0000000000626806
AUTHOR
Jaan Kalda
The Problem of Time Arrow in Financial Time Series
According to the efficient market hypothesis, future movements of the market cannot be predicted. This introduces an intrinsic time asymmetry of the financial time series as there are no laws forbidding “predicting” past based on the current market fluctuations. This clear time asymmetry in the basic laws of finance raises a question which we shall be referring to as the problem of time arrow: are there any noticeable statistical differences between forward-in-time and reverse-in-time market data. Majority of the statistical methods used for financial time series are time-symmetric and hence, not usable for our purposes. The first method used in our study is the analysis of the length-distr…
Melt extraction and accumulation from partially molten rocks
Current models for melt segregation and ascent are not adequate to accurately describe transport and accumulation in combination. We propose that transport is discontinuous and in batches, and that accumulation occurs by stepwise merging of batches. A simple numerical model of jostling spheres that merge when they touch was used to represent stepwise accumulation and transport of batches by propagation of hydrofractures. Results of the numerical model indicate that such a system may quickly develop into a self-organised critical (SOC) state. In this state, the distribution of melt batch volumes can be described by a power law, with an exponent m that lies between 2/3 and 1. Once a self-orga…
The predictive power of power-laws: An empirical time-arrow based investigation
The efficient market hypothesis forbids any predictability towards future, but there is no such restriction in the case of reversed-looking approaches. We analyze if this asymmetry in non-predictability is reflected in the statistical features of financial time series. Our study is based on the analysis of the length-distribution of periods with high variability, and introduces time-asymmetric modifications of the method which are capable of revealing differences of the time series in forward and reversed time. We show that the future and reversed-looking time-series possess very similar properties, with some features being distinguishable with our method. Our findings give also evidence of…
Propagation of Bankruptcy Risk over Scale-Free Economic Networks.
The propagation of bankruptcy-induced shocks across domestic and global economies is sometimes very dramatic; this phenomenon can be modelled as a dynamical process in economic networks. Economic networks are usually scale-free, and scale-free networks are known to be vulnerable with respect to targeted attacks, i.e., attacks directed towards the biggest nodes of the network. Here we address the following question: to what extent does the scale-free nature of economic networks and the vulnerability of the biggest nodes affect the propagation of economic shocks? We model the dynamics of bankruptcies as the propagation of financial contagion across the banking sector over a scale-free network…