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<article xmlns:xlink="http://www.w3.org/1999/xlink">
  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Improving the Tools Used in Computer Modelling of the Bond Liquidity Assessment on the Russian Market</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Yulia V. Semernina</string-name>
          <email>ysemernina@yandex.ru</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Alla V. Yakunina</string-name>
          <email>alla.yackunina@yandex.ru</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Ekaterina A. Nesterenko</string-name>
          <email>nesterenko.67@bk.ru</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Sergey V. Yakunin</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Evgeny A. Korobov</string-name>
          <email>korobovea@yandex.ru</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Saratov Socio-Economic Institute (branch of Plekhanov Russian University of Economics)</institution>
          ,
          <addr-line>Saratov</addr-line>
          ,
          <country country="RU">Russia</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>Assessment of the liquidity level of Russian bonds using the computer modeling is an extremely important task which involves development of appropriate measures of bond liquidity. We found that the liquidity measures (proxies) used by academic researchers and professional portfolio managers have some shortcomings: serious interpretation di culties which reduce practical applicability; absence of hierarchy of the liquidity \dimensions"; too much data necessary to properly assess the level of liquidity. We propose a system of indicators to assess the liquidity in the bond market which consider volume being the highest level of the hierarchy of the of liquidity \dimensions", time being the second highest level of the hierarchy, and price being the lowest level of the hierarchy. We suggest calculating the indicators only as averages for the period as indicators at a moment are objectively less informative due to a rather low level of liquidity of the Russian bond market.</p>
      </abstract>
      <kwd-group>
        <kwd>Liquidity measure</kwd>
        <kwd>Corporate bonds</kwd>
        <kwd>Bond market</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>Currently, there is a high demand for computer modelling of nancial assets
management, especially bonds management. As a less risky nancial
instruments than stocks, bonds are widely used by the Pension Fund of the Russian
Federation (PFR) and private pension funds, which are legally responsible for
reliability, pro tability and safety of accumulated pension savings.
Implementation of these legal requirements is achieved through comprehensive control over
the investment processes of the pension savings which involve modeling in order
to determine the expected return, risk, and other important investment
characteristics. Quite often bonds form a signi cant proportion of the investment
portfolio of other groups of investors.</p>
      <p>The appropriate software should be used to ensure the control and to improve
the e ciency of investment decisions. Thus, in the years 2002{2003 PFR has
implemented a program named \Stock Portfolio Optimization System", which
helps to optimize the model stock portfolio based on historical and forecast data
of the relevant stock indices [18].</p>
      <p>For investors, one of the most important investment characteristic of a bonds
issue is its liquidity. Assessment of the liquidity level of Russian bonds using the
computer modeling is an extremely important and urgent task. On the one hand,
investors operating on the domestic bond market recognize the growing risk of
raising the average global interest rates; hence, they tighten requirements for
the liquidity level of the bond issues that they include in the bond portfolios.
On the other hand, given the actual \closing" of the external bond markets,
the Russian bond issuers are interested in increasing the borrowing volumes at
the domestic bond market and, accordingly, are willing to \adjust" to meet the
investors' preferences.</p>
      <p>However, there is no generally accepted criteria of the bond market liquidity
in the existing economic and nancial literature. Even the basic term \market
liquidity" is, in fact, interpreted by scientists ambiguous. As a result, there is a
diversity of liquidity measures (or proxies) suggested by researchers and used by
professional investors, but all of the measures have serious shortcomings.</p>
      <p>In this article, we de ne the bond's (bond issue's) liquidity as being an ability
to transact a bond issue of a certain volume, during a certain time period, and
at a certain price. We develop a system of indicators that helps to solve the
problem of assessing the liquidity in the bond market.
2</p>
    </sec>
    <sec id="sec-2">
      <title>Literature</title>
      <p>Systematizing the existing research, we can distinguish at least two major
approaches to understanding the economic essence of the liquidity: i)
one-dimensional approach, which treats asset liquidity only as the ability to \be converted
in the money" (the very ability to sell the asset on the market is crucial), and
ii) multidimensional approach based on the recognition of the complex nature
of liquidity. Within the latter approach, the time required to sell the asset and
the price at which it (potentially at least) can be sold are taken into account in
addition to the actual ability \to be sold".</p>
      <p>In this article we use the multidimensional approach that to the greatest
extent takes into account the investment preferences of the bond market
participants. Hence, following the general de nition of the nancial asset liquidity,
proposed by V. Rodina [17], we consider the bond's (bond issue's) liquidity as
an ability to transact a bond issue of \a certain amount, during a certain time
period, and at a certain price."</p>
      <p>A detailed review of liquidity (or illiquidity) measures used in the literature is
presented in van Loon et al. [16]. The authors divide all measures, or proxies, of
illiquidity for corporate bonds into three classes. A rst class combine measures
of illiquidity related to transaction costs including the simple bid-ask spread [4,
10,11]. A second class of illiquidity measures describes market depth by assessing
the price impact of trades [15], and trying to capture the daily price response
associated with a one currency unit of trading volume [3, 5, 6, 9, 12]. A third class
of liquidity proxies is referred to as trading intensity variables, which frequently
cover both measures based on turnover and zero-trading-days [8]. In addition to
using individual liquidity proxies, various aggregate proxies have been used [13].</p>
      <p>In the Russian research literature, studies of the bond market liquidity
measurement are rather new (started from late 1990s) and in fact represented by very
few specialized research and also by developments of the professional securities
market participants. It is noteworthy that many of those Russian researchers
who recognize the multiplicity of liquidity measurement use sets of only few
of all possible bond market liquidity measurements and ignore the other. The
most systematic studies in this area are the works of A. N. Chaykun [7] and
P. F. Kolesov [14], which will be later discussed in details.
3</p>
    </sec>
    <sec id="sec-3">
      <title>Liquidity Measures for Bond Issue</title>
      <p>A.N. Chaykun examines the bond market liquidity in the context of its
\projections" (in fact, the term \projection" is synonymous with the term \dimension"),
each of which has its own set of indicators:
1. the \time" projection:
{ \number of transactions" during a certain time period M ;
{ \trading frequency" TF , which is determined by the following formula:
where NT D { number of trading1 days with the bond issue since it was
issued; NSD { total number of days since the bond issue was issued;
2. the \price" projection:
{ \Illiquidity ratio"2 (Amihud's ratio) KA de ned by the formula:
TF =</p>
      <p>NT D</p>
      <p>N SD
KA = j P j</p>
      <p>V
= p</p>
      <p>
        D
R
(
        <xref ref-type="bibr" rid="ref1">1</xref>
        )
(
        <xref ref-type="bibr" rid="ref2">2</xref>
        )
(
        <xref ref-type="bibr" rid="ref3">3</xref>
        )
where j P j { the bond issue's price change (range of price variation) for
a certain period of time; V { bond issue's trading volume for the same
period of time;
{ \price volatility" for a period (usually a year), calculated as:
where D { standard deviation of the yield of the bond issue; R { time
period, expressed in years;
1 Here, a trading day refers to a day when at least one transaction was made with the
bond issue.
2 In some studies, this ratio is called the liquidity coe cient, with the methodology
of its calculation remains unchanged.
      </p>
      <sec id="sec-3-1">
        <title>3. the \volume" projection:</title>
        <p>{ \turnover" (or trading volume) V ;
{ \size of transaction" V M , de ned as:
{ \turnover ratio" KT , which is calculated by the formula:</p>
        <p>V M =
KT =</p>
        <p>V
M</p>
        <p>
          V
CBI
(
          <xref ref-type="bibr" rid="ref4">4</xref>
          )
(
          <xref ref-type="bibr" rid="ref5">5</xref>
          )
(
          <xref ref-type="bibr" rid="ref6">6</xref>
          )
(
          <xref ref-type="bibr" rid="ref7">7</xref>
          )
(
          <xref ref-type="bibr" rid="ref8">8</xref>
          )
        </p>
        <p>CBI { the nominal volume of the bond issue;
4. the \transaction cost" projection:
{ bid-ask spread S, which is calculated as:</p>
        <p>S = PS min</p>
        <p>PD max;
where PS min { the best price asked for the bond issue; PD max { the best
price bid for the bond issue.</p>
        <p>The majority of other researchers, recognizing \multidimensionality" of the
bond market liquidity in general, try to measure it using a \narrow" set of
indicators. In particular, P.F. Kolesov [15] considers it possible to measure the
bond market liquidity in a somewhat di erent way, proposing to use the "two
basic indicators of securities liquidity:
1. time during which the security can potentially be sold;
2. potential nancial losses when it is sold.</p>
        <p>Without o ering a clear algorithm for calculating the rst indicator (time of
the bond sale { ES ), he considers it possible to calculate the potential nancial
losses through the relative spread SR (or the relative bid-ask spread) by using
the following formula:</p>
        <p>SR =</p>
        <p>PS min</p>
        <p>PD max
PS min</p>
        <p>100%:
S =</p>
        <p>Pn
i=1 (PS min
n</p>
        <p>PD max) ;
In addition, the researcher suggests to use such an indicator as the average spread
S for the period:
where n { the number of observations.</p>
        <p>Some of the securities market professional participants followed a di erent
way. Accepting the presence of several liquidity \dimensions", they prefer to
develop their own 'universal' liquidity indicators, trying to \unite" several existing
measurements. Thus, the experts of the nancial group \DOHOD" o er to use
so called \bond liquidity index" (LI), which is an \index for assessing the
liquidity of a particular bond in relation to the liquidity of the market (quotation
list) on which it is traded on the basis of estimates of the average trading volume
and the number of transactions", de ned by the formula [2]:</p>
        <p>LI =</p>
        <p>Vi
V
a</p>
        <p>M Ti b
M T
;
where Vi { \i-th bond average daily trading volume during the previous ve
trading days"; V { \average daily trading volume for all bonds of the same
quotation list to which i-th bond belongs during the previous ve trading days";
M Ti { \average number of i-th bond transactions during the previous ve
trading days"; M T { \average daily number of trades with all bonds of the same
quotation list to which i-th bond belongs during the previous ve trading days";
a { special factor equal to 0.3; b { special factor equal to 0.7.</p>
        <p>
          JSC \Gazprombank" uses its own indicator for assessing the national bond
market liquidity [1]. The specialists of the bank point out: \In general, liquidity
is assessed only on a qualitative level based on expert estimates of the market
participants. Subjectivity of the assessments, increase in the number of traded
assets, the high volatility of nancial markets { all this leads to poor quality
of liquidity risk assessment, which is not conducive to e ective investment
decisions". They o er to use the indicator of nancial instrument's market liquidity:
L = pL1 L2;
(
          <xref ref-type="bibr" rid="ref9">9</xref>
          )
(10)
where L1 { \potential liquidity of the instrument", averaged over the last 20
trading days; L2 { \actual liquidity of the instrument", averaged over the last
20 trading days.
        </p>
        <p>In our view, all of the above elaborations in assessing the liquidity of the
bond market have some shortcomings:
{ they all have serious interpretation di culties and, accordingly, are di cult
to be applied in practice. In other words, using the above indicators, the
investor can identify the bond issue which has the highest liquidity among
those for which the calculations are made, but the investor doesn't actually
get an answer for a very important question: is the particular bond issue's
liquidity level satisfactory for the investor?
{ they are characterized by the absence of hierarchy of the liquidity
\dimensions": in fact, explicitly or implicitly their equivalence is assumed, which
is highly debatable statement due to the possibility of di erences among
investors' preferences;
{ all of the proposed indicators imply that investors have a large enough
amount of information (primarily the absolute spread value for bond issues
over an extended time period) necessary to properly assess the level of
liquidity, which is not always the case, as the vast majority of private investors
do not create nor systematically update specialized information databases
on the bond market liquidity level.</p>
        <p>Given the shortcomings of the listed above indicators, to solve the problem
of assessing the liquidity in the bond market, we propose to construct a system
of indicators based on the following hierarchy of the of liquidity \dimensions":
volume (the highest level of the hierarchy) { time { price (the lowest level of
the hierarchy). And we consider reasonable to calculate these indicators only as
averages for the period (indicators at a moment are objectively less informative
due to a su ciently low level of liquidity of the national bond market).</p>
        <p>Thus, we propose to use the following indicators to assess the potential scope
of a transaction with the bond issue:</p>
      </sec>
      <sec id="sec-3-2">
        <title>1. average total value of bonds o ered for sale:</title>
        <p>T V PS =</p>
        <p>Pn PSi
i=1 100</p>
        <p>FSi COB
;
where PSi { ith o er price, expressed as a percentage; FSi { number of bonds
in ith o er; COB { nominal value of one bond; n { number of observations
(trading days).
2. average total value of bonds bided:</p>
        <p>T V PD =</p>
        <p>Pn PDi
i=1 100</p>
        <p>FDi COB</p>
        <p>;
n
n
(11)
(12)
(13)
(14)
(15)
where PDi { price of ith bid, expressed as a percentage; FDi { number of
bonds in the ith bid;
3. average total value of bonds available for a transaction:</p>
        <p>T V = T V PS + T V PD :
2</p>
        <p>In this case, a key indicator for the assessment of the amount of bond liquidity
is the average market value of bonds available simultaneously to transact, while
other indicators are considered as auxiliary, allowing to analyze the liquidity of
the bond issue in more detail.</p>
        <p>To evaluate the potential time to transact bonds, we propose to use the
percentage of trading days characterized by a satisfactory level of liquidity:
WSL =
nSL
n
100%;
where nSL { number of trading days characterized by a satisfactory level of
liquidity.3</p>
        <p>To assess such a measurement of bond liquidity as a price, we suggest to
calculate the average spread corresponding to the required volume of the
transaction:</p>
        <p>SRV =</p>
        <p>Pn
i=1 (PSRV
n</p>
        <p>PDRV ) ;
3 The level of liquidity is satisfactory when actual average total value of bonds available
for a transaction exceeds the required by the investor.
(16)
(17)
where PSRV { average ask price of bonds corresponding to the required
transaction volume, which is determined by the formula:
PDRV { average bid price of bonds corresponding to the required transaction
volume, which is determined by the formula:</p>
        <p>PSRV =</p>
        <p>PiR=V1 PSi FSi COB</p>
        <p>PiR=V1 FSi COB</p>
        <p>;
PDRV =</p>
        <p>PiR=V1 PDi FDi COB</p>
        <p>PiR=V1 FDi COB
:</p>
        <p>If the value of bonds o ered for purchase or sale does not reach the required
volume, the indicator's value can not be identi ed correctly, and the bonds issue
is not considered as the one that meets the investor's liquidity requirements (for
the price \dimension").</p>
        <p>The speci cs of this indicator is a greater representativeness that allows more
than just a comparison of the bonds' best bids and asks (such a comparison does
not take into account the actual ask and bid volumes) through comparing the
average prices that would realize if the required bond volume were transacted.
4</p>
      </sec>
    </sec>
    <sec id="sec-4">
      <title>Empirical example</title>
      <p>We have applied the suggested set of indicators to the bond market by using a
hypothetical example. Suppose that a private investor operating on the Russian
bond market needs to purchase short-term bonds (with maturity date is up to
August 31, 2016, inclusively). His required liquidity volume (T V ) is not less than
1,000,000 rubles; the percentage of trading days characterized by a satisfactory
liquidity level (WSL) is not less than 40%, with a maximum term of a position
opening equals to ve trading days; average spread for the required transaction
volume (SRV ) is no more than 0.50%, and the required transaction volume is
equal to 200,000 rubles.</p>
      <p>At the calculation time (July 25, 2016) the investor's maturity requirements
were met by 8 bond issues, but for the two of them { AbsolyutB-5 with the
maturity date of July 27, 2016, and GPB BO-05 with the maturity date of
August 1, 2016 { the trading was stopped (\frozen") because the maturity date
was close. Calculations of the proposed indicators for the remaining 6 bond issues
are given in Table 1.</p>
      <p>
        Results of the bonds' liquidity evaluation clearly show that all investor's
requirements are satis ed by only one bond issue (Alpha BO-9) within the analyzed
bond issues totality formed by the term to maturity.
4 Source: The Moscow Exchange, http://moex.com/ru/marketdata/bulletins/
The system of indicators and bond liquidity analysis algorithm proposed in the
paper can be embedded in a computer decision support system designed for
selection and ranking bonds by the liquidity criteria. The computer support will
signi cantly increase the e ciency of decision-making when investing in bonds,
making it easier for investors to assess a large number of simultaneously traded
securities. In the proposed algorithm, using system of liquidity indicators instead
of one criteria will boost the e ciency of investment decisions and, on the other
hand, requires computer support for technical simpli cation and improvement
of assessment reliability.
10. Edwards, A.K., Harris, L.E., Piwowar, M.S.: Corporate bond market transaction
costs and transparency. The Journal of Finance 62, 1421{1451 (2007)
11. Friewald, N., Jankowitsch, R., Subrahmanyam, M.G.: Illiquidity or credit
deterioration: A study of liquidity in the US corporate bond market during nancial
crises. Journal of Financial Economics 105(
        <xref ref-type="bibr" rid="ref1">1</xref>
        ), 18{36 (2012)
12. de Jong, F., Driessen, J.: Liquidity risk premia in corporate bond markets.
Quarterly Journal of Finance 02(02), 1250006 (2012)
13. Kerry, W.: Measuring nancial market liquidity. Journal of Risk Management in
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        Financial Institutions 1(
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        ), 181{190 (2008)
14. Kolesov, P.F.: Methods of assessing the liquidity of securities used by commercial
banks of russia. Scienti c journal NRU ITMO 1(10), 23 (2012)
15. Kyle, A.S.: Continuous auctions and insider trading. Econometrica 53(
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1335 (1985)
16. van Loon, P., Cairns, A., A., M., Veys, A.: Modelling the liquidity premium of
corporate bonds. Annals of Actuarial Science 9, 264{289 (2015)
17. Masyutin, A.A., Rodina, V.A.: Medium-term investments on the russian stock
market in terms of securities liquidity parameters. Risk management in credit
organizations 2(10), 48{64 (2013)
18. Nedosekin, A.J.: Methodological bases of modeling of nancial activity using
fuzzy-multiple descriptions. Thesis for the degree of doctor of economic sciences,
University of Economics and Finance, Saint-Petersburg, Russia (2003), URL:
http://www.mirkin.ru/_docs/doctor005.pdf
      </p>
    </sec>
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          <string-name>
            <surname>Lando</surname>
            ,
            <given-names>D.</given-names>
          </string-name>
          :
          <article-title>Corporate bond liquidity before and after the onset of the subprime crisis</article-title>
          .
          <source>Journal of Financial Economics</source>
          <volume>103</volume>
          (
          <issue>3</issue>
          ),
          <volume>471</volume>
          {
          <fpage>492</fpage>
          (
          <year>2012</year>
          )
        </mixed-citation>
      </ref>
    </ref-list>
  </back>
</article>