{
"scan_date": "2026-03-24",
"sources_checked": [
"arxiv",
"openalex",
"nber",
"bis",
"ny_fed",
"chicago_fed",
"cboe",
"google_scholar",
"ssrn"
],
"papers_found": 188,
"papers_relevant": 10,
"top_papers": [
{
"title": "Mislearning of Factor Risk Premia under Structural Breaks: A Misspecified Bayesian Learning Framework",
"authors": "Yimeng Qiu",
"source": "arxiv",
"url": "https://arxiv.org/abs/2603.21672v2",
"date": "2026-03-23",
"abstract": "While asset-pricing models increasingly recognize that factor risk premia are subject to structural change, existing literature typically assumes that investors correctly account for such instability. This paper asks what happens when investors instead learn under a misspecified model that underestimates structural breaks. We propose a minimal Bayesian framework in which this misspecification generates persistent prediction errors and pricing distortions, and we introduce an empirically tractabl...",
"relevance_score": 7,
"relevance_tags": [
"opening_range"
],
"key_finding": "This paper asks what happens when investors instead learn under a misspecified model that underestimates structural breaks.",
"backtestable": true,
"data_we_have": false,
"priority": "HIGH"
},
{
"title": "Risky Intraday Order Flow and Option Liquidity May 23, 2025 Abstract",
"authors": "Unknown",
"source": "web",
"url": "https://www.bauer.uh.edu/hdoshi/docs/DPS_May_2025.pdf",
"date": "2026-03-24",
"abstract": "SPX options. First, we observe a strong positive relationship between the standard deviation \u00b7 of order \ufb02ow and illiquidity for both call and put samples. Moreover, the coe\ufb03cient is larger \u00b7 for very short-maturity options (up to 24 days), con\ufb01rming that trading costs in shorter- dated contracts are more sensitive to intraday order \ufb02ow volatility.",
"relevance_score": 6,
"relevance_tags": [
"order_flow",
"intraday"
],
"key_finding": "Moreover, the coe\ufb03cient is larger \u00b7 for very short-maturity options (up to 24 days), con\ufb01rming that trading costs in shorter- dated contracts are more sensitive to intraday order \ufb02ow volatility.",
"backtestable": false,
"data_we_have": true,
"priority": "MEDIUM"
},
{
"title": "QUANTITATIVE FINANCE VO L U M E 3 (2003) 417\u2013425 RE S E A R C H PA P E R",
"authors": "Unknown",
"source": "web",
"url": "https://www.cis.upenn.edu/~mkearns/finread/PinningPaper.pdf",
"date": "2026-03-24",
"abstract": "We propose a model to describe stock pinning on option expiration dates. We \u00b7 argue that if the open interest on a particular contract is unusually large,",
"relevance_score": 6,
"relevance_tags": [
"pinning"
],
"key_finding": "We \u00b7 argue that if the open interest on a particular contract is unusually large,",
"backtestable": false,
"data_we_have": true,
"priority": "MEDIUM"
},
{
"title": "A market-induced mechanism for stock pinning: Quantitative Finance: Vol 3, No 6",
"authors": "Unknown",
"source": "web",
"url": "https://www.tandfonline.com/doi/abs/10.1088/1469-7688/3/6/301",
"date": "2026-03-24",
"abstract": "We propose a model to describe stock pinning on option expiration dates. We argue that if the open interest on a particular contract is unusually large, delta-hedging in aggregate by floor market...",
"relevance_score": 6,
"relevance_tags": [
"pinning"
],
"key_finding": "We argue that if the open interest on a particular contract is unusually large, delta-hedging in aggregate by floor market...",
"backtestable": false,
"data_we_have": true,
"priority": "MEDIUM"
},
{
"title": "Derivative Spreads: Evidence from SPX Options* Jie Cao\u0084 Kris Jacobs Sai Ke\u00a7",
"authors": "Unknown",
"source": "web",
"url": "https://www.aeaweb.org/conference/2024/program/paper/DFs2GZND",
"date": "2026-03-24",
"abstract": "to deter imbalanced order flows at that time. In contrast, the competing market makers of \u00b7 options can avoid excessive long or short positions. Wei and Zheng (2010) investigate the de- terminants of equity options liquidity, measured by proportional spreads, and find the option \u00b7 return volatility to be a key determinant.",
"relevance_score": 6,
"relevance_tags": [
"order_flow"
],
"key_finding": "Wei and Zheng (2010) investigate the de- terminants of equity options liquidity, measured by proportional spreads, and find the option \u00b7 return volatility to be a key determinant.",
"backtestable": false,
"data_we_have": true,
"priority": "MEDIUM"
},
{
"title": "Mean Field Equilibrium Asset Pricing Models With Exponential Utility",
"authors": "Masashi Sekine",
"source": "arxiv",
"url": "https://arxiv.org/abs/2603.22058v1",
"date": "2026-03-23",
"abstract": "This thesis develops equilibrium asset pricing models in incomplete markets with a large number of heterogeneous agents using mean field game theory. The market equilibrium is characterized by a novel form of mean field backward stochastic differential equations (BSDEs). First, we propose a theoretical model that endogenously derives the equilibrium risk premium. Agents with exponential preferences are heterogeneous in initial wealth, risk aversion, and unspanned stochastic terminal liability. W...",
"relevance_score": 5,
"relevance_tags": [],
"key_finding": "We provide semi-analytic expressions for the equilibrium via the EQG framework, and the equilibrium risk-premium process is constructed endogenously using Kalman-Bucy filtering theory.",
"backtestable": false,
"data_we_have": true,
"priority": "MEDIUM"
},
{
"title": "Contract Enforcement and Young Firm Capital Structure: A Global Perspective",
"authors": "Gonzalo E. Basante Pereira, Ina Simonovska",
"source": "nber",
"url": "https://www.nber.org/papers/w34985#fromrss",
"date": "2026-03-24",
"abstract": "We develop a framework to measure the severity of financial constraints for young firms across countries. Using ORBIS balance-sheet data for 23 economies, we show that short-term leverage rises while long-term leverage falls early in firms\u2019 life cycles, with this pattern persisting longer where contract enforcement is weaker. We build a model of optimal financing under limited enforcement with endogenous debt maturity and blueprint capacity that matches these patterns and enables structural meas...",
"relevance_score": 5,
"relevance_tags": [
"opening_range"
],
"key_finding": "The framework decomposes the funding gap into within-firm borrowing constraints that ease with repayment history and a scale distortion identifiable through cross-country comparisons.",
"backtestable": false,
"data_we_have": false,
"priority": "MEDIUM"
},
{
"title": "Intraday Jumps and 0DTE Options: Pricing and Hedging Implications ...",
"authors": "Unknown",
"source": "ssrn",
"url": "https://papers.ssrn.com/sol3/Delivery.cfm/5223127.pdf?abstractid=5223127&mirid=1",
"date": "2026-03-24",
"abstract": "This paper investigates how intraday jumps affect the pricing and hedging of 0DTE options on the S&P 500. We develop a continuous-time stochastic volatility model with Poisson jumps and derive semi-closed-form solutions for European option prices, ...",
"relevance_score": 5,
"relevance_tags": [
"0DTE",
"intraday"
],
"key_finding": "This paper investigates how intraday jumps affect the pricing and hedging of 0DTE options on the S&P 500.",
"backtestable": false,
"data_we_have": true,
"priority": "MEDIUM"
},
{
"title": "Same-Day Options, Same-Day Alpha? Institutional Lessons from 0DTE\u2019s Boom | Resonanz Capital",
"authors": "Unknown",
"source": "web",
"url": "https://resonanzcapital.com/insights/same-day-options-same-day-alpha-institutional-lessons-from-0-dtes-boom",
"date": "2026-03-24",
"abstract": "Traditional Black-Scholes models, calibrated to daily data, underestimate the frequency and severity of intraday price swings. Risk teams now look to realized volatility distributions measured in five-minute or even one-minute intervals. Back tests are being stress-tested against episodes like the August 2024 CPI release, when the S&P 500 gapped nearly two percent in fifteen minutes. It is no longer enough to model volatility in calendar terms \u2014 you must model it in clock-time. For allocator...",
"relevance_score": 5,
"relevance_tags": [
"0DTE",
"intraday",
"volatility"
],
"key_finding": "For allocators, the rise of 0DTE strategies poses both an opportunity and a challenge.",
"backtestable": true,
"data_we_have": true,
"priority": "MEDIUM"
},
{
"title": "VIX Term Structure | Cboe",
"authors": "Unknown",
"source": "web",
"url": "https://www.cboe.com/tradable-products/vix/term-structure/",
"date": "2026-03-24",
"abstract": "Term Structure and Volatility Indices on the S&P 500\u00ae Index Cboe Options Exchange offers these five gauges of expectations of future volatility based on real-time trading of S&P 500 options: the VIX9D Index (9-day volatility), VIX Index (30-day volatility), VIX3M (3-month volatility), VIX6M Index (6-month volatility), and VIX1Y Index (1-year volatility). The five indices can serve as tools to gain valuable insights on investor sentiment, and on the historical and current term structure r...",
"relevance_score": 5,
"relevance_tags": [
"vix"
],
"key_finding": "Monthly and weekly expirations are available and trade nearly 24 hours a day, five days a week.",
"backtestable": false,
"data_we_have": true,
"priority": "MEDIUM"
},
{
"title": "FinRL-X: An AI-Native Modular Infrastructure for Quantitative Trading",
"authors": "Hongyang Yang, Boyu Zhang, Yang She, Xinyu Liao, Xiaoli Zhang",
"source": "arxiv",
"url": "https://arxiv.org/abs/2603.21330v1",
"date": "2026-03-22",
"abstract": "We present FinRL-X, a modular and deployment-consistent trading architecture that unifies data processing, strategy construction, backtesting, and broker execution under a weight-centric interface. While existing open-source platforms are often backtesting- or model-centric, they rarely provide system-level consistency between research evaluation and live deployment. FinRL-X addresses this gap through a composable strategy pipeline that integrates stock selection, portfolio allocation, timing, a...",
"relevance_score": 4,
"relevance_tags": [
"ml_trading"
],
"key_finding": "The official FinRL-X implementation is available at https://github.com/AI4Finance-Foundation/FinRL-Trading.",
"backtestable": true,
"data_we_have": true,
"priority": "LOW"
},
{
"title": "Neural Hidden Markov Model with Adaptive Granularity Attention for High-Frequency Order Flow Modeling",
"authors": "Tianzuo Hu",
"source": "arxiv",
"url": "https://arxiv.org/abs/2603.20456v1",
"date": "2026-03-20",
"abstract": "We propose a Neural Hidden Markov Model (HMM) with Adaptive Granularity Attention (AGA) for high-frequency order flow modeling. The model addresses the challenge of capturing multi-scale temporal dynamics in financial markets, where fine-grained microstructure signals and coarse-grained liquidity trends coexist. The proposed framework integrates parallel multi-resolution encoders, including a dilated convolutional network for tick-level patterns and a wavelet-LSTM module for low-frequency dyna...",
"relevance_score": 4,
"relevance_tags": [
"order_flow"
],
"key_finding": "We propose a Neural Hidden Markov Model (HMM) with Adaptive Granularity Attention (AGA) for high-frequency order flow modeling.",
"backtestable": true,
"data_we_have": false,
"priority": "LOW"
},
{
"title": "Designing Agentic AI-Based Screening for Portfolio Investment",
"authors": "Mehmet Caner, Agostino Capponi, Nathan Sun, Jonathan Y. Tan",
"source": "arxiv",
"url": "https://arxiv.org/abs/2603.23300v1",
"date": "2026-03-24",
"abstract": "We introduce a new agentic artificial intelligence (AI) platform for portfolio management. Our architecture consists of three layers. First, two large language model (LLM) agents are assigned specialized tasks: one agent screens for firms with desirable fundamentals, while a sentiment analysis agent screens for firms with desirable news. Second, these agents deliberate to generate and agree upon buy and sell signals from a large portfolio, substantially narrowing the pool of candidate assets. Fi...",
"relevance_score": 4,
"relevance_tags": [],
"key_finding": "Empirically, our method achieves superior Sharpe ratios relative to an unscreened baseline portfolio and to conventional screening approaches, evaluated on S&P 500 data over the period 2020--2024.",
"backtestable": true,
"data_we_have": true,
"priority": "LOW"
},
{
"title": "Implementation Risk in Portfolio Backtesting: A Previously Unquantified Source of Error",
"authors": "Dong Yin, Takeshi Miki, Vladislav Lesnichenko, Vasyl Gural",
"source": "arxiv",
"url": "https://arxiv.org/abs/2603.20319v1",
"date": "2026-03-19",
"abstract": "Portfolio backtesting is the primary tool for evaluating investment strategies before deployment, yet practitioners implicitly assume that different engines produce identical results for the same strategy. we formalise implementation risk, the systematic divergence in backtested portfolio metrics arising solely from differences in how engines implement the same logical strategy, and propose four metrics grounded in metrology to quantify it: engine sensitivity, implementation uncertainty interval...",
"relevance_score": 4,
"relevance_tags": [],
"key_finding": "code and benchmark data are publicly available.",
"backtestable": true,
"data_we_have": true,
"priority": "LOW"
},
{
"title": "Option pricing model under the G-expectation framework",
"authors": "Ziting Pei, Xingye Yue, Xiaotao Zheng",
"source": "arxiv",
"url": "https://arxiv.org/abs/2603.22831v1",
"date": "2026-03-24",
"abstract": "G-expectation, as a sublinear expectation, provides a powerful framework for modeling uncertainty in financial markets. Motivated by the need for robust valuation under model uncertainty, this work develops a unified risk-neutral valuation approach within the G-expectation environment, yielding a nonlinear generalization of the Black-Scholes model, termed the G-Black-Scholes equation. To enhance computational efficiency and reduce numerical cost, we introduce a logarithmic transformation of the ...",
"relevance_score": 4,
"relevance_tags": [],
"key_finding": "Numerical examples confirm that the proposed schemes achieve high accuracy, while the logarithmic transformation relaxes the stability constraints of explicit schemes and improves computational effici",
"backtestable": false,
"data_we_have": true,
"priority": "LOW"
},
{
"title": "Generative Diffusion Model for Risk-Neutral Derivative Pricing",
"authors": "Nilay Tiwari",
"source": "arxiv",
"url": "https://arxiv.org/abs/2603.20582v1",
"date": "2026-03-21",
"abstract": "Denoising diffusion probabilistic models (DDPMs) have emerged as powerful generative models for complex distributions, yet their use in arbitrage-free derivative pricing remains largely unexplored. Financial asset prices are naturally modeled by stochastic differential equations (SDEs), whose forward and reverse density evolution closely parallels the forward noising and reverse denoising structure of diffusion models. In this paper, we develop a framework for using DDPMs to generate risk-neut...",
"relevance_score": 4,
"relevance_tags": [],
"key_finding": "We show that the change of measure from the physical to the risk-neutral measure induces an additive shift in the score function, which translates into a closed-form risk-neutral epsilon shift in the ",
"backtestable": false,
"data_we_have": true,
"priority": "LOW"
},
{
"title": "Proxy-Reliance Control in Conformal Recalibration of One-Sided Value-at-Risk",
"authors": "Tenghan Zhong",
"source": "arxiv",
"url": "https://arxiv.org/abs/2603.22569v1",
"date": "2026-03-23",
"abstract": "We introduce a proxy-reliance-controlled conformal recalibration framework for one-sided Value-at-Risk (VaR), and study a question that existing state-aware methods do not usually isolate: how strongly should the recalibration adjustment depend on an imperfect volatility proxy? We formalize this through a proxy-reliance parameter that continuously interpolates between an approximately constant-shift correction and a fully proxy-scaled correction. This makes proxy reliance a distinct and practica...",
"relevance_score": 4,
"relevance_tags": [
"vix"
],
"key_finding": "We show theoretically that larger proxy reliance increases the responsiveness of the tail adjustment to proxy scale, but also increases stressed-state fragility when the proxy underreacts.",
"backtestable": true,
"data_we_have": true,
"priority": "LOW"
},
{
"title": "Dynamic Pareto Optima in Multi-Period Pure-Exchange Economies",
"authors": "Brandon Tam, Mario Ghossoub, Silvana M. Pesenti",
"source": "arxiv",
"url": "https://arxiv.org/abs/2603.19414v1",
"date": "2026-03-19",
"abstract": "We study a problem of optimal allocation in a discrete-time multi-period pure-exchange economy, where agents have preferences over stochastic endowment processes that are represented by strongly time-consistent dynamic risk measures. We introduce the notion of dynamic Pareto-optimal allocation processes and show that such processes can be constructed recursively starting with the allocation at the terminal time. We further derive a comonotone improvement theorem for allocation processes, and we ...",
"relevance_score": 4,
"relevance_tags": [],
"key_finding": "We illustrate our results in a two-period setting.",
"backtestable": false,
"data_we_have": false,
"priority": "LOW"
},
{
"title": "Reserve Demand Estimation with Minimal Theory",
"authors": "Ricardo Lagos, Gast\u00f3n Navarro",
"source": "nber",
"url": "https://www.nber.org/papers/w34972#fromrss",
"date": "2026-03-24",
"abstract": "We propose a new reserve-demand estimation strategy---a middle ground between atheoretical reduced-form econometric approaches and fully structural quantitative-theoretic approaches. The strategy consists of an econometric specification that satisfies core restrictions implied by theory and controls for changes in administered-rate spreads that induce rotations and shifts in reserve demand. The resulting approach is as user-friendly as existing reduced-form econometric methods but improves upon ...",
"relevance_score": 4,
"relevance_tags": [],
"key_finding": "We propose a new reserve-demand estimation strategy---a middle ground between atheoretical reduced-form econometric approaches and fully structural quantitative-theoretic approaches.",
"backtestable": false,
"data_we_have": false,
"priority": "LOW"
},
{
"title": "Artificial Intelligence, Productivity, and the Workforce: Evidence from Corporate Executives",
"authors": "Salom\u00e9 Baslandze, Zachary Edwards, John Graham, Ty McClure, Brent H. Meyer, Michael Sparks, Sonya R. Waddell, Daniel Weitz",
"source": "nber",
"url": "https://www.nber.org/papers/w34984#fromrss",
"date": "2026-03-24",
"abstract": "We use novel data from a survey of nearly 750 corporate executives to study the effects of artificial intelligence (AI) on productivity and the workforce. We document substantial heterogeneity in AI adoption across firms, with more than half having already invested, though many smaller firms are only beginning to do so. Labor productivity gains are positive, vary across sectors, and are expected to strengthen in 2026, with the largest effects concentrated in high-skill services and finance. Thes...",
"relevance_score": 4,
"relevance_tags": [],
"key_finding": "We document substantial heterogeneity in AI adoption across firms, with more than half having already invested, though many smaller firms are only beginning to do so.",
"backtestable": false,
"data_we_have": true,
"priority": "LOW"
},
{
"title": "Private Credit, Balance Sheets and Financial Stability",
"authors": "Gregor Matvos, Tomasz Piskorski, Amit Seru",
"source": "nber",
"url": "https://www.nber.org/papers/w34991#fromrss",
"date": "2026-03-24",
"abstract": "We document new evidence on the capitalization, funding structure, and performance of private credit funds using comprehensive fund- and asset-level data covering most of the industry. Private credit funds are highly capitalized, with equity typically accounting for 65\u201380% of total assets\u2014more than six times the capitalization of U.S. banks, where equity represents about 10%. Debt usage is moderate and largely reflects bank credit lines used for liquidity management. Fund lives average 10\u201312 yea...",
"relevance_score": 4,
"relevance_tags": [],
"key_finding": "We document new evidence on the capitalization, funding structure, and performance of private credit funds using comprehensive fund- and asset-level data covering most of the industry.",
"backtestable": false,
"data_we_have": true,
"priority": "LOW"
},
{
"title": "Weekly Options on Stock Pinning",
"authors": "Unknown",
"source": "web",
"url": "https://www.wpunj.edu/Weekly%20Options%20on%20Stock%20Pinning%20upto%20page%208.pdf",
"date": "2026-03-24",
"abstract": "To investigate the possible reasons for stock pinning, we obtain several additional option \u00b7 variables. In particular, we obtain the trading volume of the at-the-money calls and puts on \u00b7 expiration day (VolExp) and the open interest of the at-the-money calls and puts on the day before",
"relevance_score": 4,
"relevance_tags": [
"pinning"
],
"key_finding": "In particular, we obtain the trading volume of the at-the-money calls and puts on \u00b7 expiration day (VolExp) and the open interest of the at-the-money calls and puts on the day before",
"backtestable": false,
"data_we_have": true,
"priority": "LOW"
},
{
"title": "CME Group Equity Index Options \u2013 A Quick Look at the Current State of Play - CME Group",
"authors": "Unknown",
"source": "web",
"url": "https://www.cmegroup.com/articles/2025/equity-index-options-state-of-play.html",
"date": "2026-03-24",
"abstract": "[3] For order risk mitigation methodology available for market makers on CME Globex, please see CME Group Mass Quote Protections. [4] For more information on pre-hedging of option block trades, please see Question 13 listed on the CME Group Market Regulation Advisory Notice (MRAN) [5] To adjust for homogenized contract value factors, the CME Group positions have been scaled up by a factor of 2 as the ES contract represents $50 x S&P 500 Index, while SPX represents $100 x S&P 500 Index.",
"relevance_score": 4,
"relevance_tags": [],
"key_finding": "[4] For more information on pre-hedging of option block trades, please see Question 13 listed on the CME Group Market Regulation Advisory Notice (MRAN) [5] To adjust for homogenized contract value fac",
"backtestable": false,
"data_we_have": true,
"priority": "LOW"
},
{
"title": "What Is Gamma Exposure? An In-Depth Analysis for Traders - Cheddar Flow",
"authors": "Unknown",
"source": "web",
"url": "https://www.cheddarflow.com/blog/what-is-gamma-exposure-an-in-depth-analysis-for-traders/",
"date": "2026-03-24",
"abstract": "Understanding where dealers are forced to hedge due to their gamma exposure lets you anticipate where the market may stabilize, reverse, or accelerate. These aren\u2019t random intraday moves, they\u2019re structural forces shaping price behavior. Heavily traded, high-volatility stocks can experience \u201cgamma squeezes\u201d if traders buy large amounts of at-the-money (or slightly out-of-the-money) call options.",
"relevance_score": 4,
"relevance_tags": [
"gamma",
"intraday"
],
"key_finding": "Heavily traded, high-volatility stocks can experience \u201cgamma squeezes\u201d if traders buy large amounts of at-the-money (or slightly out-of-the-money) call options.",
"backtestable": false,
"data_we_have": true,
"priority": "LOW"
},
{
"title": "Gamma Squeeze Explained Guide - MenthorQ",
"authors": "Unknown",
"source": "web",
"url": "https://menthorq.com/guide/gamma-squeeze-explained/",
"date": "2026-03-24",
"abstract": "If the market moves toward a gamma-neutral zone, dealers may flip from short gamma to long gamma. If the market crosses resistance zones loaded with short gamma, the hedging response may turn into a buying cascade. This flow is entirely mechanical\u2014it\u2019s not about investors becoming bullish, but about how dealers must respond to price and volatility changes to stay hedged.",
"relevance_score": 4,
"relevance_tags": [],
"key_finding": "This flow is entirely mechanical\u2014it\u2019s not about investors becoming bullish, but about how dealers must respond to price and volatility changes to stay hedged.",
"backtestable": false,
"data_we_have": false,
"priority": "LOW"
},
{
"title": "Gamma Squeeze Explained: How Dealer Hedging Moves Markets",
"authors": "Unknown",
"source": "web",
"url": "https://flyonthewall.ai/gamma-squeeze-explained/",
"date": "2026-03-24",
"abstract": "They happen any time the options market\u2019s hedging flows overwhelm the available liquidity in the underlying. This guide explains the gamma squeeze mechanism in practical terms, shows how dealer positioning creates the conditions for one, and identifies how structural traders use these events ...",
"relevance_score": 4,
"relevance_tags": [
"dealer_hedging"
],
"key_finding": "This guide explains the gamma squeeze mechanism in practical terms, shows how dealer positioning creates the conditions for one, and identifies how structural traders use these events ...",
"backtestable": false,
"data_we_have": true,
"priority": "LOW"
},
{
"title": "How to Spot Buying Opportunities in Options Order Flow | Nasdaq",
"authors": "Unknown",
"source": "web",
"url": "https://www.nasdaq.com/articles/how-to-spot-buying-opportunities-in-options-order-flow",
"date": "2026-03-24",
"abstract": "In summary, to identify buying ... to analyze the trade side distribution data, the relationship between volume and open interest (both intraday and historically), and how the price and implied volatility have shifted...",
"relevance_score": 4,
"relevance_tags": [
"order_flow",
"options_microstructure",
"intraday",
"volatility"
],
"key_finding": "to analyze the trade side distribution data, the relationship between volume and open interest (both intraday and historically), and how the price and implied volatility have shifted.",
"backtestable": false,
"data_we_have": true,
"priority": "LOW"
},
{
"title": "Gamma Exposure (GEX) | SpotGamma\u2122",
"authors": "Unknown",
"source": "web",
"url": "https://spotgamma.com/gamma-exposure-gex/",
"date": "2026-03-24",
"abstract": "They aren\u2019t. Dealers take the opposite side of customer trades \u2014 direction matters. Focusing only on monthly expiry misses the growing dominance of 0DTE options, which now account for over 50% of SPX volume and have enormous intraday impact. Standard tools give you a number \u2014 not a roadmap. You need to know where the regime changes: the exact price level where calm markets turn chaotic.",
"relevance_score": 4,
"relevance_tags": [
"0DTE",
"gamma",
"intraday"
],
"key_finding": "You need to know where the regime changes: the exact price level where calm markets turn chaotic.",
"backtestable": false,
"data_we_have": true,
"priority": "LOW"
},
{
"title": "Flexible Information Acquisition in the Kyle Model",
"authors": "S. Viswanathan, Hao Xing",
"source": "arxiv",
"url": "https://arxiv.org/abs/2603.21842v1",
"date": "2026-03-23",
"abstract": "We study an information acquisition problem in which an informed trader acquires costly information prior to trading in the Kyle equilibrium. The cost of information acquisition is represented by an entropy cost. Regardless of the prior distribution of the asset payoff, continuous signals are optimal. Moreover, any continuously distributed signal, together with an associated logit type posterior distribution of the payoff, yields the same ex-ante value for the informed trader, the same distribut...",
"relevance_score": 3,
"relevance_tags": [
"order_flow"
],
"key_finding": "We further show that when the information acquisition cost increases or the volatility of noise trades decreases, the variance of the posterior expected payoff declines, the profit potential from trad",
"backtestable": true,
"data_we_have": false,
"priority": "LOW"
},
{
"title": "Approximate Dynamic Programming for Degradation-aware Market Participation of Battery Energy Storage Systems: Bridging Market and Degradation Timescales",
"authors": "Flemming Holtorf, Sungho Shin",
"source": "arxiv",
"url": "https://arxiv.org/abs/2603.21089v1",
"date": "2026-03-22",
"abstract": "We present an approximate dynamic programming framework for designing degradation-aware market participation policies for battery energy storage systems. The approach employs a tailored value function approximation that reduces the state space to state of charge and battery health, while performing dynamic programming along a pseudo-time axis encoded by state of health. This formulation enables an offline/online computation split that separates long-term degradation dynamics (months to years) fr...",
"relevance_score": 3,
"relevance_tags": [],
"key_finding": "Backtests on historical market data show that the resulting policy outperforms several benchmark strategies with optimized hyperparameters.",
"backtestable": true,
"data_we_have": false,
"priority": "LOW"
}
]
}