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A class-weighted ridge-logistic model estimates the probability of near-term VIX stress and continuously scales a long-only SPY allocation, leaving the balance in cash. Volatility targeting, drawdown control, and exposure smoothing further reduce risk.
we backtested it — Sharpe 0.11 · quant relevance 1.00
The paper tests a cointegration-based PEP–KO pairs strategy and finds that its in-sample profitability weakens out of sample. Much of the earlier performance was concentrated around the COVID-19 dislocation, and the daily-price strategy and robustness tests are reproducible subject to the platform's available end date.
we backtested it — Sharpe 0.00 · quant relevance 0.96
The paper uses a LASSO path to compute mean–variance efficient frontiers for long-only and leverage-constrained portfolios. Its empirical results assess numerical accuracy and computation time rather than trading performance.
we backtested it — Sharpe 2.30 · quant relevance 0.95
The paper develops a data-driven method for selecting derivative hedges and reports results on synthetic and real data. Its daily, end-of-day application can be tested with listed US equity options and their underlying stocks, but the excerpt does not identify the contracts used in the real-data experiments.
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RADAR retrieves historical price-and-news regimes to denoise market representations and determine SDF-based portfolio weights.
The paper draws on financial-news topics to build stock exposures, latent risk factors, and an out-of-sample equity portfolio.
The paper derives a rule for optimally liquidating an existing asset position under price dynamics with distinct support and resistance levels.
The paper examines pricing rules for liquidity provision in oracle-parametrized automated market makers, measuring arbitrage losses and capital efficiency in a counterfactual backtest.
The paper proposes a loss function for return prediction intended to improve directional trading signals.
The paper develops a method for pricing and dynamically hedging European options that accounts for price impact.
and 9 more · see the full radar
Backtest and model results are research artifacts, not live trading results and not a guarantee of future performance. Informational and educational purposes only. Not individualised investment advice.