FinStressTS is a parametric synthetic benchmark with 30 environments across six mechanism families for evaluating point and probabilistic forecasting models on financial time series.
Hawkes processes in finance
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Compensator-based estimating equations unify several moment methods for compact-memory multivariate Hawkes processes, delivering uniform high-probability O(sqrt(log T / T)) rates, asymptotic normality, and exact efficiency-loss quantification relative to the likelihood score.
Non-unique time arising from event-driven order flow points to a foundational market incompleteness beyond usual no-arbitrage assumptions.
citing papers explorer
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FinStressTS: A Parametric Synthetic Benchmark for Time-Series Forecasting in Finance
FinStressTS is a parametric synthetic benchmark with 30 environments across six mechanism families for evaluating point and probabilistic forecasting models on financial time series.
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Optimal Estimating Equations for Compact-Memory Hawkes Processes
Compensator-based estimating equations unify several moment methods for compact-memory multivariate Hawkes processes, delivering uniform high-probability O(sqrt(log T / T)) rates, asymptotic normality, and exact efficiency-loss quantification relative to the likelihood score.
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Non-unique time and market incompleteness
Non-unique time arising from event-driven order flow points to a foundational market incompleteness beyond usual no-arbitrage assumptions.