Power law cross-correlations between price change and volume change of Indian stocks

Within the paper, the problem of globalisation during financial crises is analysed. The research is based on the Forex exchange rates. In the analysis, the power law classification scheme (PLCS) is used. The study shows that during crises cross-correlations increase resulting in significant growth of cliques, and also the ranks of nodes on the converging time series network are growing. This suggests that the crises expose the globalisation processes, which can be verified by the proposed analysis.

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Volume change on melting for systems with inverse-power-law interactions

Physical Review B ◽

10.1103/physrevb.24.1530 ◽

1981 ◽

Vol 24 (3) ◽

pp. 1530-1535 ◽

Cited By ~ 48

Author(s):

John D. Weeks

Keyword(s):

Power Law ◽

Volume Change ◽

Inverse Power ◽

Inverse Power Law

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Area and volume quantification of arctic thaw slumps using time-series of digital elevation models generated from radar interferometry

10.5194/egusphere-egu21-2280 ◽

2021 ◽

Author(s):

Philipp Bernhard ◽

Simon Zwieback ◽

Irena Hajnsek

Keyword(s):

Probability Density ◽

Power Law ◽

Volume Change ◽

Digital Elevation Models ◽

Probability Density Functions ◽

The Arctic ◽

Density Functions ◽

Digital Elevation ◽

Beta Coefficient ◽

Area And Volume

Vast areas of the Arctic host ice-rich permafrost, which is becoming increasingly vulnerable to terrain-altering thermokarst in a warming climate. Among the most rapid and dramatic changes are retrogressive thaw slumps. These slumps evolve by a retreat of the slump headwall during the summer months, making their change visible by comparing digital elevation models over time. In this study we use digital elevation models generated from single-pass radar TanDEM-X observations to derive volume and area change rates for retrogressive thaw slumps. At least three observations in the timespan from 2011 to 2017 are available with a spatial resolution of about 12 meter and a height sensitivity of about 0.5-2 meter. Our study regions include regions in Northern Canada (Peel Plateau/Richardson Mountains, Mackenzie River Delta Uplands, Ellesmere Island), Alaska (Noatak Valley) and Siberia (Yamal, Gydan, Taymyr, Chukotka) covering an area of 220.000 km2 with a total number of 1853 thaw slumps.In this presentation we will focus on the area and volume change rate probability density functions of the mapped thaw slumps in these study areas. For landslides in temperate climate zones the area and volume change probability density function typically follow a distribution that can be characterized by three quantities: A rollover point defined as the peak in the distribution, a cutoff-point indicating the transition to a power law scaling for large landslides and the exponential beta coefficient of this power law. Here we will show that thaw slumps across the arctic follow indeed such a distribution and that the obtained values for the rollover, cutoff and beta coefficient can be used to distinguish between regions. Furthermore we will elaborate on possible reason why arctic thaw slumps can be described by such probability density functions as well as analyzing the differences between regions. This characterization can be useful to further improve our understanding of thaw slump initiation, the investigation of the drivers of their evolution as well as for modeling future thaw slump activity.

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Cross-Correlations in the Brownian Motion of Colloidal Nanoparticles

Studia Universitatis Babeș-Bolyai Physica ◽

10.24193/subbphys.2020.04 ◽

2020 ◽

Vol 65 (1-2) ◽

pp. 27-34

Author(s):

Sz. Kelemen ◽

◽

L. Varga ◽

Z. Néda ◽

◽

...

Keyword(s):

Brownian Motion ◽

Power Law ◽

Cross Correlation ◽

Colloidal Particles ◽

Pearson Correlation ◽

Transverse Component ◽

Collective Effects ◽

Colloidal Nanoparticles ◽

Diffusive Motion ◽

Cross Correlations

"The two-body cross-correlation for the diffusive motion of colloidal nano-spheres is experimentally investigated. Polystyrene nano-spheres were used in a very low concentration suspension in order to minimize the three- or more body collective effects. Beside the generally used longitudinal and transverse component correlations we investigate also the Pearson correlation in the magnitude of the displacements. In agreement with previous studies we find that the longitudinal and transverse component correlations decay as a function of the inter-particle distance following a power-law trend with an exponent around -2. The Pearson correlation in the magnitude of the displacements decay also as a power-law with an exponent around -1. Keywords: colloidal particles, Brownian motion, cross-correlation. "

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Fractal approach towards power-law coherency to measure cross-correlations between time series

Communications in Nonlinear Science and Numerical Simulation ◽

10.1016/j.cnsns.2017.02.018 ◽

2017 ◽

Vol 50 ◽

pp. 193-200 ◽

Cited By ~ 17

Author(s):

Ladislav Kristoufek

Keyword(s):

Time Series ◽

Power Law ◽

Fractal Approach ◽

Cross Correlations

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EFFECTS OF INTRADAY PATTERNS ON ANALYSIS OF STOCK MARKET INDEX AND TRADING VOLUME

International Journal of Modern Physics Conference Series ◽

10.1142/s2010194512007763 ◽

2012 ◽

Vol 16 ◽

pp. 41-50

Author(s):

HYUNG WOOC CHOI ◽

SEONG EUN MAENG ◽

JAE WOO LEE

Keyword(s):

Time Series ◽

Distribution Function ◽

Probability Distribution ◽

Stock Market ◽

Power Law ◽

Volume Change ◽

Probability Distribution Function ◽

Stock Index ◽

The Absolute ◽

Intraday Patterns

We review the stylized properties of the stock market and consider effects of the intraday patterns on the analysis of the time series for the stock index and the trading volume in Korean stock market. In the stock market the probability distribution function (pdf) of the return and volatility followed the power law for the stock index and the change of the volume traded. The volatility of the stock index showed the long-time memory and the autocorrelation function followed a power law. We applied two eliminating methods of the intraday patterns: the intraday patterns of the time series itself, and the intraday patterns of the absolute return for the index or the absolute volume change. We scaled the index and return by two types of the intraday patterns. We considered the probability distribution function and the autocorrelation function (ACF) for the time series scaled by the intraday patterns. The cumulative probability distribution function of the returns scaled by the intraday patterns showed a power law, P>(r) ~ r-α±, where α± corresponds to the exponent of the positive and negative fat tails. The pdf of the return scaled by intraday patterns by the absolute return decayed much steeper than that of the return scaled by intraday patterns of the index itself. The pdf for the volume change also followed the power law for both methods of eliminating intraday patterns. However, the exponents of the power law at fat tails do not depend on the intraday patterns. The ACF of the absolute return showed long-time correlation and followed the power law for the scaled index and for the scaled volume. The daily periodicity of the ACF was removed for scaled time series by the intraday patterns of the absolute return or the absolute volume change.

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MODELING CROSS-CORRELATIONS OF TRAFFIC FLOW

International Journal of Bifurcation and Chaos ◽

10.1142/s0218127410027714 ◽

2010 ◽

Vol 20 (10) ◽

pp. 3323-3328 ◽

Cited By ~ 1

Author(s):

PENGJIAN SHANG ◽

KEQIANG DONG ◽

SANTI KAMAE

Keyword(s):

Time Series ◽

Traffic Flow ◽

Power Law ◽

Cross Correlation ◽

Heavy Tails ◽

Fluctuation Analysis ◽

Cross Correlation Analysis ◽

Cross Correlations ◽

Large Increment ◽

Active Research

The study of diverse natural and nonstationary signals has recently become an area of active research for physicists. This is because these signals exhibit interesting dynamical properties such as scale invariance, volatility correlation, heavy tails and fractality. The focus of the present paper is on the intriguing power-law autocorrelations and cross-correlations in traffic series. Detrended Cross-Correlation Analysis (DCCA) is used to study the traffic flow fluctuations. It is demonstrated that the time series, observed on the Anhua-Bridge highway in the Beijing Third Ring Road (BTRR), may exhibit power-law cross-correlations when they come from two adjacent sections or lanes. This indicates that a large increment in one traffic variable is more likely to be followed by large increment in the other traffic variable. However, for traffic time series derived from nonadjacent sections or lanes, we find that even though they are power-law autocorrelated, there is no cross-correlation between them with a unique exponent. Our results show that DCCA techniques based on Detrended Fluctuation Analysis (DFA) can be used to analyze and interpret the traffic flow.

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