A Geometrical Approach to Forecast Burst-time of Stock Market Bubbles

Date

2017-01-21

Author

Kürüm, Efsun
Weber, Gerhard Wilhelm
İyigün, Cem

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In order to avoid destructive results of financial bubbles that affect the entire economy, it is important to develop an early-warning signaling. By using optimization-supported tools, we introduce a new method for an early-warning signaling, which approaches the bubble concept geometrically by determining and evaluating ellipsoids. We generate a volume-based index via minimum-volume covering ellipsoid clustering method, and to visualize these ellipsoids, we utilize Radon transform from the theory of the Inverse Problems. The analyses were conducted for US, Japan and China stock markets, also fitted and simulated data were used to observe the performance of our method. For all real, fitted and simulated data, we have found that when the bubble-burst time approaches, the volumes of the ellipsoids gradually decrease and, correspondingly, the figures obtained by Radon transform become more brilliant, i.e., more strongly warning.

URI

https://hdl.handle.net/11511/78119

Conference Name

21st IFORS Annual Meeting (17 Temmuz 2017)

Collections

Graduate School of Applied Mathematics, Conference / Seminar

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Citation Formats

E. Kürüm, G. W. Weber, and C. İyigün, “A Geometrical Approach to Forecast Burst-time of Stock Market Bubbles,” presented at the 21st IFORS Annual Meeting (17 Temmuz 2017), Québec, Canada, 2017, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/78119.