Valuation of banking business in Russia for empirical studies icon

Valuation of banking business in Russia for empirical studies



НазваниеValuation of banking business in Russia for empirical studies
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Valuation of banking business in Russia for empirical studies

Vassily Bokov (Higher School of Economics, research@vassilybokov.ru),

Andrei Vernikov (Higher School of Economics, a_vern@bk.ru)


This paper compares various techniques of valuating banks in Russia for empirical research purposes. From comparing the existing valuation methodologies we proceed to devise an alternative methodology of valuation that would be more relevant and applicable to the Russian banking industry. Our technique is based on the linkage of sales prices of banks in M&A transactions to the prices of fixed-income securities issued by these banks. The novelty of our approach lies in the utilization of a broader range of sources of price data that might prove useful in measuring investor perception of different performance characteristics of banking firms. We illustrate the application of our method with a calculation of the impact produced by the quality of corporate governance on the price of the bank measured through the price of its equity and other securities. The downside of our valuation method is being geared towards banking firms while its applicability to industrial companies remains to be researched.

Introduction


Valuation is defined as estimation of market value [Barron’s, 2006], whether at present (asset appraisal) or in the future (detection of mispriced assets). To arrive at an accurate estimate of asset value, one of the major approaches must be taken – either the estimation of some sort of intrinsic value (e.g. dividend-discount models for valuation of equity) or finding a comparable asset which was recently priced by the market (e.g. valuation using accounting ratios or multiples). Either approach has advantages as well as shortcomings and is suitable in a specific range of situations.

Our primary goal being an empirical study of corporate governance, we sought ways to discern the preferences of investors towards a given set of corporate practices which could be built into their pricing of the company’s stock or debt. In other words, we believe that genuine interest in a particular governance practice can only be gauged by the investors’ willingness to pay for it, rather than by results of opinion surveys. Therefore, it is necessary to look at some sort of market data to see what attracts investors and what repels them from a given company. This approach would have been more trivial if Russia had a developed market for bank stocks, but unfortunately this is not the case and therefore we have to glean the investor preferences from the limited data available to us – a small sample of M&A deals and the relatively more developed market for fixed-income securities.

We argue that synthesizing the two aforementioned sources of data could yield a rather reliable and extensive source of information about investor preferences, which would otherwise be severely limited in scope or biased. The result of this synthesis is a model that links actual sales prices of bank equity to market prices of other types of securities issued by banks, thus allowing the valuation of privately-held banks.

^

Review of literature


An extensive discussion of generally accepted valuation approaches can be found in [Damodaran, 2002]. Much of the theory developed in the West applies to mature market economies and does not give due regard to institutional features of emerging market countries. Looking at the specific problems of valuation of assets in Russia, one must mention the work of [Chirkova, 2005] on the application of valuation multiples to the appraisal of Russian companies. [Rutgayzer, Buditsky, 2007] and [Nikonova, Shamgunov, 2007] take a closer look at valuation of banks in Russia. Having been developed to produce a mandatory appraisal as required in certain cases by the Russian law, rather than to actually price a sizable banking business, these methodologies rely heavily on accounting data non-compliant with International Financial Reporting Standards. It makes the outcome susceptible to bias and manipulation. Chirkova [2005] study is practice-oriented but its scope is not industry-centric, so certain banking industry-specific factors such as access to financial markets receive insufficient coverage.

As for the link between governance and the valuation of companies, Morck et al. [2005] offer a review of literature on connection between country-level rules affecting corporate governance and firm behavior and the strengths of securities markets. Klapper and Love [2004] analyze connection between a measure of firm-level governance and share price on a cross-country basis. Bernard S. Black made a seminal contribution to the study of the impact of governance on firm valuation in Russia and other emerging markets [Black, 2001; Black et al., 2006]. Caprio et al. [2003] deal specifically with the link between the value of a banking firm and shareholder protection devices and state-imposed controls. Choi and Hasan [2005] examine the effect of ownership and governance on bank performance in Korea. Staryuk [2008] used value-based management concept to research how corporate governance has driven stock market valuation of Russian ‘blue chip’ companies. [Bokov, Vernikov, 2008] made an attempt to explain the differences in the valuation of Russian banks from a quality of governance point of view.


^ Valuation methods

Established methodologies of business valuation comprise such staple methods as discounted cash flows, multiples valuation, and real options approach. The former category comprises the discounted cash flows (DCF) analysis approach, the multiples valuation approach and the real options method. There are also alternative methodologies that do not fall into the established methodologies category but are usually some variation of one of the established approaches adapted for a particular purpose. Focusing on the problem of valuing a bank, the more widely used approaches are interest rate build-up (a variant of DCF analysis that is based on an elaborate procedure of determining the discount factor based on a set of risk factors pertaining to the bank’s business); use of yield spreads between different forms of bank’s liabilities or components of regulatory capital as an input for a modified multiples-based valuation and use of derivatives price data either to arrive at a discount factor for DCF model or to be used as an input in a multiples-based procedure.

We see 3 main obstacles to the direct application of existing methods of firm valuation to banks operating in Russia: (i) unreliable accounting data, (ii) lack of informational transparency, and (iii) very limited market for bank equity. In order to overcome these impediments we had to consider devising our own methodology that would allow us to base our research on as objective measure of value as possible.

The proposed solution is to look at the firms that were priced in recently completed M&A transactions (the center-piece of information for a multiples-based approach). However, instead of devising a proportionality coefficient based on comparing the accounting ratios, we suggest using another piece of market data – prices (or, rather, yields) of debt securities. In order to account for the time value of money we propose to convert the prices into appropriate yields, which are then adjusted for the benchmark interest rate in order to net out the variability due to economy-wide changes (in the case of Russia – for MosPrime interbank rate). The bank sales prices are then regressed on the yield spreads of their debt securities to arrive at an equation explaining the P/BV multiples in terms of the level of premium required by the market in excess of the prevailing market rate from each bank in the sample. It might also be useful to add control variables to improve the precision of the model by accounting for different time periods or structural differences between the M&A transactions. The model thus constructed could then be extrapolated out of sample to value the banks which had their bonds traded actively in the secondary market, but were neither sold nor had their stock freely traded.

In order to arrive at an estimate of P/BV multiple for a bank which does not have readily available stock price data, there arises a need to convert bond yields into B/BV. This can be accomplished via the following equation:


P/BV = α + β1^ *SPREAD + β2*STRATEGIC + β3*TIME


where SPREAD is the yield spread to MosPrime (that is, the yield on bonds adjusted for the benchmark interest rate to isolate the effect of interest rate dynamics), STRATEGIC is the control variable accounting for control premium contained in M&A transactions and TIME is the trend variable.

To estimate the coefficients in this equation we have collected a sample of large transactions with bank equity in Russia between 2004 and 2008 (a detailed list can be found in Appendix Table 1). We then matched P/BV multiples disclosed following the completion of each transaction with yields on bonds issued by banks in question immediately prior to equity transactions. The resulting sample included 13 transactions. The least-squares estimation procedure for the model outlined above returns an R2 of slightly above 0.55, with the regressors collectively insignificant at confidence levels below 33% and individually at level as varying as 0.3% (for intercept), 32% (for SPREAD), 35% (for STRATEGIC) and 51% (for TIME).

Although the model demonstrates a below-average fit, we proceed to use the model for further analysis. The primary reason is that we believe that the poor fit of the model can be explained by the very small sample on which the model was estimated.

Having established the relationship between P/BV and yield spreads we proceed to calculate ‘synthetic’ P/BV multiples for a host of Russian banks that had a liquid market for their bonds. We looked at the first trading day of 2008, so as to (i) use the most recent data, and (ii) avoid overlap with the crisis period. Having run the model on the sample of bond prices we have arrived at a sample of further 21 data points (that is, in addition to the initial sample of market-priced banks).

^

Application to empirical research: Impact of corporate governance on bank value


This section provides a numerical example to illustrate the mechanics of the proposed approach.

Corporate governance is the system by which companies are directed and controlled. A positive connection is assumed to exist between measures of firm-level corporate governance quality and higher share prices [Black et al., 2006].

We have created a model aimed at appraising the relative importance of corporate governance practices employed by Russian banks in terms of value creation or destruction. An earlier version of the model was published in [Bokov, Vernikov, 2008]. We focus on the following range of factors to be included as independent variables:

  1. Asset size (LN_ASSETS)

  2. Time period (TIME)

  3. Average age of Directors (BOD_AGE)

  4. Average age of top managers (MB_AGE)

  5. Stability of the Management Board (MB_TENURE)

  6. Stability of the Board of Directors (BOD_TENURE)

  7. Size of the Board of Directors (BOD_SIZE)

  8. Degree of Board independence (BOD_INDEPENDENCE)

  9. Rating agency coverage (RATINGS)

  10. Quality of auditors (AUDIT)

  11. Shareholder concentration (SCR)

Appendix Table 2 provides a brief description of each variable and the expected sign of its impact on the dependent variable (P/BV). We then use the P/BV multiples estimated above as dependent variable to be explained by the aforementioned list of corporate governance factors.

As the next step towards building our model for appraising corporate governance, we check the candidate regressors for potential correlations between each other so as to control for multicollinearity. We construct a correlation matrix and on its basis eliminate several independent variables exhibiting correlations in excess of 0.5 with other explanatory variables.

We then run a least-squares estimation procedure for the regression model of P/BV multiples on the explanatory variables outlined above. The estimation was performed stepwise, starting from the full set of remaining candidate regressors and eliminating the statistically insignificant ones. After making these adjustments, our final model took the following form:


P/BV = α + β1^ *BOD_INDEPENDENCE + β2*TIME + β3*BOD_AGE


The estimation procedure yields an R2 of slightly above 0.41, F-test is passed at all standard confidence levels and all regressors are individually significant at 10% confidence level. Holding all else equal, as time passes the average bank is valued slightly less each quarter as a multiple of its equity capital. As average age of Board members increases, P/BV multiple marginally increases too. The growth in the degree of Board independence significantly reduces the valuation multiple as Board composition approaches full independence. Contrary to our ex ante expectations, TIME exhibits a negative relationship with P/BV multiple, even more surprising is the negative sign of BOD_INDEPENDENCE and the size of the coefficient. Considering that the bulk of the sample was constituted by transactions not involving a transfer of control, it appears that minority shareholders strongly favor Board membership by owners and/or top managers.

Conclusions


We considered the established valuation methodologies and concluded that neither provides a satisfactory tool to be used in empirical studies of Russian banks. We proceeded to develop our own methodology, employing a market-based valuation technique to gauge the actual investor sentiment towards Russian banks. Our exercise has yielded a model based on conversion of bond yields into generally used valuation multiples. Though the model is far from being statistically perfect, it gives a first impression of usability of the approach on which it is based and is sufficiently capable of revealing investor preferences. It can be used in empirical studies of the differences in investor sentiment towards different financial institutions.

Further, we attempted to quantify the impact of various governance practices on the valuation of banking firms in Russia using an original set of explanatory variables incorporated into a multiple linear regression model. Methodological imperfections notwithstanding, our attempt yielded some interesting findings.

^ First, investors clearly prefer mature Boards of Directors, while disregarding the indicators of top management’s experience or stability. Second, efforts and expenses incurred in the process of upgrading corporate governance to ‘international best-practice’ do not necessarily pay off. Third, with regard to transparency, investors appear to place no value on a bank’s exposure to the scrutiny of rating agencies, or the quality of external auditors.

As a direction for future research, we plan to increase the coverage and the sample size. One dimension of improvement could be the extension of the sample size for ‘synthetic’ valuations by looking at a larger number of quarters and including data from before Q1 2008. We may also try going beyond plain senior bonds and employ subtler differences between fixed-income products, e.g. by considering yields on hybrid capital products [Bokov, 2007].

References


Bankscope Database www.bankscope.bvdep.com

Bankers’ Almanac www.bankersalmanac.com

Barron’s (2006), Dictionary of Banking Terms, Barron’s Educational Series, New York.

Black, B. (2001), The corporate governance behavior and market value of Russian firms, ^ Emerging Markets Review, 2: 89-108.

Black, B., Love, I. and Rachinsky, A. (2006), Corporate governance and firms' market values: Time series evidence from Russia, Emerging Markets Review 7 (4): 361-379.

Bokov, V. (2007), The use of hybrid financial products for commercial bank valuation. - M.A. thesis, Higher School of Economics (Department of Banking), Moscow. - in Russian.

Bokov, V. and Vernikov, A. (2008), Governance quality and bank valuation in Russia: An empirical study, ^ EJournal of Corporate Finance (Moscow), 3 (7): 5-16.

Caprio, G., Laeven, L., and Levine, R. (2003), Governance and bank valuation, NBER Working Paper No.10158, National Bureau of Economic Research.

Chirkova, E.V. (2005), Kak otsenity biznes po analogii (How to Value a Business by Analogy), Alpina Business Books, Moscow. – in Russian.

Choi, S. and Hasan, I. (2005), Ownership, governance, and bank performance: Korean experience, ^ Financial Markets, Institutions and Instruments (New York University), 14 (4): 215-242.

Damodaran, A. (2002), Investment Valuation, John Wiley and Sons, New York.

Hoover’s Database www.hoovers.com

IFC (2007), Russia banking sector corporate governance survey: A snapshot on improvements made, International Finance Corporation, Moscow.

Klapper, L.F. and Love, I. (2004), Corporate governance, investor protection, and performance in emerging markets, J. of Corporate Finance 10: 287-322.

La Porta, R., López-de-Silanes, F. and Shleifer, A. (1999), Corporate ownership around the world, J. of Finance 54 (2): 471-517.

Morck, R., Wolfenzon, D. and Yeung, B. (2005), Corporate governance, economic entrenchment, and growth, J. of Economic Literature 43: 655-720.

Nikonova, I.A. and Shamgunov, R.N. (2007), Strategiya i stoimost’ kommercheskogo banka (Strategy and Value of a Commercial Bank), Alpina Business Books, Moscow. – in Russian.

RID & Expert-RA. National Rating of Corporate Governance./ Russian Institute of Directors & Expert Rating Agency. raexpert.ru/ratings/corporate/

Rutgayzer, V.M. and Buditsky, A.E. (2007), ^ Otsenka rynochnoy stoimosti kommercheskogo banka (Appraisal of Market Value of Commercial Banks), Maroseika, Moscow. – in Russian.

Standard & Poor’s (2006), Corporate governance ratings: Criteria and methodology. www.standardandpoors.ru

Standard & Poor’s (2007), Transparency & Disclosure Survey of Russian Banks 2007. www.standardandpoors.ru

Standard & Poor’s (2008), Criteria: Corporate governance rating GAMMA — Governance, Accountability, Management Metrics and Analysis. www.standardandpoors.ru/page.php?path=gammawww.standardandpoors.ru/page.php?path=gamma

Staryuk, P. (2008), Impact of corporate governance on the valuation of Russian companies (an empirical analysis). – PhD thesis, Higher School of Economics, Moscow. – in Russian

Vernikov, A. (2007), Corporate governance and control in Russian banks, CSESCE Economics Working Paper No.78. L.: UCL-SSEES (School of Slavonic and East European Studies). www.ssees.ac.uk/publications/working_papers/wp78.pdf

Appendix

^ Table 1: Sample of transactions*

Target

P/BV

Source

Target

P/BV

Source

Absolut Bank

3.80

Market

Probusinessbank

3.00

Market

AK BARS Bank

3.32

Appraisal

Promsvyazbank

3.40

Market

Bank Saint-Petersburg

2.74

Appraisal

Rosbank

4.50

Market

Bank Saint-Petersburg

2.90

Market

Rosbank

4.50

Market

Bank SOYUZ

3.27

Appraisal

Rosbank

3.67

Market

Bank VTB 24

2.54

Appraisal

Russ-Bank

2.91

Appraisal

Bank ZENIT

3.29

Appraisal

Russian Agricultural Bank

3.45

Appraisal

Credit Bank of Moscow

2.29

Appraisal

Russian Standard Bank

3.04

Appraisal

Expobank

4.00

Market

SKB-Bank

2.81

Appraisal

Gazprombank

3.50

Appraisal

TransCreditBank

3.57

Appraisal

Home Credit & Finance Bank

2.83

Appraisal

Uniastrum Bank

3.01

Appraisal

Impexbank

2.90

Market

Uniastrum Bank

3.10

Market

KMB Bank

2.43

Appraisal

URSA Bank

3.04

Appraisal

MDM Bank

3.30

Appraisal

Vozrozhdenie

4.00

Market

NOMOS-Bank

3.29

Appraisal

Vozrozhdenie

3.80

Market

Orgresbank

4.30

Market

VTB Bank

3.44

Appraisal

Petrocommerce

3.25

Appraisal










Sources: public disclosure; media; our database


^ Table 2: Preliminary set of explanatory variables

Variable

Stands for

^ Expected impact

ASSETS

Natural logarithm of asset size

+

AUDIT

Quality of auditors (1 if auditors are a Big-4 firm. 0 – otherwise)

+

BOD_AGE

Average age of Directors

+

BOD_IND

Percentage of independent directors on the Board of Directors

+

BOD_SIZE

Size of the Board of Directors

- (if over 7)

BOD_STABILITY

Average tenure of directors (in months)

+

MB_AGE

Average age of top managers

+

MB_STABILITY

Average tenure of the members of the Management Board (in months)

+

RATINGS

Number of major rating agencies covering the bank

+

SCR

Sum of top 3 shareholders’ shares of equity

+

TIME

Quarter in which the transaction has been completed

+






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