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.
16,925 papers screened · 589 on the radar
Reinforcement learning trading systems published in the academic literature overwhelmingly rely on price-aggregate state representations (OHLCV bars) or limit-order-book depth features, leaving microstructure pattern theories from the practitioner literature,…
PAPER REPORTS · TSLA: +163.6% ROI, -27.5% max drawdown, 27,019 trades, held-out final 12 months of Jan 2020-Feb 2026 data, zero… · NVDA: +116.5% ROI, -47.8% max drawdown, 12,892 trades, same held-out 12-month partition, zero leverage, $0.0002/share…
We consider two canonical market-microstructure regularities: the long-memory of trade signs and the square-root law of meta-order impact. The point is not to propose new empirical laws, but to separate the clocks on which existing laws are defined.
Price-level limit order book (L2) data reveal aggregate liquidity but not the ordered queue required by price--time priority.
PAPER REPORTS · Passive-at-touch implementation shortfall, 1301.T, 18 held-out July 2025 dates, 1,080 episodes, zero… · Passive-at-touch implementation shortfall, 7911.T, same 18 held-out dates: 0.765 bps [0.547, 0.974] front, 0.926…
The favorite--longshot bias (FLB) is one of the most persistent return patterns in betting markets, but its prevalence in modern prediction markets and its relation to recurrent longshot demand remain unclear.
Stock price prediction remains challenging due to the non-stationary and noisy nature of financial time series.
PAPER REPORTS · S&P 500 2024 out-of-sample (365 days): total return 29.41%, Sharpe 1.43, Sortino 1.85, max drawdown -9.75%, win rate… · DJIA 2024: total return 21.44%, Sharpe 1.15, Sortino 1.75, max DD -8.94%, win rate 57.7%, 26 trades — vs buy-and-hold…
An ensemble of roughly 3,000 signals over 20 assets was reported to have approximately 90% correlation with the leading component of the asset-space return structure.
OUR BACKTEST · Sharpe -0.16 · Return -29.7% · Max DD -97.0%
In this note, we propose a general structural approach to model a default time $τ$ as the first-passage time (FPT) of a (``firm-value'') process $S$ below a (``debt'') barrier $K$ that comply with a pre-specified survival probability curve $G(t)=\Pr(τ>t)$.
We give a two-period counterexample to the absence of arbitrage for the posterior-weighted pricing rule in Estimate nothing by Duembgen and Rogers.
Forecasting financial markets remains challenging due to nonlinear dynamics, structural changes, volatility clustering, and uncertainty transmission across asset classes.
PAPER REPORTS · No trading strategy, Sharpe ratio, return, alpha or drawdown is reported anywhere in the paper; performance is reported… · Best-model out-of-sample R2 by target (one-step-ahead monthly, price levels, final 20% of sample): VIX 0.999982…
Abstract Counterintuitively, the S&P 500 Index rose between January 3, 2022, and December 29, 2023, while exchange-traded funds (ETFs) seeking to deliver $$2\times $$ and $$3\times $$ daily returns of the index delivered substantially negative returns.
OUR BACKTEST · Sharpe 0.05 · Return +0.3% · Max DD -3.2%
In recent years, when traditional portfolio optimization (PO) models deal with highly volatile and irrational market environments, they often face problems of deviation in return prediction and lag in risk response.
PAPER REPORTS · Annualized return 0.196 (out-of-sample test set within 2018-2023, daily rebalancing, no trading costs) · Annualized volatility 0.187; Sharpe ratio 1.048 with risk-free rate assumed zero (no trading costs)
Abstract This paper examines the effect of US-China tensions on stock market volatility across developed and emerging economies using a newly developed US-China Tension (UCT) index.
Abstract Although investor contribution is central to impact investing, research offers limited and fragmented evidence on whether and how investors can influence company-level social and environmental outcomes.
Abstract This paper investigates Magic: The Gathering (MTG) trading cards as a modern class of emotional assets and evaluates their role within diversified portfolios.
PAPER REPORTS · TCG Equal-Weighted Index, Oct 2010 - Mar 2025: annualized mean log return 18.73% (t = 5.48), volatility 13.01%, Sharpe… · TCG index alpha vs S&P 500: 17.84% annualized (t = 5.06), beta 0.07, R² = 0.01, same period, no cost adjustment stated
Abstract This paper introduces a Coupled realised real-time EGARCH model with Filtered Historical Simulation (FHS), referred to as the “CouRTES” model, as an extension of the Realised EGARCH-type models for multi-horizon volatility and distributional…
PAPER REPORTS · QLIKE loss (realised measure target, 250 rolling origins, 30 May 2018 - 29 May 2019): lowest in 11/14 horizons within… · sMAPE (total log-return target): best in 9/14 horizons; mean improvement 0.84% vs Coupled GARCH(1,1) and 1.75% vs…
Abstract We analyze the niche market for social bonds and empirically investigate the existence of a negative social bond premium.
Abstract Whether richer information systematically improves portfolio allocation remains an open question in extreme-risk digital asset markets.
PAPER REPORTS · Gross of costs (2021-01-01 to 2024-03-31, out-of-sample rolling windows): GBRT+MV cumulative return 4.978, annual SD… · Gross: RF+MV return 4.806, SD 1.195, Sharpe 4.020; RF+MMV return 4.944, SD 1.386, Sharpe 3.567
Abstract This paper investigates the pricing of ESG momentum in corporate bond markets, identifying a credibility barrier that conditions whether sustainability improvements are rewarded by investors.
PAPER REPORTS · Long-short ESG momentum quintile spread: mean 0.926 bps per month, t = 1.302, p = 0.196, Dec 2014 - Apr 2025 (114… · Conditional ESG momentum marginal effect of 0.877 bps per month (95% CI [0.292, 1.462]) for issuers excluded by 5+…
This paper introduces FinAnalyzeNet, a novel hybrid deep learning framework designed to address the complex challenges of financial volatility prediction in dynamic market environments.
PAPER REPORTS · Sharpe ratio 1.42 for the volatility-based trading strategy (test period 2021-2023 implied; no transaction-cost… · Directional accuracy 84.7% (sd 1.2%) on volatility direction, test period 2021-2023
OUR BACKTEST · Sharpe 0.64 · Return +21.0% · Max DD -18.7%
We develop Entropic Value-at-Risk (EVaR) parity for tempered stable returns. EVaR-based inverse risk parity (IRP) and equal risk contribution (ERC) portfolios are constructed using multivariate normal tempered stable models and independent component analysis…
PAPER REPORTS · SECTOR EVaR-ERC ICA+NTS: cumulative return 853.79%, Sharpe 0.588, max drawdown 48.56%, turnover 6.93% (out-of-sample… · SECTOR EVaR-ERC ICA+CTS: cumulative return 821.40%, Sharpe 0.579, MDD 48.39%, turnover 9.49% (gross)
OUR BACKTEST · Sharpe 0.37 · Return +14.3% · Max DD -22.0%
Modeling the joint distribution of extreme values in high-dimensional financial time series is challenging because extremes are sparse and locally extreme observations are not necessarily extreme relative to their full marginal distribution.
PAPER REPORTS · Out-of-sample average log score (lower better), healthcare 2021–2024: HR JEAM p75 w5 = 2.878 lower tail, 3.189 upper… · Out-of-sample average log score, finance: HR JEAM p75 w5 = 3.023 lower tail, 3.367 upper tail vs baseline 3.478 / 3.812
Classical market-making strategies based on stochastic control, such as the Avellaneda-Stoikov and the Guéant-Lehalle-Fernandez-Tapia (GLFT) extension, provide closed-form quoting rules, but rest on assumptions that break down at realistic microstructure…
PAPER REPORTS · Stationary flow: DQN risk-return frontier lies above the GLFT frontier throughout the observed risk range (N_sim = 1000… · Regime-switching (tau_r = 60 MO events, omega = 0.30, N_sim = 100 paired episodes of 100,000 LOB events): Algorithm B…
We prove that the skew stickiness ratio converges to two at short maturity under local volatility models. This appears to be the first rigorous proof of this limit for a general time-dependent local volatility function.
Signal correlation and PnL correlation are correlations over different index sets - across assets at each date versus across dates for scalar payoffs - and practitioners often treat the first as a proxy for the second.
OUR BACKTEST · Sharpe -0.83 · Return -17.6% · Max DD -18.1%
Decentralized exchanges record trading and liquidity provision on public blockchains, but empirical analysis requires interpreting these records and linking them to execution metadata.
Abstract This research seeks to delve deeper into the financial significance of the eigenvector associated with the second-largest eigenvalue of the correlation matrix of returns.
OUR BACKTEST · Sharpe -0.48 · Return -35.9% · Max DD -49.7%
Robust portfolio rules that reconstruct confidence sets after learning need not preserve the evaluator obtained by prior-by-prior Bayesian transport.
OUR BACKTEST · Sharpe 0.60 · Return +10.8% · Max DD -7.6%
The Log S-fBM model, introduced by Wu et al., is a stochastic volatility model whose log volatility is a stationary fractional Brownian motion (S-fBM): a stationary Gaussian process with power-decaying autocovariance driven by the Hurst exponent $H$, and…
We develop a global framework for joint S&P 500 (SPX)-VIX smile calibration across multiple maturities without the conditional-independence restriction induced by Markovian stitching.
Let \(P\) be a fixed physical law and let \(Q\) be an equivalent martingale measure selected from the martingale-measure set associated with a chosen numeraire.
OUR BACKTEST · Sharpe 0.54 · Return +50.1% · Max DD -37.6%
We define the variance swap delta as the sensitivity of the price of variance to a change in underlying price. We use Carr-Madan spanning formulas to analyze this sensitivity when the implied volatility smile curve may depend on the underlying price.
We develop a theoretical model that endogenizes the regulator's decision to impose short-selling bans to prevent large stock price declines.
Formulaic alpha discovery is a pool-dependent symbolic search problem in which informative feedback is observed primarily when a complete expression is evaluated.
PAPER REPORTS · No Sharpe, annualized return, alpha, t-stat, hit rate or drawdown is reported anywhere. · ICIR 0.379±0.159 (CSI500), 0.307±0.058 (CSI300), 0.339±0.027 (CSI800), 0.505±0.003 (CSI1000), test period 2022-2024.
MASTER's inter-stock multi-head attention -- the module responsible for modeling cross-sectional stock relationships -- accounts for 42.5% of model parameters and 25% of predictive value.
PAPER REPORTS · Long-short portfolio Sharpe at N~3,500 (full A-share, test 2019-2020, 4 seeds, frictionless): PureLSTM 5.6 +/- 0.5;… · IC / Rank IC as the primary reported performance: CSI300 Original 0.058 +/- 0.007 / 0.066 +/- 0.003 (5 seeds); CSI800…
OUR BACKTEST · Sharpe -0.58 · Return -50.8% · Max DD -63.3%
We study variance-optimal stock hedging and the convergence of approximate strategies in the rough Hawkes--Heston model.
For more than four decades, the 60/40 stock/bond portfolio has served as a benchmark for delivering reasonable returns without excessive risk. More recently, a 50/30/20 stock/bond/alternative portfolio has been suggested.
PAPER REPORTS · Markowitz: 11.6% annualized return, 9.0% annualized volatility, Sharpe 1.08, max DD 18.1%, mean DD 3.0%, turnover… · Simple Markowitz: 10.4% return, 9.3% volatility, Sharpe 0.91, max DD 15.8%, turnover 278.9%, same period and costs
OUR BACKTEST · Sharpe 0.43 · Return +18.9% · Max DD -16.4%
We build and evaluate a pre-game win-probability forecaster for individual maps (``games'') in professional \emph{League of Legends} (LoL).
PAPER REPORTS · Global time-based 0.2 holdout, n_te = 912, 2024-2026 corpus: proposed one-stage model RPS/Brier 0.2230, log-loss… · Per-game walk-forward, 4,605 scored games (min 500 prior games): proposed model RPS 0.2207; calibration intercept…
Financial markets alternate between periods of relative stability and instability, with structural breaks marking the transitions between these regimes.
We develop semi-closed pricing formulas and lifted-model hedging methods for discretely monitored geometric and arithmetic Asian options in the Volterra-Heston stochastic volatility model.
Decentralized finance (DeFi) lending has grown from nonexistent in 2017 to nearly 40 billion US Dollars in deposited funds in May 2022.
We develop a filter for time series, defined at each time $t$ as the minimizer of a discounted convex combination of observed and expected losses.
We introduce ALM-GARCH, an asymmetric long-memory GARCH model in which positive and negative innovations enter conditional variance with different injection amplitudes and kernel offsets.
OUR BACKTEST · Sharpe 0.19 · Return +7.4% · Max DD -20.9%
Investment performance is commonly presented either as a conventional cumulative-return chart, which fixes a historical starting date and traces performance forward, or as a trailing-return table, which fixes the current endpoint but reports only a small set…
OUR BACKTEST · Sharpe 0.43 · Return +53.4% · Max DD -59.1%
Pathwise differentiation of Monte Carlo estimators fails at payoff discontinuities, producing zero or biased sensitivities for barriers, autocallables, and digital options.
Understanding the joint dynamics of prices and trades is central to market microstructure, where returns and order flow interact through nonlinear and state-dependent mechanisms.
Frequent market instability and the lack of rigorously validated forecasting frameworks pose significant challenges for predicting market stress in the Dhaka Stock Exchange (DSE).
PAPER REPORTS · Random Forest crash-gated risk-off strategy, pooled equal-weighted, 2019-2022 test period: total return 67.26% (15.01%… · Annualized volatility 16.39% (strategy) vs. 18.11% (buy-and-hold); maximum drawdown -32.21% vs.
OUR BACKTEST · Sharpe 0.47 · Return +25.2% · Max DD -21.6%
Clean energy equities play a pivotal role in sustainable finance and the global energy transition, yet their performance remains highly sensitive to global fossil energy price fluctuations and climate policy uncertainty.
OUR BACKTEST · Sharpe 0.07 · Return +5.2% · Max DD -40.7%
This study constructs a climate risk attention indicator for Chinese funds by applying Word2Vec-based text analysis to annual fund reports.
PAPER REPORTS · Carhart four-factor alpha regression coefficients (2013-2023, annual fund-year panel, fund and year fixed effects):… · Authors' summary claim: "an annualized alpha of approximately 2.7% associated with acute risk focus" (conclusion…
Artificial intelligence (AI) now supports investment workflows from data and prediction through research, portfolios, execution, and tool use. Technical capability, however, is not evidence of investment profitability.
We propose a new model of expected stock returns that incorporates quantity information from market trading activities into the factor pricing framework.
PAPER REPORTS · Panel OOS predictive R2 (2010-2022, monthly individual stock returns, no demeaning): 0.75% single-factor CAPM BTQ;… · In-sample R2 (2000-2022 full sample): 1.01% single-factor MKT BTQ, 1.21% FF5C BTQ, vs 0.05% and 0.22% for beta-only