Research
A continuously updated feed of research papers that pass our automated relevance screening for systematic trading — plus every paper we have published a review of, whatever it scored. 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.
15,697 papers screened · 250 on the radar · 36 shown
Artificial intelligence (AI) now supports investment workflows from data and prediction through research, portfolios, execution, and tool use. Technical capability, however, is not evidence of investment profitability.
Herein, we propose a quantum circuit learning framework for modeling the realized volatility (RV) of Bitcoin and investigate the statistical properties of the predicted time series through multifractal analysis.
Abstract This study examines the dynamic and quantile-dependent spillover connectedness among African stock markets, precious metals, and cryptocurrencies.
We establish the consistency and asymptotic normality of a two-step estimator of conditional expectiles in the context of conditional scale models.
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…
Abstract Existing studies of cryptocurrency contagion typically analyse either event-driven shock propagation or time-varying correlations in isolation and often focus on small asset panels.
Similar to banks, DeFi protocols expose depositors to operational risk (USD 9.45 billion across 1,075 events since 2020). Unlike banks, they are not required to hold capital against it. A protocol may maintain a buffer voluntarily.
The object of this research is the economic security policy controlling algorithmic trading strategies for prop traders based on Polynomial Moving Regression Bands (MRB).
PAPER REPORTS · Six-month live trading test, four cryptocurrencies: buy-and-hold outperformed the proposed PAR automated system on all…
Stablecoins, typically pegged to fiat currencies, cannot achieve true stability because they inherit fluctuations in the underlying unit of account.
PAPER REPORTS · USD evaluation, USD risk space: annualized return 0.117, annualized volatility 0.211, Sharpe 0.554, max drawdown… · USD evaluation, MLV risk space: annualized return 0.156, annualized volatility 0.223, Sharpe 0.699, max drawdown…
Loss-versus-Rebalancing (LVR) is the dominant adverse-selection cost borne by liquidity providers on automated market makers.
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)
Bitcoin inverse options, traded on the Deribit exchange and settled in the underlying cryptocurrency rather than in fiat currency, combine extreme and genuinely rough volatility dynamics with a non-linear, currency-dependent payoff structure.
Abstract The emergence of cryptocurrencies has presented investors with novel portfolio diversification opportunities.
PAPER REPORTS · Unconstrained mean-CVaR with crypto: mean monthly return 2.63%, mean monthly CVaR 1.15%, mean monthly risk-return ratio… · Unconstrained without crypto: mean monthly return 0.46%, CVaR 0.42%, risk-return ratio 1.09%
We report a market in which a positive return is visible in prices yet cannot be realized by a fixed trading policy, and we measure why.
PAPER REPORTS · Out-of-sample RMSE (70-30 split, 2021–2024, no transaction costs): LLF BTC 0.541, ETH 0.256, USDT 0.244, BNB 0.676, BCH… · Out-of-sample MAE: LLF BTC 0.377, ETH 0.199, BNB 0.446, BCH 0.567, LTC 0.458, ICP 0.519, MATIC 0.612, USDT 0.137 (RF…
PAPER REPORTS · Baseline HRP: annualised Sharpe 0.741, total return +417%, max DD -85%, 76 monthly rebalances 2020-02 to 2026-05,… · HRP-family variants span Sharpe 0.701-0.749 over the same window and cost assumption (best HRP_Dynamic_94 0.749,…
This work complements our previous paper, which studies borrower-side strategies in decentralized lending markets, by focusing on lender-side capital allocation.
PAPER REPORTS · core-inspired strategy: 5.5% APY, $100k budget, Morpho USDC markets on Ethereum, Jan 1 2026 - Apr 1 2026, daily… · prime-inspired strategy: 3.3% APY, $100k budget, same period and cost assumption
We study equilibria in a closed, fee-free constant-function market maker (CFMM) economy with two assets and two traders.
At 15-minute horizons, directional mean reversion is far stronger and more pervasive in cryptocurrency markets than in US equities: scored under one matched, strictly out-of-sample protocol, 90% of 183 Binance pairs carry significant directional reversal…
PAPER REPORTS · Gross edge per trade peaks near 1.3 bp of notional (BTC/ETH, 15m, 2025-01 to 2026-02) against a 5 bp cheapest maker… · Directional accuracy rises monotonically with confidence threshold, clearing 56% on the most confident bars (BTC/ETH);…
Automated market makers (AMMs) are a cornerstone of decentralised finance (DeFi). Constant product markets with concentrated liquidity, such as UniswapV3, are now a well-established design.
PAPER REPORTS · PPO_narrow, risk-neutral, sigma=0.01, g=2: mean PnL 49.91 +/- 0.38 USDC, 5% CVaR 9.15 +/- 0.65, over 1000 evaluation… · PPO, risk-neutral, sigma=0.01, g=2: mean PnL 42.31 +/- 0.97 USDC, 5% CVaR 6.08 +/- 0.97
Abstract We study the distributional and tail-risk properties of Bitcoin and the major cryptocurrencies using daily returns from June 2014 to May 2026.
Narrow Uniswap v3 liquidity ranges resemble short dated options, and Panoptic's streaming premium echoes the short maturity concentration of Black-Scholes theta near the strike.
Cryptocurrency time-series forecasting is a challenging task because market data usually exhibit high noise, strong volatility, non-stationarity, nonlinear dynamics, and long-range dependencies.
PAPER REPORTS · Bitcoin h=96: MSE 0.175 ± 0.009, MAE 0.314 ± 0.008 (5 seeds, most recent 20% of data as test) · Dogecoin h=96: MSE 0.413 ± 0.012, MAE 0.374 ± 0.010
The Triadic Stress Index (TSI) takes a network index whose four factors were first observed in soil microbiome co-occurrence networks and applies it, without alteration, to the correlation network of financial assets.
PAPER REPORTS · Out-of-sample F1@p90 = 0.447 (TSI with memory, 2016-2026, 897 windows, OFR 23-window crisis list; no transaction costs… · F1 gap vs Absorption Ratio = 0.273 (0.447 vs 0.174) out of sample 2016-2026, block-bootstrap 95% CI [0.095, 0.392],…
OUR BACKTEST · Sharpe 0.87 · Return +229.7% · Max DD -46.7%
Crypto-listed equity perpetuals trade while the primary cash market is closed, yet still need a mark for margin, funding, and liquidation.
Cryptocurrency exchange-traded products (ETPs) listed on European exchanges provide a regulated environment for studying intraday market anomalies.
PAPER REPORTS · AUC-ROC up to 0.823 for one-bar-ahead DPOT prediction (LR, cumulative features, VIRBTC.ST), out-of-sample last 20% of… · AUC-ROC 0.821 for DPOT, LR, cumulative, VBTC.XE; 0.812 session-based
The growth of decentralized finance (DeFi) and sustainability-linked investment markets has been rapid.
Risk-aware Q-learning (RaQL) provides a model-free, two-timescale estimator for dynamic risk objectives, but its finite-budget behavior remains fragile: fixed inner-loop hyperparameters can produce unstable value estimates, persistent Bellman residuals, and…
PAPER REPORTS · Scheme 6 out-of-sample (918 daily obs, chronological test set, after 5bp turnover costs, mean over 20 seeds): Sharpe… · Scheme 0 fixed-parameter baseline out-of-sample (same test set, after 5bp costs, 20 seeds): Sharpe 0.5628 (sd 0.2281),…
OUR BACKTEST · Sharpe 0.34 · Return +16.6% · Max DD -10.4%
Informed traders are supposed to need anonymity: they profit by hiding among the uninformed. A decentralized exchange now publishes the counterparty. Every committed order, cancellation, rejection, and fill carries a persistent pseudonymous wallet address.
PAPER REPORTS · One-second out-of-sample R2: 10.88% anonymous vs 12.31% with identity, +13.2% relative (t=9.2), ridge, evaluation July… · Gradient-boosted trees, one second: 19.48% -> 20.65%, +6.0% (t=5.0), same evaluation window, no costs
We study seven major crypto-perpetual liquidation cascades (2022-2025), and in the largest of them we can watch the mechanism directly.
Automated market makers (AMMs) are typically interpreted and evaluated as decentralized exchanges.
PAPER REPORTS · VBIAX, monthly TE, Jan 2, 2014 – Jun 30, 2026: G3M Pareto-dominates (higher CAGR and lower TE) for gamma in [2.73%,… · EQL NAV, economic mandate, Jun 19, 2018 – May 29, 2026: G3M dominates for gamma in [3.22%, 7.09%]
OUR BACKTEST · Sharpe 0.71 · Return +133.0% · Max DD -42.0%
This paper develops bootstrap inference for autoregressive conditional duration (ACD) models observed over a fixed calendar span, so that the number of durations is random.
Production forecasting systems retrain models regularly, but a retrained candidate does not necessarily outperform a continuously maintained incumbent that has continued to learn.
PAPER REPORTS · Metric is negative log-likelihood of a 3-class 300s direction forecast, not trading P&L; no Sharpe, return, alpha or… · Pooled 48 weeks (4 Aug 2025 - 5 Jul 2026, Binance USD-M + COIN-M, 8 underlyings, 3 seeds): SBS relative NLL reduction…
We audit whether candle-based machine-learning models can turn predictions of cryptocurrency extrema or short-horizon outcomes into positive Binance Spot paper policies after assumed costs.
PAPER REPORTS · Frozen mandatory-daily selector: -6.72% compounded, 2026-07-01 to 07-19, 19 cycles, 3 wins/16 losses, 31 bps… · Frozen mandatory-daily selector cost stress, same period: -4.74% at 20 bps, -6.72% at 31 bps, -10.21% at 51 bps…
OUR BACKTEST · Sharpe 0.00 · Return +0.0% · Max DD 0.0%