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 · 103 shown
We propose a market-making game played among $N \ge 2$ strategic market makers and a single non-strategic representative trader.
We model the dynamics of the liquidity profile in Uniswap~V3 and other concentrated-liquidity automated market makers with a stochastic partial integro-differential equation (SPIDE).
We study changes in underlying-market quality around Korea's May 2026 introduction of single-stock leveraged ETFs, using Samsung Electronics and SK Hynix as a case study. These were the first eligible underlying stocks.
We study strategic liquidity provision in decentralized exchanges with concentrated liquidity as a mean-field game.
PAPER REPORTS · Margin-gated provision backtest on four Base pools, 7497 hours, September 2024 to July 2025: in the market 2.5–12% of…
Autoregressive foundation models offer state-of-the-art capabilities to simulate the market by generating the message flow of limit order books (LOBs).
The electricity system in Great Britain (GB) allows participants to deliberately produce or consume a different volume to their traded position and has incentivised this practice with a single imbalance price since 2015.
Realistic market impact is essential for generative limit order book (LOB) models to serve as world models for trading agents. If a simulator misprices this mechanism, agents learn policies that are optimal in the simulator but wrong in the real market.
PAPER REPORTS · Decile long-short, intraday momentum (even lags, last 5 days): 0.23% per half-day (t=19.85); CAPM alpha 0.23 (t=19.87);… · Decile long-short, overnight momentum (even lags, last 5 days): 0.42% per half-day (t=19.34); TW alpha 0.37 (t=18.90);…
OUR BACKTEST · Sharpe 0.92 · Return +94.9% · Max DD -29.7%
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%…
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.
Background: Foreign investors can improve liquidity in emerging markets, but concentrated withdrawals may coincide with sharp price adjustment.
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.
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.
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).
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.
Temporal point processes are used both to measure market mechanisms, for example how fast prices absorb news and how much of the reaction is the market responding to itself, and to predict the next event.
When a trader executes a large order, the relevant question is not \emph{what will the price be?} but \emph{what would the price have been had I not traded?} Market impact is thus a causal quantity, yet classical models (Almgren--Chriss, propagators) regress…
Renewed attention to the identity of Bitcoin’s pseudonymous creator has revived an old worry: that the roughly 1.148 million BTC mined by Satoshi and never moved represent a major tail risk for Bitcoin. This paper argues that the worry is overstated.
Structural price diffusivity explains many empirical regularities of market impact including the ``square-root law'' and its crossover to a linear regime for low trading rates \citep{bonart2026diffusive}.
The square-root impact law (SRIL), $I = Yσ\sqrt{Q/V}$, bundles two facts that a single mechanism must explain at once: a shape (impact proportional to square-root of traded volume $Q$) and an amplitude ($Y=O(1)$, independent of the participation rate…
Abstract Using Gate.io hourly spot-order-book archives from January 2022 through June 2023, this paper reconstructs a long-horizon five-second panel for comparing the direct Ether/Tether (ETH/USDT) quote with the synthetic Ether/Bitcoin (ETH/BTC) $$\times $$…
The growing importance of intraday trading in Europe, driven by the increasing penetration of renewable energy sources, has led to higher volatility and periods of market stress.
We give a unified analytic account of a finite bid--ask spread in a two-field reaction--diffusion order book. The model retains separate bid and ask densities in operational time, with diffusion, cancellation, reaction and external order creation.
Trade-sign errors can change measured trading costs even when classification accuracy is high. We validate the side of Polymarket's public trade prints against the taker leg of each print's on-chain settlement.
Market-regime models typically assume a finite set of discrete latent states. We examine whether high frequency limit-order-book dynamics exhibit distinct regime separation or apparent regimes result from discretising an underlying continuum, analysing deep…
PAPER REPORTS · Intraday volatility forecast (not a trading strategy): pooled expanding-year walk-forward OOS R2 0.6821 / 0.7273 /… · Next-window RV direction hit rate: 61.2% (30s), 60.5% (45s), 59.5% (60s) from the continuous predictive block;…
Flashblocks divide a block's priority gas auction into shorter sequential auctions that commit transaction order before the block is complete. We ask how this auction cadence affects bidding and competition among automated arbitrageurs, or searchers.
Reinforcement learning (RL) is increasingly used for financial optimal-control problems when complex dynamics make analytical strategies difficult to obtain.
PAPER REPORTS · Proposed method (frozen analytical policy + residual PPO), execution cost halved from 0.0012 to 0.0006, σ_ξ=100, full… · Same method at a_true=0.0012: change 0.00019 [-0.00041,0.00079]; at a_true=0.0018: change 0.00019 [-0.00034,0.00071]…
Short-horizon price-trend prediction from limit order books in equity and intraday electricity markets requires models that combine predictive quality with low single-sample latency and a small serialized model size to keep pace with rapid and continuous…
PAPER REPORTS · Classification performance only. These are not trading returns: no Sharpe, PnL or cost assumption is reported, and the… · MBOFormer test macro-F1 (mean of 3 seeds), h=10/20/50/100: - EPEX (3 test days, March 2021): 0.651/0.577/0.517/0.472 -…
We study whether model diversity survives selection into trading. In synthetic markets with a fixed mixture of three language-model families, news presentation changes their representation among submitted orders.
In this paper, we extend earlier findings of supra-competitive outcomes in optimal-execution games by identifying a learned punitive mechanism that deters deviations and provides behavioural evidence of collusion.
Liquidity provision in automated market makers is typically analyzed at the pool level, implicitly assuming LP homogeneity.
Power systems with increasing variable renewable generation face greater uncertainty in scheduling and balancing. Intraday and balancing electricity markets facilitate position adjustments and real-time balancing close to delivery.
We model market impact as the response to submitted order flow net of counterflow from latent traders, activated when price displacements from the level that would prevail without the order exceed individual thresholds.
We study the joint dynamics of the best bid and ask prices with a spread-gated Hawkes-flocking model.
Hedging a derivative by trading the underlying asset changes the payoff that the hedging intended to replicate. We study this phenomenon when trading generates price impact and execution costs.
This paper introduces oracle-parametrized automated market makers (OP-AMMs), i.e., automated market makers whose quoted price depends jointly on the pool reserves and an external oracle price.
PAPER REPORTS · Counterfactual arbitrage-only SPY backtest, one-second NBBO, 2023 (250 trading days, daily reset): the Pull-oracle GA…
Market microstructure studies how trading rules turn orders into prices and allocations.
Private and encrypted mempools hide pending transactions to stop sandwich attacks and other forms of maximal extractable value (MEV), but what they hide is rarely everything: a transaction's pair, direction, and a coarse range for its size can still leak.
Abstract The Probability of Informed Trading (PIN) treats informational events as independent across trading days, leaving it silent on how long informational regimes last.
We investigate the systemic macroscopic dynamics emerging from Limit Order Books (LOBs) populated exclusively by autonomous reinforcement-learning agentic traders.
The National Best Bid and Offer (NBBO), the consolidated "now" at the centre of U.S. equity market structure under Regulation NMS, requires comparing price events at exchanges whose separation places those events outside one another's light cones.
Stock price forecasting is a long-standing challenge in computational finance, driven by the inherent randomness of markets and complex temporal patterns.
PAPER REPORTS · CSI300 test (2017-01-01 to 2020-08-01), Qlib top-50 long, 20 replacements/day: excess annualized return 0.1809, excess… · CSI500 test (2017-01-01 to 2020-08-01), same strategy: excess annualized return 0.1529, excess information ratio…