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 · 248 shown
Quantitative trading is moving from isolated predictive models toward agentic workflows that combine reasoning, tool use, memory, and feedback.
This paper investigates the dynamic response of Shanghai crude oil futures (INE) to international benchmark price shocks and evaluates the evolution of market maturity from its inception to early 2025.
This study investigates the time-varying interactions between financial stress and selected financial assets within the Diebold–Yilmaz connectedness framework.
The study examines whether the information transfer between speculative positions and real interest rates in the gold price formation process operates as a linear, time-independent, and unidirectional mechanism, or whether it exhibits a nonlinear structure…
The standard Fama-French three-factor model assumes constant factor loadings for the market, size, and value factors.
Portfolio risk assessment ordinarily relies on reliable estimates of cross-asset return covariances, which are difficult to obtain in short, high-dimensional panels.
PAPER REPORTS · In-sample standardized variance percentile of the news-only allocation: 0.69%-1.33% across four prespecified capped… · Standardized in-sample variance 0.357, 8.3% below the equal-risk (inverse-volatility) benchmark and 35.6% above the…
OUR BACKTEST · Sharpe 0.47 · Return +44.2% · Max DD -29.9%
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)
The factor HJM stochastic volatility model introduced by Sepp and Rakhmonov (2025) obtains tractable swaption pricing by freezing the nonlinear swap-rate loading along a deterministic expected-state path.
We study the quadratic tracking problem of a general stochastic target process with absolutely continuous controls, with and without terminal constraint. We derive explicit, non-asymptotic upper bounds in terms of a Besov-type modulus of the target.
Haug and Haug extend the Margrabe exchange option by adding knock-in and knock-out provisions written on the ratio of two asset prices. This paper applies and develops their framework for stock-for-stock takeover bids with collars.
This paper studies European option pricing in a regime-switching Heston-Hull-White framework.
PAPER REPORTS · In-sample (train, 2 Jan-6 Aug 2024, 8,286 obs) DL-RS-HHW pricing error: RMSE 0.0072, MAE 0.0050 (option prices in yuan;… · Out-of-sample (test, 7 Aug-30 Sep 2024, 1,234 obs) DL-RS-HHW pricing error: RMSE 0.0179, MAE 0.0097
This paper provides robust empirical evidence that shocks to aggregate Research and Development (R&D) have persistent effects on macroeconomic dynamics and represent a significant risk for investors, as predicted by the ‘long-run risk’ literature.
PAPER REPORTS · Risk premium associated with effective R&D structural shocks: approximately 2% per year, estimated via Giglio and Xiu… · 4-year rolling-sum shock, 14 factors: premium 0.48, t = 3.28 (baseline specification)
In this paper, we study causal non-causal state space models to model time series characterised by a local explosive increase followed by a sharp decrease such as stock prices.
In financial markets, a sequential policy that reacts systematically to price movements may become predictable to other market participants.
PAPER REPORTS · Exposure-matched within-stock timing alpha, principal 10-minute Qwen3.5 price text: -45.7 bps per stock-day, 95% CI… · Chart-only 10m: -29.9 bps, CI [-33.7,-26.2], 14,937 stock-days; multimodal 10m: -48.9 bps, CI [-52.7,-45.0], 14,438…
Abstract Conventional financial market forecasting models are challenged by the non-stationarity, the existence of regime changes, the presence of structural breaks, and the phenomena of volatility clustering in financial markets.
PAPER REPORTS · Directional accuracy 87.5% ± 2.1, NIFTY-50 daily, 2010-2025, walk-forward validation, no transaction cost assumption… · MSE 0.012 ± 0.003 (normalized), RMSE 0.110 ± 0.014 (121.8 index points), MAE 0.084 ± 0.011 (93.1 index points), MAPE…
Bitcoin inverse options, traded on the Deribit exchange and settled in the underlying cryptocurrency rather than in fiat currency, combine extreme and genuinely rough volatility dynamics with a non-linear, currency-dependent payoff structure.
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%
Algorithmic trading now represents a market exceeding $20 billion, where even marginal gains in signal robustness can translate into economically significant returns.
PAPER REPORTS · Hybrid ensemble, OOS 2025 (252 trading days), 2.2bp per trade per leg: total return 51.26%, Sharpe 2.44, Sortino 5.35,… · Hybrid ensemble, OOS 2025: annualised CAPM alpha 0.423 (p = 0.011), beta 0.048, Probabilistic Sharpe Ratio 0.960
OUR BACKTEST · Sharpe 0.75 · Return +696.5% · Max DD -365.1%
We model equity markets using geometric Brownian particles entering and exiting at rank-dependent intensities.
PAPER REPORTS · p=0 (equally weighted) diversity-weighted portfolio capitalization growth: +3.4% per year above the front speed,… · p=1 (market) portfolio: -0.5% per year relative to the front, 1975-2024, frictionless
OUR BACKTEST · Sharpe 0.63 · Return +66.6% · Max DD -37.1%
This paper develops a unified framework for assessing systemic risk and identifying contagion channels in the global banking system using a Temporal Heterogeneous Multiplex Graph Neural Network.
PAPER REPORTS · MSE 0.0309 on one-quarter-ahead change in log(1+CDS), out-of-sample, N=336 bank-quarter forecasts (sample 1998-2025,… · MAE 0.1342, out-of-sample
Abstract House flipping has been increasingly popular in Poland since the mid-2010s yet it’s economic nature remains unexplored. This study investigates the problem of the primary source of profits of flippers – value creation generated by improvements (e.g.
PAPER REPORTS · Mean profit of all identified flips: 36.45% (profit relative to purchase price), 14 Polish cities, 2005-2023; no… · Method I sample overall average profitability 39.82% (text also states 39.92%); unimproved flips 32.82%; improved flips…
Abstract The emergence of cryptocurrencies has presented investors with novel portfolio diversification opportunities.
PAPER REPORTS · Unconstrained mean-CVaR with crypto: mean monthly return 2.63%, mean monthly CVaR 1.15%, mean monthly risk-return ratio… · Unconstrained without crypto: mean monthly return 0.46%, CVaR 0.42%, risk-return ratio 1.09%
Abstract Precious metals historically have been adopted as an effective hedging instrument by investors due to their price dynamics shaped in line with economic and financial risks.
We report a market in which a positive return is visible in prices yet cannot be realized by a fixed trading policy, and we measure why.
Coupled feedback networks are often monitored channel by channel even though cross-channel paths alter both stability margins and transmitted disturbances.
PAPER REPORTS · Detection power 1.00 with false-alarm rate 0.12 on zero-coupling entries under independent regime-switching gains (n =… · Detection power 1.00, false-alarm rate 0.22, off-diagonal RMSE 0.28 under correlated staircase gains (same design)
PAPER REPORTS · Out-of-sample RMSE (70-30 split, 2021–2024, no transaction costs): LLF BTC 0.541, ETH 0.256, USDT 0.244, BNB 0.676, BCH… · Out-of-sample MAE: LLF BTC 0.377, ETH 0.199, BNB 0.446, BCH 0.567, LTC 0.458, ICP 0.519, MATIC 0.612, USDT 0.137 (RF…
PAPER REPORTS · Optimized ESG portfolio: average conditional volatility 1.29% (2020) declining to 1.18% (2022) and 1.23% (2023-2024),… · Optimized ESG portfolio breach rates: 0.3526 volatility violations and 0.4261 drawdown violations on average 2020-2024…
PAPER REPORTS · US single-country equity portfolios, static risk-minimizing FX exposure (lambda=0), 1990s-2023, in-sample, no… · US single-country equity portfolios, unhedged (full exposure), same period: Sharpe 32.13% (CAD), 45.92% (INR), 31.62%…
PAPER REPORTS · Baseline HRP: annualised Sharpe 0.741, total return +417%, max DD -85%, 76 monthly rebalances 2020-02 to 2026-05,… · HRP-family variants span Sharpe 0.701-0.749 over the same window and cost assumption (best HRP_Dynamic_94 0.749,…
PAPER REPORTS · GMV portfolio realised variance (own model AL-MGARCH): 1.261 at h=1, 1.334 at h=5, 1.402 at h=22, vs MGARCH 1.382 /… · MV portfolio realised variance (own model AL-MGARCH): 2.241 at h=1, 2.352 at h=5, 2.437 at h=22, vs MGARCH 2.452 /…
PAPER REPORTS · Minimum Variance Portfolio (MVP), 2019-2025 daily, no transaction costs stated: mean daily return 0.0005519, daily… · Minimum Correlation Portfolio (MCP): mean daily return 0.0007516, std dev 0.0014739, Sharpe (std dev) 0.5099, Sharpe…
OUR BACKTEST · Sharpe 0.21 · Return +11.2% · Max DD -24.8%
PAPER REPORTS · Monthly PCI-based mean-variance portfolio (1871:02-2023:12), leverage/risk-aversion setting 6: return 2.3331,… · Monthly PCI-based portfolio, setting 8: return 2.9252, volatility 0.0260, Sharpe 16.6522 vs RV benchmark 0.8883; no…
Abstract High-dimensional multivariate normal (MVN) integration is a computational bottleneck in many statistical applications, particularly in finance and econometrics.
We develop a PDE-based methodology for pricing and hedging European contingent claims in general one-dimensional diffusion markets characterized solely by their scale function and speed measure, possibly without a classical SDE representation, and with…
PAPER REPORTS · Bachelier (premium 2.0), N_MC=2000, N^space_FD=4000, T=10, no transaction costs: MTE* −0.002 ± 0.008 and StDTE* 0.192 ±… · Skew-Sticky 1 (premium 0.271, κ₋₁=0.3, κ₁=0.7, ρ=1, r=0.2, ELMM exists): MTE* 0.058 ± 0.022 and StDTE* 0.506 ± 0.024 at…
This work complements our previous paper, which studies borrower-side strategies in decentralized lending markets, by focusing on lender-side capital allocation.
PAPER REPORTS · core-inspired strategy: 5.5% APY, $100k budget, Morpho USDC markets on Ethereum, Jan 1 2026 - Apr 1 2026, daily… · prime-inspired strategy: 3.3% APY, $100k budget, same period and cost assumption
We show that the key optimization results of the classical Markowitz portfolio selection theory, originally formulated for variance as the risk measure, remain available in explicit closed form under a broader class of strictly convex quadratic risk measures.
OUR BACKTEST · Sharpe 0.50 · Return +143.8% · Max DD -75.0%
Lead-lag relationships are widely used in financial time series, and many clustering algorithms based on them have been developed. The traditional DTW-KMedoids algorithm performs well both on the synthetic dataset and the real financial dataset.
PAPER REPORTS · Sharpe 0.866, annual return 6.21%, annual volatility 7.17%, max drawdown -63.908, hit rate 0.520, profit-loss ratio… · Sharpe 0.808 / 0.790 (KShape mod / med), lead strategy, 679 assets, same period; drawdowns -67.604 / -69.418
OUR BACKTEST · Sharpe 0.39 · Return +27.5% · Max DD -39.3%
This paper develops the first end-to-end application of cross-sectional learning-to-rank to the S&P 500 weekly options (SPXW) zero-day-to-expiration surface, integrated with margin-aware position sizing, an abstention rule driven by model uncertainty, and a…
PAPER REPORTS · Out-of-time 2025 annualized Sharpe 4.308 to 5.761 across seven sizing methods, net of Reg-T margin, tiered IBKR fees,… · Headline Edge Allocation OOT 2025: Sharpe 5.7612, Sortino 7.0291, annualized return 10.48% (excess of risk-free),…
Backtests of trading strategies are often selected after many parameter trials. A strong historical result can therefore reflect search luck rather than a persistent signal.
PAPER REPORTS · Genuine-edge discrimination AUROC 0.9890 in synthetic ground truth at headline difficulty (n = 2000, T = 1260 daily… · OOS-survival (Sharpe_OOS > 0) AUROC 0.863 and Spearman 0.611 vs realized OOS Sharpe, same synthetic headline cell
We study equilibria in a closed, fee-free constant-function market maker (CFMM) economy with two assets and two traders.
A companion paper \cite{ItkinDF2026} introduced the Diagonal Frog (DF) positivity-preserving schemes for anisotropic Fokker--Planck equations, advancing each directional substep by a Krylov-computed matrix exponential, which dominates the cost.
The stability of markets hosting leveraged exchange-traded products is governed not by any single product's loop gain but by the spectral radius of a loop-gain matrix, and scalar per-product monitoring underestimates system feedback by construction.
Large language models (LLMs) are increasingly used in investment decision-making, yet prior work shows that they exhibit systematic, model-specific investment preferences.
PAPER REPORTS · Weekly rebalanced equal-weight long-only top-100 portfolio from Qwen3-8B scores, 427 S&P 500 stocks, 29 signal weeks /… · Realized Sharpe of the top-100 portfolios is shown only graphically (Figure 5c, axis range roughly 2–4); no point…
OUR BACKTEST · Sharpe 0.52 · Return +57.3% · Max DD -40.6%
In this paper we propose a new formulation of the Bayesian Filter as used in the discrete-time Markov-Switching-Multifractal (MSM) model of volatility based on existing permutation symmetry within the likelihood structure.
OUR BACKTEST · Sharpe 0.90 · Return +54.5% · Max DD -20.2%
Understanding the propagation of extreme events is important in many economic and environmental applications, yet most econometric methods for causal inference focus on average effects rather than tail behavior.
Tick-level trade-and-quote data for the Tokyo Stock Exchange is distributed through the Nikkei NEEDS service as thousands of zipped CSV archives spanning four data types with era-dependent schemas and Japanese-language layouts.