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
We develop a non-perturbative framework for stochastic-volatility option pricing organised by the two-particle-irreducible (2PI) effective action and the Dyson-Schwinger gap equations of quantum field theory.
Liquidity provision in automated market makers is typically analyzed at the pool level, implicitly assuming LP homogeneity.
Power systems with increasing variable renewable generation face greater uncertainty in scheduling and balancing. Intraday and balancing electricity markets facilitate position adjustments and real-time balancing close to delivery.
We model market impact as the response to submitted order flow net of counterflow from latent traders, activated when price displacements from the level that would prevail without the order exceed individual thresholds.
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%
In quantitative finance, standard regression losses are misaligned with the economics of return prediction.
PAPER REPORTS · BTC 15-min, CZAR tuned (alpha about 0.054). Test window 2,000 candles (about 21 days); costs, slippage and sizing… · BTC 15-min, CZAR fixed alpha=0.005 to 1: naive annualized Sharpe of 5.62, -0.95, 3.95, 1.15, 4.76 and 5.08…
We study the joint dynamics of the best bid and ask prices with a spread-gated Hawkes-flocking model.
Hedging a derivative by trading the underlying asset changes the payoff that the hedging intended to replicate. We study this phenomenon when trading generates price impact and execution costs.
We solve the perpetual liquidation problem for a geometric multi-skew Brownian motion carrying local-time pushes upward at a support level and downward at a resistance level, a model of technical analysis that is Markov in the price alone.
OUR BACKTEST · Sharpe -0.21 · Return -3.5% · Max DD -10.3%
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)
We introduce a deep kernel hedging framework that combines the flexibility of deep learning with the structural inductive bias of kernel methods.
PAPER REPORTS · S&P500 out-of-sample (Jan 1 2023 to May 31 2026), ATM European call, quadratic hedging with order-3 signature features,… · S&P500 out-of-sample (Jan 1 2023 to May 31 2026), ATM European call, CVaR hedging, frictionless.
OUR BACKTEST · Sharpe 2.30 · Return +22.0% · Max DD -2.8%
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…
Building on the forest expansion of Alòs, Gatheral and Radoičić and on the explicit Bergomi-Guyon smile expansion derived by Bourgey and Gatheral (2026), we derive fixed-point approximations, in terms of the implied total variance at a small number of magic…
This paper introduces oracle-parametrized automated market makers (OP-AMMs), i.e., automated market makers whose quoted price depends jointly on the pool reserves and an external oracle price.
PAPER REPORTS · Counterfactual arbitrage-only SPY backtest, one-second NBBO, 2023 (250 trading days, daily reset): the Pull-oracle GA…
We present an end-to-end deep learning framework for systematic options trading that directly embeds hedging behavior through explicit control of portfolio-level risk exposures.
PAPER REPORTS · DP (L1), α=10^2: annualized Sharpe 2.339, E[Return] 0.436, Vol 0.186, MDD 0.210, Sortino 3.583, Calmar 2.078, hit rate… · ENP (L2), α=10^1: Sharpe 2.260, E[Return] 0.409, MDD 0.236, hit rate 0.638. Zero costs.
Self-evolving agents aim to turn research feedback into reusable skills, tools, and research rules. Whether these accumulated capabilities continue to improve later research requires controlled evaluation.
PAPER REPORTS · Mean final portfolio IC, development 2025-01-01 to 2025-12-31 (in-sample, per-bar cross-sectional Pearson vs next… · Mean final portfolio IC, OOS 2026-01-01 to 2026-06-30, with development-period weights frozen (predictive IC only; no…
Market microstructure studies how trading rules turn orders into prices and allocations.
Monetary-policy announcements and central-bank communications play a central role in foreign exchange markets, yet their qualitative, unstructured form makes their forecasting value difficult to quantify.
PAPER REPORTS · Directional hit rate, out-of-sample rolling windows, 2024-06-13 to 2026-06-12, no transaction costs considered: 66.08%… · Directional AUC 0.744 at 1h, 0.729 at 3h, 0.707 at 8h, 0.634 at 24h. Balanced accuracy 0.721, 0.698, 0.705, 0.626.
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%
The internal-models approach of the Fundamental Review of the Trading Book (FRTB-IMA) determines market-risk capital at the aggregate level of a bank's approved trading desks, but it does not say how that charge should be attributed to individual trades.
Whether abnormal returns around different pharmaceutical policy events exhibit similar patterns, and whether these patterns vary across industry-index levels, return scales, and event windows, has received limited comparative examination within a unified…
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%
We study simple predictable processes whose coefficients are represented by neural networks. On finite measure spaces, we establish density results for neural networks in Orlicz spaces.
This article is concerned with the asymptotic shape of quantile surfaces, defined as the set of quantiles at a given level $α$ generated by a controlled one-dimensional distribution.
OUR BACKTEST · Sharpe 0.53 · Return +55.1% · Max DD -40.5%
Private and encrypted mempools hide pending transactions to stop sandwich attacks and other forms of maximal extractable value (MEV), but what they hide is rarely everything: a transaction's pair, direction, and a coarse range for its size can still leak.
Abstract The Probability of Informed Trading (PIN) treats informational events as independent across trading days, leaving it silent on how long informational regimes last.
We investigate the systemic macroscopic dynamics emerging from Limit Order Books (LOBs) populated exclusively by autonomous reinforcement-learning agentic traders.
Abstract Binary direction classifiers can appear stable on one chronological split while offering little predictive or economic value out of sample.
PAPER REPORTS · Full AND-gate (LightGBM + trend + Hurst), 3 expanding walk-forward folds, Mar-May 2025, 9 configurations: precision… · Full AND-gate unlevered next-bar accepted-signal mean return: -0.16 bps at 0 cost, -10.16 bps at 10 bp round-trip cost,…
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…
European electricity trading in the EU operates as a constrained multi-layer system in which legal design, exchange microstructure, and network physics are executed jointly across forward, day-ahead, intraday, and balancing horizons.
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%
Commodity option surfaces contain information beyond the at-the-money volatility level.
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%
Macroeconomic crises are rare, yet they can have large effects on asset prices. Because the probability of entering a crisis from normal times is small relative to the probability of recovery, the dynamics are nearly reducible: setting the crisis-entry…
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…
Volatility forecasts play a central role in financial risk management because their overall level and day-to-day movements affect downstream decisions. Most studies compare forecasting models while keeping the training loss fixed.
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…
We study the infinite-horizon optimal investment and consumption problem in a general class of continuous financial markets, where uncertainty is driven by a continuous non-decreasing stochastic clock representing accumulated variance.
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%
We examine the conditional volatility dynamics of the USD 1Yx10Y forward swap rate using GARCH(1,1), GJR-GARCH(1,1), and a two-regime Markov-switching GARCH (MSGARCH) model.
PAPER REPORTS · 95% one-day-ahead interval coverage, 1500 test days (34.36% of sample): GJR 94.00%, GARCH 93.80%, MSGARCH 93.8% · 1300 test days: GJR 93.62%, GARCH 93.23%, MSGARCH 93.154%
In this paper, we study the diversification properties of convex combinations of iid random variables with infinitely divisible distributions.
OUR BACKTEST · Sharpe 0.45 · Return +46.7% · Max DD -40.4%
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…
We study affine stochastic Volterra equations on the cone of symmetric positive semidefinite matrices.