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 · 10 shown
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%
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%
We study dynamic portfolio decarbonization under incomplete information about firms' carbon intensities and the underlying transition state.
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%
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…
Financial markets alternate between periods of relative stability and instability, with structural breaks marking the transitions between these regimes.
In this paper we propose a new formulation of the Bayesian Filter as used in the discrete-time Markov-Switching-Multifractal (MSM) model of volatility based on existing permutation symmetry within the likelihood structure.
OUR BACKTEST · Sharpe 0.90 · Return +54.5% · Max DD -20.2%
This study focuses on developing an AI-supported prototype for multiperspective interest rate forecasting that combines classical econometric models with modern artificial intel-ligence methods.
We propose Adaptive Refinement Bayesian Optimization for Day-Ahead and Real-Time (ARBO-DART) markets, an algorithm for BESS intraday dispatch co-optimization in which day-ahead (DA) commitment profiles are optimized against value of real-time (RT) recourse…
PAPER REPORTS · Case Study 1 DART PnL $104.50/day (4 MWh / 1 MW battery, gamma=0.2, single representative CAISO SP-15 day averaged over… · Case Study 1 at gamma=0.1: $104.53; at gamma=0.4: $104.49