RT Journal Article
SR Electronic
T1 High-Frequency Runs and Flash-Crash Predictability
JF The Journal of Portfolio Management
FD Institutional Investor Journals
SP 113
OP 123
DO 10.3905/jpm.2014.40.3.113
VO 40
IS 3
A1 Irene Aldridge
YR 2014
UL https://pm-research.com/content/40/3/113.abstract
AB This article describes research into the short-term nature of movements in price data. The study’s key finding is that asset returns do not evolve at the Gaussian increments commonly assumed by continuous pricing models. Instead, prices exhibit strong autocorrelation, often resulting in predictable one-directional sequences, or runs. These runs are more pronounced ahead of market crashes. Identifying these runs can help predict impending flash crashes as much as a day before a crash. The research further contributes to asset pricing and derivatives literature by deriving discreet and continuous closed-form expressions for the probability of flash crashes.TOPICS: Exchanges/markets/clearinghouses, in markets, statistical methods