18,975 research outputs found
Models of Financial Markets with Extensive Participation Incentives
We consider models of financial markets in which all parties involved find
incentives to participate. Strategies are evaluated directly by their virtual
wealths. By tuning the price sensitivity and market impact, a phase diagram
with several attractor behaviors resembling those of real markets emerge,
reflecting the roles played by the arbitrageurs and trendsetters, and including
a phase with irregular price trends and positive sums. The positive-sumness of
the players' wealths provides participation incentives for them. Evolution and
the bid-ask spread provide mechanisms for the gain in wealth of both the
players and market-makers. New players survive in the market if the
evolutionary rate is sufficiently slow. We test the applicability of the model
on real Hang Seng Index data over 20 years. Comparisons with other models show
that our model has a superior average performance when applied to real
financial data.Comment: 17 pages, 16 figure
Information transmission around block trades on the Spanish stock market
Current fmancial research is placing increasing attention on the effects of large transactions, or Block Trades (BT), on the fmancial markets. In order to analyze whether BT transmit information, we assume that information can be better reflected by changes in asset true value, proxied by the midpoint of bid-ask best quotes, instead of
transactions prices or returns. Moreover, following market microstructure literature, we also look at changes in relative spread and in their adverse selection component. The Madrid Stock Exchange offers us a particularly appropriate testing ground for examining these issues, since this topic has not been facilitated as in other markets
till 1998. We analyze 195 BT, classified according with trading volume, the side of the market initiating the BT (buyer,
seller or indeterminate initiated), its type (inside the spread, sweeping or not classified) and if they change or not
the asset true value. The main result of the paper is that it seems that there is BT information transmission when we look at adverse selection spread component in the different subsample classification, but there is no significant permanent effect in
returns. We also observe changes in liquidity around BTs but the effect is related with temporary spread component
Wavelet Multiresolution Analysis of High-Frequency FX Rates, Summer 1997
FX pricing processes are nonstationary and their frequency characteristics are time-dependent. Most do not conform to geometric Brownian motion, since they exhibit a scaling law with a Hurst exponent between zero and 0.5 and fractal dimensions between 1.5 and 2. This paper uses wavelet multiresolution analysis, with Haar wavelets, to analyze the nonstationarity (time-dependence) and self-similarity (scale-dependence) of intra-day Asian currency spot exchange rates.foreign exchange, anti-persistence, multi-resolution analysis, wavelets, Asia
Wavelet Multiresolution Analysis of High-Frequency Asian FX Rates, Summer 1997
FX pricing processes are nonstationary and their frequency characteristics are time-dependent. Most do not conform to geometric Brownian motion, since they exhibit a scaling law with a Hurst exponent between zero and 0.5 and fractal dimensions between 1.5 and 2. This paper uses wavelet multiresolution analysis, with Haar wavelets, to analyze the nonstationarity (time-dependence) and self-similarity (scale-dependence) of intra-day Asian currency spot exchange rates. These are the ask and bid quotes of the currencies of eight Asian countries (Japan, Hong Kong, Indonesia, Malaysia, Philippines, Singapore, Taiwan, Thailand), and of Germany for comparison, for the crisis period May 1, 1998 - August 31, 1997, provided by Telerate (U.S. dollar is the numeraire). Their time-scale dependent spectra, which are localized in time, are observed in wavelet based scalograms. The FX increments can be characterized by the irregularity of their singularities. This degrees of irregularity are measured by homogeneous Hurst exponents. These critical exponents are used to identify the fractal dimension, relative stability and long term dependence of each Asian FX series. The invariance of each identified Hurst exponent is tested by comparing it at varying time and scale (frequency) resolutions. It appears that almost all FX markets show anti-persistent pricing behavior. The anchor currencies of the D-mark and Japanese Yen are ultra-efficient in the sense of being most anti-persistent. The Taiwanese dollar is the most persistent, and thus unpredictable, most likely due to administrative control. FX markets exhibit these non- linear, non-Gaussian dynamic structures, long term dependence, high kurtosis, and high degrees of non-informational (noise) trading, possibly because of frequent capital flows induced by non-synchronized regional business cycles, rapidly changing political risks, unexpected informational shocks to investment opportunities, and, in particular, investment strategies synthesizing interregional claims using cash swaps with different duration horizons.foreign exchange markets, anti-persistence, long-term dependence, multi-resolution analysis, wavelets, time-scale analysis, scaling laws, irregularity analysis, randomness, Asia
Seasonal Trends in Lithuanian Stock Market
Purpose of the article is to disentangle different calendar effects which leave efficiency holes in
Lithuanian market. This paper presents and tests if commonly described seasonal patterns exist in
Lithuanian stock market. Analysis of three different sections: period-of-the-year; week-of-the-month
and day-of-the-week, suggests that calendar effects do exist in this market. The multitude of
explanations for the seasonal effect leaves the reader confused about its primary cause(s): is it tax-loss
selling, window dressing, information, bid-ask bounce, or a combination of these causes? The
confusion arises, in part, because evidence has generally been presented in support of a particular
hypothesis though the same evidence may be consistent with another hypothesis.
Methodology/methods are logical and systemic analysis of research literature based on the
comparative and generalization methods as well as statistical methods.
Scientific aim of the article is the lack of arguments questioning if market prices operating system is
fully effective. Novelty of the paper is to the answer to the question what seasonal anomalies are also
present in the stock market of new open economy countries.
Findings show that using this modified strategy investor could achieve 20.7% compounded annual
growth rate versus 7.8% achieved using simply holding stocks throughout. The hypothesis asserts that
returns generally will be greater following the “January effect”. There is limited amount of data for
constructing robust seasonal strategies so we modified Buy and Hold strategy with simple rules of
using best and worst months to show how they influence OMXV index performance.
In the conclusions, empirical results using stock index returns for 2000 - 2010 support the hypothesis
in Lithuaian stock market. Abnormal activity of OMXV index’s performance is found in the end of
summer and throughout autumn. August is best performer of the year while October is performing
worst
Characteristics of Real Futures Trading Networks
Futures trading is the core of futures business, and it is considered as one
of the typical complex systems. To investigate the complexity of futures
trading, we employ the analytical method of complex networks. First, we use
real trading records from the Shanghai Futures Exchange to construct futures
trading networks, in which nodes are trading participants, and two nodes have a
common edge if the two corresponding investors appear simultaneously in at
least one trading record as a purchaser and a seller respectively. Then, we
conduct a comprehensive statistical analysis on the constructed futures trading
networks. Empirical results show that the futures trading networks exhibit
features such as scale-free behavior with interesting odd-even-degree
divergence in low-degree regions, small-world effect, hierarchical
organization, power-law betweenness distribution, disassortative mixing, and
shrinkage of both the average path length and the diameter as network size
increases. To the best of our knowledge, this is the first work that uses real
data to study futures trading networks, and we argue that the research results
can shed light on the nature of real futures business.Comment: 18 pages, 9 figures. Final version published in Physica
Fractal Markets Hypothesis and the Global Financial Crisis: Scaling, Investment Horizons and Liquidity
We investigate whether fractal markets hypothesis and its focus on liquidity
and invest- ment horizons give reasonable predictions about dynamics of the
financial markets during the turbulences such as the Global Financial Crisis of
late 2000s. Compared to the mainstream efficient markets hypothesis, fractal
markets hypothesis considers financial markets as com- plex systems consisting
of many heterogenous agents, which are distinguishable mainly with respect to
their investment horizon. In the paper, several novel measures of trading
activity at different investment horizons are introduced through scaling of
variance of the underlying processes. On the three most liquid US indices -
DJI, NASDAQ and S&P500 - we show that predictions of fractal markets hypothesis
actually fit the observed behavior quite well.Comment: 11 pages, 3 figure
Interacting agents in finance, entry written for the New Palgrave Dictionary of Economics, Second Edition, edited by L. Blume and S. Durlauf, Palgrave Macmillan, forthcoming 2006.
Interacting agents in finance represent a behavioral, agent-based approach in which financial markets are viewed as complex adaptive systems consisting of many boundedly rational agents interacting through simple heterogeneous investment strategies, constantly adapting their behavior in response to new information, strategy performance and through social interactions. An interacting agent system acts as a noise filter, transforming and amplifying purely random news about economic fundamentals into an aggregate market outcome exhibiting important stylized facts such as unpredictable asset prices and returns, excess volatility, temporary bubbles and sudden crashes, large and persistent trading volume, clustered volatility and long memory.
A nonlinear structural model for volatility clustering
A simple nonlinear structural model of endogenous belief heterogeneity is proposed. News about fundamentals is an IID random process, but nevertheless volatility clustering occurs as an endogenous phenomenon caused by the interaction between different types of traders, fundamentalists and technical analysts. The belief types are driven by adaptive, evolutionary dynamics according to the success of the prediction strategies as measured by accumulated realized profits, conditioned upon price deviations from the rational expectations fundamental price. Asset prices switch irregularly between two different regimes --periods of small price fluctuations and periods of large price changes triggered by random news and reinforced by technical trading -- thus, creating time varying volatility similar to that observed in real financial data.
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