440 research outputs found
Statistical properties of absolute log-returns and a stochastic model of stock markets with heterogeneous agents
This paper is intended as an investigation of the statistical properties of
{\it absolute log-returns}, defined as the absolute value of the logarithmic
price change, for the Nikkei 225 index in the 28-year period from January 4,
1975 to December 30, 2002. We divided the time series of the Nikkei 225 index
into two periods, an inflationary period and a deflationary period. We have
previously [18] found that the distribution of absolute log-returns can be
approximated by the power-law distribution in the inflationary period, while
the distribution of absolute log-returns is well described by the exponential
distribution in the deflationary period.\par To further explore these empirical
findings, we have introduced a model of stock markets which was proposed in
[19,20]. In this model, the stock market is composed of two groups of traders:
{\it the fundamentalists}, who believe that the asset price will return to the
fundamental price, and {\it the interacting traders}, who can be noise traders.
We show through numerical simulation of the model that when the number of
interacting traders is greater than the number of fundamentalists, the
power-law distribution of absolute log-returns is generated by the interacting
traders' herd behavior, and, inversely, when the number of fundamentalists is
greater than the number of interacting traders, the exponential distribution of
absolute log-returns is generated.Comment: 12 pages, 5 figure
Balance, growth and diversity of financial markets
A financial market comprising of a certain number of distinct companies is
considered, and the following statement is proved: either a specific agent will
surely beat the whole market unconditionally in the long run, or (and this "or"
is not exclusive) all the capital of the market will accumulate in one company.
Thus, absence of any "free unbounded lunches relative to the total capital"
opportunities lead to the most dramatic failure of diversity in the market: one
company takes over all other until the end of time. In order to prove this, we
introduce the notion of perfectly balanced markets, which is an equilibrium
state in which the relative capitalization of each company is a martingale
under the physical probability. Then, the weaker notion of balanced markets is
discussed where the martingale property of the relative capitalizations holds
only approximately, we show how these concepts relate to growth-optimality and
efficiency of the market, as well as how we can infer a shadow interest rate
that is implied in the economy in the absence of a bank.Comment: 25 page
Mean reversion in annual earnings and its implications for security valuation
This article documents the long-horizon mean reverting character of annual earnings and tests the implications of such mean reversion for security valuation. First, both theory-based and nonparametric measures of earnings persistence decrease as the estimation order increases, revealing 40 percent less long-horizon persistence than expected under the commonly used random walk model. Second, the return responses to the earnings shocks are more closely related across firms to the higher-order measures of persistence that reflect significant long-horizon mean reversion. Third, the persistence measure derived from classical valuation theory outperforms the generic measure in explaining the return responses. Taken as a whole, these results provide evidence for significant mean reversion in the higher-order properties of earnings and for the stock market incorporating these properties in a manner consistent with classical valuation theory.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47883/1/11156_2005_Article_BF01082663.pd
Farmland Prices: Is This Time Different?
The historical behavior of farmland prices, rental rates, and rates of return are examined by treating farmland as an asset with an infinitely long life. It is found that high (low) farmland prices relative to rents have historically preceded extended periods of low (high) net rates of return, rather than greater (smaller) growth in rents. Our analysis shows that this attribute is shared with stocks and housing, and the financial literature provides ample evidence that other assets feature it as well. The long-run relationship linking farmland prices, rents, and rates of return is analyzed. Based on this relationship, we conclude that recent trends are unlikely to be sustainable. The study explores the expected paths that farmland prices and rates of return might follow if they were to eventually conform to the average values observed in the historical sample, and concludes with a discussion of the policy implications. Recommendations for policy makers include close monitoring of farmland lending practices and institutions to allow early identification of potential problems, and identifying in advance appropriate interventions in case recent farmland market trends were to suddenly change
Can the Consumption–Wealth Ratio Predict Housing Returns? Evidence from OECD Countries
This is the peer reviewed version of the following article: CAPORALE, G.M., SOUSA, R.M. and WOHAR, M.E., 2016. Can the consumption-wealth ratio predict housing returns? Evidence from OECD countries. Real Estate Economics, In Press. which has been published in final form at http://dx.doi.org/10.1111/1540-6229.12135. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.©2016 American Real Estate and Urban Economics Association We use a representative consumer model to analyze the relation between the transitory deviations of consumption from its common trend with aggregate wealth and labor income, cay, and the housing risk premium. The evidence based on data for 15 OECD countries shows that, if financial and housing assets are seen as complements, investors will temporarily allow consumption to rise when they expect a rise in future housing returns. By contrast, if housing assets are treated as substitutes for financial assets, consumption will be reduced
A Multifractal Analysis of Asian Foreign Exchange Markets
We analyze the multifractal spectra of daily foreign exchange rates for
Japan, Hong-Kong, Korea, and Thailand with respect to the United States Dollar
from 1991 to 2005. We find that the return time series show multifractal
spectrum features for all four cases. To observe the effect of the Asian
currency crisis, we also estimate the multifractal spectra of limited series
before and after the crisis. We find that the Korean and Thai foreign exchange
markets experienced a significant increase in multifractality compared to
Hong-Kong and Japan. We also show that the multifractality is stronge related
to the presence of high values of returns in the series
Accounting for risk of non linear portfolios: a novel Fourier approach
The presence of non linear instruments is responsible for the emergence of
non Gaussian features in the price changes distribution of realistic
portfolios, even for Normally distributed risk factors. This is especially true
for the benchmark Delta Gamma Normal model, which in general exhibits
exponentially damped power law tails. We show how the knowledge of the model
characteristic function leads to Fourier representations for two standard risk
measures, the Value at Risk and the Expected Shortfall, and for their
sensitivities with respect to the model parameters. We detail the numerical
implementation of our formulae and we emphasizes the reliability and efficiency
of our results in comparison with Monte Carlo simulation.Comment: 10 pages, 12 figures. Final version accepted for publication on Eur.
Phys. J.
Dynamical model and nonextensive statistical mechanics of a market index on large time windows
The shape and tails of partial distribution functions (PDF) for a financial
signal, i.e. the S&P500 and the turbulent nature of the markets are linked
through a model encompassing Tsallis nonextensive statistics and leading to
evolution equations of the Langevin and Fokker-Planck type. A model originally
proposed to describe the intermittent behavior of turbulent flows describes the
behavior of normalized log-returns for such a financial market index, for small
and large time windows, both for small and large log-returns. These turbulent
market volatility (of normalized log-returns) distributions can be sufficiently
well fitted with a -distribution. The transition between the small time
scale model of nonextensive, intermittent process and the large scale Gaussian
extensive homogeneous fluctuation picture is found to be at a 200 day
time lag. The intermittency exponent () in the framework of the
Kolmogorov log-normal model is found to be related to the scaling exponent of
the PDF moments, -thereby giving weight to the model. The large value of
points to a large number of cascades in the turbulent process. The
first Kramers-Moyal coefficient in the Fokker-Planck equation is almost equal
to zero, indicating ''no restoring force''. A comparison is made between
normalized log-returns and mere price increments.Comment: 40 pages, 14 figures; accepted for publication in Phys Rev
From Social Data Mining to Forecasting Socio-Economic Crisis
Socio-economic data mining has a great potential in terms of gaining a better
understanding of problems that our economy and society are facing, such as
financial instability, shortages of resources, or conflicts. Without
large-scale data mining, progress in these areas seems hard or impossible.
Therefore, a suitable, distributed data mining infrastructure and research
centers should be built in Europe. It also appears appropriate to build a
network of Crisis Observatories. They can be imagined as laboratories devoted
to the gathering and processing of enormous volumes of data on both natural
systems such as the Earth and its ecosystem, as well as on human
techno-socio-economic systems, so as to gain early warnings of impending
events. Reality mining provides the chance to adapt more quickly and more
accurately to changing situations. Further opportunities arise by individually
customized services, which however should be provided in a privacy-respecting
way. This requires the development of novel ICT (such as a self- organizing
Web), but most likely new legal regulations and suitable institutions as well.
As long as such regulations are lacking on a world-wide scale, it is in the
public interest that scientists explore what can be done with the huge data
available. Big data do have the potential to change or even threaten democratic
societies. The same applies to sudden and large-scale failures of ICT systems.
Therefore, dealing with data must be done with a large degree of responsibility
and care. Self-interests of individuals, companies or institutions have limits,
where the public interest is affected, and public interest is not a sufficient
justification to violate human rights of individuals. Privacy is a high good,
as confidentiality is, and damaging it would have serious side effects for
society.Comment: 65 pages, 1 figure, Visioneer White Paper, see
http://www.visioneer.ethz.c
The non-random walk of stock prices: The long-term correlation between signs and sizes
We investigate the random walk of prices by developing a simple model
relating the properties of the signs and absolute values of individual price
changes to the diffusion rate (volatility) of prices at longer time scales. We
show that this benchmark model is unable to reproduce the diffusion properties
of real prices. Specifically, we find that for one hour intervals this model
consistently over-predicts the volatility of real price series by about 70%,
and that this effect becomes stronger as the length of the intervals increases.
By selectively shuffling some components of the data while preserving others we
are able to show that this discrepancy is caused by a subtle but long-range
non-contemporaneous correlation between the signs and sizes of individual
returns. We conjecture that this is related to the long-memory of transaction
signs and the need to enforce market efficiency.Comment: 9 pages, 5 figures, StatPhys2
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