A number of papers claim that a Log Periodic Power Law (LPPL) fitted to financial market bubbles that precede large market falls or 'crashes', contain parameters that are confined within certain ranges. The mechanism that has been claimed as underlying the LPPL, is based on influence percolation and a martingale condition. This paper examines these claims and the robustness of the LPPL for capturing large falls in the Hang Seng stock market index, over a 30-year period, including the current global downturn. We identify 11 crashes on the Hang Seng market over the period 1970 to 2008. The fitted LPPLs have parameter values within the ranges specified post hoc by Johansen and Sornette (2001) for only seven of these crashes. Interestingly, the...
We aim to provide an algorithm to predict the distribution of the critical times of financial bubble...
AbstractBy combining (i) the economic theory of rational expectation bubbles, (ii) behavioral financ...
We show that a two-harmonic log-periodic formula fits the high-frequency data from the Dow Jones Ind...
Stock market crashes were considered as an chaotic even for a long time. However, more than a decade...
Sornette et al. (1996), Sornette and Johansen (1997), Johansen et al. (2000) and Sornette (2003a) pr...
AbstractBy combining (i) the economic theory of rational expectation bubbles, (ii) behavioral financ...
Latex document of 38 pages including 16 eps figures and 3 tablesWe clarify the status of log-periodi...
In a series of papers based on analogies with statistical physics models, we have proposed that most...
This bachelor thesis concerns itself with multiple objectives. First, to compare two apparently cont...
In a series of papers based on analogies with statistical physics models, we have proposed that most...
This article presents Log-Periodic Power Law and considers its usefulness as a forecasting tool on t...
The study of critical phenomena that originated in the natural sciences has been extended to the fin...
Log-periodic power laws often occur as signatures of impending criticality of hierarchical systems i...
Abstract Stock markets have been of great interest to investors and academicians due to the uncertai...
By combining (i) the economic theory of rational expectation bubbles, (ii) behavioral finance on imi...
We aim to provide an algorithm to predict the distribution of the critical times of financial bubble...
AbstractBy combining (i) the economic theory of rational expectation bubbles, (ii) behavioral financ...
We show that a two-harmonic log-periodic formula fits the high-frequency data from the Dow Jones Ind...
Stock market crashes were considered as an chaotic even for a long time. However, more than a decade...
Sornette et al. (1996), Sornette and Johansen (1997), Johansen et al. (2000) and Sornette (2003a) pr...
AbstractBy combining (i) the economic theory of rational expectation bubbles, (ii) behavioral financ...
Latex document of 38 pages including 16 eps figures and 3 tablesWe clarify the status of log-periodi...
In a series of papers based on analogies with statistical physics models, we have proposed that most...
This bachelor thesis concerns itself with multiple objectives. First, to compare two apparently cont...
In a series of papers based on analogies with statistical physics models, we have proposed that most...
This article presents Log-Periodic Power Law and considers its usefulness as a forecasting tool on t...
The study of critical phenomena that originated in the natural sciences has been extended to the fin...
Log-periodic power laws often occur as signatures of impending criticality of hierarchical systems i...
Abstract Stock markets have been of great interest to investors and academicians due to the uncertai...
By combining (i) the economic theory of rational expectation bubbles, (ii) behavioral finance on imi...
We aim to provide an algorithm to predict the distribution of the critical times of financial bubble...
AbstractBy combining (i) the economic theory of rational expectation bubbles, (ii) behavioral financ...
We show that a two-harmonic log-periodic formula fits the high-frequency data from the Dow Jones Ind...