Portfolio Optimization under Fast and Slow Latent Mean-Reverting and Momentum Drift
“We show that the filtered estimate of the latent mean-reversion level is driven by the difference between fast and slow exponential moving average (EMA)-type processes of the trailing price history, yielding a Moving Average Convergence Divergence (MACD)-type signal, along with a deterministic Volterra correction.”
StrategyPortfolio optimizationmomentum
InputsPrice and volume
Missing from abstract: benchmark, out-of-sample test, costs, multiple testing, universe
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