56,162 research outputs found
Origin of Crashes in 3 US stock markets: Shocks and Bubbles
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?
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
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
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
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 corresponding to the scaling ratio . 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)
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?"
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
On the maximum drawdown during speculative bubbles
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
Fundamental Factors versus Herding in the 2000-2005 US Stock Market and Prediction
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
Probing Human Response Times
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 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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