New Trading Practices and Short-run Market Efficiency

We document a large decrease in autocorrelation and increase in variance of recent short-run returns on several broad stock market indexes, over the 1983-89 period, 15-minute returns went from being highly positively serially correlated to practically uncorrelated. Over the past twenty years, daily and weekly autocorrelations have also fallen, we use transactions data to decompose short-run index autocorrelation into three components: bid-ask bounce, nontrading effects, and noncomtemporaneous cross-stock correlations in specialists' quotes. The first two factors do not explain the autocorrelation's decline. We argue that new trading practices have improved the processing of market-wide information, and that the recent decreases in autocorrelation and increases in volatility simply reflect these improvements.

Theoretical and Numerical Analysis of an Optimal Execution Problem with Uncertain Market Impact

This paper is a continuation of Ishitani and Kato (2015), in which we derived a continuous-time value function corresponding to an optimal execution problem with uncertain market impact as the limit of a discrete-time value function. Here, we investigate some properties of the derived value function. In particular, we show that the function is continuous and has the semigroup property, which is strongly related to the Hamilton-Jacobi-Bellman quasi-variational inequality. Moreover, we show that noise in market impact causes risk-neutral assessment to underestimate the impact cost. We also study typical examples under a log-linear/quadratic market impact function with Gamma-distributed noise.Comment: 24 pages, 14 figures. Continuation of the paper arXiv:1301.648

Estimating Portfolio Risk for Tail Risk Protection Strategies

We forecast portfolio risk for managing dynamic tail risk protection strategies, based on extreme value theory, expectile regression, Copula-GARCH and dynamic GAS models. Utilizing a loss function that overcomes the lack of elicitability for Expected Shortfall, we propose a novel Expected Shortfall (and Value-at-Risk) forecast combination approach, which dominates simple and sophisticated standalone models as well as a simple average combination approach in modelling the tail of the portfolio return distribution. While the associated dynamic risk targeting or portfolio insurance strategies provide effective downside protection, the latter strategies suffer less from inferior risk forecasts given the defensive portfolio insurance mechanics