Estimating the Hurst parameter in financial time series via heuristic approaches

Cheong, Chin Wen

doi:10.1080/02664760802582280

Cited by 12 publications

(7 citation statements)

References 25 publications

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“…This finding could indicate that Hurst exponents behave differently before and during the financial turmoil. A similar result is shown in [20] during the Asian crisis in the Malaysian market.…”

Section: Resultssupporting

confidence: 81%

“…Also, [51] uses a sample of 16 stock markets of OECD countries and finds evidence of long memory only in 3 of them and [34] find that among the four main central European countries (Czech Republic, Hungary, Poland and Slovak Republic), only the last one exhibits long memory. [20] compute the Hurst exponent by means of three heuristic methods and find evidence of long memory in the returns of five Malaysian equity market indices. This study finds that the Asian economic crisis affected the extent of long-range memory of the Malaysian stock market.…”

Section: Literature Reviewmentioning

confidence: 99%

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The impact of the financial crisis on the long-range memory of European corporate bond and stock markets

Martinez,

Guercio,

Bariviera

et al. 2016

Preprint

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This paper investigates the presence of long memory in corporate bond and stock indices of six European Union countries from July 1998 to February 2015. We compute the Hurst exponent by means of the DFA method and using a sliding window in order to measure long range dependence. We detect that Hurst exponents behave differently in the stock and bond markets, being smoother in the stock indices than in the bond indices. We verify that the level of informational efficiency is time-varying. Moreover we find an asymmetric impact of the 2008 financial crisis in the fixed income and the stock markets, affecting the former but not the latter. Similar results are obtained using the R/S method. JEL classification: G14,C40.

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Section: Resultssupporting

confidence: 81%

Section: Literature Reviewmentioning

confidence: 99%

The impact of the financial crisis on the long-range memory of European corporate bond and stock markets

Martinez,

Guercio,

Bariviera

et al. 2016

Preprint

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“…A fractal analysis of the time series dynamics of the frequency of requests for exchange rates as a macroeconomic indicator of information activity of socio-economic market agents was carried out in [3] on the basis of processing the corresponding methodology [4,19,20]. Thus, the research of the time series of the behavior parameters of market agents lies in the plane of nonlinear dynamics problems [5,6,7,18], the object of research of which in modern scientific works is the courses of financial and electronic tools, crisis phenomena, the dynamics of the development of financial markets [8,9,10,22,23] with the aim of identifying natural trends, selfsimilarity, cyclicity, and other properties [11,21]. Only the information space of the online environment remains superficially studied, although it quantitatively reflects the range of interests of agents in the markets in dynamics.…”

Section: Related Workmentioning

confidence: 99%

Recurrence Analysis of the Economic Behavior of Agents of the Frequency of Online Exchange Rate in the Information Environment

Kucherova¹,

Ocheretin

Los

et al. 2020

Proceedings of the III International Scientific Congress Society of Ambient Intelligence 2020 (ISC-SAI 2020)

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The behavior of the socioeconomic agents of the foreign exchange market has always been characterized by insufficient predictability, therefore today researchers do not leave the search for new methods and indicators for their prediction. With the development of the information society and online technologies, one of the manifestations of the behavior of agents in the foreign exchange market has become their semantic-thematic online queries in search engines. Considering that the time series of exchange rates have been sufficiently studied, insufficient attention has been paid to the dynamics of the frequency of requests for exchange rates as to the parameters of the online behavior of foreign exchange market agents. Since the dynamics of the frequency of requests for exchange rates (dollar, euro) is non-linear, a recurrence analysis was applied. The results of this analysis proved that the tendencies of informational activity of agents are characterized by an antipersistent type of behavior with periodicity and the presence of drift, which are manifested in varying degrees for each exchange rate. If for the indicator of the dollar exchange rate a concentration of interest of market agents near the trajectory of a certain attractor with other deviations due to other factors is shown, then a similar indicator of the euro exchange rate is characterized by a more pronounced and stable over time cyclical manifestation of information activity of agents. In further researches, it is planned to implement a quantitative analysis of the constructed recurrence plots in order to take into account the behavior of the agents of the foreign exchange market.

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“…The method of R/S analysis is definitely the most widespread evaluation of long memory in time series, but it is unstable for non-stationary time series (see, for example [38] - [40]). In particular, R/S analysis provides biased estimates for Hurst statistics, when the studied series: (i) contains short-term dependencies; (ii) is nonstationary; (iii) is heterogeneous, i.e., the series contains a heterogeneous sample.…”

Section: R/s Analysismentioning

confidence: 99%

Modelling multifractal properties of cryptocurrency market

Derbentsev¹,

Kibalnyk²,

Radzihovska³

2019

PEN

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The paper focuses on the study of the effect of long memory and the analysis of the multifractal properties of the time series of the most capitalized cryptocurrencies for the period from 2010 to 2018. To do this, the Hurst exponent is calculated by both R/S analysis and the Detrended Fluctuation Analysis being more stable in the case of non-stationary time series. Our results show that time series of cryptocurrencies to be persistent during almost the whole study period that do not allow accepting the hypothesis concerning the efficiency of the cryptocurrency market. We also found that (i) time series became anti-persistent during the periods of market crisis phenomena and turbulence; (ii) the Hurst exponents showed significant fluctuations about the value of 0.5. In addition, we conduct a multifractal analysis of cryptocurrency time series that allows us to assess the state and stability of the market.The calculated spectrum of multifractality shows that the cryptocurrency market comes out of a crisis state, since the width of the multifractality spectrum has the maximum value for all cryptocurrencies.

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Estimating the Hurst parameter in financial time series via heuristic approaches

Cited by 12 publications

References 25 publications

The impact of the financial crisis on the long-range memory of European corporate bond and stock markets

The impact of the financial crisis on the long-range memory of European corporate bond and stock markets

Recurrence Analysis of the Economic Behavior of Agents of the Frequency of Online Exchange Rate in the Information Environment

Modelling multifractal properties of cryptocurrency market

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