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 · 210 shown
This paper develops inference for a Gaussian-nested hypergeometric family of distribution functions.
Abstract We develop a modular forecast-to-construction framework for static option-portfolio design with piecewise-affine contingent claims.
PAPER REPORTS · Out-of-sample predictive-region coverage on 200 purged test origins (20 Jun 2025 – 7 Apr 2026): 200/200 = 1.000000 at… · Deterministic hedge certificate for the single deployed portfolio: Profit(x) ≥ 0 on [4.0, 8.5] (e.g.
This study examines the financial interaction between stock returns and fan tokens of the four major football clubs competing in the Türkiye Super League and publicly traded.
Modern economic and financial data are increasingly organized as multiway arrays, with observations indexed simultaneously by geographic regions, industrial sectors, asset categories, and other economic characteristics.
PAPER REPORTS · TF-BEKK constrained global minimum-variance portfolio, 250-day out-of-sample period 2024-04-09 to 2025-04-18, Chinese… · TF-BEKK has the highest cumulative return at the end of the 250-day out-of-sample window (Figure 4) and the highest AV…
This study integrates the Black-Litterman (BL) model with deep learning techniques to construct a stock portfolio that incorporates investor sentiment.
PAPER REPORTS · BERT_BL, 2024-07-11 to 2024-12-31 (117 trading days), zero transaction costs: annualized return 106.58%, Sharpe 2.64,… · BERT_BL, same period, net of 0.03% commission + 0.1% sell stamp duty: annualized return 51.87%, Sharpe 1.55, Sortino…
Early warning of market turbulence is usually treated as a classification problem, yet a usable system must also produce trustworthy probabilities, stay parsimonious and convert forecasts into defensible positions.
PAPER REPORTS · Optimized policies, mean of the eleven metaheuristics on the untouched holdout (25 Apr 2019-21 Feb 2020, 5 bp per unit… · Best optimized method by mean return (CS), 30 runs: balanced accuracy 0.693 +/- 0.026, AUC 0.763 +/- 0.019, return…
OUR BACKTEST · Sharpe 0.89 · Return +22.5% · Max DD -8.6%
Bu çalışma, Türkiye’de kamu ve özel kesime ait kısa ve uzun vadeli dış borcun BIST Banka Endeksi üzerindeki asimetrik etkilerini 1996–2024 dönemi için incelemektedir.
Managing drawdown, the peak-to-trough decline in an investment portfolio's value, is a precondition for long-term survival in practical investment management.
PAPER REPORTS · NASDAQ 2010.01-2025.04, zero transaction costs and zero slippage: CAST annualized Sharpe 0.523, MDD 0.114, Calmar… · CSI300 2010.01-2025.04, frictionless: CAST ASR 0.269, MDD 0.158, CR 0.104, SoR 0.257, FV $1272
Special Markowitz (SM) regularises returns and covariance jointly, relative to a reference state (mu_ref, Sigma_ref). Each eigendirection of the whitened relative operator carries a spectral reliability potential Phi_k, derived from its estimation quality.
OUR BACKTEST · Sharpe 0.30 · Return +32.3% · Max DD -54.9%
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…
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…
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…
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%
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 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…
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%
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
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%
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%
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.
Financial markets alternate between periods of relative stability and instability, with structural breaks marking the transitions between these regimes.
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%
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
Let a finite population of n labelled examples carry a class-weighted loss, with pi*n in a rare positive class weighted by N0/N1. We study estimation of total risk from a subsample K << n under designs allocating K0 and K1 draws to the two strata.
This article investigates the risk exposure of eight Central and Eastern European markets using monthly data.
Abstract This study develops a robust framework for modeling dynamic volatility, asymmetry, and tail dependence in financial returns, focusing on the daily returns of Natural Resource Index () and the Oil and Gas Index ().
OUR BACKTEST · Sharpe 0.47 · Return +42.5% · Max DD -27.9%
Abstract This study examines the dynamic and quantile-dependent spillover connectedness among African stock markets, precious metals, and cryptocurrencies.
Abstract We examine whether disproportionate insider control, or the divergence between insider voting and cash flow rights at dual-class firms, influences the extent to which stock price reflects information about future firm performance.
We study deep hedging in the context of dynamics risk measures, where sequential decisions are time-consistent.
PAPER REPORTS · Terminal hedging loss CVaR95% at 1-year maturity, 10,000-path test set with initial state perturbation, 0.1%… · Mean terminal P&L, same setup (alpha=95%): log -1.1143 (std 1.7095), static +0.2161 (std 2.6423)
Modern portfolio management increasingly demands a balance between traditional risk-adjusted returns and strict Environmental, Social, and Governance (ESG) mandates.
PAPER REPORTS · Europe persona, out-of-sample 2015–mid-2016: Sharpe drop −0.144 (±0.335) vs Λ=[1,0,0,0] baseline; ESG score gains… · Asia persona, out-of-sample 2015–mid-2016: Sharpe drop −0.045 (±0.068); ESG gains +13.12%/+28.75%/+46.60%.
This study investigates the forecasting performance of machine learning models and traditional econometric volatility models in predicting daily stock price volatility across selected Southern African Development Community (SADC) markets from 02 January 2015…
This paper proposed a new model to price a stock option based on the Skewed Laplace distribution approach (SLOP).
PAPER REPORTS · MSE of SLOP 65.6667 vs MSE of BSOP 87.1059 across all 44 contracts (May 14, 2018 - May 14, 2019 sample for volatility;… · APE of SLOP 0.0425 (underpricing) vs APE of BSOP -0.1929 (overpricing), same sample
Abstract Publicly listed companies are increasingly disclosing climate-related financial risks to their businesses since the promulgation of the Task Force on Climate-related Financial Disclosures (TCFD), and more recently under the climate-related…
We propose a deterministic numerical method for pricing and hedging surrenderable equity-linked life-insurance contracts with periodic premiums and fund contributions, maturity and death guarantees, and Bermudan surrender under correlated stochastic…
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%
Recent advances in LLM agents enable a new paradigm for asset pricing, which we call Agentic Empirical Asset Pricing (AEAP): systems that autonomously conduct the scientific discovery process itself. We define AEAP and identify its core building blocks.
PAPER REPORTS · SEADS mean per-factor OOS Sharpe 0.25 on Panel A (JKP) and 0.16 on Panel B (CRSP/Compustat), OOS windows 2020\u20132025… · SEADS productivity 14.0 (Panel A) / 13.8 (Panel B) admissions out of a 300-candidate budget
The standard Fama-French three-factor model assumes constant factor loadings for the market, size, and value factors.
Abstract This study examines the role of different social media sentiment dimensions in explaining stock market volatility in Pakistan.
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)
Market-order flow in financial markets exhibits long-range correlations. This is a widely known stylised fact of financial markets. A popular hypothesis for this stylised fact comes from the Lillo-Mike-Farmer (LMF) order-splitting theory.
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