-Financial Stability in a Fragmented World Economy.' Three papers were published as BIS Working Papers 1384, 1385, and 1386, with a fourth to follow as BIS Working Paper 1387.

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  21. Bank for International Settlements BIS: Research papers53

    BIS Working Paper: Measuring Firms' Responses to Geoeconomic Pressure with Large Language Models

    The Bank for International Settlements (BIS) released Working Paper No. 1386, which proposes an LLM-based reasoning pipeline to identify firms' actions in response to geoeconomic pressure from earnings call transcripts and summarize the underlying logic. Compared with traditional NLP methods, it can extract implicit conditional relationships in the text rather than merely counting keywords.

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16 OctFri
  3. Bank for International Settlements BIS: Research papers51

    BIS Working Paper: How Offshore Non-Deliverable Forward Markets Transmit Exchange Rate Pressure in Emerging Markets

    The Bank for International Settlements (BIS) has released a working paper that studies the transmission effects of offshore NDF markets on onshore spot exchange rates, using centralized clearing NDF transaction-level data for 10 emerging market currencies from 2013 to 2025. The study shows that a $1 billion long USD order flow causes the onshore spot exchange rate to depreciate by approximately 10 basis points, while the offshore NDF exchange rate moves by about 18 basis points, and offshore transactions widen the spread between offshore and onshore rates; when dealer balance sheets are strained, the impact on the spot exchange rate is larger.

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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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  2. Bank for International Settlements BIS: Research papers40

    Disruptions of Key Chokepoints and Their Macroeconomic Impact

    A research paper published by the Bank for International Settlements (BIS) points out that geopolitical tensions are increasing the risk of disruptions to key chokepoints in global supply chains. Substitution effects and inventory buffers can mitigate output shocks, but often come with higher input prices. Addressing such disruptions requires tailored policies based on the cause, the criticality of the chokepoint, and the private sector's ability to substitute and buffer.

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14 OctWed
  2. Bank for International Settlements BIS: Research papers45

    Money and the Architecture of Trust

    This research paper, published by the Bank for International Settlements (BIS), is based on the credit theory of money. Starting from payment as a fundamental monetary behavior, it outlines four core tensions in the operation of the monetary system and proposes that money is essentially an institutional achievement sustained by trust. The paper applies this framework to the analysis of gold, Bitcoin, and stablecoins. The views expressed are those of the authors and do not necessarily reflect the views of the BIS or its member central banks.

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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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8 OctThu
  1. Alpha Architect69

    How Tail Risk Projects Survive the Waiting Period: From Two Failure Cases to an Eight-Step Due Diligence Framework

    This article treats the holding costs, behavioral pressures, and governance burdens of tail risk hedging during calm periods as design constraints rather than post-hoc inconveniences. The authors first break down three types of "bleeding" sources: direct holding costs, opportunity costs, and evaluation pressure, and provide a table of cumulative sleeve losses for different annualized carry rates over 3 to 15 years, as well as a table of portfolio-level annual drag converted by sleeve weight.

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  2. 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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7 OctWed
6 OctTue
  1. 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. Alpha Architect59

    Buying complex retail investment products may not be a good idea: Interpretation of a paper in the Review of Finance

    Alpha Architect interprets the paper "Competition, complexity, and security design: evidence from retail investment products" published in the Review of Finance in 2026. This study takes yield-enhancement products in the Swiss market as a sample and finds that issuers deliberately increase product complexity to weaken price competition when competition intensifies.

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  2. 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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