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 · 69 shown
Automated market makers (AMMs) are typically interpreted and evaluated as decentralized exchanges.
PAPER REPORTS · VBIAX, monthly TE, Jan 2, 2014 – Jun 30, 2026: G3M Pareto-dominates (higher CAGR and lower TE) for gamma in [2.73%,… · EQL NAV, economic mandate, Jun 19, 2018 – May 29, 2026: G3M dominates for gamma in [3.22%, 7.09%]
OUR BACKTEST · Sharpe 0.71 · Return +133.0% · Max DD -42.0%
We develop a unified modeling framework that connects two distinct types of bubbles defined in the literature: the rational bubbles (aka P-bubbles), and the local martingale bubbles (aka Q-bubbles).
OUR BACKTEST · Sharpe 0.47 · Return +220.6% · Max DD -131.6%
Agentic AI is gaining acceptance in asset management, but governance has not kept pace: 88% of surveyed finance professionals report no operational governance framework for agentic AI despite universal awareness of its deployment, and only 24 of 75 large U.S.
OUR BACKTEST · Sharpe -1.47 · Return -45.1% · Max DD -49.7%
This paper builds Path Portfolio Optimization: portfolio theory on a path-first framework in which the signature is the universal coordinate of the price path, and asks whether it survives estimation.
PAPER REPORTS · Cross-area lead-lag portfolio, sign-carrying excitation 1→2 with q=0.85: mean P&L +0.000189, s.e. · Cross-area, sign-carrying excitation 2→1 with q=0.85: mean P&L −0.000227, s.e. 0.000012, t=−18.92, annualized Sharpe…
OUR BACKTEST · Sharpe 0.45 · Return +21.4% · Max DD -19.5%
Local-stochastic volatility (LSV) combines vanilla marginals with richer smile dynamics, but calibration requires a slow, noisy and sequential McKean--Vlasov fixed point. We learn a projection-consistent operator for the calibration triple.
PAPER REPORTS · Calibration latency 0.60 ms/surface vs 98.5 ms particle baseline (paired, same hardware, synthetic held-out states) · Vanilla repricing RMSE 58.2 +/- 3.3 bps on 8 held-out surfaces, 2 seeds (spread across seeds, not a confidence…
OUR BACKTEST · Sharpe 0.53 · Return +5.6% · Max DD -2.0%
Conformal prediction has traditionally been used to quantify prediction uncertainty.
PAPER REPORTS · DEV 2016-2021 (1,511 days), Config A: 28.45% annualised net log growth, Sharpe 1.336, max drawdown 27.68%, Calmar… · DEV 2016-2021, Config B: 25.84% annualised net log growth, Sharpe 1.386, max drawdown 20.26%, Calmar 1.376, annualised…
OUR BACKTEST · Sharpe 0.41 · Return +45.1% · Max DD -40.4%
We propose an arbitrage-aware latent flow-matching framework for unconditional implied volatility surface generation.
OUR BACKTEST · Sharpe -0.06 · Return -1.2% · Max DD -5.1%
This note studies the conditional-density equation and its pathwise transformation in local stochastic rough volatility models, with rough Heston (rHeston) as the main explicit example.
OUR BACKTEST · Sharpe -0.45 · Return -4.2% · Max DD -7.5%
Recent advances in Generative AI have substantially improved financial sentiment analysis through post-trained financial large language models (LLMs).
PAPER REPORTS · FinSMART (static): cumulative return 264.9%, annualized return 91.5%, Sharpe 1.97, Sortino 2.40, Calmar 4.23, RankIC… · FinSMART (periodically retrained every 6 months): cumulative return 406.2%, annualized return 125.7%, Sharpe 2.41,…
OUR BACKTEST · Sharpe -0.46 · Return -48.2% · Max DD -75.2%
Finite multiplicative systems often cease to evolve when a lower continuation threshold is reached,whereas standard growth-optimal benchmarks assume uninterrupted continuation.
OUR BACKTEST · Sharpe 0.68 · Return +16.4% · Max DD -8.3%
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%
The theory of portfolios, and its allied notions and fundamental results concerning growth optimality, the numéraire property, and ``market viability'' -- which rules out the possibility of financing nontrivial future liability streams starting with…
OUR BACKTEST · Sharpe 0.51 · Return +48.5% · Max DD -23.8%
The distribution of a normal mean-variance mixture depends on the law of its positive mixing variable. We compare six parametric mixing laws with a grid nonparametric maximum likelihood estimator under the same determinant identification constraint.
PAPER REPORTS · Model-based lower-envelope CPT value at the robust optimum: -0.04478 at 5% annual reference return; -0.09245 at 10%… · Empirical holdout CPT value at the robust weights: -0.04867 at 5% reference; -0.10049 at 10% reference (holdout 483…
OUR BACKTEST · Sharpe 0.13 · Return +0.1% · Max DD -0.2%
Building on the identity that expected regret equals the covariance between costs and decisions, this paper develops the complete derivative theory of the covariance regret functional.
OUR BACKTEST · Sharpe 0.57 · Return +131.1% · Max DD -35.8%
The Observable Matrix Dynamics (OMD) approach monitors the time development of complex non-linear systems through the trajectory of a fixed-size distance matrix and its spectrum.
PAPER REPORTS · Early-warning ROC AUC (the paper's own signal, causal trailing 126-day features, label = forward peak-to-trough…
OUR BACKTEST · Sharpe 0.69 · Return +120.4% · Max DD -33.3%
Heavy-tailed diffusion models replace Gaussian noise by a Gaussian variance mixture: denoising Levy probabilistic models (DLPM) take the mixing variables i.i.d. across coordinates, while Student-t EDM shares one mixing variable per sample.
OUR BACKTEST · Sharpe -0.33 · Return -3.3% · Max DD -5.8%
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%