Searcharxiv⌕ Search

arXiv · physics/0512169

Volatility of an Indian stock market : A random matrix approach

Abstract

We examine volatility of an Indian stock market in terms of aspects like participation, synchronization of stocks and quantification of volatility using the random matrix approach. Volatility pattern of the market is found using the BSE index for the three-year period 2000-2002. Random matrix analysis is carried out using daily returns of 70 stocks for several time windows of 85 days in 2001 to (i) do a brief comparative analysis with statistics of eigenvalues and eigenvectors of the matrix C of correlations between price fluctuations, in time regimes of different volatilities. While a bulk of eigenvalues falls within RMT bounds in all the time periods, we see that the largest (deviating) eigenvalue correlates well with the volatility of the index, the corresponding eigenvector clearly shows a shift in the distribution of its components from volatile to less volatile periods and verifies the qualitative association between participation and volatility (ii) observe that the Inverse participation ratio for the 'last' eigenvector is sensitive to market fluctuations (the two quantities are observed to anti correlate significantly) (iii) set up a variability index, V whose temporal evolution is found to be significantly correlated with the volatility of the overall market index.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

V. Kulkarni, N. Deo. 2005-12-19. Volatility of an Indian stock market : A random matrix approach. https://arxiv.org/abs/physics/0512169

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

CrowdEgress: A Multi-Agent Simulation Platform for Pedestrian Crowd

This article introduces a simulation platform to study complex crowd behavior in social context. The agent-based model is extended based on the social force model, and it mainly describes how agents interact with each other, and also with surrounding facilities such as walls, doors and exits. The simulation platform is compatible to FDS+Evac, and the input data in FDS+Evac could be imported into our simulation platform to create single-floor compartment geometry, and a flow solver is used to generate the roadmap towards exits. Most importantly, we plan to integrate advanced social and psychological theory into our simulation platform, especially investigating human behavior in emergency evacuation,such as pre-evacuation behavior, exit-selection activities, social group and herding effect and so forth.

physics.soc-ph↗

The distribution of violent event and interevent times in conflicts

Ongoing violent conflicts at all scales are interrupted by lulls without violence. Studies of interevent times found power-law distributions, based on coarse-grained data with a resolution of days or longer. Fine-grained data with a resolution of seconds or shorter is rare. Here, interevent times in violent conflicts are represented as multiplicative processes, and video-recorded street fights are used as fine grained data. For multiplicative processes, a mathematical theorem predicts that coarse grained data are power-law distributed, but fine grained data are lognormal. To the street violence data, however, the lognormal does not fit better than the power law (and vice versa), although the lognormal covers more data. Violent events, by contrast, take much energy and their durations are shorter, hence their distribution is better approximated by an exponential.

physics.soc-ph↗

Generalized Discrete Fractal Dimensions of Graph Families

Quantifying the self-similarity of complex networks via discrete fractal dimensions is a fundamental problem in network science. In this paper, we investigate some general fractal dimensions of graph families based on q-energy and Rényi entropy. We first establish several bounds for the energy, and then discuss the monotonicity, measure invariance of the dimensions, as well as some concrete graph families.

physics.soc-ph↗