Forecasting the critical points of stock markets’ indices using log-periodic power law

• Authors: Piotr Korzeniowski , Ireneusz Kuropka
• Languages of publication: EN

Abstracts

EN

This article presents Log-Periodic Power Law and considers its usefulness as a forecasting tool on the financial markets. One of the estimation methods of this function was presented and six models were built, based on time series of the DJIA and the WIG20. Estimated models were utilized to predict crashes of those indices. The variations between the actual values of analyzed indices observed in the forecasted period and values observed in the actual period of their downturn were assembled to assess the results. In three cases, relative errors were below 5%; and in three cases, they were higher than 15%.

Keywords

EN

Log-Periodic Power Law; critical point of stock market index; forecast

• Publisher: Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
• Journal: Econometrics. Ekonometria. Advances in Applied Data Analytics
• Year: 2013
• Issue: 1(39)
• Pages: 100-110

Dates

published

2013

Contributors

author

Piotr Korzeniowski

• Uniwersytet Ekonomiczny we Wrocławiu

author

Ireneusz Kuropka

• Uniwersytet Ekonomiczny we Wrocławiu

References

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