arXiv subjects

Ladislav Kristoufek

Publications and source records attributed to Ladislav Kristoufek.

At least 19 recordsLinked to original sources

arXiv2020

Grandpa, grandpa, tell me the one about Bitcoin being a safe haven: Evidence from the COVID-19 pandemics

Bitcoin being a safe haven asset is one of the traditional stories in the cryptocurrency community. However, during its existence and relevant presence, i.e. approximately since 2013, there has been no severe situation on the financial markets globally to prove or disprove this story until the COVID-19 pandemics. We study the quantile correlations of Bitcoin and two benchmarks -- S\&P500 and VIX -- and we make comparison with gold as the traditional safe haven asset. The Bitcoin safe haven story is shown and discussed to be unsubstantiated and far-fetched, while gold comes out as a clear winner in this contest.

q-fin.ST↗

arXiv2018

Power-law cross-correlations: Issues, solutions and future challenges

Analysis of long-range dependence in financial time series was one of the initial steps of econophysics into the domain of mainstream finance and financial economics in the 1990s. Since then, many different financial series have been analyzed using the methods standardly used outside of finance to deliver some important stylized facts of the financial markets. In the late 2000s, these methods have started being generalized to bivariate settings so that the relationship between two series could be examined in more detail. It was then only a single step from bivariate long-range dependence towards scale-specific correlations and regressions as well as power-law coherency as a unique relationship between power-law correlated series. Such rapid development in the field has brought some issues and challenges that need further discussion and attention. We shortly review the development and historical steps from long-range dependence to bivariate generalizations and connected methods, focus on its technical aspects and discuss problematic parts and challenges for future directions in this specific subfield of econophysics.

q-fin.ST↗

arXiv2017

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

We focus on power-law coherency as an alternative approach towards studying power-law cross-correlations between simultaneously recorded time series. To be able to study empirical data, we introduce three estimators of the power-law coherency parameter $H_ρ$ based on popular techniques usually utilized for studying power-law cross-correlations -- detrended cross-correlation analysis (DCCA), detrending moving-average cross-correlation analysis (DMCA) and height cross-correlation analysis (HXA). In the finite sample properties study, we focus on the bias, variance and mean squared error of the estimators. We find that the DMCA-based method is the safest choice among the three. The HXA method is reasonable for long time series with at least $10^4$ observations, which can be easily attainable in some disciplines but problematic in others. The DCCA-based method does not provide favorable properties which even deteriorate with an increasing time series length. The paper opens a new venue towards studying cross-correlations between time series.

q-fin.ST↗

arXiv2016

Has global warming modified the relationship between sunspot numbers and global temperatures?

We study time evolution of the relationship between sunspot numbers and global temperatures between 1880 and 2016 using wavelet coherence framework. The results suggest that the relationship is stable in time. Changes in the sunspot numbers precede changes in the temperatures by more than two years as suggested by the wavelet phase differences. This leading position of the sun activity is stable in time as well. However, the relationship has been disturbed by increasing $CO_2$ emissions since 1960s. Without controlling for the effect of possible global warming, or more precisely the positive connection between increasing $CO_2$ emissions and the global temperatures, the findings would have been quite different. Combination of the cointegration analysis and wavelet coherence framework has enabled uncovering a hidden relationship between the solar activity and global temperatures, and possibly explaining equivocal results in the topical literature.

stat.AP↗

arXiv2016

Power-law cross-correlations estimation under heavy tails

We examine the performance of six estimators of the power-law cross-correlations -- the detrended cross-correlation analysis, the detrending moving-average cross-correlation analysis, the height cross-correlation analysis, the averaged periodogram estimator, the cross-periodogram estimator and the local cross-Whittle estimator -- under heavy-tailed distributions. The selection of estimators allows to separate these into the time and frequency domain estimators. By varying the characteristic exponent of the $α$-stable distributions which controls the tails behavior, we report several interesting findings. First, the frequency domain estimators are practically unaffected by heavy tails bias-wise. Second, the time domain estimators are upward biased for heavy tails but they have lower estimator variance than the other group for short series. Third, specific estimators are more appropriate depending on distributional properties and length of the analyzed series. In addition, we provide a discussion of implications of these results for empirical applications as well as theoretical explanations.

q-fin.ST↗

arXiv2015

Gold, currencies and market efficiency

Gold and currency markets form a unique pair with specific interactions and dynamics. We focus on the efficiency ranking of gold markets with respect to the currency of purchase. By utilizing the Efficiency Index (EI) based on fractal dimension, approximate entropy and long-term memory on a wide portfolio of 142 gold price series for different currencies, we construct the efficiency ranking based on the extended EI methodology we provide. Rather unexpected results are uncovered as the gold prices in major currencies lay among the least efficient ones whereas very minor currencies are among the most efficient ones. We argue that such counterintuitive results can be partly attributed to a unique period of examination (2011-2014) characteristic by quantitative easing and rather unorthodox monetary policies together with the investigated illegal collusion of major foreign exchange market participants, as well as some other factors discussed in some detail.

q-fin.ST↗

arXiv2015

Power-law correlations in finance-related Google searches, and their cross-correlations with volatility and traded volume: Evidence from the Dow Jones Industrial components

We study power-law correlations properties of the Google search queries for Dow Jones Industrial Average (DJIA) component stocks. Examining the daily data of the searched terms with a combination of the rescaled range and rescaled variance tests together with the detrended fluctuation analysis, we show that the searches are in fact power-law correlated with Hurst exponents between 0.8 and 1.1. The general interest in the DJIA stocks is thus strongly persistent. We further reinvestigate the cross-correlation structure between the searches, traded volume and volatility of the component stocks using the detrended cross-correlation and detrending moving-average cross-correlation coefficients. Contrary to the universal power-law correlations structure of the related Google searches, the results suggest that there is no universal relationship between the online search queries and the analyzed financial measures. Even though we confirm positive correlation for a majority of pairs, there are several pairs with insignificant or even negative correlations. In addition, the correlations vary quite strongly across scales.

q-fin.ST↗

arXiv2015

Worldwide clustering of the corruption perception

We inspect a possible clustering structure of the corruption perception among 134 countries. Using the average linkage clustering, we uncover a well-defined hierarchy in the relationships among countries. Four main clusters are identified and they suggest that countries worldwide can be quite well separated according to their perception of corruption. Moreover, we find a strong connection between corruption levels and a stage of development inside the clusters. The ranking of countries according to their corruption perfectly copies the ranking according to the economic performance measured by the gross domestic product per capita of the member states. To the best of our knowledge, this study is the first one to present an application of hierarchical and clustering methods to the specific case of corruption.

econ.GN↗

arXiv2015

Can the bivariate Hurst exponent be higher than an average of the separate Hurst exponents?

In this note, we investigate possible relationships between the bivariate Hurst exponent $H_{xy}$ and an average of the separate Hurst exponents $\frac{1}{2}(H_x+H_y)$. We show that two cases are well theoretically founded. These are the cases when $H_{xy}=\frac{1}{2}(H_x+H_y)$ and $H_{xy}<\frac{1}{2}(H_x+H_y)$. However, we show that the case of $H_{xy}>\frac{1}{2}(H_x+H_y)$ is not possible regardless of stationarity issues. Further discussion of the implications is provided as well together with a note on the finite sample effect.

physics.data-an↗

arXiv2015

Detrended fluctuation analysis as a regression framework: Estimating dependence at different scales

We propose a framework combining detrended fluctuation analysis with standard regression methodology. The method is built on detrended variances and covariances and it is designed to estimate regression parameters at different scales and under potential non-stationarity and power-law correlations. The former feature allows for distinguishing between effects for a pair of variables from different temporal perspectives. The latter ones make the method a significant improvement over the standard least squares estimation. Theoretical claims are supported by Monte Carlo simulations. The method is then applied on selected examples from physics, finance, environmental science and epidemiology. For most of the studied cases, the relationship between variables of interest varies strongly across scales.

q-fin.ST↗

arXiv2014

On the interplay between short and long term memory in the power-law cross-correlations setting

We focus on emergence of the power-law cross-correlations from processes with both short and long term memory properties. In the case of correlated error-terms, the power-law decay of the cross-correlation function comes automatically with the characteristics of separate processes. Bivariate Hurst exponent is then equal to an average of separate Hurst exponents of the analyzed processes. Strength of short term memory has no effect on these asymptotic properties. Implications of these findings for the power-law cross-correlations concept are further discussed.

stat.ME↗

arXiv2014

Spectrum-based estimators of the bivariate Hurst exponent

We introduce two new estimators of the bivariate Hurst exponent in the power-law cross-correlations setting -- the cross-periodogram and local $X$-Whittle estimators -- as generalizations of their univariate counterparts. As the spectrum-based estimators are dependent on a part of the spectrum taken into consideration during estimation, a simulation study showing performance of the estimators under varying bandwidth parameter as well as correlation between processes and their specification is provided as well. The newly introduced estimators are less biased than the already existent averaged periodogram estimator which, however, has slightly lower variance. The spectrum-based estimators can serve as a good complement to the popular time domain estimators.

q-fin.ST↗

arXiv2014

Finite sample properties of power-law cross-correlations estimators

We study finite sample properties of estimators of power-law cross-correlations -- detrended cross-correlation analysis (DCCA), height cross-correlation analysis (HXA) and detrending moving-average cross-correlation analysis (DMCA) -- with a special focus on short-term memory bias as well as power-law coherency. Presented broad Monte Carlo simulation study focuses on different time series lengths, specific methods' parameter setting, and memory strength. We find that each method is best suited for different time series dynamics so that there is no clear winner between the three. The method selection should be then made based on observed dynamic properties of the analyzed series.

physics.data-an↗

arXiv2014

Can Google searches help nowcast and forecast unemployment rates in the Visegrad Group countries?

Online activity of the Internet users has been repeatedly shown to provide a rich information set for various research fields. We focus on the job-related searches on Google and their possible usefulness in the region of the Visegrad Group -- the Czech Republic, Hungary, Poland and Slovakia. Even for rather small economies, the online searches of their inhabitants can be successfully utilized for macroeconomic predictions. Specifically, we study the unemployment rates and their interconnection to the job-related searches. We show that the Google searches strongly enhance both nowcasting and forecasting models of the unemployment rates.

econ.GN↗

arXiv2014

Rockets and feathers meet Joseph: Reinvestigating the oil-gasoline asymmetry on the international markets

We reinvestigate the "rockets and feathers" effect between retail gasoline and crude oil prices in a new framework of fractional integration, long-term memory and borderline (non-)stationarity. The most frequently used error-correction model is examined in detail and we find that the prices return to their equilibrium value much more slowly than would be typical for the error-correction model. Such dynamics is usually referred to as "the Joseph effect". The standard procedure is shown to be troublesome and we introduce three new tests to investigate possible asymmetry in the price adjustment to equilibrium under these complicated time series characteristics. On the dataset of seven national gasoline prices, we report that apart from Belgium, there is no asymmetry found. The proposed methodology is not limited to the gasoline and crude oil case but it can be utilized for any asymmetric adjustment to equilibrium analysis.

q-fin.ST↗

arXiv2014

What are the main drivers of the Bitcoin price? Evidence from wavelet coherence analysis

Bitcoin has emerged as a fascinating phenomenon of the financial markets. Without any central authority issuing the currency, it has been associated with controversy ever since its popularity and public interest reached high levels. Here, we contribute to the discussion by examining potential drivers of Bitcoin prices ranging from fundamental to speculative and technical sources as well as a potential influence of the Chinese market. The evolution of the relationships is examined in both time and frequency domains utilizing the continuous wavelets framework so that we comment on development of the interconnections in time but we can also distinguish between short-term and long-term connections.

q-fin.CP↗

arXiv2014

Measuring capital market efficiency: Long-term memory, fractal dimension and approximate entropy

We utilize long-term memory, fractal dimension and approximate entropy as input variables for the Efficiency Index [Kristoufek & Vosvrda (2013), Physica A 392]. This way, we are able to comment on stock market efficiency after controlling for different types of inefficiencies. Applying the methodology on 38 stock market indices across the world, we find that the most efficient markets are situated in the Eurozone (the Netherlands, France and Germany) and the least efficient ones in the Latin America (Venezuela and Chile).

q-fin.ST↗

arXiv2014

Leverage effect in energy futures

We propose a comprehensive treatment of the leverage effect, i.e. the relationship between returns and volatility of a specific asset, focusing on energy commodities futures, namely Brent and WTI crude oils, natural gas and heating oil. After estimating the volatility process without assuming any specific form of its behavior, we find the volatility to be long-term dependent with the Hurst exponent on a verge of stationarity and non-stationarity. Bypassing this using by using the detrended cross-correlation and the detrending moving-average cross-correlation coefficients, we find the standard leverage effect for both crude oil. For heating oil, the effect is not statistically significant, and for natural gas, we find the inverse leverage effect. Finally, we also show that none of the effects between returns and volatility is detected as the long-term cross-correlated one. These findings can be further utilized to enhance forecasting models and mainly in the risk management and portfolio diversification.

q-fin.ST↗