Multifractal analysis and instability index of prior-to-crash market situations
This work provides a potential early warning system for financial market crashes, but the results are based on historical data and may not generalize to future events.
The authors apply multifractal analysis to stock market prices (NASDAQ, Dow Jones) to identify early warning signals of crashes, finding that both multifractal spectra and an instability index can characterize and predict prior-to-crash market situations.
We take prior-to-crash market prices (NASDAQ, Dow Jones Industrial Average) as a signal, a function of time, we project these discrete values onto a vertical axis, thus obtaining a Cantordust. We study said cantordust with the tools of multifractal analysis, obtaining spectra by definition and by lagrangian coordinates. These spectra have properties that typify the prior-to-crash market situation. Any of these spectra entail elaborate processing of the raw signal data. With the unprocessed raw data we obtain an instability index, also with properties that typify the prior-to-crisis market situation. Both spectra and the instability index agree in characterizing such crashes, and in giving an early warning of them.