=Paper=
{{Paper
|id=Vol-1726/paper-10
|storemode=property
|title=Improving the Tools Used in Computer Modelling of the Bond Liquidity Assessment on
the Russian Market
|pdfUrl=https://ceur-ws.org/Vol-1726/paper-10.pdf
|volume=Vol-1726
|authors=Yulia V. Semernina,Alla V. Yakunina,Ekaterina A. Nesterenko,Sergey V. Yakunin,Evgeny A. Korobov
}}
==Improving the Tools Used in Computer Modelling of the Bond Liquidity Assessment on
the Russian Market==
https://ceur-ws.org/Vol-1726/paper-10.pdf
Improving the Tools Used in Computer
Modelling of the Bond Liquidity Assessment
on the Russian Market
Yulia V. Semernina, Alla V. Yakunina, Ekaterina A. Nesterenko,
Sergey V. Yakunin, and Evgeny A. Korobov
Saratov Socio-Economic Institute (branch of Plekhanov Russian University
of Economics), Saratov, Russia
ysemernina@yandex.ru, alla.yackunina@yandex.ru
nesterenko.67@bk.ru, ysw@yandex.ru, korobovea@yandex.ru
Abstract. Assessment of the liquidity level of Russian bonds using the
computer modeling is an extremely important task which involves devel-
opment of appropriate measures of bond liquidity. We found that the liq-
uidity measures (proxies) used by academic researchers and professional
portfolio managers have some shortcomings: serious interpretation diffi-
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.
Keywords: Liquidity measure, Corporate bonds, Bond market
1 Introduction
Currently, there is a high demand for computer modelling of financial assets
management, especially bonds management. As a less risky financial instru-
ments 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, profitability and safety of accumulated pension savings. Implementa-
tion 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 char-
acteristics. Quite often bonds form a significant proportion of the investment
portfolio of other groups of investors.
The appropriate software should be used to ensure the control and to improve
the efficiency 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].
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.
However, there is no generally accepted criteria of the bond market liquidity
in the existing economic and financial 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.
In this article, we define 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 Literature
Systematizing the existing research, we can distinguish at least two major ap-
proaches to understanding the economic essence of the liquidity: i) one-dimen-
sional 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”.
In this article we use the multidimensional approach that to the greatest
extent takes into account the investment preferences of the bond market par-
ticipants. Hence, following the general definition of the financial 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.”
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 first 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].
In the Russian research literature, studies of the bond market liquidity mea-
surement 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 Liquidity Measures for Bond Issue
A.N. Chaykun examines the bond market liquidity in the context of its “projec-
tions” (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:
NT D
TF = (1)
N SD
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 defined by the formula:
|∆P |
KA = (2)
V
where |∆P | – 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 δ (usually a year), calculated as:
δD
δ=√ (3)
R
where δD – 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 coefficient, with the methodology
of its calculation remains unchanged.
3. the “volume” projection:
– “turnover” (or trading volume) V ;
– “size of transaction” V M , defined as:
V
VM = (4)
M
– “turnover ratio” KT , which is calculated by the formula:
V
KT = (5)
CBI
CBI – the nominal volume of the bond issue;
4. the “transaction cost” projection:
– bid-ask spread S, which is calculated as:
S = PS min − PD max , (6)
where PS min – the best price asked for the bond issue; PD max – the best
price bid for the bond issue.
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 different way, proposing to use the ”two
basic indicators of securities liquidity:
1. time during which the security can potentially be sold;
2. potential financial losses when it is sold.
Without offering a clear algorithm for calculating the first indicator (time of
the bond sale – ES ), he considers it possible to calculate the potential financial
losses through the relative spread SR (or the relative bid-ask spread) by using
the following formula:
PS min − PD max
SR = · 100%. (7)
PS min
In addition, the researcher suggests to use such an indicator as the average spread
S̄ for the period: Pn
(PS min − PD max )
S̄ = i=1 , (8)
n
where n – the number of observations.
Some of the securities market professional participants followed a different
way. Accepting the presence of several liquidity “dimensions”, they prefer to de-
velop their own ’universal’ liquidity indicators, trying to “unite” several existing
measurements. Thus, the experts of the financial group “DOHOD” offer to use
so called “bond liquidity index” (LI), which is an “index for assessing the liq-
uidity 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”, defined by the formula [2]:
a b
Vi M Ti
LI = · , (9)
V MT
where Vi – “i-th bond average daily trading volume during the previous five
trading days”; V – “average daily trading volume for all bonds of the same quo-
tation list to which i-th bond belongs during the previous five trading days”;
M Ti – “average number of i-th bond transactions during the previous five trad-
ing 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 five trading days”;
a – special factor equal to 0.3; b – special factor equal to 0.7.
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 financial markets – all this leads to poor quality
of liquidity risk assessment, which is not conducive to effective investment deci-
sions”. They offer to use the indicator of financial instrument’s market liquidity:
p
L = L1 · L2 , (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.
In our view, all of the above elaborations in assessing the liquidity of the
bond market have some shortcomings:
– they all have serious interpretation difficulties and, accordingly, are difficult
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 “dimen-
sions”: in fact, explicitly or implicitly their equivalence is assumed, which
is highly debatable statement due to the possibility of differences 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 liq-
uidity, 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.
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 sufficiently low level of liquidity of the national bond market).
Thus, we propose to use the following indicators to assess the potential scope
of a transaction with the bond issue:
1. average total value of bonds offered for sale:
Pn PSi
i=1 100 · FSi · COB
T V PS = , (11)
n
where PSi – ith offer price, expressed as a percentage; FSi – number of bonds
in ith offer; COB – nominal value of one bond; n – number of observations
(trading days).
2. average total value of bonds bided:
Pn PDi
i=1 100 · FDi · COB
T V PD = , (12)
n
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:
T V PS + T V PD
TV = . (13)
2
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.
To evaluate the potential time to transact bonds, we propose to use the
percentage of trading days characterized by a satisfactory level of liquidity:
nSL
WSL = · 100%, (14)
n
where nSL – number of trading days characterized by a satisfactory level of
liquidity. 3
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 trans-
action: Pn
(P̄SRV − P̄DRV )
S̄RV = i=1 , (15)
n
3
The level of liquidity is satisfactory when actual average total value of bonds available
for a transaction exceeds the required by the investor.
where P̄SRV – average ask price of bonds corresponding to the required transac-
tion volume, which is determined by the formula:
PRV
i=1 PSi · FSi · COB
P̄SRV = PRV , (16)
i=1 FSi · COB
P̄DRV – average bid price of bonds corresponding to the required transaction
volume, which is determined by the formula:
PRV
i=1 PDi · FDi · COB
P̄DRV = PRV . (17)
i=1 FDi · COB
If the value of bonds offered for purchase or sale does not reach the required
volume, the indicator’s value can not be identified correctly, and the bonds issue
is not considered as the one that meets the investor’s liquidity requirements (for
the price “dimension”).
The specifics 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 Empirical example
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 five trading days; average spread for the required transaction
volume (S̄RV ) is no more than 0.50%, and the required transaction volume is
equal to 200,000 rubles.
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.
Results of the bonds’ liquidity evaluation clearly show that all investor’s re-
quirements are satisfied 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/
Table 1. Calculations of the liquidity indicators for bond issues being traded at the
Moscow Stock Exchange, with a maturity up to August 31, 2016, inclusive4
Bond Issue Maturity Date T V , rubles WSL , % S̄RV , %
AkBars-BO3 August 18. 2016 2 632 364,98 80 Undefined
MSPBankBO1 August 19.2016 0 – –
MSPBankBO2 August 19.2016 0 – –
Alpha BO-9 August 20.2016 6 948 127,42 100 0,4500
MedvedF2 August 22.2016 1 065,89 – –
MegtopEnB1 August 31.2016 1 071 312,70 80 0,8777
5 Conclusion
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
significantly increase the efficiency 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 efficiency of investment decisions and, on the other
hand, requires computer support for technical simplification and improvement
of assessment reliability.
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