Endogenous versus Exogenous Crashes in Financial Markets

Abstract

In a series of papers based on analogies with statistical physics models, we have proposed that most financial crashes are the climax of so-called log-periodic power law signatures (LPPS) associated with speculative bubbles [Sornette and Johansen, 1998. In addition, a large body of empirical evidence supporting this proposition have been presented . Along a complementary line of research, we have established that, while the vast majority of drawdowns occurring on the major financial markets have a distribution which is well-described by a stretched exponential, the largest drawdowns are occurring with a significantly larger rate than predicted by extrapolating the bulk of the distribution and should thus be considered as outliers [Johansen and Sornette, 1998. Here, these two lines of research are merged in a systematic way to offer a classification of crashes as either events of an endogenous origin associated with preceding speculative bubbles or as events of an exogenous origin associated with the markets response to external shocks.We first perform an extended analysis of the distribution of drawdowns in the two leading exchange markets (US dollar against the Deutsmark and against the Yen), in the major world stock markets, in the U.S. and Japanese bond market and in the gold market, by introducing the concept of "coarse-grained drawdowns," which allows for a certain degree of fuzziness in the definition of cumulative losses and improves on the statistics of our previous results. Then, for each identified outlier, we check whether LPPS are present and take the existence of LPPS as the qualifying signature for an endogenous crash: this is because a drawdown outlier is seen as the end of a speculative unsustainable accelerating bubble generated endogenously. In the absence of LPPS, we are able to identify what seems to have been the relevant historical event, i.e., a new piece of information of such magnitude and impact that it is seems reasonable to attribute the crash to it, in agreement with the standard view of the efficient market hypothesis. Such drawdown outliers are classified as having an exogenous origin. Globally over all the markets analyzed, we identify 49 outliers, of which 25 are classified as endogenous, 22 as exogeneous and 2 as associated with the Japanese anti-bubble. Restricting to the world market indices, we find 31 outliers, of which 19 are endogenous, 10 are exogenous and 2 are associated with the Japanese anti-bubble. The combination of the two proposed detection techniques, one for drawdown outliers and the second for LPPS, provides a novel and systematic taxonomy of crashes further subtantiating the importance of LPPS.

Renormalization group analysis of the 2000–2002 anti-bubble in the US S&P500 index: explanation of the hierarchy of five crashes and prediction

“…In this spirit, Ref. [14] has stressed that twothird of the major crashes in a large number of markets are of an endogenous origin and only the most dramatic piece of news (such as the announcement of World War I) are able to move the markets with an amplitude similar to the endogenous crashes. Table 1 Values of the parameters of the fits of the S&P500 index from Aug-09-2000 to t last given in the first column with formula (15) for different models of the phases ψ n .…”

“…The negative trend is then amplified by the collective herding behavior of investors, who, similarly to lemmings rushing over a cliff, run to sell, leading to each of these five observed crashes. Within our framework, these five crashes pertaining to the S&P500 anti-bubble phase are thus intrinsically endogenous to the market dynamics, similarly to most of the crashes found in many markets worldwide [14].…”

Is there a real-estate bubble in the US?

“…These predictions were performed in Feb. 2003 (again our paper was released in early March 2003 on an electronic archive 6 ). We stress that these turning points can be either crashes or changes of regimes according to the theory coupling rational expectation bubbles with collective herding behavior described in [2,5,11,4]. In other words, the theory describes bubbles and their end but not the crash itself: the end of a bubble is the most probable time for a crash, but a crash can occur earlier (with low probability) or not at all; the possibility that no crash occurs is necessary for the bubble to exist, otherwise, rational investors would anticipate the crash and, by backward reasoning, would make it impossible to develop.…”

Microeconomic co-evolution model for financial technical analysis signals

“…[26,31] let the financial signal data fyðtÞg t¼1;T be the logarithm transformation of the NASDAQ 100 Composite index daily closing value between January 01, 1997 and March 10, 2000, i.e., T ¼ 833. The best fit of (1) to the ascending part of the bubble has been performed using the minimum least squares method.…”

“…Evolution models more complex than (1) can be considered for the description of the main oscillations [31], but the scaling of correlations changes only slightly. The periods that correspond to the rise and to the successive burst of a speculative bubble due to endogenous causes are characterized by several oscillations around the main trend [24,[36][37][38], as widely examined through the papers that assess the similarities of large financial crashes properties with earthquake phenomena [31] or sandpile avalanches on fractal structures [24,39].…”