Kraken has announced the official launch of the Kraken Prop multi-account trading feature on Kraken Desktop. The feature allows users to use a single master account as the trading initiator to synchronously copy the same trade to multiple selected follower accounts. This feature is available for free with Kraken Desktop, with no additional fees.
Read originalThis study formulates and solves a stochastic control problem for Ethena protocol's core yield strategy, which generates returns through a delta-neutral combination of long stETH positions and short ETH perpetual contracts of equal size. The model takes the rate of simultaneously buying stETH and shorting perpetual contracts as the control variable, incorporating both permanent price impact and temporary execution slippage. The study solves both the infinite-horizon discounted problem and the finite-horizon problem with terminal liquidation costs, obtaining explicit optimal control solutions in both cases.
Read originalThe study addresses market-making challenges in Polymarket's thin order books, using the JaxMARL-HFT framework to train cooperative multi-agent market-making models on 417 real markets. The market-making agents are split into quoters and risk managers, trained using recurrent independent proximal policy optimization (IPPO) combined with RNN policies. Testing showed that the improved single-agent market-making model quoted more frequently and had smaller out-of-sample losses, but none of the models achieved positive average portfolio value in out-of-sample evaluation, with only single-seed training completed.
Read originalThis arXiv paper tests the degree to which 4 AI trading agents adhere to their own strategies and risk rules, based on 2627 closed trades from February 12 to August 27, 2026. 18% of the trades were live orders on Hyperliquid, while the rest were simulated at real-time prices, with a uniform round-trip fee of 0.09%.
Read originalThis study introduces LOBGrad, a conditional DDPM framework for probabilistic order book forecasting. The framework combines an autoregressive RNN encoder with a diffusion-based generator, and establishes an excess-risk oracle inequality for the single-step DDPM noise prediction objective under exponential mixing and regularity assumptions.
Read originalThe study proposes an Alpha-stable Lévy diffusion predictor called SHADE, which achieves distribution-level shrinkage through a residual stable kernel by reading outputs at non-zero depths, addressing the problem of overly narrow predictive distributions and overconfidence when Gaussian diffusion models forecast heavy-tailed time series.
Read originalQuantpedia analyzes a paper by Josh Molnar published on SSRN, noting that classic Bitcoin cycle signals such as MVRV, Mayer Multiple, and Pi Cycle Top are gradually losing effectiveness as price volatility narrows. The three mature cycle peaks occurred 525, 546, and 534 days after their respective halvings.
Read originalQuantocracy has compiled the latest quant research-related links as of October 18, 2026, covering topics including trend following, futures continuous contract construction, in-sample to out-of-sample Sharpe ratio decay, the impact of liquidity on stock returns and option pricing, and cryptocurrency cross-sectional trend factors. One study based on 12 commodity futures found that the expected retention ratio of in-sample Sharpe ratios from a 10-year backtest on new data is 30%.
Read originalThe CFTC released a proposed rule to further define the inclusion scope of the 'swap' definition and clarify the regulatory boundary of event contracts. This proposal does not further define 'security-based swaps', and the CFTC has sought the opinion of the Board of Governors of the Federal Reserve System on this proposal.
Read originalThe research team built behavioral models for three types of trading agents—rational arbitrageurs, manipulators, and retail momentum followers—based on reinforcement learning, and conducted a pilot study on hourly cryptocurrency data (AAVE, ETC, SUI). The results show that the behavioral characteristics of different agents have differentiated impacts on market pressure, liquidity, volatility, and risk-adjusted returns. The research conclusions support formulating differentiated regulatory rules for different behavioral types, rather than uniformly restricting volatility or turnover rates.
Read originalThis study proposes a framework for identifying and quantifying arbitrage opportunities between logically related prediction market contracts, demonstrating that arbitrage exists when prices fall outside the convex hull of feasible return vectors, and solving for the optimal arbitrage portfolio via integer programming. The study recovered 1.9 million logical relationships through semantic analysis of platform metadata and settlement rules, constructing a constraint system covering more than 255,000 contracts.
Read originalThis 16-page paper, accepted by MARBLE 2026, argues that crypto-exchange stock-like perpetual contracts calculate funding rates from the real-time basis and cannot replicate shareholder dividend cash flows for traders entering or exiting at arbitrary times. The authors derive a fair funding-rate identity, convert point-in-time fairness into an optimal stopping condition, and use measure theory to show that predictable dividends are atomic events. Absolutely continuous funding-rate paths cannot replicate this atom over a holding interval and must be matched with discrete event credits.
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