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The Russian banking system is in its worst crisis since 1998, a fact made particularly evident by the collapse in share prices for every financial service company, together with the fall of Russian stock markets. However, differently from 1998, the banking system finds itself in a better position thanks to the previous macroeconomics boom, which lasted almost ten years. The highly fragmented structure of the banking sector still relies heavily on state banks, but the contribution by foreign banks as well as local private banks has increased steadily in the last years. We discuss the major improvements and weaknesses that currently characterize the Russian banking system, together with systemic risk, which still plays the major role in such a market.
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Dangers and Opportunities for the Russian Banking Sector:
2007 - 2008
Dean Fantazzini Alexander Kudrov Andrew Zlotnik
Moscow - December, the 11th 2009
(Due to copyright restrictions, I can not upload the full paper on SSRN, but only the
slides of the presentation at the first Russian Economic Congress, December the 11th
2009, Moscow - Russia.)
Overview of the Presentation
• Introduction
2007-2009: Dangers and Opportunities for the Russian Banking Sector 2
Overview of the Presentation
• Introduction
• Current Situation in Russian Banking Sector
2007-2009: Dangers and Opportunities for the Russian Banking Sector 2-a
Overview of the Presentation
• Introduction
• Current Situation in Russian Banking Sector
• Econometric Analyses of the Banking Stocks: the
Zero-Price-Probability (ZPP)
2007-2009: Dangers and Opportunities for the Russian Banking Sector 2-b
Overview of the Presentation
• Introduction
• Current Situation in Russian Banking Sector
• Econometric Analyses of the Banking Stocks: the
Zero-Price-Probability (ZPP)
• Econometric Analyses of the Banking Stocks: An Extreme Value
Theory Approach to Value at Risk Estimation
2007-2009: Dangers and Opportunities for the Russian Banking Sector 2-c
Overview of the Presentation
• Introduction
• Current Situation in Russian Banking Sector
• Econometric Analyses of the Banking Stocks: the
Zero-Price-Probability (ZPP)
• Econometric Analyses of the Banking Stocks: An Extreme Value
Theory Approach to Value at Risk Estimation
• Econometric Analyses of the Banking Sectors
2007-2009: Dangers and Opportunities for the Russian Banking Sector 2-d
Overview of the Presentation
• Introduction
• Current Situation in Russian Banking Sector
• Econometric Analyses of the Banking Stocks: the
Zero-Price-Probability (ZPP)
• Econometric Analyses of the Banking Stocks: An Extreme Value
Theory Approach to Value at Risk Estimation
• Econometric Analyses of the Banking Sectors
• What is Next?
2007-2009: Dangers and Opportunities for the Russian Banking Sector 2-e
Introduction
The Russian banking system is in its worst crisis since 1998: on the one
hand, this is a consequence of global financial and economic crisis; on the
other hand there are specific country factors.
• First of all, Russian economy depends on a relative small number of
industries.
• Secondly, Russian firms have a large amount of foreign debt.
• Furthermore, when oil prices decrease, this then leads to a decline in
the ruble against the dollar and the euro.
• Another problem is represented by the large amount of risky
investments.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 3
Introduction
In the last 10 years, risk managers in Russia (and worldwide, too) were not
really independent and unprejudiced:
⇒ since risk managers know what top management wants (usually, they
want money), this has determined a large increase in risky investments
which has generated high profits, but also high risk.
⇒ The main institutional problem is that risk management measures risk
but does not manage it.
In this regard, this clearly implies that Basel II conception should be
revised and (real!) stress testing should lead to real protection.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 4
Current Situation in Russian Banking Sector
The current total number of banks in Russia hasn’t changed significantly
from the past years before the crisis.
⇒ According to a report by the Central Bank of Russia (CBR), during the
year 2008 the amount of banks decreased by 3.1%, from 1092 banks to
1058 banks in Russia.
These banks were acquired by State banks or by top private banks with
government protection, and their market share was less than 5%.
⇒ The main reasons of these deals were the impossibility of refinancing
(due to the seizure in global credit markets since July), non-optimal
structure of assets and liabilities, as well as low quality risk management.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 5
Current Situation in Russian Banking Sector
The Russian authorities have tried to deal with this threat to protect
population, banks and large firms:
⇒ The Deposit Insurance Agency now guarantees the deposits up to
20 000 dollars in each bank, while the local Parliament passed a law
extending the time for the VAT (value added tax) paymentsa.
⇒ Besides, Vnesheconombank (VEB) received $50 bln in refinancing
facilities (5 years at LIBOR + 5).
⇒ The CBR has also taken some measures for increasing liquidity: it has
increased the limit of free budget funds on deposits of Commercial Banks,
enlarged the number of banks for which budget funds are available up to
28, and decreased the rate of legal reserve requirements by 0.5%.aIn this paper, we assume 35 ruble for 1 dollar for current and future events, while
we use 25 to 1 Rub/$ for the period of time before December, 2008.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 6
Current Situation in Russian Banking Sector
Furthermore, the CBR and the Ministry of Finance have provided $38 bln
in subordinated long debt financing (maturity at 2019 at 8%): $20 bln for
Sberbank, $8 bln for VTB, $1 bln for Rosselkhozbank and $ 9 bln for other
top banks.
⇒ It is important to highlight that the first 200 Russian banks have
accumulated the 95% of assets, while the first 50 banks have concentrated
the 80% of assets.
On January 1 2009, the total capital of the registered operating credit
institutions amounted to 25.2 billion dollars, more than 20.4% higher than
the level of that capital on January 1, 2008 (see Figures 1 a-b-c-d below).
2007-2009: Dangers and Opportunities for the Russian Banking Sector 7
Current Situation in Russian Banking Sector
Figure 1a: Currencies (Ruble or foreign) in which the credits are denominated and distribution of
banking credits by sectors. Sources: Central Bank of Russia, Troika Dialog, Renaissance Capital
2007-2009: Dangers and Opportunities for the Russian Banking Sector 8
Current Situation in Russian Banking Sector
Figure 1b: Distribution of banking credits by sectors. Sources: Central Bank of Russia, Troika
Dialog, Renaissance Capital
2007-2009: Dangers and Opportunities for the Russian Banking Sector 9
Current Situation in Russian Banking Sector
Figure 1c: Currencies (Ruble or foreign) in which the credits are denominated and distribution of
banking credits by sectors. Sources: Central Bank of Russia, Troika Dialog, Renaissance Capital
2007-2009: Dangers and Opportunities for the Russian Banking Sector 10
Current Situation in Russian Banking Sector
Figure 1d: Distribution of banking credits by sectors and banks. Sources: Central Bank of Russia,
Troika Dialog, Renaissance Capital
2007-2009: Dangers and Opportunities for the Russian Banking Sector 11
Current Situation in Russian Banking Sector
General trends in Russian Banking sector:
1) The first important trend is the outflow of retail and wholesale deposits
in 2008-4th quarter.
Retail deposits accounted for almost 25% of banks’ finance but, in general,
the situation on the outflow of funds can not be described as extremely
problematic.
The outflow of funds from retail deposits in state-owned banks was about
5-6% in October 2008. With regard to private banks, the outflow was
much more serious, having lost on average 10-12% of retail deposits in
October 2008.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 12
Current Situation in Russian Banking Sector
Interestingly, there is no substantial outflow of funds from corporate
deposits in Sberbank, but rather there is a flow of funds in settlement
funds.
⇒ This is consistent with the expectation that corporations are now
sending their funds to those financial institutions which are more stable.
⇒ Consequently, the probability of a fall of the financial sustainability for
many smaller banks has increased, together with the probability of a fall of
the Ruble as a result of large-scale conversion of deposits denominated in
Rubles into dollars and euros.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 13
Current Situation in Russian Banking Sector
⇒ However, since January 2009, the Ruble has stabilized thanks to these
contemporaneous events:
1. the ending of large currency conversions by small investors: → most
Russian savers has already converted by then a significant part of their
deposits in $ and Euros, while keeping the remaining part in Ruble for
everyday life and business.
2. Interventions by the CBR to block speculations on the Ruble by
Russian banks: by the end of October 2008, the outflow of money by
foreign investors was largely finished, and the pressure on the Ruble
were mainly due to Russian banks betting on further devaluations.
⇒ It was sufficient an “order call” to tell these banks that the
speculation game had to finish.
We remark that the Ruble has started stabilizing two months before the
world markets started rebounding in March 2009.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 14
Current Situation in Russian Banking Sector
2) The second trend is that the wholesale funding (debt market) works only
partially.
The only source of liquidity for the Russian banks is now represented by
the resources of the CBR and the Ministry of Finance.
Banks will not start recovering large-scale lending until the debt market
has stabilized.
In November 2008, the CBR has amended the regulations to support not
only banks with rating assigned by agencies such as S&P, Fitch and
Moody’s, but also banks with ratings assigned by national agencies
recognized by CBR.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 15
Current Situation in Russian Banking Sector
→ The consequences of this situation on banks will depend mainly on their
abilities and dimensions.
→ As a result, for example, top banks are forecasted to remain quite
stable, because they are supported by the state and the CBR.
→ So far, the risk of large-scale bankruptcies in the banking sector remains
low and is fully manageable.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 16
Current Situation in Russian Banking Sector
3) The third new trend is the new lending structure. Most private banks
have reduced lending activity and their lending portfolio have declined by
5-7% on average in October:
Out of $33 bln. received in November 2008 from the CBR, the largest banks have used
only a third of this amount for lending activities, whereas they used the remaining
part to finance their own debts, mainly debts towards to the Ministry of Finance.
Nevertheless, in October 2008, the two largest state-controlled banks (VTB
and Sberbank) significantly increased lending: both by $5 bln.
→ In general, the aggregate effect on the credit system can be described as
a neutral or slightly negative.
→ However, the majority of new loans were taken by large borrowers,
while small businesses are experiencing significant problems in refinancing
their debts.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 17
Current Situation in Russian Banking Sector
4) Another result of the difficult situation for lending is the deteriorating
quality of assets.
According to the aggregate balance sheet for 30 Russian banks issued by the CBR, the
amount of outstanding debt in the major banks loaned to other credit organizations
has increased seven times and reached $0.3 bln., whereas the amount loaned to
non-financial organizations has increased by 25% and amounted to $7 bln.
While such figures are the first signs of a general deterioration in the
quality of credit portfolios, nevertheless its importance for the banking
system is not crucial. For example, the percentage of credit-related crimes
increased only by 15-20%.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 18
Current Situation in Russian Banking Sector
5) The last new trend (now partially over) is represented by the fact that
Russian banks increased their assets in the interbank foreign exchange
market, for example by 15-20 bln dollars in October 2008 alone.
The CBR initially did not take effective action to stop or mitigate the
effects of these speculations:
As we said before, in September 2008 the most aggressive players against
the Ruble were foreign banks, but in October 2008 they were Russian
banks.
→ The CBR has since then imposed sanctions on those banks that use
funds from the state support to buy foreign currencies.
→ This measure has proved extremely effective and, together with the
contemporaneous ending of large currency conversions by Russian savers, it
helped stabilizing the Ruble.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 19
Econometric Analyses of the Banking Stocks:the Zero-Price-Probability (ZPP)
The recent default of the food giant Parmalat in the 2003 and Enron in
2002 clearly showed how the debts reported in the certified balanced sheet
can represent only a part of the true debt figures.
In general, the debt values reported in the certified balance sheets are
underestimated for two reasons:
1) to “window dress” the financial health of the company, in the best case;
2) to hide financial fraud, in the worst case (see, Parmalat, Enron, etc.).
Ketz (2003) discusses a wide variety of techniques to hide debts and
financial risk:
⇛ This explains why the default probabilities computed with
KMV-Merton type models (or other balance sheet based models) are
usually underestimated.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 20
Econometric Analyses of the Banking Stocks:the Zero-Price-Probability (ZPP)
Besides, the standard log-normal assumption is not an appropriate
distribution for price dynamics.
Furthermore, heteroskedasticity is not considered at all in the
KMV-Merton type models: increasing volatility and leptokurtosis can be
interpreted as a signal of informed trading (see Biais et al. (2005) and
Hasbrouck (2007), for recent surveys about market microstructure studies).
⇒ Therefore, using accounting data to infer the firm’s default probability
can be misleading and result in a very poor estimate.
⇒ In order to avoid such problems, we use a recent approach proposed in
Fantazzini, DeGiuli and Maggi (2008), Fantazzini (2009) and Fantazzini,
Kudrov and Slotnik (2010), that uses the null price as a default barrier to
separate an operative firm from a defaulted one, and to estimate its default
probability without resorting to accounting data.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 21
Econometric Analyses of the Banking Stocks:the Zero-Price-Probability (ZPP)
If we consider the following two quantities:
ET = AT − BT
E′
T = AT = (AT − BT ) + BT = ET + BT
we can easily see that the meanings and signs of ET and E′
T can be
completely different according to the situation faced by the firm:
Table 3: Financial Meaning and Signs of ET and E′
T
ET = AT − BT E′
T = AT
OPERATIVE Equity belonging Asset value
to shareholders (+) (+)
DEFAULTED Loss given default Equity belonging to Debtholders
for Debtholders (−) (+)
7→ Therefore, we can estimate the Distant to Default (D.D.) simply by
using ET , instead of Merton’s formula [ln(AT ) − ln(BT ) − T · (µE − σE/2)]/σA,
and the default probability by P(ET < 0).
2007-2009: Dangers and Opportunities for the Russian Banking Sector 22
Econometric Analyses of the Banking Stocks:the Zero-Price-Probability (ZPP)
If we are at time t and we want to compute the (implicit) probability at a
given time t + T that the stock price will cross the truncation level of zero,
i.e. p(Pt+T < 0), then
1. Consider a generic conditional model for the differences of prices levels
Xt = Pt − Pt−1, without the log-transformation :
Xt = E [Xt|Ft−1] + εt (1)
εt = H1/2t ηt, ηt ∼ i.i.d(0, 1) (2)
where H1/2t is the conditional standard deviation, while Ft is the
information set available at time t.
2. Simulate a high number N of price trajectories up to time t + T , using
the estimated time series model:
3. The default probability is simply the number of times n out of N when
the price touched or crossed PT = 0 along the simulated trajectory.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 23
Econometric Analyses of the Banking Stocks:the Zero-Price-Probability (ZPP)
Example: 5000 simulated price trajectories, 1-year ahead, for a
risky stock (ZPP∼40%)
2007-2009: Dangers and Opportunities for the Russian Banking Sector 24
Econometric Analyses of the Banking Stocks:the Zero-Price-Probability (ZPP)
This method entails a number of important benefits:
1. We only need the stock prices for estimating the default probability;
2. We do not need any latent default barrier D, or firm’s volatility σA,
like in Merton style models;
3. We can estimate the default probability for any given time horizon
t + T ;
4. We can consider more realistic distributions than the log-normal;
5. We can screen the default risk daily or even intra-daily. The ZPP can
therefore be used as a tool for risk management.
6. Given the face value of the debt BT , we can compute the average loss
given default for debtholders and therefore the average recovery rate.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 25
Zero-Price-Probability (ZPP): Some Recent Examples
Fantazzini, DeGiuli, Maggi (2008) estimate the 1-year ahead ZPP
considering the last 200 / 1000 trading days for four famous defaulted
stocksa:
1. Cirio: 24/09/1999 - 24/07/2003 (Last 1000 days). Second largest
default in the Italian food sector (the first is Parmalat, see below);
2. Enron: 13/02/2001 - 03/12/2001 (Last 200 days). Largest default in
American history.
3. Parmalat : 22/02/2000 - 22/12/2003 (Last 1000 days). Largest default
in Italian history.
4. Swissair : 12/12/2000 - 03/10/2001 (Last 200 days). Largest default in
European Airline Industry.
aAR(p)-GARCH(1,1)/TGARCH(1,1) models with Student’s T distribution
were used. Data from Datastream.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 26
Zero-Price-Probability (ZPP): Some Recent Examples
Figure 2: KMV-Merton default probability and ZPP:
CIRIO and PARMALAT
2007-2009: Dangers and Opportunities for the Russian Banking Sector 27
Zero-Price-Probability (ZPP): Some Recent Examples
Figure 3: KMV-Merton default probability and ZPP:
ENRON and SWISSAIR
2007-2009: Dangers and Opportunities for the Russian Banking Sector 28
Zero-Price-Probability (ZPP): Some Recent Examples
• The KMV-Merton model shows numerical instability due to abrupt
changes in the debt values at the end of the year;
• The log-normal is not an appropriate distribution for price dynamics
⇒ tail underestimation
• Debt values reported in the certified balance sheets are
underestimated, and so are default probabilities
2007-2009: Dangers and Opportunities for the Russian Banking Sector 29
Econometric Analyses of the Banking Stocks:the Zero-Price-Probability (ZPP)
Fantazzini, Kudrov and Zlotnik (2010) examined the development of credit
risk in the last two years (2007-2008), with particular reference to the
Russian banking sector.
They analyze four single banks (one for Russia, one for USA, one for Italy
and one for UK), that represent important cases due to their dimension
and/or financial history:
• Sberbank (Russia)
• Citigroup (USA)
• Unicredit (Italy)
• Royal Bank of Scotland (UK)
2007-2009: Dangers and Opportunities for the Russian Banking Sector 30
Econometric Analyses of the Banking Stocks:the Zero-Price-Probability (ZPP)
Figure 1: Estimated Default Probability by using the ZPP: Citigroup,
RBS, Sberbank and Unicredit
2007-2009: Dangers and Opportunities for the Russian Banking Sector 31
Econometric Analyses of the Banking Stocks:the Zero-Price-Probability (ZPP)
⇒ Second bailout for RBS in January-February 2009
⇒ Citigroup split in two in January 2009 and a new capital infusion may be
required after the recent “Stress tests”
⇒ As for Unicredit and Sberbank, even though their risks of default have
increased after the financial turmoil in October 2008 , nevertheless these risks
have stabilized since then, differently from the previous American and English
banks
2007-2009: Dangers and Opportunities for the Russian Banking Sector 32
Econometric Analyses of the Banking Stocks: An ExtremeValue Theory Approach to Value at Risk Estimation
As a confirmation of these insights, Fantazzini, Kudrov and Zlotnik (2010)
used a completely different methodology based on Extreme Value Theory.
⇒ Robust estimation algorithm for Value at Risk :
1. For every consecutive 250 days (during the considered period of time)
we compute the set of Hill’s estimators (γ(k)) for the extremal index
of the distribution function of negative returns:
Suppose to have, within the considered period, m negative returns
X1, ..., Xm and let X(1) ≤ X(2) ≤ ... ≤ X(m) be their ordered statistics.
Then the set of Hill’s estimators (γ(k)) is defined as follows:
γ(k) =1
k
k∑
i=1
(ln X(m−i+1) − ln X(m−k)), 1 ≤ k ≤ m − 1
2007-2009: Dangers and Opportunities for the Russian Banking Sector 33
Econometric Analyses of the Banking Stocks: An ExtremeValue Theory Approach to Value at Risk Estimation
Consider the following model for the sequence of Hill’s estimators γ(k):
γ(k) = γ + β1k + εk, k = 1, ..., κ, (3)
where E[γ(k)] = γ + β1k, V ar(εk) = σ2/k and γ is the true value of the
extremal index for the distribution of negative returns.
We can then estimate γ by using the method of weighted least squares with
a weighting κ × κ matrix W , that has (√
1, ...,√
κ) on the main diagonal and
zeroes elsewhere.
2. To estimate the excess level or Value a Risk xp at the probability level p
(0 < p < 1) for the next day, we use the following estimator:
xp =
(
rpn
)γ− 1
1 − 2−γ(X(n−r) − X(n−2r)) + X(n−r) (4)
where n is the number of negative returns, r = [κ/2] ([.]-integer part), γ is
the estimator for the extremal index γ, X(n−r), X(n−2r) are (n − r)- and
(n − 2r)-ordered statistics of the absolute valued positive returns sequence
X1, ..., Xn, respectively.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 34
Econometric Analyses of the Banking Stocks: An ExtremeValue Theory Approach to Value at Risk Estimation
⇛ The estimator of extremal index γ, used in the first step of the
estimation algorithm for VaR was proposed by Huisman et al. (2001),
where it is recommended to take κ = m/2.
⇒ Instead of selecting an optimal threshold for the Hill’s estimator of the
extremal index, this approach allows to compute an optimal unbiased
estimate of γ on the basis of the Hill’s estimators set (with the thresholds
k = 1, ..., κ).
⇛ On the second step we use the consistent estimator of the excess level xp
proposed by Dekkers and De Haan (1989).
2007-2009: Dangers and Opportunities for the Russian Banking Sector 35
Econometric Analyses of the Banking Stocks: An ExtremeValue Theory Approach to Value at Risk Estimation
Figure 2: Estimated Value at Risk at the 1% probability level: Citi-
group, RBS, Sberbank and Unicredit.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 36
Econometric Analyses of the Banking Sectors
The structure in Table 3 can be easily generalized to a general sector :
instead of having the equity for a single firm, we can have the equity
belonging to all shareholders of a specific sector composed of n firms, for
example, the financial sector:
Table 4: The ZPP framework extended to a general business SECTOR∑ n
i=1 ET,i =∑ n
i=1(AT,i − BT,i)∑ n
i=1 E′
T,i =∑ n
i=1 AT,i
OPERATIVE Equity belonging SECTOR Asset value
to the SECTOR shareholders (+) (+)
DEFAULTED Loss given default for Equity belonging to the
the SECTOR Debtholders (−) SECTOR Debtholders (+)
⇒ Therefore, by using a sector index instead of a single stock, the ZPP can
be used as an early warning system for systemic default of a general sector.
Fantazzini, Kudrov and Zlotnik (2010) consider the Russian RTS Financial
Index, the American Dow Jones Financial Index, the English FTSE
Banking Index and the Italian MIBTEL Financial Index.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 37
Econometric Analyses of the Banking Sectors
Figure 3: Estimated Default Probability: American English, Russian
and Italian financial sectors indexes
2007-2009: Dangers and Opportunities for the Russian Banking Sector 38
Econometric Analyses of the Banking Sectors
The Russian financial index clearly shows a higher degree of riskiness than
the other markets, that was quite high already at the beginning of 2007
and peaked in October 2008.
⇒ However, this higher risk is mostly due to a higher country risk (Russia
has a rating of BBB+), than the competing countries (US and UK have
AAA, while Italy A+).
Besides, the increases in the default probabilities for the American and
English banking sectors in 2008 are very large and reflect the difficulties
that they have experienced so far.
⇒ Interestingly, the Italian financial sector currently shows the smallest
default probability (although it was still higher than the American and
English ones till July 2008), thus confirming the smaller impact the
subprime crisis has had on Italian banks
2007-2009: Dangers and Opportunities for the Russian Banking Sector 39
Econometric Analyses of the Banking Sectors
Figure 4: Estimated Value at Risk at the 1% probability level: Amer-
ican, English, Russian and Italian financial sectors indexes
2007-2009: Dangers and Opportunities for the Russian Banking Sector 40
What is Next?
1.) Consolidation of Banking sector
The Government has helped stated-controlled banks to buy banks with
troubles. However, the current situation is profitable also for some large
Commercial Banks, which can acquire troubled banks, too.
In general, in terms of stability of the banking system, the risks remain
manageable.
⇒ The top 20-30 Russian banks as well as the strongest regional banks are
most likely to overcome the crisis: for them, the crisis is a good opportunity
to raise their market share and to acquire small banks by negligible price.
⇒ Moreover, the liquidity provided by the state has become the
determining factor in the banking system.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 41
What is Next?
2.) Dangers
• A continued decrease in oil prices may determine a drop in economic
growth, which may last much longer in the absence of cash and credits;
• While we have seen some stabilization in the FOREX market, it is
difficult to expect the recovering of the lending activity immediately.
Most likely, there will be further restructured loans and the declining
quality of the collaterals, with an increase of bad loans in the banks’
portfolios
• A rising unemployment and the deteriorating economic conditions can
lead to a loss of public confidence in the government
2007-2009: Dangers and Opportunities for the Russian Banking Sector 42
What is Next?
3.) Opportunities
⇒ The Russian banks have used the current situation to try to optimize
their expenses.
For example, Sberbank announced the next target values for the main
parameters of efficiency in a long term perspective:
expenses/revenue: 40-45 % (in a previous Sberbank report in 2008q1, this
parameter was set to 51%), assets/employee - $3,3 bln. (it was $0,8 bln.),
total number of employees 200 - 220 thousands (they were 258 thousands).
Besides, VTB announced a cut in its working stuff and re-organization, too.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 43
References
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Autoregressive Unit Root, Econometrica, 64, 813-836.
Fantazzini, D., DeGiuli, M.E., and M. Maggi (2008). A New Approach for Firm Value
and Default Probability Estimation beyond Merton Models, Computational
Economics, 31(2), 161-180.
Fantazzini, D. (2009). Forecasting Default Probability without Accounting Data:
Evidence from Russia. In: Stock Market Volatility, Chapman & Hall / CRC, 527-548.
Fantazzini, D., Kudrov, A., and Zlotnik, A. (2010). 2007-2008: Dangers and
Opportunities for the Russian Banking Sector. In: Handbook of Banking Crises,
Chapman-Hall/Taylor and Francis Group, forthcoming.
Granger, C. Terasvirta, T. and Patton, A. (2006). Common factors in conditional
distributions for bivariate time series, Journal of Econometrics, 132(1), 43-57.
Huisman, R., Koedijk, K. G., Kool, C., Palm F. (2001) Tail-Index Estimates in Small
Samples. Journal of Business and Economic Statistics, 19(2), 208-216
Kwiatkowski, D., Phillips, P., Schmidt, P., and Y. Shin (1992). Testing the Null
Hypothesis of Stationary against the Alternative of a Unit Root, Journal of
Econometrics, 54, 159-178.
Sklar, A. (1959). Fonctions de repartition a n dimensions et leurs marges.
Publications de l’Institut de Statistique de l’Universit e de Paris, 8, 229-231.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 44
Appendix. The ZPP applied to Sovereign Default Probabilities:The case of Greece
Given the current hot debate on the Greek sovereign default risk, we
wanted to use the ZPP with the Athens composite stock index (ASE).
⇛ The rationale is to extend the idea of tables 3 and 4 to an entire
nation:
Table 4: The ZPP framework extended to a NATION∑ n
i=1 ET,i =∑ n
i=1(AT,i − BT,i)∑ n
i=1 E′
T,i =∑ n
i=1 AT,i
OPERATIVE Equity belonging NATION Asset value
to the NATION shareholders (+) (+)
DEFAULTED Loss given default for Equity belonging to the
the NATION Debtholders (−) NATION Debtholders (+)
⇛ While a composite stock index is only a proxy for a nation “net
assets”, it surely can serve well to signal the level of sovereign default
risk, given the high liquidity and including the most important and
largest country businesses.
2007-2009: Dangers and Opportunities for the Russian Banking Sector 45
Appendix. The ZPP applied to Sovereign Default Probabilities:The case of Greece
Figure 5: 1-year-ahead ZPP: Greece (05/12/2007 - 09/12/2009)
2007-2009: Dangers and Opportunities for the Russian Banking Sector 46
Appendix. The ZPP applied to Sovereign Default Probabilities:The case of Greece
Figure 6: 1-year-ahead ZPP: Russia (Last 500 trading days before the
default in August 1998)
2007-2009: Dangers and Opportunities for the Russian Banking Sector 47
Appendix. The ZPP applied to Sovereign Default Probabilities:The case of Greece
Figure 7: 1-year-ahead ZPP: Argentina (Last 500 trading days before
the default in December 2001)
2007-2009: Dangers and Opportunities for the Russian Banking Sector 48
Appendix. The ZPP applied to Sovereign Default Probabilities:The case of Greece
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2007-2009: Dangers and Opportunities for the Russian Banking Sector 49