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
To extend conventional model-level feature importance to economically meaningful portfolio outcomes and decisions, we propose a local first-order attribution-propagation framework that maps allocation-function feature exposures to local sensitivities of…
PAPER REPORTS · XGB baseline, OOS 2006-2024: net Sharpe 0.6175 (annualised, 5bp per unit turnover); gross Sharpe 1.0207; net mean 2.55%… · FFN baseline, OOS 2006-2024: net Sharpe 0.5750 (5bp); gross Sharpe 1.3051; net mean 2.65% p.a.; net FF5 alpha 1.12%…
OUR BACKTEST · Sharpe -0.82 · Return -24.2% · Max DD -31.5%
Formulaic alpha mining seeks to discover executable expressions that capture predictive market signals in a vast, noisy search space.
PAPER REPORTS · AlphaRLM-8B CSI 300: annualized excess return 12.14% (0.1214±0.0011), MDD -6.15%, IC 0.0256, RankIC 0.0424, ICIR… · AlphaRLM-8B CSI 1000 (CSI 300-trained factor pool): annualized excess return 17.45%, MDD -11.98%, IC 0.0302, RankIC…
OUR BACKTEST · Sharpe 0.83 · Return +105.8% · Max DD -50.8%
Temporal point processes are used both to measure market mechanisms, for example how fast prices absorb news and how much of the reaction is the market responding to itself, and to predict the next event.
Portfolio decisions are often made under uncertainty about expected returns, and investors revise their beliefs as new information arrives.
OUR BACKTEST · Sharpe 1.07 · Return +152.8% · Max DD -57.4%
We study a two-sided singular stochastic control problem in which changes in consumption carry utility costs and the risk premium follows the mean-reverting Kim-Omberg model.
PAPER REPORTS · AIM_PU_CVaR (real data, daily, 2020-01-01 to present, T=1471 days): Sharpe ratio 0.7718; annualization not stated; no… · AIM_PU_CVaR: total reward 1.5048, mean daily return 0.0010, total CVaR-like cost 0.0194, 23 crisis days (>5% daily…
OUR BACKTEST · Sharpe 0.98 · Return +61.8% · Max DD -22.0%
Conditional volatility-based option pricing research generally emphasizes improving volatility inputs, but has not yet fully explained the relative contribution of each parameter to variation in simulated option-pricing responses for Indonesian index stocks.
We examine climate variables in a pipeline for dynamic Value-at-Risk (VaR) of the SRI-KEHATI ESG index and the IHSG (Jakarta Composite Index).
PAPER REPORTS · Main QRNN backtest, test N=300 (Nov 2023-Dec 2025), VaR violation rates and Kupiec p: SRI-KEHATI tau=0.01 0.33% (1… · Main QRNN DM statistics on pinball loss (positive = QRNN better), all p<0.001. Vs HS-VaR: SRK 4.31 / 6.43 / 7.23 and…
Abstract: This study aims to analyze stock price developments, fundamental performance, and stock valuation as a basis for determining investment decisions in banking companies listed on the Indonesia Stock Exchange during the 2020–2025 period.
This study examines whether Shannon entropy regularization can mitigate the concentration associated with classical minimum-variance portfolio optimization while preserving risk-adjusted performance.
PAPER REPORTS · ERMV (λ=0.01), full sample (in-sample Σ), 2015–Jul 2026, daily simple returns, no transaction costs: annualized mean… · ERMV (λ=0.01), full sample, no costs: Sharpe 0.2966 at 4.5% rf, 0.5140 at 2% rf, 0.6879 at 0% rf.
This study examined the volatility effects of climate policy uncertainty on renewable energy stock returns in Nigeria using the Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) model.
This desk-review article examines the ecological damage and lost investment opportunities associated with the prevailing economic paradigm.
This study examined the effect of dividend policy son the stock market performance of listed Consumer Goods Firms in Nigeria. The study covered all 21 firms within the sector, with the Bird-in-Hand theory serving as the theoretical foundation.
How can we identify stable patterns to accurately predict stock price movements amidst severe market noise? Predicting stock price movements is a crucial problem in financial data mining, and has attracted significant attention from researchers and financial…
PAPER REPORTS · COVID-19 crisis (test 2020-01 to 2020-03), threshold long-short, 6 bps cost on sells, zero risk-free rate: S&P500 ASR… · AI rally (test 2024-01 to 2024-06), same protocol: S&P500 ASR 2.842, RMDD 6.8%; CSI300 (long-only) ASR 1.653, RMDD…
Correlation matrices combine nonlinear positive-definiteness constraints with a simultaneous row-column permutation symmetry. Their generation therefore involves two distinct problems.
OUR BACKTEST · Sharpe 0.00 · Return +0.0% · Max DD 0.0%
This paper studies semi-static variance-optimal hedging of variance swaps in the rough Heston model under a risk-neutral measure.
PAPER REPORTS · In-model (simulated, risk-neutral, frictionless) hedging error reduction of the paper's semi-static hedge vs purely… · Same setting with m=12 options: 97.13% (H=0.1), 99.32% (H=0.3), 99.96% (H=0.5).
A realized tail-risk conditional autoregressive expectile (RTCARE) model is proposed for joint forecasting of value-at-risk (VaR) and expected shortfall (ES).
PAPER REPORTS · RTCARE out-of-sample mean FZ0 loss (IBM, 3513 rolling one-day forecasts within 2005-2024): 1.100 (5%), 1.379 (2.5%),… · RTCARE NO INT out-of-sample mean FZ0 loss: 1.097 (5%), 1.372 (2.5%), 1.769 (1%), 2.057 (0.5%)
OUR BACKTEST · Sharpe 1.82 · Return +9.2% · Max DD -6.2%
This paper studies entropy regularization for the discrete-time dynamic mean--variance portfolio problem with no-shorting constraints.
PAPER REPORTS · Rolling Fama-French 10 industries, 72 non-overlapping six-month out-of-sample episodes, first beginning Jan 1990 and… · Simulated data (lognormal mixture, 10,000 test paths, no costs), deterministic mode policy: - tau=10^-4: terminal mean…
This paper studies exit timing for SPX short-straddle portfolios using a two-stage supervised and reinforcement-learning framework.
PAPER REPORTS · Supervised MLP exit policy, OOS 2024-2026 (T≈2.42y), stress-budget compounding sizing, bid entry/ask exit plus… · AC+MLP, 7 seeds, OOS 2024-2026, same costs: cumulative return 37.54% ± 0.92%, ARC 14.05% ± 0.32%, ASD 7.97% ± 0.14%,…
Abstract Time series forecasting models play a crucial role as decision support tools in various real-world domains.
PAPER REPORTS · Multi-stock swing trading (17 stocks, equal budget, 3-day confirmation), uptrend Jul 1–Dec 31 2021: average gain 7.64%… · Multi-stock swing trading, downtrend Jan 1–Sep 20 2022: average gain -0.34% across Max Shares 1/5/10 (-7.16%, 3.61%,…
Global financial markets are increasingly exposed to shocks that propagate rapidly across countries, sectors, and asset classes, generating synchronized volatility that reflects the systemic dimension of financial risk.
The rapid growth of crypto markets is increasing investment opportunities, but also volatility risks. There is a need to automate portfolio construction to rapidly adapt investment decisions to rapidly changing markets.
PAPER REPORTS · Crew B (30-day rolling Sharpe max), out-of-sample per Table 6: expected return 10%, volatility 10%, Sharpe 0.72,… · Crew B (30-day window), out-of-sample per the window-sensitivity table: expected return -20.58%, volatility 39.88%,…
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.
FLEX options are customized exchange-traded contracts allowing participants to choose nonstandard strikes, expirations, exercise styles, and settlement terms while retaining central clearing.
PAPER REPORTS · Rich-IV short straddle, research proxy (0.85 haircut, event close): N 40, mean P&L 1.5350% per trade, win rate 80.0%,… · Rich-IV short straddle, execution-stressed (1.25× median chain relative spread + $0.65/contract × 4 legs): N 40, mean…
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…
Renewed attention to the identity of Bitcoin’s pseudonymous creator has revived an old worry: that the roughly 1.148 million BTC mined by Satoshi and never moved represent a major tail risk for Bitcoin. This paper argues that the worry is overstated.
We represent (weighted-)selection-elliptical distributions as an affine combination of the $q$ selection variables plus an elliptical term whose direction alone is independent.
OUR BACKTEST · Sharpe 0.75 · Return +27.1% · Max DD -21.2%
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%,…
Structural price diffusivity explains many empirical regularities of market impact including the ``square-root law'' and its crossover to a linear regime for low trading rates \citep{bonart2026diffusive}.
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…
Wavelet-based financial forecasters typically use the transform only to denoise, or reduce it to a single spectral snapshot at the forecast origin, and the convolution that produces the coefficients is usually bilateral, so it can read past the forecast…
PAPER REPORTS · S&P 500 DSTNet asymmetric risk-off allocation, test 2023-06-01 to 2024-05-31, 10 bps per unit turnover, idealised… · NYSE DSTNet risk-off, same period, 10 bps: Sharpe 1.80, MaxDD 5.65%, CumRet 11.31%, exposure 56.77%, total turnover…
OUR BACKTEST · Sharpe 0.46 · Return +21.1% · Max DD -24.7%
As option markets grow and AI advances, agentic systems for option trading are gaining increasing attention.
PAPER REPORTS · Total return 18.32% over 2025-03-03 to 2025-08-29 (six-month out-of-sample), 10 underlyings; fills at bid-ask midpoint… · Annualized Sharpe ratio 1.60 (same period and costs)
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
The square-root impact law (SRIL), $I = Yσ\sqrt{Q/V}$, bundles two facts that a single mechanism must explain at once: a shape (impact proportional to square-root of traded volume $Q$) and an amplitude ($Y=O(1)$, independent of the participation rate…
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%
Risk evaluation under distributional ambiguity is central to decision making in finance, economics, and operations research. Wasserstein balls provide a natural way to describe uncertainty around a reference distribution.
OUR BACKTEST · Sharpe 0.58 · Return +43.5% · Max DD -29.9%
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%
Abstract Using Gate.io hourly spot-order-book archives from January 2022 through June 2023, this paper reconstructs a long-horizon five-second panel for comparing the direct Ether/Tether (ETH/USDT) quote with the synthetic Ether/Bitcoin (ETH/BTC) $$\times $$…
Abstract The energy and digital transitions are increasing demand for metals used in renewable energy, electrification, storage, and digital infrastructure.
Abstract We formulate a dimensionally consistent time-fractional Black–Scholes model through inverse-stable subordination. A product pricing measure fixes the clock law and operational numeraire, while clock risk remains unspanned.
We investigate a continuous-time financial market where the asset price exhibits weak (sublinear) mean reversion and has a nonzero drift.
OUR BACKTEST · Sharpe 0.09 · Return +0.0% · Max DD -0.1%
The growing importance of intraday trading in Europe, driven by the increasing penetration of renewable energy sources, has led to higher volatility and periods of market stress.
We give a unified analytic account of a finite bid--ask spread in a two-field reaction--diffusion order book. The model retains separate bid and ask densities in operational time, with diffusion, cancellation, reaction and external order creation.
This article studies a retirement planning problem from a new perspective in which a retiree delegates an initial lump sum to a professional fund manager.
We develop a posteriori primal-dual bounds for numerical approximations of European option prices in the Uncertain Volatility Model.
Deep hedging learns trading policies from historical or simulated market trajectories, yet under nonstationarity these training paths may not represent future market conditions.
PAPER REPORTS · Nonstationary Heston (simulated), European call, CVaR_0.95 of hedging loss, no transaction costs: WRAP-W far-future… · Nonstationary Heston (simulated) with proportional costs c=0.005: WRAP-U far-future CVaR 8.349±0.189 vs ERM-U…
Trade-sign errors can change measured trading costs even when classification accuracy is high. We validate the side of Polymarket's public trade prints against the taker leg of each print's on-chain settlement.
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…