@article {Aldridge113, author = {Irene Aldridge}, title = {High-Frequency Runs and Flash-Crash Predictability}, volume = {40}, number = {3}, pages = {113--123}, year = {2014}, doi = {10.3905/jpm.2014.40.3.113}, publisher = {Institutional Investor Journals Umbrella}, abstract = {This article describes research into the short-term nature of movements in price data. The study{\textquoteright}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}, issn = {0095-4918}, URL = {https://jpm.pm-research.com/content/40/3/113}, eprint = {https://jpm.pm-research.com/content/40/3/113.full.pdf}, journal = {The Journal of Portfolio Management} }