Research
A continuously updated feed of research papers that pass our automated relevance screening for systematic trading — plus every paper we have published a review of, whatever it scored. 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.
15,697 papers screened · 250 on the radar · 22 shown
Transaction costs can make or break a trading strategy, particularly in relative-value trading of commodity and macro markets, where edges are a few basis points. Price impact is a central component of transaction cost.
PAPER REPORTS · Net P&L, monthly average over 2004-2011 (96 months), in basis points of $1B gross limit, after simulated impact cost…
This paper develops a mechanism through which costly changes in the representations used for portfolio choice can contribute to persistent signed order flow.
This paper develops uniform inference and certified capacity decisions for an estimated financial stability boundary. Conditional risk, temporary cross-impact, and effective risk-bearing capacity are jointly estimated from dependent observations.
PAPER REPORTS · Capacity/regret under the baseline loss convention (simulated 60-cell design, no market data): Projected safe - planned… · Under the high convention-loss calibration: projected-safe mean regret 0.107, below pointwise delta 0.120 and plug-in…
We study whether nuclear and energy-adjacent equity options exhibit a harvestable variance risk premium. Using CRSP and OptionMetrics data for 2000-2024, we construct a systematic cash-secured short-put strategy on a curated universe of nuclear-related firms.
PAPER REPORTS · EW put unconditional, 2000-2024 (300 months): 18.7% annualized return, 2.4% annualized volatility, Sharpe 7.81, MaxDD… · CAP-10 unconditional: 18.6% return, 2.4% vol, Sharpe 7.79, MaxDD 0.0%
Small-cap-inclusive equity universes contain recently listed and intermittently traded securities, so enforcing a common look-back discards a substantial fraction of the available information.
PAPER REPORTS · Annualized five-session volatility 11.17%, January 2000 - December 2025, net of all modeled execution costs… · Sharpe 0.814, same period, net of execution costs
Classical option-hedging methods like Black-Scholes delta assume constant, free rebalancing, which real markets don't allow. Deep hedging trains a neural network to handle these frictions directly, and prior work reports strong results.
PAPER REPORTS · Whalley-Wilmott (paper's best strategy), test period Sep 2023-Dec 2024, 11,546 episodes, 5bp round-trip cost: mean… · Whalley-Wilmott cost saving vs BS delta: -$1.79 per episode, 95% CI [-2.21, -1.39], p < 0.0001 (test period, 5bp cost)
Large language models (LLMs) are increasingly used to discover trading strategies, and much of the resulting literature shares a methodological weakness: many candidate strategies are generated, the best is reported, and neither look-ahead bias nor the…
PAPER REPORTS · Best gpt-4.1 discovery (E3, RSI x volume, 453-stock universe): design Sharpe 1.69 (2017-2021), evaluation Sharpe 0.18… · Best claude-sonnet-5 discovery: design Sharpe 0.44 (2017-2021), evaluation Sharpe -0.33 / -29% (2022-2025), DSR 0.18,…
OUR BACKTEST · Sharpe -0.10 · Return -10.8% · Max DD -47.8%
We study discrete-time asset pricing with bid-ask spreads and model uncertainty. The family of probability measures enters the no-arbitrage condition through the union of its supports.
At 15-minute horizons, directional mean reversion is far stronger and more pervasive in cryptocurrency markets than in US equities: scored under one matched, strictly out-of-sample protocol, 90% of 183 Binance pairs carry significant directional reversal…
PAPER REPORTS · Gross edge per trade peaks near 1.3 bp of notional (BTC/ETH, 15m, 2025-01 to 2026-02) against a 5 bp cheapest maker… · Directional accuracy rises monotonically with confidence threshold, clearing 56% on the most confident bars (BTC/ETH);…
Deep hedging is a data-driven approach to learn hedging strategies. It relies on synthetic price paths generator, as real market data is often limited for training.
OUR BACKTEST · Sharpe 1.78 · Return +5.9% · Max DD -0.6%
Abstract Market timing models aim to anticipate short-term market movements according to a given source of information. Such information could be extracted from an analysis of history or a forecast of the future.
PAPER REPORTS · S&P500 timing, 2018: index -6.7% annualized; Strat1-L 3.8%, Strat1-LS 14.3%, Strat2-L 0.8%, Strat2-LS 8.2% (no… · S&P500 timing, 2023: index 21.6%; Strat1-L 21.9%, Strat1-LS 22.1%, Strat2-L 25.5%, Strat2-LS 29.4% (no transaction…
OUR BACKTEST · Sharpe 0.61 · Return +49.0% · Max DD -31.2%
Reinforcement learning has gained increasing attention as a data-driven approach for stock trading. However, learning a policy that is both profitable and stable remains challenging due to non-stationary market behaviour and noisy reward signals.
PAPER REPORTS · DJI (test 1 Jan 2024 - 31 Mar 2025, 0.1% transaction fee both sides): annual return 21.785%±1.42, cumulative return… · FTSE (same period and costs): annual return 19.164%±1.36, cumulative return 24.596%±1.79, Sharpe 1.124±0.08, max…
This paper investigates whether textual tone derived from large language models (LLMs) can predict future stock returns. Using Korean news articles, we employ five LLMs to extract textual tones: BERT (KrFinBERT), DistilBERT, RoBERTa, ELECTRA, and Llama3.
PAPER REPORTS · BERT (KrFinBERT) equal-weighted quintile High-Low: 0.242% per day, t=3.772 (5.324% per month), May 2023-May 2024, gross… · BERT High-Low Fama-French 3-factor alpha 0.232% per day (t=3.582); 5-factor alpha 0.232% per day (t=3.566), same…
Current portfolio construction methods are either agnostic to the effects of idiosyncratic shocks (standard factor models) or to the latent data structure driving systematic returns (recent graph-based approaches).
PAPER REPORTS · Contagion Cut (proposed): CAGR 21.0%, Sharpe 1.07, Calmar 0.611, Jan 2019-Mar 2026, 0 bps transaction costs · Contagion Cut: Sharpe 1.04 at 10 bps, 1.01 at 20 bps, 0.929 at 50 bps (CAGR 20.5%, 19.9%, 18.3%), Jan 2019-Mar 2026
OUR BACKTEST · Sharpe 0.75 · Return +143.1% · Max DD -40.3%
Risk-aware Q-learning (RaQL) provides a model-free, two-timescale estimator for dynamic risk objectives, but its finite-budget behavior remains fragile: fixed inner-loop hyperparameters can produce unstable value estimates, persistent Bellman residuals, and…
PAPER REPORTS · Scheme 6 out-of-sample (918 daily obs, chronological test set, after 5bp turnover costs, mean over 20 seeds): Sharpe… · Scheme 0 fixed-parameter baseline out-of-sample (same test set, after 5bp costs, 20 seeds): Sharpe 0.5628 (sd 0.2281),…
OUR BACKTEST · Sharpe 0.34 · Return +16.6% · Max DD -10.4%
At the scale of seconds the observed mid carries a stationary, mean-reverting error around a latent efficient price.
Gerhold and Gülüm derived necessary calendar-vertical-basket conditions for finite call bid-ask quotes when the cash-settlement reference price lies inside a dynamically traded stock spread of bounded absolute width.
Parent-order execution is a core problem in algorithmic trading, where the goal is to split a large order into smaller orders while reducing execution costs.
PAPER REPORTS · Aggressive setting, April 2026, DS-v4-f: value-weighted price performance -2.26 bps vs TWAP benchmark price, i.e. · Passive setting, April 2026, DS-v4-f: -3.92 bps wbp, +1.07 bps vs TWAP and +0.71 bps vs strongest baseline; 100%…
We audit whether candle-based machine-learning models can turn predictions of cryptocurrency extrema or short-horizon outcomes into positive Binance Spot paper policies after assumed costs.
PAPER REPORTS · Frozen mandatory-daily selector: -6.72% compounded, 2026-07-01 to 07-19, 19 cycles, 3 wins/16 losses, 31 bps… · Frozen mandatory-daily selector cost stress, same period: -4.74% at 20 bps, -6.72% at 31 bps, -10.21% at 51 bps…
OUR BACKTEST · Sharpe 0.00 · Return +0.0% · Max DD 0.0%
We present a unified approach to designing trend-following (TF) systems and classify them into European, American, and Time Series Momentum categories.
PAPER REPORTS · European TF system: annualized Sharpe 0.47, monthly returns net of transaction costs and net of 2%/20%… · American TF system: annualized Sharpe 0.50, net of transaction costs and 2%/20% fees, 31 December 1999 to 30 June 2026…
OUR BACKTEST · Sharpe 0.10 · Return +8.4% · Max DD -30.4%
Gaussian Boson Sampling (GBS) provides a native photonic quantum heuristic for sampling dense subgraphs from adjacency matrices, offering a scalable physical approach to combinatorial graph search problems.
PAPER REPORTS · {"costs": "zero transaction costs and zero price impact assumed", "period": "2020 (trading effectively April 2020… · {"costs": "zero transaction costs and zero price impact assumed", "period": "2020", "sharpe": "2.050 ± 0.190",…
OUR BACKTEST · Sharpe -1.00 · Return -5.8% · Max DD -6.2%
This paper studies conditional allocation between a growth/technology ETF basket, denoted by $G$, and a defensive income/value-oriented ETF basket, denoted by $D$.
PAPER REPORTS · Selected smooth-score policy, 2017-06-28 to 2026-05-15, 10bp cost: 19.24% CAGR, 19.29% vol, Sharpe 1.01, Sortino 1.22,… · Selected policy vs 50/50 G/D: annual excess 1.78%, tracking error 3.74%, info ratio 0.48, max DD improvement 1.95%
OUR BACKTEST · Sharpe 0.92 · Return +111.2% · Max DD -31.6%