On The Utility Of Sornette’S Crash Prediction Model Within The Romanian Stock Market

Stock market crashes have been a constant subject of interest among capital market researchers. Crashes’ behavior has been largely studied, but the problem that remained unsolved until recently, was that of a prediction algorithm. Stock market crashes are complex and global events, rarely taking place on a singular national capital market. They usually occur simultaneously on several if not most capital markets, implying important losses among the investors. Investments made within various stock markets have an extremely important role within the global economy, influencing people’s lives in many ways. Presently, stock market crashes are being studied with great interest, not only because of the necessity of a deep understanding of the phenomenon, but also because of the fact that these crashes belong to the so-called category of “extreme phenomena”. Those are the main reasons that determined scientists to try building mathematical models for crashes prediction. Such a model was built by Professor Didier Sornette, inspired and adapted from an earthquake detection model. Still, the model keeps many characteristics of its predecessor, not being fully adapted to the economic realities and demands, or to the stock market’s characteristics. This paper attempts to test the utility of the model in predicting Bucharest Stock Exchange’s price falls, as well as the possibility of it being successfully used by investors.