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
Introduction & purpose Capital structure is an important determinant of investment decision as it influences share price as well as the overall earnings of the firm.
PAPER REPORTS · SMB (small minus big, equal-weighted, 2x3 sort) mean return 0.014 (1.4%), t 5.722; monthly data Jan 2010 to Dec 2024;… · LMH (low minus high P/B) mean return 0.003 (0.3%), t 0.845; same sample; no transaction costs stated.
When a trader executes a large order, the relevant question is not \emph{what will the price be?} but \emph{what would the price have been had I not traded?} Market impact is thus a causal quantity, yet classical models (Almgren--Chriss, propagators) regress…
Expectiles are the only law-invariant risk measures that are both coherent and elicitable. Unlike Conditional Value-at-Risk (CVaR), however, they do not admit a Rockafellar--Uryasev representation that admits tractable Wasserstein reformulations.
PAPER REPORTS · Proposed model, (rho, lambda)=(0.005, 0.10), FTSE 90 stocks, 3,341 OOS days 2012-2026, gross of transaction costs: ann. · Proposed model, (0.001, 0.10), same sample, gross: ann. return 20.62%, ann. vol 20.52%, Sharpe 1.005, MaxDD 44.41%,…
Abstract This study examines the predictive relationship between sentiment extracted from Google News headlines and the log spreads of cointegrated or highly correlated stock pairs, aiming to enhance pairs trading profitability.
PAPER REPORTS · MA_V, Full-Predicted gn_a: return 301.52%, Sortino 1.029, Sharpe 0.693, Max DD 0.016, 181 trades (68-day test period,… · MA_V, Full-Predicted rand_a (random sentiment): return 314.36%, Sortino 0.446, Sharpe 0.686, Max DD 0.021, 325 trades…
Reality may establish that an outcome occurred without identifying which evolving procedure produced it or why. This distinction matters in production ML systems whose code, configuration, and artifacts change while external feedback accumulates.
PAPER REPORTS · Full year 2025-10-01 to 2026-09-30 (241 daily obs), net of recorded actual settlement costs: total return +11.1391% vs… · Full year multi-factor (liquidity/momentum/volatility proxies) annualized intercept 13.52%, HAC(3) p=0.226
We develop a framework for an investor who trades until she either reaches a financial goal or an exogenous deadline arrives. Analogous to utility functions over wealth, we measure satisfaction with the timing of reaching a goal by a discount function.
OUR BACKTEST · Sharpe 0.63 · Return +44.3% · Max DD -26.3%
Shallow models are special cases of deep models, and deep models theoretically have the potential to outperform the shallow ones. However, the existing empirical asset pricing literature provides strong benchmarks for shallow models.
PAPER REPORTS · Deep ResNet+ (depths 11-20, spec-averaged): annualized VW decile long-short SR 2.07, monthly mean 3.48%, SD 5.82%, Feb… · Deep ResNet+ FF5 alpha 3.35% per month (significant at 1%, Newey-West 12 lags), Feb 1987-Dec 2023, gross of costs
Learning effective representations helps characterize the structure and dynamics of equity markets from financial data with a low signal-to-noise ratio.
PAPER REPORTS · CN_ALL top-30 equal-weighted long-only, 21-day overlapping batches, test Jan 2024–June 2026, net of 5 bps per unit… · US_ALL top-30 minus bottom-30 long-short, same horizon and costs, test Jan 2024–June 2026: Net annualized return…
In this paper, we present robust portfolio selection models by incorporating a reward and penalty mechanism into portfolio management.
OUR BACKTEST · Sharpe 0.97 · Return +77.6% · Max DD -27.8%
Formulaic alpha discovery seeks symbolic expressions that predict cross-sectional asset returns.
PAPER REPORTS · CSI300, test 2023-2025, long-only top-20% daily cohorts held 20 days, net of 5bp buy / 15bp sell, mean of 5 runs: IC… · CSI500, test 2023-2025, same protocol and costs: IC 0.0444, ICIR 0.2855, RankIC 0.0763, RankICIR 0.4578, annualized…
Factor mining seeks to discover signals from financial data that predict future asset returns and guide portfolio construction. Automated factor mining now spans genetic programming, reinforcement learning, generative models, and large language model agents.
We study when to buy a share that will later be sold optimally, when the price follows a geometric multi-skew Brownian motion whose skew levels model support and resistance.
OUR BACKTEST · Sharpe 0.21 · Return +40.7% · Max DD -78.0%
We develop a price-based framework for stochastic portfolio theory in which trading strategies are generated from nominal price weights and evaluated relative to a price-weighted benchmark.
PAPER REPORTS · Cap-based p-diversity-weighted portfolios, terminal log relative wealth vs cap-weighted index on U^S (2002–2021,… · Cap-based p-diversity-weighted portfolios, terminal log relative wealth vs cap-weighted index on U^P (2002–2021, no…
OUR BACKTEST · Sharpe 0.38 · Return +39.6% · Max DD -47.5%
The enhanced index tracking (EIT) portfolio selection problem aims to construct a portfolio that is expected to outperform a benchmark index.
PAPER REPORTS · M-ER, known mean/covariance, short selling allowed, OOS Jan 2020-Dec 2024, monthly rebalancing, transaction costs not… · M-TSV, known mean/covariance, short selling allowed, same period, costs not stated: mean return 0.048939, SD 0.150532,…
OUR BACKTEST · Sharpe 0.70 · Return +62.4% · Max DD -32.5%
Financial LLM agents are often evaluated by comparing their end-to-end returns with those of a baseline and testing the paired difference against zero.
PAPER REPORTS · Full agent (A0) vs frozen-rule baseline, 723 earnings events, 2020-2024: gross deployment value +15.2 bps/event… · Same comparison net of a pre-stated 40 bps cost per nonzero event position: -1.2 bps/event (95% CI [-59.8, +54.3]),…
Abstract The fact that the solution of the Markowitz model is numerically unstable is recognized as one of the principal reasons for its poor out-of-sample results when applied in practice.
PAPER REPORTS · Out-of-sample Sharpe ratio of the μp=β (δ-stable) portfolio, daily data 2000–2020, rolling window, net of 10 bp ×… · Same setup, DAX: 0.0099 (w=120), 0.013 (w=180), 0.0206 (w=240), 0.0312 (w=480).
OUR BACKTEST · Sharpe 0.66 · Return +49.0% · Max DD -31.1%
The complex and nonlinear behaviors of financial markets make it exceedingly challenging for average investors to evaluate the performance of a specific asset or make meaningful predictions about its future behavior.
PAPER REPORTS · Directional hit rate (MDA) of the LSTM forecaster on a random 80/20 holdout validation set (27,433 samples, 159 stocks,… · Diebold–Mariano statistics vs baselines on the same validation set: 3.42 (p = 0.001) vs persistence and 2.15 (p =…
We propose an interactive robo-advising framework that learns personalized risk preferences from scores provided by clients.
Short-horizon price-trend prediction from limit order books in equity and intraday electricity markets requires models that combine predictive quality with low single-sample latency and a small serialized model size to keep pace with rapid and continuous…
PAPER REPORTS · Classification performance only. These are not trading returns: no Sharpe, PnL or cost assumption is reported, and the… · MBOFormer test macro-F1 (mean of 3 seeds), h=10/20/50/100: - EPEX (3 test days, March 2021): 0.651/0.577/0.517/0.472 -…
We study whether model diversity survives selection into trading. In synthetic markets with a fixed mixture of three language-model families, news presentation changes their representation among submitted orders.
We study finite-horizon portfolio optimization with proportional transaction costs and trading opportunities arriving at the jump times of a Cox process.
OUR BACKTEST · Sharpe 0.52 · Return +0.0% · Max DD -0.0%
Liberalisation has been a catalyst for the strengthening of India’s banking sector; however, financial distress, fraud, and unethical practices continue to threaten the stability of the financial and stock markets.
Decision-focused learning (DFL) trains predictors through downstream objectives, but a different loss need not provide an independent parameter-update direction.
PAPER REPORTS · Neural DFL vs MSE, N=100, K=20, 9 annual test folds 2016–2025: annualized TE 0.0276 vs 0.0331 (−16.5%), one-sided… · Same neural folds, K=20: worst-fold TE 0.0360 vs 0.0564 (−36.3%), max tracking drawdown 0.0306 vs 0.0362 (−15.5%),…
OUR BACKTEST · Sharpe 0.71 · Return +69.7% · Max DD -35.0%
Machine-learning signals built from financial text treat what institutions say, and what the media repeat, as evidence about value. But whoever shapes a narrative may be trading against it.
PAPER REPORTS · Linear model, raw voices + theory features: out-of-sample cross-sectional IC 0.171±0.018 (simulated main market, 5… · Gradient boosting, raw voices + theory features: IC 0.118±0.019 (simulated main market, 5 seeds; costs not stated)
Global shocks - ranging from climate-related disasters and geopolitical conáicts to pandemics - transmit rapidly across borders and shape Önancial market co-movements.
In a recent paper, Schmelzer and Hastie argue that Markowitz's Critical Line Algorithm and the LASSO path trace the same curve. Here we use that identity to compute efficient frontiers with a stock LASSO solver, \texttt{lars\_path} from \texttt{scikit-learn}.
OUR BACKTEST · Sharpe 0.00 · Return +0.0% · Max DD 0.0%
We study the joint dynamics of the best bid and ask prices with a spread-gated Hawkes-flocking model.
Abstract. In this paper, infinite horizon stochastic difference equations and backward stochastic difference equations with fractional noise are studied. The main difficulty comes from the self-dependence of fractional noise on an infinite horizon.
OUR BACKTEST · Sharpe 0.59 · Return +40.5% · Max DD -26.3%
OUR BACKTEST · Sharpe -0.03 · Return -1.8% · Max DD -19.0%
This paper examines whether a cointegration-based pairs trading strategy between PepsiCo and The Coca-Cola Company is statistically robust and economically exploitable.
PAPER REPORTS · In-sample 2018–2023, θ*=(2.15, 0.50): annualised net Sharpe 0.67, net P&L $16,941 on $100,000, 9 round-trips. · In-sample 2018–2023 excluding the COVID window: annualised net Sharpe 0.28, net P&L $5,759, 8 trades (0.20% costs).
OUR BACKTEST · Sharpe 0.11 · Return +0.2% · Max DD -1.4%
In this work, we study portfolio optimization under the stochastic discount factor (SDF) framework by learning market state representations that capture the underlying risk structures of financial data.
PAPER REPORTS · Sharpe ratio 1.062 (out-of-sample rolling 1-year test windows within June 2011–June 2020, 7-day rebalancing;… · Sortino ratio 1.352; Calmar ratio 0.924 (same setting; costs not stated)
Predicting stock price movements is highly challenging due to the noisy, nonlinear, and multi-factor nature of financial markets.
OUR BACKTEST · Sharpe 0.70 · Return +20.9% · Max DD -6.5%
News may reveal systematic risk, but whether its context enhances the construction of systematic risk factors is still unclear.
PAPER REPORTS · Spherical ST + sparse-soft c-TF-IDF + multi-horizon IPCA, L=60: annualized OOS excess-return Sharpe 1.0334, Sep 2020 to… · Same raw spherical portfolio: annualized volatility 81.68%, maximum drawdown 62.23%; not risk-managed, not…
While symbolic regression (SR) has been successfully used in science to discover new equations, its use in financial valuation is hindered by several limitations.
PAPER REPORTS · Out-of-sample (last 20% of quarters) next-quarter price-level MAPE, not trading performance; no portfolio, Sharpe,…
OUR BACKTEST · Sharpe 0.41 · Return +37.0% · Max DD -44.3%
Option-implied factors are largely, but not entirely, spanned by the equity factor zoo. We construct 137 option-implied characteristics for optionable U.S.
PAPER REPORTS · bakshiKurt long-short factor (value-weighted decile, S&P 500 constituents, 30-day maturity): -11.23% annualized mean,… · ivs_convexity long-short factor: -14.78% annualized mean, vol 17.94%, Sharpe -0.82, MDD -96.94%, skew -3.59, t = -2.57;…
OUR BACKTEST · Sharpe -0.19 · Return -21.5% · Max DD -44.4%
This paper investigates cost-sensitive online window size selection for portfolio management under changing market conditions.
PAPER REPORTS · Hedge, DJIA 2021/03/04-2024/02/25, net of c=0.001 turnover cost: cumulative return 41.6977%, MDD -12.6326%, annualized… · Fixed Share, DJIA 2021/03/04-2024/02/25, net of c=0.001: cumulative return 38.1074%, MDD -12.9282%, annualized Sharpe…
The National Best Bid and Offer (NBBO), the consolidated "now" at the centre of U.S. equity market structure under Regulation NMS, requires comparing price events at exchanges whose separation places those events outside one another's light cones.
We develop a model-agnostic framework for noise reduction in high-dimensional time series that explicitly targets optimal recovery of a low-dimensional latent dynamic component contaminated by observational white noise.
PAPER REPORTS · Macro panel one-step-ahead forecast (not a trading strategy): average MSE 23.47 (standard error 10.87) for VAR(2) on…
OUR BACKTEST · Sharpe -0.50 · Return -21.3% · Max DD -34.9%
The equal-weighted portfolio is a passive, rule-based strategy that has historically been difficult to outperform, delivering higher returns than the capitalization-weighted "market" benchmark across many markets and periods.
PAPER REPORTS · Mean-reverting frictional λ*,mr, 1995–2024 monthly, net of 15bp proportional costs: - cumulative net return 44.92 -… · Trending frictional λ*,trend, 1995–2024, net of 15bp costs: - cumulative net return 31.41 - return 0.13, volatility…
OUR BACKTEST · Sharpe 0.24 · Return +0.0% · Max DD -0.0%
Language-model agents now run the whole of quantitative factor research: they propose investment factors, backtest them, select the survivors and retire them. We ask which of those jobs an agent should keep.
PAPER REPORTS · Certified (frozen-referee) book, 4-family library, 20 groups of 5 seeds, campaigns starting 2016-2019 through 2026-08:… · Deflated Sharpe ratio 0.49-0.69 against 108 groups.
Financial time series evolve across multiple temporal resolutions, challenging forecasting systems to incorporate newly available information without repeatedly recomputing unchanged representations.
PAPER REPORTS · HARN test-split forecast error (not a trading strategy; no costs or P&L), AAPL M15, 2025-03-06 to 2026-08-10: MAE… · HARN test-split forecast error, EURUSD M15, 2025-12-19 to 2026-07-29: MAE 0.000306±0.000002, RMSE 0.000467, sMAPE…
Stock price forecasting is a long-standing challenge in computational finance, driven by the inherent randomness of markets and complex temporal patterns.
PAPER REPORTS · CSI300 test (2017-01-01 to 2020-08-01), Qlib top-50 long, 20 replacements/day: excess annualized return 0.1809, excess… · CSI500 test (2017-01-01 to 2020-08-01), same strategy: excess annualized return 0.1529, excess information ratio…
Forecasters often score the same units per date against one standardized realized outcome. We show that every standardized forecast splits exactly into a component aligned with this common target and a component uncorrelated with it.
PAPER REPORTS · Three-way equal-weight selection, LLM equity panel, 157 weekly test dates Mar 2023–Jun 2026: relative-score risk 1.079,… · Three-way equal-weight selection, ETF panel, 196 monthly test dates (2005–2026 sample): relative-score risk 1.076,…
OUR BACKTEST · Sharpe 0.14 · Return +27.2% · Max DD -59.8%
Abstract. We study equilibrium feedback strategies for a family of dynamic mean-variance problems with competition among a large group of agents.
OUR BACKTEST · Sharpe 1.68 · Return +3.0% · Max DD -0.3%
Financial language models can transform unstructured firm-specific news into structured decision signals, but financial AI research lacks an integrated deployment framework for evaluating whether those signals remain useful in financial decision systems.
PAPER REPORTS · Long-short net Sharpe 2.85 (LLaMA-3, value-weighted quintile, net of 5bp one-way costs, 10% ADV cap, Jun 2024-Jan 2026) · Mean daily net return 0.34%, daily vol 1.89%, max drawdown -12.3%, cumulative long-short return 180% (LLaMA-3, same…
Modeling the dynamics of option implied volatility surface (IVS) is crucial for pricing, hedging, and risk-managing option portfolios.
Abstract This research utilizes explainable artificial intelligence (XAI) techniques to explore the relationship between size-sorted environmental, social, and governance (ESG) portfolio indices (large-cap, mid-cap, and small-cap ESG portfolios) and their…
This study examines capital market reactions to the gazettal of Hong Kong's Stablecoin Ordinance. This event provides a clearly identifiable informational signal that resolves regulatory uncertainty.
PAPER REPORTS · Cumulative average abnormal return of 13.0% over the 2-day window (-1, 0), t = 8.230 (CAPM), event date May 30, 2025;… · Cumulative average abnormal return of 18.8%-18.9% over window (-1, +3), t = 7.661 (CAPM) / 7.697 (FF3); no transaction…
We study a representative-agent Epstein-Zin economy with geometric dividends and a hidden finite-state Markov drift.
In a statistical factor model, principal components (or eigenvectors) of a sample covariance matrix serve as estimates of {\it principal directions}, the true drivers of co-movement of a collection of observed variables.
OUR BACKTEST · Sharpe 0.52 · Return +30.7% · Max DD -31.0%