56,638 research outputs found

    Origin of Crashes in 3 US stock markets: Shocks and Bubbles

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    This paper presents an exclusive classification of the largest crashes in Dow Jones Industrial Average (DJIA), SP500 and NASDAQ in the past century. Crashes are objectively defined as the top-rank filtered drawdowns (loss from the last local maximum to the next local minimum disregarding noise fluctuations), where the size of the filter is determined by the historical volatility of the index. It is shown that {\it all} crashes can be linked to either an external shock, {\it e.g.}, outbreak of war, {\it or} a log-periodic power law (LPPL) bubble with an empirically well-defined complex value of the exponent. Conversely, with one sole exception {\it all} previously identified LPPL bubbles are followed by a top-rank drawdown. As a consequence, the analysis presented suggest a one-to-one correspondence between market crashes defined as top-rank filtered drawdowns on one hand and surprising news and LPPL bubbles on the other. We attribute this correspondence to the Efficient Market Hypothesis effective on two quite different time scales depending on whether the market instability the crash represent is internally or externally generated.Comment: 7 pages including 3 tables and 3 figures. Subm. for Proceeding of Frontier Science 200

    Another type of log-periodic oscillations on Polish stock market?

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    Log-periodic oscillations have been used to predict price trends and crashes on financial markets. So far two types of log-periodic oscillations have been associated with the real markets. The first type are oscillations which accompany a rising market and which ends in a crash. The second type oscillations, called "anti-bubbles" appear after a crash, when the prices decreases. Here, we propose the third type of log-periodic oscillations, where a exogenous crash initializes a log-periodic behavior of market, and the market is growing up. Such behavior has been identified on Polish stock market index between the "Russian crisis" (August 1998) and the "New Economy crash" in April 2000.Comment: 10 pages (6 figures): conference APFA4 (Warsaw, November 2003

    Renormalization Group Analysis of the 2000-2002 anti-bubble in the US S&P 500 index: Explanation of the hierarchy of 5 crashes and Prediction

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    We propose a straightforward extension of our previously proposed log-periodic power law model of the ``anti-bubble'' regime of the USA market since the summer of 2000, in terms of the renormalization group framework to model critical points. Using a previous work by Gluzman and Sornette (2002) on the classification of the class of Weierstrass-like functions, we show that the five crashes that occurred since August 2000 can be accurately modelled by this approach, in a fully consistent way with no additional parameters. Our theory suggests an overall consistent organization of the investors forming a collective network which interact to form the pessimistic bearish ``anti-bubble'' regime with intermittent acceleration of the positive feedbacks of pessimistic sentiment leading to these crashes. We develop retrospective predictions, that confirm the existence of significant arbitrage opportunities for a trader using our model. Finally, we offer a prediction for the unknown future of the US S&P500 index extending over 2003 and 2004, that refines the previous prediction of Sornette and Zhou (2002).Comment: Latex document, 11 eps figures and 1 tabl

    The 2006-2008 Oil Bubble and Beyond

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    We present an analysis of oil prices in US$ and in other major currencies that diagnoses unsustainable faster-than-exponential behavior. This supports the hypothesis that the recent oil price run-up has been amplified by speculative behavior of the type found during a bubble-like expansion. We also attempt to unravel the information hidden in the oil supply-demand data reported by two leading agencies, the US Energy Information Administration (EIA) and the International Energy Agency (IEA). We suggest that the found increasing discrepancy between the EIA and IEA figures provides a measure of the estimation errors. Rather than a clear transition to a supply restricted regime, we interpret the discrepancy between the IEA and EIA as a signature of uncertainty, and there is no better fuel than uncertainty to promote speculation!Comment: 4 pages; 4 figures, discussion of the oil supply-demand view point and uncertaintie

    Non-Parametric Analyses of Log-Periodic Precursors to Financial Crashes

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    We apply two non-parametric methods to test further the hypothesis that log-periodicity characterizes the detrended price trajectory of large financial indices prior to financial crashes or strong corrections. The analysis using the so-called (H,q)-derivative is applied to seven time series ending with the October 1987 crash, the October 1997 correction and the April 2000 crash of the Dow Jones Industrial Average (DJIA), the Standard & Poor 500 and Nasdaq indices. The Hilbert transform is applied to two detrended price time series in terms of the ln(t_c-t) variable, where t_c is the time of the crash. Taking all results together, we find strong evidence for a universal fundamental log-frequency f=1.02±0.05f = 1.02 \pm 0.05 corresponding to the scaling ratio λ=2.67±0.12\lambda = 2.67 \pm 0.12. These values are in very good agreement with those obtained in past works with different parametric techniques.Comment: Latex document 13 pages + 58 eps figure

    InfoInternet for Education in the Global South: A Study of Applications Enabled by Free Information-only Internet Access in Technologically Disadvantaged Areas (authors' version)

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    This paper summarises our work on studying educational applications enabled by the introduction of a new information layer called InfoInternet. This is an initiative to facilitate affordable access to internet based information in communities with network scarcity or economic problems from the Global South. InfoInternet develops both networking solutions as well as business and social models, together with actors like mobile operators and government organisations. In this paper we identify and describe characteristics of educational applications, their specific users, and learning environment. We are interested in applications that make the adoption of Internet faster, cheaper, and wider in such communities. When developing new applications (or adopting existing ones) for such constrained environments, this work acts as initial guidelines prior to field studies.Comment: 16 pages, 1 figure, under review for a journal since March 201

    Comment on "Are financial crashes predictable?"

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    Comment on "Are financial crashes predictable?", L. Laloux, M. Potters, R. Cont, J.P Aguilar and J.-P. Bouchaud, Europhys. Lett. 45, 1-5 (1999)Comment: 2 pages including 2 figures. Subm. to Eur. Phys Lett. Previous error in fig. 1 correcte

    Fundamental Factors versus Herding in the 2000-2005 US Stock Market and Prediction

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    We present a general methodology to incorporate fundamental economic factors to our previous theory of herding to describe bubbles and antibubbles. We start from the strong form of Rational Expectation and derive the general method to incorporate factors in addition to the log-periodic power law (LPPL) signature of herding developed in ours and others' works. These factors include interest rate, interest spread, historical volatility, implied volatility and exchange rates. Standard statistical AIC and Wilks tests allow us to compare the explanatory power of the different proposed factor models. We find that the historical volatility played the key role before August of 2002. Around October 2002, the interest rate dominated. In the first six months of 2003, the foreign exchange rate became the key factor. Since the end of 2003, all factors have played an increasingly large role. However, the most surprising result is that the best model is the second-order LPPL without any factor. We thus present a scenario for the future evolution of the US stock market based on the extrapolation of the fit of the second-order LPPL formula, which suggests that herding is still the dominating force and that the unraveling of the US stock market antibubble since 2000 is still qualitatively similar to (but quantitatively different from) the Japanese Nikkei case after 1990.Comment: 19 Elsart pages + 10 eps figure

    On the maximum drawdown during speculative bubbles

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    A taxonomy of large financial crashes proposed in the literature locates the burst of speculative bubbles due to endogenous causes in the framework of extreme stock market crashes, defined as falls of market prices that are outlier with respect to the bulk of drawdown price movement distribution. This paper goes on deeper in the analysis providing a further characterization of the rising part of such selected bubbles through the examination of drawdown and maximum drawdown movement of indices prices. The analysis of drawdown duration is also performed and it is the core of the risk measure estimated here.Comment: 15 pages, 7 figure

    Probing Human Response Times

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    In a recent preprint \cite{eck}, the temporal dynamics of an e-mail network has been investigated by J.P. Eckmann, E. Moses and D. Sergi. Specifically, the time period between an e-mail message and its reply were recorded. It will be shown here that their data agrees quantitatively with the frame work proposed to explain a recent experiment on the response of ``internauts'' to a news publication \cite{www2} despite differences in communication channels, topics, time-scale and socio-economic characteristics of the two population. This suggest a generalized response time distribution ∌t−1\sim t^{-1} for human populations in the absence of deadlines with important implications for psychological and social studies as well the study of dynamical networks.Comment: 6 pages including 2 figures. Subm. for Proceedings of Frontier Science 200
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