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Liquidity regimes and optimal dynamic asset allocation

Journal of Financial Economics 2020 136(2), 379-406 open access
We solve a portfolio choice problem when expected returns, covariances, and trading costs follow a regime-switching model. The optimal policy trades towards an aim portfolio given by a weighted-average of the conditional mean-variance-efficient portfolios in all future states. The trading speed is higher in more persistent, riskier, and higher-liquidity states. It can be optimal to overweight low Sharpe-ratio assets such as Treasury bonds because they remain liquid even in crisis states. We illustrate our methodology by constructing an optimal US equity market timing portfolio based on an estimated regime-switching model and on trading costs estimated using a large-order institutional trading data set.

Slow-moving capital and execution costs: Evidence from a major trading glitch

Journal of Financial Economics 2021 139(3), 922-949 open access
We investigate the impact of an exogenous trading glitch at a high-frequency market-making firm on standard measures of stock liquidity (spreads, price impact, turnover, and depth) and institutional trading costs (implementation shortfall and volume-weighted average price slippage). Stocks in which the firm accumulates large long (short) positions increase (decrease) by about 4% during the glitch and become substantially more illiquid. It takes one day for prices and spread-based liquidity measures to revert. Institutional trading costs, however, remain significantly higher for more than one week. Both liquidity measures are also weakly correlated outside the glitch period, suggesting they capture different aspects of liquidity.