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
Classical execution models assume linear impact, diffusive prices, and an exogenous horizon. We study execution under concave power-law impact and Hurst-scaled price fluctuations, and make two contributions.
OUR BACKTEST · Sharpe -0.29 · Return -9.4% · Max DD -22.3%
As renewable energy integration accelerates, intraday continuous (IDC) electricity markets have become essential for short-term balancing.
We develop a framework to identify and quantify arbitrage across logically related prediction-market contracts.
PAPER REPORTS · Accumulated take, settled windows, 23 Jun-3 Aug 2026, net of spreads and taker fees at displayed depth, held to… · First take, settled windows, same period and costs: guaranteed return 2.7% ($1.10M on $40.6M); at resolution 3.2%…
Weak-form efficiency implies symmetry restrictions on the Markov chain governing movement across the cryptocurrency capitalisation distribution.
PAPER REPORTS · Equal-weighted bottom-decile, survivors only, market-adjusted, gross: 27.49%/wk (t=3.69) frontier 2013:04-2017:11;… · Bottom decile with delisting at -100%, gross, market-adjusted: 20.41%/wk (t=2.84) frontier; 6.91%/wk (t=8.06)…
Crypto venues increasingly list perpetual futures on equities and other real-world assets (RWAs), which trade continuously yet reference dividend-paying stocks: a long equity perpetual marked to the ex-dividend cash price bears the ex-dividend drop without…
Abstract This study examines the association between derivatives trading and the spot return volatility of cryptocurrencies, focusing specifically on Bitcoin (BTC) and Ethereum (ETH).
Although advances in artificial intelligence (AI) and machine learning (ML) have transformed financial risk assessment, many early-warning frameworks for systematic risk still rely on isolated macro-financial indicators with limited integration of established…
Abstract Evaluating systemic risk transmission across financial and commodity markets is vital for maintaining macroeconomic stability in hydrocarbon-dependent economies.
Pergerakan harga emas yang dipengaruhi oleh volatilitas pasar dan ketidakpastian ekonomi memerlukan metode peramalan serta analisis risiko yang akurat.
PAPER REPORTS · ARIMA(1,1,1) price forecast: MAPE 9.15%, MAE USD 396.14, RMSE USD 454.31, directional accuracy 100%. · MC GBM Geopolitik scenario: MAPE 10.37%, MAE USD 426.43, RMSE USD 465.29, directional accuracy 100%.
OUR BACKTEST · Sharpe 0.01 · Return +0.6% · Max DD -35.1%
Bitcoin's extreme price volatility poses significant challenges for investors and traders in making informed investment decisions. Conventional technical analysis approaches are often subjective and unable to capture complex market dynamics accurately.
PAPER REPORTS · Trailing-stop strategy, threshold 0.37, test period 1 Jan 2025-1 Mar 2026: net profit +8,491 USD on 10,000 USD (total… · No-trailing-stop strategy, threshold 0.35, same test period: net profit +8,978 USD (total return +89.78%), win rate…
Language models that read financial news are usually trained on text from the same years used to test them, so a backtest can reward hindsight.
PAPER REPORTS · Monthly, price+text combination across all readers and models, 63-day shocks, test 2022–2024, net of 10bp per dollar… · Same monthly buffered portfolio: net return 12.4%/yr, volatility 10.4%, max drawdown 8%, turnover 60% per month,…
OUR BACKTEST · Sharpe -0.73 · Return -19.9% · Max DD -34.5%
Automated markets increasingly host autonomous, learning trading agents and are powered by formulaic automated market makers (AMMs).
PAPER REPORTS · Rolling 7-day annualized Sharpe ratio of net strategy returns ranges roughly between -20 and +20 for every agent…
We study the conditional distribution of limit-order volume submitted over the next five minutes, given the current order book and recent order flow. The task requires capturing price placement, total volume, and predictive uncertainty jointly.
Portfolio optimization is constrained by linear assumptions and limited integration of multi-modal information.
PAPER REPORTS · SBCA 2-asset (CAT, GILD), test 2021–2022, net of 0.25% one-way commission: final portfolio value 1.4392, annual return… · SBCA 4-asset (CAT, GILD, GS, KO), test 2021–2022, net of 0.25% one-way commission: final portfolio value 1.3564, annual…
OUR BACKTEST · Sharpe 2.62 · Return +54.1% · Max DD -10.1%
Background: Foreign investors can improve liquidity in emerging markets, but concentrated withdrawals may coincide with sharp price adjustment.
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.
The Oracle Approximating Shrinkage (OAS) estimator provides a closed-form, data-driven shrinkage intensity for regularizing sample covariance matrices toward a scaled identity target, but its derivation assumes Gaussian data.
PAPER REPORTS · OAS-Extended GMV portfolio, p=50 US large caps, Jan 2010–Dec 2023, 155 monthly-stepped windows: mean annualized… · OAS-Extended vs OAS realized-variance improvement: t=3.83, p<0.001; bootstrap 95% CI for mean variance reduction [2.0,…
OUR BACKTEST · Sharpe 0.53 · Return +40.1% · Max DD -29.9%
Which inputs drive a language model's financial forecast? We construct synthetic earnings announcements that independently reverse 20-day momentum, non-informational commentary tone, and whether fixed actual EPS beats a manipulated consensus.
Backtests of intraday strategies can drift away from what the live system actually does; in our case, the drift never showed in summary statistics.
Corporate financial disclosures often unfold over time, with announcements, prepared remarks, and discussion spanning multiple high-frequency return intervals.
Privacy-preserving protocols can repair a vulnerability without establishing whether it was exploited beforehand, even when no theft is reported and aggregate supply is protected. We call the potential value reduction from this gap the verifiability discount.
We study the spread a liquidity provider needs to break even against counterparties that can exploit a stale quote, and we place two defenses on a single scale: repricing sooner and screening informed flow.
We study long-term investment in an Ornstein-Uhlenbeck diffusion model with exponential utility. We solve the finite-horizon problem explicitly and show that information delay qualitatively alters long-horizon behavior.
OUR BACKTEST · Sharpe -0.06 · Return -0.6% · Max DD -3.9%
Tokenized equities trade while listed markets are closed, so their marks could improve off-hours measurement along layered exposures that link Bitcoin, crypto-treasury stocks, and leveraged ETFs.
PAPER REPORTS · Expanding-window out-of-sample forecasts of the opening gap (BTC-and-age spec plus token, July 2025-June 2026, no… · July 2026 holdout with coefficients frozen on June 5, 2026 (forecast, not a trading strategy, no costs): sign hit rate…
This paper studies decision functionals under ambiguity when pure-risk evaluation is determined by a general, possibly non-affine statistic.
OUR BACKTEST · Sharpe 0.54 · Return +30.9% · Max DD -25.2%
The end-of-month option allows the short in a futures contract to choose when to deliver during a window in which the delivery price is fixed. We characterize optimal delivery through a universal index obtained from the Bank--El Karoui representation theorem.
This project investigates the valuation of American commodity options using the Schwartz two-factor model.
Score-based diffusion methods usually perturb data with Brownian Gaussian noise, corresponding to a light-tailed forward stochastic differential equation (SDE).
PAPER REPORTS · Feishu A-share OOS (one-year out-of-sample period, dates not stated), StochLOB (jump-Poisson) constrained long-only… · BTC chronological held-out directional classification (test 2026-07-10 to 2026-07-13, no trading costs): StochLOB…
We study liquidity provision in automated market makers when trading in the external market incurs proportional transaction costs. We consider both separately collected fees and fees retained in reserves.
Stock price forecasting is considered difficult due to the volatility of financial markets. A reliable stock price forecasting model is critical for making sound investing decisions while managing financial risks and portfolios.
Abstract Climate change increasingly affects real estate markets because property assets are location-specific and directly exposed to environmental conditions.
In its traditional form, the smart order router only cares about price when deciding where to send a trade; send the order to the exchange currently showing the tightest spread.
PAPER REPORTS · Mean effective execution cost 6.561 bp (latency-aware router) vs 6.548 bp (price-only baseline). · Hit rate vs baseline: 2.2% of 14,400 held-out rows (latency-aware cheaper than price-only).
Regime-switching multi-factor models are widely used in quantitative finance, but filtering does not by itself determine when an agent should act on inferred regime changes.
OUR BACKTEST · Sharpe 0.63 · Return +57.2% · Max DD -14.2%
Physics-informed neural networks provide a flexible framework for learning parametric PDE solution families without labeled data, yet preserving accurate derivatives across heterogeneous regimes remains challenging.
We develop a data-driven approach to dynamic portfolio selection that combines vine-copula simulation with reinforcement learning.
PAPER REPORTS · NN-vine-RL ensemble, 22 complete monthly holding periods within 31 Jul 2024–30 Jun 2026 decisions: CAGR 34.13%, net of… · Sharpe ratio 2.309 (zero annual risk-free rate), same sample and costs.
We study finite-maturity American puts in the Heston model without the Feller condition. At positive variance, the exercise boundary is smooth and strictly decreasing in remaining maturity and variance.
We study how retained ownership supports the value of an asset that pays no dividends and is held only for resale.
We propose a structured continuous-time stochastic volatility model for one-day-ahead integrated-variance forecasting.
PAPER REPORTS · SPX out-of-sample (second half of 2004–2022, raw RV proxy): QLIKE 0.0709, MSE_var 2.6538, MAE_var 0.4285 · Best-loss counts across 17 indices: QLIKE 15/17, MSE_var 12/17, MAE_var 17/17; retained in 90% MCS on 15/17 (QLIKE),…
Abstract Implied temperature rise (ITR) metrics translate corporate emissions pathways into a temperature-based measure of climate alignment at the company and portfolio levels.
This study aims to analyze the effect of media exposure on stock returns of clothing and luxury goods companies listed on the Indonesia Stock Exchange for the 2020–2024 period, and to examine the role of firm size as a moderating variable with profitability…
We study a local stochastic volatility (LSV) model in which the variance factor follows a generalized Langevin equation (GLE) with colored noise, and past returns act on variance through a memory kernel with state-dependent amplitudes.
The most widely used investment risk measures - variance, standard deviation, and tracking error - treat upside deviations as equally undesirable as downside losses.
OUR BACKTEST · Sharpe 0.71 · Return +64.4% · Max DD -36.4%
We study dynamic portfolio decarbonization under incomplete information about firms' carbon intensities and the underlying transition state.
In stochastic control problems involving optimal portfolio choice, one often seeks an optimizer of some local criterion (dynamic programming value function) generated by some global criterion (e.g., expected utility).
OUR BACKTEST · Sharpe 0.80 · Return +34.1% · Max DD -15.2%
Expected Shortfall (ES) measures the average size of tail losses. Its sequential backtests typically also require a Value-at-Risk (VaR) forecast.
A conditional normalizing flow can produce extreme scenarios even when its point forecasts appear reasonable. We compare two fitted models for daily Treasury yield changes at eleven maturities reconstructed from Federal Reserve curve parameters.
PAPER REPORTS · Stabilized flow, development windows (5×60 dates, 2002–2026; forecast metrics only, no trading strategy or costs):… · Stabilized flow, subsequent window April 13–July 8, 2026 (frozen checkpoints): scenario-mean MSE 0.3351, 90% coverage…
OUR BACKTEST · Sharpe 0.03 · Return +0.2% · Max DD -5.6%
We study whether stock disclosures by recognizable investors generate abnormal market reactions beyond the reactions produced by comparable but non-recognizable managers.
PAPER REPORTS · High-recognition minus control long-short calendar-time Carhart alpha: 10.4 bps/day at H=21 (p<0.001), 4.8 bps/day at… · High-recognition buys long-only calendar-time Carhart alpha: 9.8 bps/day H=21 (p<0.001), 4.4 bps/day H=63 (p=0.003),…
We present a statically and dynamically arbitrage-free European option market model with smooth interpolation between option prices, based on the SANOS framework, and prove that its dynamics admit a unique strong solution.
Market making under realistic order-flow dynamics is challenging due to the clustered, self-exciting nature of order arrivals, which are naturally modeled by non-Markovian Hawkes processes.
PAPER REPORTS · HSN mean cumulative episodic reward, simulated (no market data), multi-asset cross-excitation cs=0.7: 0.0548±.0007 over… · HSN, simulated power-law kernel ε=0.15: 0.0216±.0004 mean cumulative reward, +32.5% vs the best baseline (p<0.001).
A path indistinguishable from its own reverse carries no arrow of time, so time irreversibility is a necessary condition for a directed mechanism to be readable from trajectories alone.