Sample research 24 November 2010

Transcription

1 Peter Kadish, Banks EMEA Company: Rosbank, Bloomberg ticker ROSB RM All data presented has been based solely on financial statements (IFRS financial reports for 2009, 2008,) found on the company website at Important objective of this report is to adhere to complete transparency. All ratios, coefficients, rate of change, etc presented here can be found in supporting excel file which themselves are cross-referenced with the balance sheet data presented in the excel file. Electronic copy available at:

2 Part I. Company analysis Company valuation via Free cash flow to equity model and Residual income model: FCFE model Mio rubles Net income Depreciation and amortization Other NCA Changes to non-cash capital Minimum reserve deposits with Central Bank of Russian Federation Deposits from Central Bank of Russian Federation Due from banks-due to banks Net financial assets at fair value through profit or loss Wk Disposal of fixed assets Net change in l.t. borrowing FCFE (e) 2011(e) 2012(e) 2013(e) 2014(e) FCFE EX CB SUPPORT PV of FCFE TV PV of TV Total fair value of the company Per share value Residual income model Common equity Shares outstanding Book value per share Per share value 55.5 Risk on Russia is closely related to oil price as can be evident from the oil/cds 1 relationship. Current CDS level is at historical lows 2. Rosbank valuation is standing in line with international comparisons, very close to the regression line (Chart 1). Any raise in risk free rate will raise COE and therefore lower valuation. 1 Credit default swap on Russia 2 More on this issue at Kadish (2010) at Electronic copy available at:

3 Sensitivity analysis to COE/ROE and Value of the company for Residual income model COE 15% 16% 17% 18% 19% 20% 21% 22% 16% 50 17% % ROE 19% % % % % Cost of equity calculation Ungeared beta based on regression results versus RTS index ( ) 0.93 Russia l.t. bond yield, RUB 7.5% Market risk premium for Russia* 10.7% Terminal growth rate** 5.0% CAPM cost of equity 17.3% * Damadaran at ttp://ssrn.com/abstract= ** According to DB estimation Input Data Number of shares, mio ROE, assumed 25% increase from average 20.4% Assumptions average prices (midcycle ROE) ROE* 16.9% 15.5% 15.0% 17.9% 1.5% 16.3% CAGR Net income (mio Rubles) % *Net income before extraordinary items - minority interest/average equity

4 Chart 1. P/B versus ROE P/B ROE R-squared: , t-statistic: , sample = 118 banks from EM, Rosbank marked in red Chart 2. P/B versus ROE, Averages P/B 5Yr Avg Yr Avg ROE R-squared: , t-statistic: , sample = 92 banks from EM, Rosbank marked in red

5 Company analysis and comparables, ROSBANK Company analysis Balance-sheet ratios Loans/Assets Loans/Deposits Deposits/Liabilities Gearing (Assets/Equity) Income statement ratios Asset Margin Liability Margin NIM Growth rates Revenue 0.09 Operating expense 0.03 Provisions expense 2.24 Net profit Comprehensive profit Loans Deposits 0.08 Assets Performance Efficiency ratio ROAA ROAE Dividend Payout Per share data EPS DPS NA NA BVPS Asset Quality NPL/gross loans Reserves/NPL Reserves/total loans Valuation P/E negative earnings 0.87 P/B International comparison, 93 sample banks, only some presented here Short Name ROE 3Yr Avg ROE P/B P/B 5Yr Avg SBERBANK-CLS TURKIYE GARANTI AKBANK ISBANK-C PKOBP PEKAO YAPI KREDI BANK KOMERCNI BANKA OTP BANK PLC TURKIYE VAKIFL-D FINANSBANK DENIZBANK AS BZWBK BRE HANDLOWY INGBSK BRD-GROUPE SOCIE GETIN ZAGREBACKA BANKA TURK EKONOMI BAN PRIVREDNA BANKA FORTIS BANK AS BANKBPH KREDYTB VUB AS TURKIYE SINAI TATRA BANKA SEKERBANK NORDEABP JSCB UKRSOTSBANK ALTERNATIFBANK BANK OF COMMUN-H Eastern Europe Comparables median Emerging Asia Comparables median Latin America Comparables median Total sample median ROSBANK, midcycle

6 Part 2. Macro view on banking sector in Russia Central bank does not target amount of credit (money) in the economy, it targets short term interest rate (bank reserves) to run monetary policy today 3. By having too much excess reserves (which central bank can create via open market operations), banks can expand credit (deposits) in the economy and make profit on the difference between cost of liabilities and return on assets. Differently put, commercial banks are important vehicle in credit creation 4. However, the ability of banks to create credit does not necessarily mean that credit will be created. Credit can be either used for transactions that are within GDP accounting and within non-gdp accounting, such as all asset (real estate) and financial transactions. Thus during the last several decades we have observed increased amount of credit that has been used in financial and real estate transactions and therefore traditional quantity equation has recorded a decline in velocity (say M2, M3 velocity) since raising part of the money supply was used for non-gdp transactions. In sum, the accurate representation of money supply in a large non-cash based economy is credit creation 5. It is important to distinguish between productive credit creation, which is used for the creation of new goods and services, and which is noninflationary, and unproductive credit creation, which leads to one of two types of inflation. Unproductive credit creation can take the form of consumptive credit, which is the extension of credit for the consumption (but not creation) of goods and services consumer price inflation (which hasn t been observed due to emerging markets and China integration in the world economy with vast productive capacity and labor force). Unproductive credit creation can also take the form of non-gdp credit, which is credit created for the use in asset or financial transactions (observed in the USA, elsewhere). Excessive (>GDP growth rates) unproductive credit creation is unsustainable in the medium to long run 6. When banks are exposed to unproductive credit, they are exposed to asset price fluctuations. Consequently, if prices fall (when borrowing (credit) raises quicker than income (GNDI which is equal to GDP) is growing, at one stage the borrower will not be able to pay back/refinance all those loans) and as bank assets shrink, they can no longer expand credit to productive sector (and neither to unproductive) this is Fisher s debt deflation theory. Credit in the broad term is what matters for asset prices. Asset prices and development of financial system is what mattered for growth during the last decade. Below relationship between credit as proxied by major Russian banks 7 assets, nominal GDP, real estate prices and RTS index is being analyzed. 3 Many countries that introduced monetary targeting failed. The Bank of England went through a number of monetary targets without success. It finally abolished the procedure entirely in the mid-1980s. The bank of Japan was more successful, it met monetary targets with the utmost precision. By precisely controlling credit creation through its window guidance it could also achieve any targeted goal for deposit measures, such as M2+CD. Fed and Bank of England did not have window guidance. The reason for abandoning targets for money growth and instead setting interest rates as a way of making monetary policy comes from 1970s when prior stable relationship between money growth and either inflation or nominal income growth no longer existed (more in Friedman, Kutter (2010)). 4 An accurate representation of credit creation is given in (Werner (2009)) 5 Via regression analysis, credit to productive part of GDP has been proved to be the most efficient in explaining the long turn performance. Other variable such as interest rates, M0, M2 monetary aggregates are insignificant at conventional level of alpha. Bank credit appears to be in a stable long-term relationship with nominal GDP growth. 6 The problem with contemporary monetary policy is that credit creation vehicle is given to commercial banks. Being private entities, they aim at raise in profitability and do not consider social wellbeing when conducting regular business. Short-termism is associated with raise in leverage and boom-bust cycles. 7 Sberbank, VTB.

7 Table 1 shows that relationship between nominal GDP and money (credit) is better proxied by bank assets rather than M2 monetary aggregate. Table 1. Relationship between GDP and money, regression results Dependent Variable: GDP, annual data M R-squared Bank assets R-squared Dependent Variable: lngdp, annual data M R-squared Bank assets 4.21E E R-squared Since GDP is a flow concept and monetary aggregate/bank credit is a stock concept, nominal GDP data is regressed on change in the monetary aggregate/bank credit for equalization purpose. Real estate prices are too better aligned with credit rather than money stock, M2. (table 2) Table 2. Relationship between GDP and money, regression results Dependent Variable: ln Real Estate 8, annual data M R-squared Bank assets 5.32E E R-squared It is, therefore, possible to conclude that bank assets have higher explanatory power in real estate movements, GDP movements. Banks have access to funding via bonds, syndicated loans that get transferred to the real economy for productive usage as well as for unproductive usage (real estate, stock market). 8 Bloomberg data

8 Below, bank assets are regressed on oil price relationship is strong. Table 3. Relationship between bank assets and oil price, regression results Dependent Variable: Bank assets, annual data OIL Price R-squared Dependent Variable: lnbank assets, annual data LnOIL Price R-squared Vector autoregression is applied to see if autoregressive process takes place. Table 4. Vector Autoregression Estimates for bank assets and oil price, regression results Standard errors in ( ) & t-statistics in [ ] Bank Assets OIL Price Bank Assets t e-05 ( ) (4.8E-05) [ ] [ ] Bank Assets t E-05 ( ) (5.5E-05) [ ] [ ] Bank Assets t E-05 ( ) (7.1E-05) [ ] [ ] OIL Price t ( ) ( ) [ ] [ ] OIL Price t ( ) ( ) [ ] [ ] OIL Price t ( ) ( ) [ ] [ ] R-squared

9 Indeed, there is an autoregression process in place, i.e. developments in oil price predict developments in credit but developments in credit do not predict developments in oil (unsurprisingly, since Russian credit is analyzed). It is, therefore, possible to conclude that credit in the economy that is created by banks is basically explained by the oil price. If oil price is high, capital flows into the country, increasing money supply and credit and leading to raise in inflation. The latter occurs in the Russian economy for the following reasons: first of all, undeveloped (relatively to developed markets) financial system does not allow for complete sterilization of increases in money supply. Second of all, capacity (physical, labor) in Russia is relatively (relatively to, say, China) scarce, therefore scarce supply raises input prices and puts pressure on wages immediately, which is forwarded to final prices. Finally, Russia, being an exporting country, cannot afford strong currency (to support current account), and relatively weak currency leads to inflation since, naturally, import prices raise in local currency. The economic structure is, therefore, quite straightforward. The application of the above analysis to the banking sector is straightforward, too. Profitability (ROA, ROE) is going to be dependent on commodity prices until structural changes take place in the economy (to move higher up the value creation chain and not to be dependent on commodities this discussion is beyond the scope of this paper.)