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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Fractal Analysis of Currency Market: Hurst Index as an Indicator of Abnormal Events</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Olena Liashenko</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Tetyana Kravets</string-name>
          <email>tankravets@univ.kiev.ua</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="editor">
          <string-name>Key Terms. Model, Research, Management</string-name>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Taras Shevchenko National University of Kyiv</institution>
        </aff>
      </contrib-group>
      <pub-date>
        <year>2016</year>
      </pub-date>
      <fpage>21</fpage>
      <lpage>24</lpage>
      <abstract>
        <p>The article is devoted to analysis of currency quotes behavior on the currency market by defining dynamic changes over time. The main tool of fractal analysis is the Hurst under the hypothesis of fractal market. For 17 major currency pairs on closing prices and the prices maximum-minimum the Hurst index is calculated by formula for the adjusted R/S analysis. Values at the currency markets of different countries in different economic conditions are compared during 2008-2015. For currency pairs Hurst index tends to maintain its average value in stable economic situation, while it is an indicator of events affecting directly or indirectly on the state's economy and the rate of its national currency. Application of sliding window method allows to simulate the dynamics of Hurst index for the currency pairs USD/JPY, GBP/JPY, EUR/USD, GBP/USD and establish certain patterns of conduct series of quotes due to appropriate reaction to economic, political and natural disturbances.</p>
      </abstract>
      <kwd-group>
        <kwd />
        <kwd>Fractal analysis</kwd>
        <kwd>exchange rates</kwd>
        <kwd>crisis</kwd>
        <kwd>Hurst index</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>The transition of Ukraine to the market economy, creation of modern infrastructure,
evolution of ownership and increasing independence of participants of market
relations inevitably leads to the need for constant monitoring of trends and identification
of features of financial and monetary system functioning. Foreign exchange market as
one of the main elements of the system in the last decade characterized by increasing
globalization and transformation processes.</p>
      <p>Due to the fact that international economic relations generate the corresponding
cash requirements and obligations of the parties, a prerequisite for their settlement is
national currency using, as the only universal global means of payment does not exist
yet. It leads to the need to exchange one currency for another in the form of purchase
of foreign currency by payer or recipient of funds in international operations. The
international payment transactions related to payment of receivables and liabilities of</p>
      <p>- 551
businesses and individuals around the world are serviced by foreign exchange market,
defining its objective necessity.</p>
      <p>The features of contemporary currency markets are internationalization,
globalization, standardization and automation of communication facilities in the
implementation of foreign exchange transactions. Thus there is the instability of exchange rates.
Predicting future behavior of exchange rates is important because it allows to reduce
currency risks and ensure the efficiency of various solutions in international financial
management.</p>
      <p>The aim is to study the behavior of the currency pairs using Hurst index monitoring
as one of the tools of fractal analysis, under the hypothesis of fractal market.
2</p>
    </sec>
    <sec id="sec-2">
      <title>Analysis of Recent Research</title>
      <p>
        During the last three decades an efficient market theory was the most famous theory
of financial markets. The statement of this theory is that changes in asset prices reflect
the important new information release fully and immediately. In addition, through a
flow of information that can be provided between the current and the next trading
period, changes in asset prices are independent. In other words, the unpredictable
release of information drives asset prices in a random order, and price fluctuations
comply the normal distribution [
        <xref ref-type="bibr" rid="ref1 ref2 ref3 ref4 ref5 ref6">1-6</xref>
        ].
      </p>
      <p>Efficient market hypothesis (EMH), like all other economic concepts is based on
linear paradigm, whereby each economic action (event) causes linearly proportional
reaction that produced some cause and effect relationships. However, economic
theory, based on the principles of balance, couldn’t explain many complex financial
phenomena. Revolution was needed and put into nonlinearity analysis.</p>
      <p>
        Based on the nonlinear paradigm the fractal market hypothesis (FMH) emerged
and was developed, whereby a certain action (or event) causes a nonlinear response
that is exponential, unexpected, extremely strong and no one expected reaction. In
contrast to the efficient market hypothesis the fractal market hypothesis states that the
information is evaluated depending on the investment horizon of the investor. As
different investment horizons evaluate information differently, dissemination of
information is uneven also. At any certain time moment the price may not reflect all
existing information, it can display only the part that is important for this investment
horizon. FMH admits that chaotic mode occurs when investors lose confidence in the
long-term fundamental information [
        <xref ref-type="bibr" rid="ref1 ref2 ref3 ref4 ref5">1-5</xref>
        ].
      </p>
      <p>
        One of the results of exchange and stock markets research made by Mandelbrot,
Peters [
        <xref ref-type="bibr" rid="ref1 ref2 ref3">3, 1-2</xref>
        ] is that the distribution of price changes are fractal Pareto distribution.
This distribution has the property of statistical self-similarity in time (the presence of
long memory). In addition, it was shown that the financial markets are nonlinear
dynamic systems, which opened up opportunities for the study of financial markets by
means of the theory of dynamical systems and deterministic chaos [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ].
      </p>
      <p>
        There are several alternative approaches to assessing the fractal structure of the
time series: R/S-analysis; method based on the determination of cell dimensions;
standard fluctuation analysis; detrend fluctuation analysis (DFA); multifractal DFA.
The description and practical application of these methods can be found in [
        <xref ref-type="bibr" rid="ref10 ref11 ref12 ref13 ref14 ref15 ref16 ref3 ref5 ref6 ref7 ref8 ref9">3, 5-16</xref>
        ].
For example, using the R/S-analysis in [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ] the Hurst index was estimated and it was
H 
log  R / S 
log  aN 
      </p>
      <p>
        , where H - Hurst index; S - standard deviation of observations
numproved that hypothesis of FMH could be "reasonable" generalization of the efficient
market hypothesis. In [
        <xref ref-type="bibr" rid="ref12">12</xref>
        ], the authors conducted an empirical study of scaling and
multifractal properties of currency pair USD/DEM.
      </p>
      <p>
        Multifractal spectra singularities for different currency pairs were studied in
[1316]. The use of different approaches to assessing the performance of fractal time
series supports the hypothesis of FMH and allows to generalize it to multifractal market
hypothesis (MFMH). In [
        <xref ref-type="bibr" rid="ref8">8</xref>
        ] it is demonstrated that a change of fractal properties of
returns in exchange rates are an indicator of a currency crisis.
3
      </p>
    </sec>
    <sec id="sec-3">
      <title>Research method</title>
      <p>
        R/S-analysis method of study of fractal time series was proposed by Mandelbrot [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ]
and it is based on research conducted by the British explorer Hurst. It is based on the
analysis of accumulated magnitude deviation of observations series and standard
deviation. Hurst offered new statistics - Hurst index, which is widely used in the
analysis of time series due to its stability. Its calculation requires minimum assumptions
about studied system and time series can be classified by the type and the depth of
memory on its basis. It can distinguish a random series of non-random one, even if the
random series has non-Gaussian distribution [
        <xref ref-type="bibr" rid="ref18">18</xref>
        ].
      </p>
      <p>
        Calculation of Hurst index can be carried out as follows: R / S   aN H
or
ber; R – variation of accumulated deviation; N - number of observation periods; a
positive constant [
        <xref ref-type="bibr" rid="ref17 ref9">9, 17</xref>
        ].
      </p>
      <p>The scale of the accumulated deviation R is the most important element of Hurst
index formula: R  max  Zu   min  Zu  , where Zu - the accumulated deviations
num1uN 1uN
u
ber of values x from the mean x , i.e. Zu    xi  x  . Formula for Hurst index
i1
shows that the increasing scale, reducing standard deviation and reducing number of
observations influence on its growth.</p>
      <p>
For further calculations we use a </p>
      <p>
         1, 5708 as the choice of another constant
2
for calculating. Hurst index inflates its value significantly. It will lead to erroneous
conclusions about persistence of random series [
        <xref ref-type="bibr" rid="ref9">9</xref>
        ].
      </p>
      <p>While a small number of observations, actual calculations of normalized variation
R/S for random series give much too low results compared to theoretical ones</p>
      <p>N
R / S </p>
      <p>
        2
number of observations N  250 . To avoid this contradiction, it is necessary to
transform actually calculated values of normalized variation using the formula [
        <xref ref-type="bibr" rid="ref9">9</xref>
        ]:
. This contradiction leads to lower values of Hurst index when the
      </p>
      <p>
        However, due to feature of logarithmic calculations of Hurst index, the adjusted
value of normalized variation will contain a minor error also. On the basis of the
correlation between the number of observations and the ratio of the standard and actual
Hurst index it is necessary to adjust the formula for Hurst index calculation so that its
value was close at most to a standard one for random series ( H  0, 5 ) for all N. The
final formula is [
        <xref ref-type="bibr" rid="ref9">9</xref>
        ]:
      </p>
      <p>HT </p>
      <p>log  R / ST 
log   N / 2</p>
      <p>  0, 0011 ln N  1, 0136</p>
      <p>So Hurst index above 0.5 confirms the presence of long-term memory of the
market: current depends on the past and the future depends on the present.</p>
      <p>
        The economic literature is usually gives recommendation to calculate the
accumulated variation on closing prices. However, for practical market trade minimum and
maximum prices set in the middle of interval are also important. To calculate the
Hurst index on the maximum-minimum prices we use the formula [
        <xref ref-type="bibr" rid="ref9">9</xref>
        ]:
HM 
      </p>
      <p>log  R / ST 
log   (N 1) / 2</p>
      <p>  0, 0011 ln(N 1) 1, 0136</p>
      <p>Testing hypotheses about market on the basis of Hurst index can be done in case of
data mixing. If the result of calculations on randomly mixed data is Hurst index close
to 0.5, and it is different from the actual calculations, it may indicate that some data is
not Brownian motion.
4</p>
    </sec>
    <sec id="sec-4">
      <title>Results</title>
      <p>The studies calculated the Hurst index by adjusted formulas for 17 major currency
pairs on annual data within 2008 - 2014. Figure 1 presents the dynamics of Hurst
index change, which is calculated on closing prices for different currency pairs.</p>
      <p>Note that the values of the Hurst index are higher than 0.68, i.e. series are
persistent. Herewith there is the tendency to change the depth of long-term memory for
different periods. Most pairs characterized by increase in the degree of persistence an
average over the period 2008-2014, which means the stabilization of the economic
situation in the world, overcoming of the global economic crisis.</p>
      <p>However, for some currency pairs, especially USD/JPY, USD/CAD, GBP/JPY,
Hurst index dynamics is characterized by significant fluctuations throughout the study
period.</p>
      <p>
        Currency pairs EUR/USD, GBP/USD, USD/CHF, USD/JPY are highly liquid
financial instruments that are characterized by significant volatility and therefore have
great potential for profit. The most popular is EUR/USD. The EUR is highly
dependent on interest rates, economic conditions in the euro area, policies of central banks of
the US and EU, political stability in the world [
        <xref ref-type="bibr" rid="ref19">19</xref>
        ].
      </p>
      <p>Currency pair GBP/USD is one of the most moving and aggressive currency pairs.
The dynamics of the currency pair largely follows the trend of the currency pair
EUR/USD.</p>
      <p>
        The feature of the currency pair USD/CHF is more dependence of its change of
information on the economic situation in the United States than in Switzerland. The
growth trend of US dollar against the Swiss franc, the tendency of weakening of other
currencies against the US dollar is observed. This is especially true for currency pairs
USD/CAD, AUD/USD [
        <xref ref-type="bibr" rid="ref18">18</xref>
        ].
      </p>
      <p>Japanese yen - one of the world reserve currency, a tool for international
settlements of countries with the lowest short-term interest rates. There is a significant
correlation between currency pairs USD/JPY, EUR/JPY and CHF/JPY. Since the bulk
of Japan's funds invested in European assets, changing the course of the currency pair
EUR/JPY to a large extent depends on the level of interest rates of Eurozone and
Japan.</p>
      <p>Figure 2 presents the dynamics of Hurst index change, which is calculated by the
maximum-minimum prices for various currency pairs.
Comparison of the results (Fig. 1, 2) suggests a similarity diagrams and increasing
values of Hurst index, designed for maximum-minimum prices compared with the
Hurst index for closing prices. Calculation of average values of years gives identical
pattern shift 0.1.</p>
      <p>For further study consider a pair of the most pronounced drop Hurst index:
USD/JPY and GBP/JPY. Using the method of sliding windows simulate of dynamic
change of Hurst index for these pairs in the time period 2010-2015 (Fig. 3). On the
horizontal axis the right end of the time window is marked. There is a consistency of
behavior expected of these pairs, due to the presence of the yen and the
interconnectedness of economies of the US and Britain as the developed countries, members of
the Group of Seven.
The graphs in Fig. 3 are typical manifestations of cyclical and periodic drop of
Hurst index in relatively insignificant period of time. Consider in more detail the
dynamics of Hurst index for pair USD/JPY, because it is one of the most influential in
the foreign exchange market.</p>
      <p>
        The first decline of Hurst index and thus persistence weakening can be seen in the
summer of 2010. It is a consequence of the global currency crisis 2008. The event
which caused the decrease in the degree of predictability of the market currencies,
was active company fight for the preservation of the national economies. It was in
2010, the government of Japan has allocated 1 trillion yen for forming a reserve to
combat the crisis and restore regions, and in summer 2010 "new growth strategy" was
adopted and a significant reform of the economy of rising sun was conducted. Large
inflows of funds, coupled with the instability of the economic situation led to a drop
in Hurst index, reducing the persistence [
        <xref ref-type="bibr" rid="ref20">20</xref>
        ].
      </p>
      <p>Thus, the events were a shock for the foreign exchange market and caused a drop
in Hurst index. During these time periods it was difficult to predict further
developments for the currency pair USD/JPY, as its behavior has not been dictated by the
internal events in the market, but external, such as monetary policy in Japan and the
US.</p>
      <p>Figure 4 presents the dynamics of Hurst index change for relatively stable and very
influential pairs in the foreign exchange: EUR/USD and GBP/USD.</p>
      <p>For the currency pair EUR/USD we could see only one, but significant "failure" of
Hurst index, which happened in the fall of 2013. The cause of this could be the
announcement by governments of the US and EU about the start of negotiations for the
establishment of so-called Transatlantic trade and investment partnership (TTIP).
However, the very mention of this agreement has caused some instability in the
economy, many meetings and public criticism from the media.
5</p>
    </sec>
    <sec id="sec-5">
      <title>Conclusions</title>
      <p>Hurst index as a tool of fractal analysis allows to determine the degree of persistency
of financial series, the presence of the long-term memory at foreign exchange market.
In stable economic situation the Hurst index for currency pairs tends to maintain their
average. However, this index is very responsive to events that directly or indirectly
affect the state's economy and the rate of its national currency. The biggest jump of
index can be seen when the country holds planned intervention to improve their
economic situation, thus reducing its currency.</p>
      <p>Another group of events affecting the persistence of the currency market are
important for the country's situations, such as changing the government, announcement
of a new policy or natural disasters. All this violates the usual course of events in the
currency markets, and changing of the Hurst index of exchange quotations is the
indicator of this. The foreign exchange market disturbance passes over the index
approaches to its average value inherent in each currency pair.</p>
    </sec>
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