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 · 33 shown
We propose a regime-aware tactical asset allocation (TAA) framework integrating market regime detection with Nested Clustered Optimization (NCO) for multi-asset portfolio construction.
PAPER REPORTS · Regime-NCO (proposed), OOS Jan 2021 to Aug 2025, monthly, 10bp proportional costs, rf 0.479%/month: cumulative return… · Regime-NCO, same period and settings: Sharpe -0.9522, Sortino -1.2271.
Purpose: This study aims to examine the effect of inflation, BI Rate, capital flow, and exchange rate on the Jakarta Composite Index (JCI), as well as to analyze the moderating role of profitability (ROA) in these relationships.
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.
Reinforcement learning for trading often struggles to balance upside participation with drawdown control.
PAPER REPORTS · SPY, test 2020–2022, seed 42, 0.1% proportional transaction cost: total return 27.62%, annualized return 8.48%, Sharpe… · SPY, test 2020–2022, mean ± std over seeds {7,11,19,23,42}, 0.1% cost: total return 0.2725 ± 0.0109, Sharpe 0.6219 ±…
OUR BACKTEST · Sharpe 0.89 · Return +42.3% · Max DD -15.6%
Macroeconomic crises are rare, yet they can have large effects on asset prices. Because the probability of entering a crisis from normal times is small relative to the probability of recovery, the dynamics are nearly reducible: setting the crisis-entry…
We examine the conditional volatility dynamics of the USD 1Yx10Y forward swap rate using GARCH(1,1), GJR-GARCH(1,1), and a two-regime Markov-switching GARCH (MSGARCH) model.
PAPER REPORTS · 95% one-day-ahead interval coverage, 1500 test days (34.36% of sample): GJR 94.00%, GARCH 93.80%, MSGARCH 93.8% · 1300 test days: GJR 93.62%, GARCH 93.23%, MSGARCH 93.154%
Purpose: This paper explores the asymmetric and state-dependent dependence relationship of the S&P Green Bond Index with six international markets and assesses whether such dependence patterns are correlated with the risk-reduction benefit associated with…
PAPER REPORTS · Long-only two-asset minimum-variance portfolio, green bonds + S&P 500: GB weight 86.8%, annualized return 1.47%,… · Green bonds + S&P Bitcoin: GB weight 99.3%, annualized return 0.13%, volatility 7.48%, Sharpe 0.017, variance reduction…
We study a representative-agent Epstein-Zin economy with geometric dividends and a hidden finite-state Markov drift.
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.
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.
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…
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%
Abstract This study examines the dynamic and quantile-dependent spillover connectedness among African stock markets, precious metals, and cryptocurrencies.
Abstract Sentiment indicators are widely used in digital asset markets, but their economic meaning remains ambiguous.
PAPER REPORTS · Expanding-window out-of-sample R-squared vs historical-mean benchmark, 2018-2026 sample, no transaction costs… · Out-of-sample directional hit rate of the ridge sentiment model: 49.8% (1d), 51.5% (7d), 48.1% (30d), no cost…
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…
This study investigates the time-varying interactions between financial stress and selected financial assets within the Diebold–Yilmaz connectedness framework.
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)
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…
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
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%
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.
Hedge ratios, factor models and diversified portfolios all rest on an estimate of which firms move together.
PAPER REPORTS · Variance-harvest attribution (selling variance at VIX-squared against the paper's 12m equal-weighted realized leg, July… · Risk by REC quartile over the same 329 months: probability of loss 0.29, 0.21, 0.26, 0.15; mean loss given loss…
OUR BACKTEST · Sharpe 0.73 · Return +68.2% · Max DD -36.5%
Against the background of increasing volatility and complex risk factors in global markets, options and futures have become important instruments for risk hedging and uncertainty management.
PAPER REPORTS · Futures hedged portfolio, 2019-2024: annualized return 7.95%, annualized volatility 10.28%, hedging efficiency 46.87%,… · Option hedged portfolio, 2019-2024: annualized return 8.31%, annualized volatility 8.76%, hedging efficiency 54.73%,…
OUR BACKTEST · Sharpe 0.74 · Return +83.0% · Max DD -47.8%
Financial volatility is regime dependent, yet incorporating regime information into neural networks can also destabilize training. This paper asks where such information should enter a neural cross-sectional volatility forecasting model.
PAPER REPORTS · U.S. panel, 30 walk-forward windows Apr 2018 - Oct 2025, mean over 30 seeds: IC 0.5469 +/- 0.0012, ICIR 6.14 +/- 0.06,… · IC advantage over capacity-matched MLP-L: +0.0048 full sample (p<1e-4); +0.0207 top market-vol decile; +0.0322 COVID…
Large language models can extract richer signals from financial news than fixed sentiment lexicons, and recent work has explored feeding such signals into portfolio construction.
PAPER REPORTS · Sharpe 2.33, annualized return 95.9%, cumulative net 100.1%, max drawdown -18.3% — pure beta, GPT-4o mini, Student-t,… · Sharpe 2.44, annualized 100.0%, net 106.9%, max DD -18.3% — same configuration at 50 bps (2025)
This paper documents an applied natural-language-processing framework for measuring the tone of Brazilian Monetary Policy Committee (Copom) statements.
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%
I revisit the exchange rate disconnect puzzle, first documented by Meese and Rogoff (1983), using generative artificial intelligence (AI) to forecast currency returns based on economic fundamentals.
PAPER REPORTS · Annualized Sharpe ratio 0.594 at 48-month lookback (cross-sectional long top-2 / short bottom-2 of 9 currencies,… · Annualized Sharpe ratios 0.577 / 0.604 / 0.594 / 0.491 / 0.467 for 36 / 42 / 48 / 54 / 60-month lookbacks (2001-2024,…
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%