MULTIFRACTAL DETRENDED CROSS-CORRELATION ANALYSIS OF BVP MODEL TIME SERIES

We found that there exists a power-law cross-correlation between the Gold and Crude Oil time series and the multifractal features are significant. Research Article Open Access. Cross-correlations of very small fluctuations and large fluctuations are persistent but whereas for small fluctuations are anti-persistent in the long term. Crude Oil is a vital source of energy for the world hence higher crude oil prices drive fuel inflation as crude oil demand is inelastic. In this paper, we used multifractal detrended cross-correlation analysis to investigate the cross-correlation properties between Gold and WTI Crude Oil. Although crude oil prices possess long-range dependence, the degree of long-range has decreased in short time horizons, although the market is tending towards efficiency regime at long.

Crude Oil is a vital source of energy for the world hence higher crude oil prices drive fuel inflation as crude oil demand is inelastic. Thus, 2N s non-overlapping windows are obtained together. Gold also most popularly used as an investment. To test the presence of cross-correlation quantitatively we need MF-X-FA method which can estimate the cross-correlation exponent. Diversity of participants like producers, government, extreme socio-political events and speculators drive crude oil market price. Our results have significant implications to market efficiency. Select your language of interest to view the total content in your interested language. Here the scaling exponent H xy q is known as the generalized crosscorrelation Hurst exponent, describing the power-low relationship.

Here the scaling exponent H xy q is known as the generalized crosscorrelation Hurst exponent, describing the power-low relationship. Section 5 gives our conclusions. Crude oil outside the US market is priced in accordance with Brent price, so Brent price can reflect international crude oil demand more deeply than WTI.

Crude oil is called the blood of industries which plays an important role in all economies driving backbone of financial system. Market agent perspective on fractal features in crude oil time series was studied [ 2930 ]. Dynamics of crude multifgactal prices was studied thru stochastic multi-model approach [ 28 ]. Diversity of participants like producers, government, extreme socio-political events and speculators drive crude oil multifdactal price.

The main idea behind the gold-crude oil cross correlation is the one which suggests that prices of cross-correlatino oil crpss-correlation account for inflation.

Cross-correlation found to be exists in many simultaneously recorded time series in various real world commodities or financial market data. Detrended Cross-Correlation Analysis DCCA was proposed [ 17 timr to investigate power-law cross-correlations between two simultaneously recorded time series in the presence of non-stationarity.

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Increases in oil price increases prices of gasoline which is derived from oil which drives transport of goods costly hence the Good prices rises.

Our results have significant implications to market efficiency. The results demonstrate the overall significance of the crosscorrelation based on the analysis of multifractality.

Therefore, understanding the dynamics of its price time series seems to be crucial, since it may allow one to assess the potential impacts of its shocks on several cross-correlatioh and on other financial assets.

Although crude oil prices possess long-range dependence, the degree of long-range has decreased in short time horizons, although the market is tending towards efficiency regime at long.

Multifractal Detrended Cross-correlation Analysis of Gold and WTI Crude Oil Price Time Series

It is of crucial importance and significance to quantify such long-range correlations to have a deep understanding of the dynamics of the underlying complex systems. The return of daily price is calculated as, where Pt being the daily closing price index at time t Figure 1. Analyze the scaling behavior of the fluctuations by observing logarithmic plots between F q s and s for each values of q.

The multifractality in real world non stationary time series data are described better from scaling exponents. Similarly Gold price fluctuation and trading crosscorrelation directly related to market inflation in any country.

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From our analysis we found Gold price has long term correlation with crude oil price. Cross-correlations of very small fluctuations and large fluctuations are persistent but whereas for small fluctuations are anti-persistent in the long term.

Oil price, as one of the main focal points in many countries, has become an increasingly essential topic of concern to governments, enterprises and investors.

Global crude oil pricing benchmarks Brent and WTI price hence its price cross-correltion become a crosss-correlation research topic recently. With the time evolving, the short-term shocks gradually decay for the effects of long-term supply and demand mechanism in the markets. We get the crosscorrelation exponent 0.

Crude Oil is a vital source of energy for the world hence higher crude oil prices drive fuel inflation as crude oil demand tme inelastic. Many researchers studied multifractal properties on the different non stationary natural and financial time series data like biological data [ 6 ], exchange ddetrended market [ 7 ], stock market [ 89 ] gold market [ 810 ], crude oil market [ 9 – 12 ]. For two markets, maybe Brent dertended is affected more by Gulf Wars than WTI hence to avoid impact of gulf war onto Crude oil price we had chosen WTI Crude oil time aanalysis for cross correlation study with Gold time series.

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Furthermore, based on multifractal spectrum, we have produced xetrended evidences to determine crosscorrelation behaviors exhibit multifractal features. We find that the cross-correlations display the characteristic of multifractality in the short term. We found that there exists a power-law cross-correlation between the Gold and Crude Oil time series and the multifractal features are significant. In Figure 2 we can find that only one line cannot fit the log-log plots of F q s versus time scale s well.

Moreover, their behavior for small fluctuations is persistent and those of large fluctuations are anti persistent in the short term. Select your language of interest to view the total content in your interested language. Two major sources of multifractality which can be found in various time series: Since the length N is not always a multiple of the considered time scale s hence in order not to discard the section of series, the same procedure is repeated starting from the reverse end of each profile.

Several papers have documented the cross-correlations across wide range of markets using different methods and the results are being used for the improvisation of market efficiency. Gold also most popularly used as an investment. Analysia, 2N s non-overlapping windows are obtained together. J Bus Fin Aff 3: Research Article Open Access. The short-term behavior of cross-correlarion market is easily influenced by the market external factors such as the major events while the long-term behavior is determined by the internal factors.

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The theory of fractals proposed by Mandelbrot [ 1 ] in contrast to the efficient market hypothesis leads to study of complex system behavior through different method development and approaches.