Research
Every research paper we have written up, newest paper first. New arrivals are screened automatically for topical fit with systematic trading; the ones that clear it are read, written up, and — where the idea is testable on our data — backtested. Particular focus on alpha hypotheses that can be formalised and tested. The Radar also covers portfolio construction, market risk and execution where the research is directly relevant to systematic investment processes. Follow new entries by RSS.
16,915 papers screened · 588 on the radar · 210 shown
LLM agents that act on live Web data must combine heterogeneous evidence, remember what they have done and improve from outcomes without weakening their own safeguards.
PAPER REPORTS · Live paper portfolio, Apr 8 to Sep 10, 2026 (102 trading days): - Return +5.0% vs SPY +12.4%. · Live paper portfolio, June 22 to July 29, 2026: -0.3%, vs SMH -24.6% over the same window.
Portfolio optimization techniques often use historical data to estimate parameters for Markowitz-type or ML models. Effective allocation requires a way to align the available data with conditions expected over the investment horizon.
PAPER REPORTS · Markowitz, lambda=0 (historical mean only, no future information in the view): net Sharpe 0.019 (gross 0.050), net MDD… · LSTM mean of 100 seeds, lambda=0: net Sharpe -0.021 (gross 0.037), net MDD -24.7%, final wealth 0.978.
This paper compares financial-market reactions to the releases of DeepSeek R1 in January 2025 and Kimi K3 in July 2026.
Financial news can influence investment decisions long after publication. Timely news may reach an investor before prices fully adjust, whereas older news may already be reflected in prices.
PAPER REPORTS · LLM (GPT-4.1 mini) Market Data + Filtered News, 2023–2025 average of annual tests, net of 10 bp per dollar traded: -… · LLM Market Data + News + News Age, 2023–2025, net of 10 bp: 16.73% / 13.26% / 17.17% annualized at 0 / 1 / 4 week…
Optimal capital allocation in financial markets has long been a challenging task due to the dynamic nature of market conditions, risk factors, and the complexity of financial data.
PAPER REPORTS · Annualized Sharpe ratio 1.91, computed from daily portfolio returns with 252 trading days and a 2% annual risk-free… · Cumulative return 1.12. The test period is not stated beyond the 250 trading days in Fig 7, and it is unclear whether…
We study changes in underlying-market quality around Korea's May 2026 introduction of single-stock leveraged ETFs, using Samsung Electronics and SK Hynix as a case study. These were the first eligible underlying stocks.
This study examines the relationship between the dispersion in analysts' target prices and stock returns for firms listed on the KOSPI and KOSDAQ markets.
PAPER REPORTS · High-minus-Low TP_DISP(T) tercile, next-month excess return: 0.595 (t=1.77). Quarterly formation, Jan 2006-Mar 2026.
In January 2021, retail investors coordinating on Reddit’s r/WallStreetBets forced large price increases in heavily shorted stocks such as GameStop and AMC, imposing substantial losses on several hedge funds.
PAPER REPORTS · Reddit-favoured (top-5 WSB mentions) cohort: mean three-month holding-period return 13.00%, median 20.00%, win rate… · Institutionally accumulated (top-5 net 13F increase) cohort: mean three-month holding-period return 6.78%, median…
Indonesia's Islamic capital market has grown rapidly, with PT Bank Syariah Indonesia Tbk (BSI) emerging as one of its actively traded Sharia-compliant issuers.
Formulaic alpha factor mining searches for symbolic expressions that transform market data into predictive signals. Recent LLM-based evolutionary factor mining methods use large language models as semantic variation operators.
PAPER REPORTS · CSI 500, test 2022-05-01 to 2026-04-30, top-20 combined signal, Qlib TopkDropout (top 50, drop 5, daily) net of open… · S&P 500, test 2022-05-01 to 2026-04-30, same backtest and cost settings: annualized return 27.00%, information ratio…
Autoregressive foundation models offer state-of-the-art capabilities to simulate the market by generating the message flow of limit order books (LOBs).
This study examines the impact of Environmental, Social, and Governance (ESG) Disclosure and commodity price volatility on the stock returns of mining companies listed on the Indonesia Stock Exchange (IDX) during the 2019–2023 period.
Realistic market impact is essential for generative limit order book (LOB) models to serve as world models for trading agents. If a simulator misprices this mechanism, agents learn policies that are optimal in the simulator but wrong in the real market.
PAPER REPORTS · DCC-ePOET-1, out-of-sample global MVP on 331 S&P 500 stocks: Var 0.445, Annual-SD 10.840, mean Sharpe ratio 2.281,… · DCC-ePOET-2 (latent factors only, no observable factors), same setup: Var 0.464, Annual-SD 11.049, mean Sharpe ratio…
PAPER REPORTS · Recommended allocation (20% equities + 100 tons gold), historical simulation Nov 2002–Oct 2022, rolling 1-year returns:… · Same recommended allocation, rolling annualized 5-year returns, Nov 2002–Oct 2022: CZK average 3.48%, volatility 2.79%,…
OUR BACKTEST · Sharpe 0.92 · Return +94.9% · Max DD -29.7%
Accurate prediction of stock price movements is of substantial importance to investors, portfolio managers, and financial regulators, and although machine learning models are increasingly deployed in quantitative finance, the limited transparency of many such…
PAPER REPORTS · XGBoost long/flat, hold-out period, as-is configuration: annualized return −11.59%, Sharpe −0.241 at 10 bps one-way… · XGBoost long/short, hold-out period, as-is configuration: annualized return −34.29%, Sharpe −1.014 at 10 bps one-way…
OUR BACKTEST · Sharpe 0.09 · Return +2.4% · Max DD -14.9%
Classical execution models assume linear impact, diffusive prices, and an exogenous horizon. We study execution under concave power-law impact and Hurst-scaled price fluctuations, and make two contributions.
OUR BACKTEST · Sharpe -0.29 · Return -9.4% · Max DD -22.3%
Although advances in artificial intelligence (AI) and machine learning (ML) have transformed financial risk assessment, many early-warning frameworks for systematic risk still rely on isolated macro-financial indicators with limited integration of established…
Abstract Evaluating systemic risk transmission across financial and commodity markets is vital for maintaining macroeconomic stability in hydrocarbon-dependent economies.
Language models that read financial news are usually trained on text from the same years used to test them, so a backtest can reward hindsight.
PAPER REPORTS · Monthly, price+text combination across all readers and models, 63-day shocks, test 2022–2024, net of 10bp per dollar… · Same monthly buffered portfolio: net return 12.4%/yr, volatility 10.4%, max drawdown 8%, turnover 60% per month,…
OUR BACKTEST · Sharpe -0.73 · Return -19.9% · Max DD -34.5%
We study the conditional distribution of limit-order volume submitted over the next five minutes, given the current order book and recent order flow. The task requires capturing price placement, total volume, and predictive uncertainty jointly.
Portfolio optimization is constrained by linear assumptions and limited integration of multi-modal information.
PAPER REPORTS · SBCA 2-asset (CAT, GILD), test 2021–2022, net of 0.25% one-way commission: final portfolio value 1.4392, annual return… · SBCA 4-asset (CAT, GILD, GS, KO), test 2021–2022, net of 0.25% one-way commission: final portfolio value 1.3564, annual…
OUR BACKTEST · Sharpe 2.62 · Return +54.1% · Max DD -10.1%
Background: Foreign investors can improve liquidity in emerging markets, but concentrated withdrawals may coincide with sharp price adjustment.
Purpose: This study aims to examine the effect of inflation, BI Rate, capital flow, and exchange rate on the Jakarta Composite Index (JCI), as well as to analyze the moderating role of profitability (ROA) in these relationships.
The Oracle Approximating Shrinkage (OAS) estimator provides a closed-form, data-driven shrinkage intensity for regularizing sample covariance matrices toward a scaled identity target, but its derivation assumes Gaussian data.
PAPER REPORTS · OAS-Extended GMV portfolio, p=50 US large caps, Jan 2010–Dec 2023, 155 monthly-stepped windows: mean annualized… · OAS-Extended vs OAS realized-variance improvement: t=3.83, p<0.001; bootstrap 95% CI for mean variance reduction [2.0,…
OUR BACKTEST · Sharpe 0.53 · Return +40.1% · Max DD -29.9%
Which inputs drive a language model's financial forecast? We construct synthetic earnings announcements that independently reverse 20-day momentum, non-informational commentary tone, and whether fixed actual EPS beats a manipulated consensus.
Backtests of intraday strategies can drift away from what the live system actually does; in our case, the drift never showed in summary statistics.
Corporate financial disclosures often unfold over time, with announcements, prepared remarks, and discussion spanning multiple high-frequency return intervals.
Tokenized equities trade while listed markets are closed, so their marks could improve off-hours measurement along layered exposures that link Bitcoin, crypto-treasury stocks, and leveraged ETFs.
PAPER REPORTS · Expanding-window out-of-sample forecasts of the opening gap (BTC-and-age spec plus token, July 2025-June 2026, no… · July 2026 holdout with coefficients frozen on June 5, 2026 (forecast, not a trading strategy, no costs): sign hit rate…
Stock price forecasting is considered difficult due to the volatility of financial markets. A reliable stock price forecasting model is critical for making sound investing decisions while managing financial risks and portfolios.
Abstract Implied temperature rise (ITR) metrics translate corporate emissions pathways into a temperature-based measure of climate alignment at the company and portfolio levels.
This study aims to analyze the effect of media exposure on stock returns of clothing and luxury goods companies listed on the Indonesia Stock Exchange for the 2020–2024 period, and to examine the role of firm size as a moderating variable with profitability…
We study dynamic portfolio decarbonization under incomplete information about firms' carbon intensities and the underlying transition state.
We study whether stock disclosures by recognizable investors generate abnormal market reactions beyond the reactions produced by comparable but non-recognizable managers.
PAPER REPORTS · High-recognition minus control long-short calendar-time Carhart alpha: 10.4 bps/day at H=21 (p<0.001), 4.8 bps/day at… · High-recognition buys long-only calendar-time Carhart alpha: 9.8 bps/day H=21 (p<0.001), 4.4 bps/day H=63 (p=0.003),…
To extend conventional model-level feature importance to economically meaningful portfolio outcomes and decisions, we propose a local first-order attribution-propagation framework that maps allocation-function feature exposures to local sensitivities of…
PAPER REPORTS · XGB baseline, OOS 2006-2024: net Sharpe 0.6175 (annualised, 5bp per unit turnover); gross Sharpe 1.0207; net mean 2.55%… · FFN baseline, OOS 2006-2024: net Sharpe 0.5750 (5bp); gross Sharpe 1.3051; net mean 2.65% p.a.; net FF5 alpha 1.12%…
OUR BACKTEST · Sharpe -0.82 · Return -24.2% · Max DD -31.5%
Formulaic alpha mining seeks to discover executable expressions that capture predictive market signals in a vast, noisy search space.
PAPER REPORTS · AlphaRLM-8B CSI 300: annualized excess return 12.14% (0.1214±0.0011), MDD -6.15%, IC 0.0256, RankIC 0.0424, ICIR… · AlphaRLM-8B CSI 1000 (CSI 300-trained factor pool): annualized excess return 17.45%, MDD -11.98%, IC 0.0302, RankIC…
OUR BACKTEST · Sharpe 0.83 · Return +105.8% · Max DD -50.8%
PAPER REPORTS · AIM_PU_CVaR (real data, daily, 2020-01-01 to present, T=1471 days): Sharpe ratio 0.7718; annualization not stated; no… · AIM_PU_CVaR: total reward 1.5048, mean daily return 0.0010, total CVaR-like cost 0.0194, 23 crisis days (>5% daily…
OUR BACKTEST · Sharpe 0.98 · Return +61.8% · Max DD -22.0%
We examine climate variables in a pipeline for dynamic Value-at-Risk (VaR) of the SRI-KEHATI ESG index and the IHSG (Jakarta Composite Index).
PAPER REPORTS · Main QRNN backtest, test N=300 (Nov 2023-Dec 2025), VaR violation rates and Kupiec p: SRI-KEHATI tau=0.01 0.33% (1… · Main QRNN DM statistics on pinball loss (positive = QRNN better), all p<0.001. Vs HS-VaR: SRK 4.31 / 6.43 / 7.23 and…
Abstract: This study aims to analyze stock price developments, fundamental performance, and stock valuation as a basis for determining investment decisions in banking companies listed on the Indonesia Stock Exchange during the 2020–2025 period.
This study examined the volatility effects of climate policy uncertainty on renewable energy stock returns in Nigeria using the Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) model.
This study examined the effect of dividend policy son the stock market performance of listed Consumer Goods Firms in Nigeria. The study covered all 21 firms within the sector, with the Bird-in-Hand theory serving as the theoretical foundation.
How can we identify stable patterns to accurately predict stock price movements amidst severe market noise? Predicting stock price movements is a crucial problem in financial data mining, and has attracted significant attention from researchers and financial…
PAPER REPORTS · COVID-19 crisis (test 2020-01 to 2020-03), threshold long-short, 6 bps cost on sells, zero risk-free rate: S&P500 ASR… · AI rally (test 2024-01 to 2024-06), same protocol: S&P500 ASR 2.842, RMDD 6.8%; CSI300 (long-only) ASR 1.653, RMDD…
Correlation matrices combine nonlinear positive-definiteness constraints with a simultaneous row-column permutation symmetry. Their generation therefore involves two distinct problems.
OUR BACKTEST · Sharpe 0.00 · Return +0.0% · Max DD 0.0%
A realized tail-risk conditional autoregressive expectile (RTCARE) model is proposed for joint forecasting of value-at-risk (VaR) and expected shortfall (ES).
PAPER REPORTS · RTCARE out-of-sample mean FZ0 loss (IBM, 3513 rolling one-day forecasts within 2005-2024): 1.100 (5%), 1.379 (2.5%),… · RTCARE NO INT out-of-sample mean FZ0 loss: 1.097 (5%), 1.372 (2.5%), 1.769 (1%), 2.057 (0.5%)
OUR BACKTEST · Sharpe 1.82 · Return +9.2% · Max DD -6.2%
Abstract Time series forecasting models play a crucial role as decision support tools in various real-world domains.
PAPER REPORTS · Multi-stock swing trading (17 stocks, equal budget, 3-day confirmation), uptrend Jul 1–Dec 31 2021: average gain 7.64%… · Multi-stock swing trading, downtrend Jan 1–Sep 20 2022: average gain -0.34% across Max Shares 1/5/10 (-7.16%, 3.61%,…