An Analytical Valuation of Common Stocks: Applied for Industrial
             Companies in Istanbul Stock Exchange




   ...
An Analytical Valuation of Common Stocks: Applied for Industrial
               Companies in Istanbul Stock Exchange



  ...
An Analytical Valuation of Common Stocks: Applied for Industrial
                   Companies in Istanbul Stock Exchange

...
At the end, the empirical evidence suggests that the QVT can estimate the actual market prices with
an encouraging accurac...
and the definition of net debt is:

Net Debt = LTFL + STFL - LA – MS                                    (4)

Here LTFL and...
Exhibit 1. The average annual interest paid on public debt.
(Source: Turkish Treasury and State Institute of Statistics - ...
parameter multiple regression model (with year, inflation and real growth). But at this point the
performance of the net i...
For the borrowing cost the assumption given in the preceding paragraphs is still valid. Accordingly,
the companies analyse...
Year             Annual Returns (%)
    1995                     60
    1996                    152
    1997              ...
recommendations, the difference is borrowed or if it is just the reverse, the difference is invested at
the overnight REPO...
3                       0                  54
    4                      31                  72
    5                     ...
5. When synthesising the costs of capital to discount the cash flows, using the average of annual
   deposit rates offered...
Pastor, L. L., 2000. Portfolio Selection and Asset Pricing Models. The Journal of Finance, Volume
  55, Issue 1, 179-223.
...
25 Sasa                   SASA         Petroleum &                                                 2
 26 Tupras           ...
Appendix C: Synthesising the Weighted Average Cost of Capital

          Company                 ROE        D/E        Tc ...
Otokar                 120.3   228.8   26.3     71.8
Petkim                 127.0    27.9   46.7    107.2
Petrol Ofisi    ...
Hurriyet Gazete              43.0%               35.7%         49.7%               43.3%
    Kent Gida                    ...
For a portfolio equals to zero at t=0, relative to index and compounded annually:

        Based on 28-Dec-01:            ...
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  1. 1. An Analytical Valuation of Common Stocks: Applied for Industrial Companies in Istanbul Stock Exchange Murat ULGEN and Suat TEKER Contact Person: Suat Teker Istanbul Technical University Faculty of Management Macka Campus, Besiktas, Istanbul 34367, Turkey Ph: 90.212.219.3030 Fax: 90.212.219.3232 E-mail: tekers@itu.edu.tr
  2. 2. An Analytical Valuation of Common Stocks: Applied for Industrial Companies in Istanbul Stock Exchange Abstract The aim of this paper is to construct the theoretical stock value of industrial companies traded in Istanbul Stock Exchange (ISE) using a quantitative valuation technique (QVT). The tool utilized in the analysis is a spreadsheet application fed by cross-sectional data (financial statements covering 1995-2001 period) as well as time-series data (adjusted stock prices for dividends and splits). The results are then compared to the actual market price in order to determine whether the stocks are selling at a premium, discount or at par. Assuming that QVT correctly values the stocks, various portfolios are constructed. The results show that the constructed portfolios considerably outperform the major market index in ISE. Keywords: Quantitative Valuation Technique (QVT), proforma financial statements, fundamental cash flows, stock valuation. NOTE. This is a preliminary version of the paper. Please don not quote.
  3. 3. An Analytical Valuation of Common Stocks: Applied for Industrial Companies in Istanbul Stock Exchange 1. Introduction There are two widely used valuation methods by stock market investors when making their investment decisions, the fundamental analysis and the technical analysis. In fundamental analysis, the analyst synthesises all fundamental information pertaining to a company and makes projections about its future performance to establish a basis for his/her investment recommendations (buy, sell or hold the stock). In technical analysis, on the other hand, the information set is composed of two sets of data; stock prices and trade volumes. The technical analyst considers only these two types of time series and employs such assumption that “all relevant information is impounded in company’s stock price”. For him/her the stock price is the ultimate parameter, which summarizes all past performance and all future expectations about a company. The trade volume alone does not carry a critical content but reinforces analyst’s interpretation when used in conjunction with the stock price. Each analytical method (technical or fundamental) has certain advantages and disadvantages one another. Buy and sell (‘trading’) strategy requires a shorter-term focus and lends itself better to the technical analysis. On the other hand, a detailed and meticulous fundamental analysis serves better for the purpose when longer-term investment decisions are in question. In theory, the more information is available for a future event, the less uncertainty exists regarding that event. This rule of thumb is also valid for financial markets. Form this point of view, the fundamental analysis might be preferred to technical analysis as it spans a larger set of financial data. But fundamental analysis is more time consuming compared to technical analysis. Utilising the most prominent parameter of the technical analysis, the stock price, along with fundamental information might add strength to the decision-making process. This combination might be defined as ‘quantitative analysis’. Quantitative analysis first requires the projections of the proforma statements up to a certain future period. The purpose here is to estimate future cash flows of a company. The next step is to find out the parameters, which will help in determining the present values of these cash flows. A computer program might be a big time saver when implementing the proposed analysis. The main goal of this study is to form the theoretical framework of the quantitative analysis and realise its practical applications with the help of Microsoft Excel. Moreover, the quality of the analysis should be expected to show improvement with each added financial statement. In the last part of the study the results of the quantitative method are compared to the current market prices of companies to judge about the performance of the ‘quantitative valuation technique (QVT)’ as a valuation method. The companies used in the study are chosen from the industrial sector, which are part of the major market index ISE100. Estimating the figures of financial statements of industrial companies is much easier compared to estimating those of the financial sector companies. In addition, the financial sector in Turkey is considered in a period of consolidation following the massive economic crises in 2000 and 2001. The direct beneficiary of the ongoing economic program, if it succeeds to bring down the inflation, is expected to be the real sector, while the financial sector recovery is anticipated to follow with certain delay. * Yazışmaların yapılacağı yazar: Derin Orhon, dorhon@ins.itu.edu.tr. Tel: (212) 285 38 55
  4. 4. At the end, the empirical evidence suggests that the QVT can estimate the actual market prices with an encouraging accuracy considering the limited amount of financial input. Furthermore, assuming that the market prices do not reflect the true intrinsic values of the stocks and QVT is a better proxy in that sense, the accompanying investment recommendations considerably outperform the market index. When measuring these performances, the investment recommendations are evaluated in portfolios, which are constructed using equal (value) weights for the companies. The logic behind equal investment in each stock is that the QVT is a tool to extract the intrinsic value of a company, not a tool to analyse the risk-return profiles of the companies to determine their respective weights in the portfolios (Pastor, 2000). 2. Commonly Used Valuation Models The valuation models are analysed under two different categories; asset-based valuation models and discounted cash-flow models. The main identity for the asset-based valuation models, Value = Assets – Liabilities (1) and the fundamental equation used in the discounted cash-flow models, i=n CFt +i Pt = ∑ (2) i = 0 (1 + r ) i In the equation above Pt denotes the price at time t, CFt+i, the cash-flow at time (t+i), r the discount rate of the asset and n the end of the discounting period. Meanwhile, the equity analysts in the financial markets apply more convenient valuation tools in real-life. The most popular one among these is the financial ratio analysis or the so-called multiple comparisons. The most widely used financial ratios can be listed as price/earnings (p/e), price/sales (p/s), price/book value (p/bv), enterprise value / sales (ev/s), enterprise value / earnings before interest and taxes, depreciation, and economic value added (Kim, 1997). The main principle when comparing financial multiple is a company more or less reflects the average financial performance - hence financial ratios- of its sector. Thus, for instance, if the average price to sales ratio of the sector is known along with the sales projection of the company, then its fair price can be estimated by multiplying these two figures. 3. Quantitative Valuation Technique (QVT) The quantitative valuation technique, in its most comprehensible form, is a valuation technique which discounts the fundamental cash flows of a company at an appropriate discount rate. Two different types of cash-flows are used in QVT analysis, Free Cash Flow to Equity (FCFE) or Free Cash Flow to Firm (FCFF). The former cash flows should be discounted at Return On Equity (ROE) (Fama and French, 1999) and the end result is the market capitalisation (MCAP) of the company. The latter cash flows, on the other hand, should be discounted by the Weighted Average Cost of Capital (WACC) and the outcome is the enterprise value of the company which may be expressed as: Enterprise Value = Market Cap + Net Debt (3)
  5. 5. and the definition of net debt is: Net Debt = LTFL + STFL - LA – MS (4) Here LTFL and STFL represent long-term financial loans and short-term financial loans, respectively. LA is for liquid assets and MS is for marketable securities. The initial step in the QVT is to forecast these cash flows up to a certain appropriate time horizon and define the rest as the terminal value (TV) of the company. After an appropriate time horizon, the growth in company’s sales revenues is assumed to reach steady-state level. Therefore, the remaining cash flows are discounted using the growing perpetuity formulation. The projection of cash flows requires proforma balance sheet and income statements. The question of when to stop the forecast horizon, or stated differently after when to calculate the terminal value is a thesis subject on its own. One possible approach would be to analyse the life-cycle of a company’s major products. For example, if the demand for a product, which makes up most of the sales of a company, is assumed to stabilise after four years, then the terminal value should be calculated after the fourth year. The application of this heuristic approach is difficult in practice. Besides, in countries such as Turkey, which was subject to chronic inflation many years (Ercel, 1999) and where macro environment still poses many threats, it is extremely difficult to make projections into the distant future. Due to this reason analysts choose to limit their estimation span for Turkish companies with at most three years. The starting point of proforma statements is the net sales. Net sales is predicted using simple and multiple regressions. After net sales, the use of the averages of certain slow-moving (steady) ratios, such as Asset Turnover (Total Sales / Total Assets), Current Ratio (Current Assets / Current Liabilities), Debt to Equity Ratio and Borrowing Cost, along with common-base statements (where other items are given as percentages of Net Sales and Total Assets) will help determine the necessary details of proforma financial statements. 50% 45.6% 40% 36.1% 30.0% 32.1% 30% 28.4% 29.7% 20% 25.7% Average 27% 10% 0% -10% -11.1% -20% 1995 1996 1997 1998 2001 2002 1999 2000 * Yazışmaların yapılacağı yazar: Derin Orhon, dorhon@ins.itu.edu.tr. Tel: (212) 285 38 55
  6. 6. Exhibit 1. The average annual interest paid on public debt. (Source: Turkish Treasury and State Institute of Statistics - SIS). To increase the forecasting power, the QVT goes through modification phases. The aim here is to minimise the estimation error (the difference between the actual and the estimated values) when estimating past financial statement figures. As an example, the net income in year 2000 is estimated using 1995-1999 statements and then the estimated net income for the year 2000 is compared to the actual net income. In summary, the focus of the improvement stages is the borrowing cost of the companies and the need for a market indicator to predict such costs. The companies whose theoretical values are computed using QVT are selected from the major market index (ISE100). ISE100 is mainly composed of blue-chip stocks. It is also assumed that these companies, each a flagship of their respective sectors, can borrow at better terms compared to other companies. The disadvantages of Turkish companies when borrowing funds on the back of the exorbitant real rates the Turkish Treasury is exposed to (see Exhibit above) are assumed to be minimal for the set of companies in this study due to their foreign connections (partner, listing, joint ventures, easier access to foreign funds, etc.) The greatest improvement in the performances of the estimates during the modification phases was forecasting financial expense from the internal dynamics of the company. Put differently, the financial expenses were also computed as a certain percentage of sales (from the average of past financial expenses to sales ratios), similar to the cases with other financial statement items such as Cost of Goods Sold (COGS), other operating profit and losses and extraordinary profit and losses. After forecasting the net sales of next years, the financial expenses are estimated using the average of past ratios. Finally, the net sales are tried to be estimated using multiple regression instead of simple regression. On this regard, a literature survey revealed important point as to which macroeconomic variable to include in the multiple regression equation (Fifild, Power and Sinclair, 2002). In the last two decades, in parallel to economy administration’s foreign exchange rate policies, Turkish economy became dependent to short-term capital flows, dubbed as ‘hot money’ (Ertugrul and Selcuk, 2001). This is the main reason why real economic growth followed a very volatile pattern during this period. Similarly, Malatyali (2000) also argues that the capital flows and investment choices are contributing in the formation of crisis conditions in Turkey. Under the light of all these research, it is decided to include the inflation and the real growth of Turkey next to the default parameter of internal dynamics of net sales (i.e. the year) in the multiple regression equation which is used to forecast net sales of a Turkish company. The tests revealed that two parameter multiple regression model (including year and inflation as the independent variables) explained more of the variation contained in net sales compared to three
  7. 7. parameter multiple regression model (with year, inflation and real growth). But at this point the performance of the net income estimates are still not satisfactory. Therefore, the QVT makes a change in strategy and switches to estimating Earnings Before Interest and Taxes (EBIT) instead of net income. 4. Estimating EBIT (rather than Net Income) Peculiar to the Turkish capital markets, the other operating income item usually consists of interest income and dividends due to the high interest rate environment. This situation is plausible for a holding company but if an industrial company is considered, other operating income item loses its meaning. Form this point of view the best counterpart of the EBIT in the income statements is the operating profit or loss. The tests that are carried out for EBIT estimates show that the average absolute deviation of the estimates from their actual counterparts fall into the following confidence interval at 0.5% error margin: Confidence Interval = [%13,72 , %37,13] (5) In its simplest form, this confidence interval shows that the average absolute deviation of EBIT estimates can be found within these bounds with 99.5% probability (confidence). The outcome is encouraging considering the limited amount of financial statements as inputs (for instance using just 1995-1999 statements to estimate 2000 results). The confidence interval is expected to contract and the QVT’s estimation performance is expected to improve with increasing number of observations, i.e. added number of financial statements. Now that the strategy has shifted to estimating EBIT, the proper fundamental cash flows that should be sought after by the QVT, namely the Free Cash Flows to Firm or FCFF, should be clarified at this point. Accordingly, FCFF = EBIT (1-T) + DEPR – NWC (6) In this equation, T denotes the corporate tax rate, DEPR the depreciation expense and i NWC the change in the net working capital. Financial analysts usually drop the last term. 5. Synthesising the Weighted Average Cost of Capital (WACC) The cash that flows to the firm is discounted today using the weighted average cost of capital, as mentioned before. The definition of the WACC is as follows: D E WACC = Rb (1 − T ) + Re (7) D+E D+E In this equation, D denotes the book value of debt, E is the book value of the equity, T the corporate tax rate again, Rb the borrowing cost and finally Re the required return on equity. * Yazışmaların yapılacağı yazar: Derin Orhon, dorhon@ins.itu.edu.tr. Tel: (212) 285 38 55
  8. 8. For the borrowing cost the assumption given in the preceding paragraphs is still valid. Accordingly, the companies analysed here are selected from the premium index ISE100, which are expected to secure debt financing in above-average terms. These companies are assumed to borrow at rates close to the annual WPI inflation given in the table below. Table 1: Annual Change in Wholesale Price Index (WPI) (1995-2001) Year WPI-Inflation (%) 1995 66 1996 85 1997 91 1998 54 1999 63 2000 33 2001 89 Average 69 The required rate of return on equity, on the other hand, is calculated with the help of the Capital Asset Pricing Model (Daniel, Hirshleifer and Subrahmanyam, 2001). At this step, the risk-free rate is represented by the average annual deposit rate offered by Turkish banks since the other two alternatives, Treasury borrowing rates and Central Bank of Turkey (CBT) overnight rates did not qualify. The maturities of the Treasury securities are very inconsistent. In other words, a particular maturity can not be easily found in the past. The overnight rates of the CBT are highly volatile. After 2001 devaluation crises these rates went as much as above 1,000%. Table 2: Risk-Free Rate Proxy (1995-2001) Year Risk-free Rate (%) 1995 92 1996 92 1997 93 1998 93 1999 86 2000 38 2001 62 Average 80 Finally, the equity market premium offered by the equities over the risk-free rate is obtained from the table below: Table 3: ISE Stock Market Index (ISE100) Annual Returns (1995-2001)
  9. 9. Year Annual Returns (%) 1995 60 1996 152 1997 247 1998 -30 1999 451 2000 -46 2001 46 Average 126 After synthesising all these date as proposed in equation 7 and the resulting Free Cash Flow to Firms are discounted using Weighted Average Cost of Capitals, the enterprise values of the companies are determined. Finally, deducting the net debt from the enterprise value yielded the quantitative values of the companies. At this stage, there area several alternatives to compare the theoretical values with the actual market prices. First of all, according to the rules and regulations of the Capital Markets Board (CMB), the companies whose stocks are listed in the stock exchange have 10 weeks to announce their year-end earnings (IMKB Kilavuzu, 1998). The end of this period corresponds to 15-Mar-02 in this analysis. Here the values computed by the QVT using 1995-2001 statements are compared to both 28- Dec-01 prices and 15-Mar-02 prices. When the empirical results (differences between quantitative prices and actual market prices) are examined, it was seen that the choice of the base date (28- Dec-02 or 15-Mar-02) is not important. The QVT estimated the stock prices of 33 companies in ISE100 with a 36% accuracy. Accuracy is defined as quantitative price being in the 1/3rd (or 33%) neighbourhood of the actual market price. Considering that the estimates are generated with a mere seven years of observation period (statements from 1995 through to 2001), the results are interpreted as encouraging. 6. QVT’s Investment Recommendations and Portfolio Approach To reach the above results the postulate that market prices do reflect the intrinsic values of companies was assumed to hold. As an alternative to this line of thought, it was also assumed that the quantitative values as computed by the QVT are better predictors of true company values. Under this assumption, investment recommendations are devised based on the difference between the quantitative value and the market price. If the theoretical (quantitative) value is within the ± %10 of the market price, the recommendation is ‘HOLD’, if the theoretical price is below 10% of the market price, the recommendation is ‘SELL’ and ‘BUY’ if the theoretical price is 10% above the market price. Two different equal-value-weighted portfolios are constructed based on these investment recommendations. The reason for equal value weighting is, as mentioned before, the QVT being a tool to determine the intrinsic values of companies using fundamental cash flows and appropriate discount rates and not a tool to construct portfolios by arranging weights. In other words, the QVT does not advise on how much to buy/sell/hold of which company by looking at their risk-return profiles, rather it advises at what fair value the company should trade. Out of the two portfolios, the first one has a zero value at the beginning (hence the name ‘zero portfolio’). If the investment recommendation is buy for a certain stock, the stock is bought, if its is a sell, the stock is sold short. If the buy recommendations are larger in number than the sell * Yazışmaların yapılacağı yazar: Derin Orhon, dorhon@ins.itu.edu.tr. Tel: (212) 285 38 55
  10. 10. recommendations, the difference is borrowed or if it is just the reverse, the difference is invested at the overnight REPO rate. The first type of portfolio is indifferent to hold recommendations, i.e. no action is taken then. The second portfolio, on the other hand, has equal investment in each stock at time zero (‘non-zero portfolio’). In this case, if the recommendation is buy, the stock is retained in the portfolio, if it is a sell, the stock is taken out of the portfolio. The difference between the second (non-zero) and the first (zero) portfolio is that if the recommendation is hold, then the stock again retained in the portfolio. Said differently, the non-zero portfolio was not indifferent to hold recommendations. The index relative returns of these portfolios with respect to the ISE100 Index are calculated for different holding period horizons from one month to 12 months. To ease comparisons, all returns are then converted to effective annual rates. The definition of the FCFF as given in equation (6) is modified by dropping the last term as suggested by the real-life practices. The results are summarised in the following tables: Table 4:‘Zero Portfolio’ ISE100 Relative Returns Base Date Month 28-Dec-2001 15-Mar-2002 1 21 18 2 17 9 3 14 29 4 17 29 5 14 39 6 2 34 7 2 32 8 5 32 9 4 35 10 4 29 11 7 25 12 6 22 Average 9 28 At first inspection, the fact that index-relative returns are positive and even around 30% when 15- Mar-02 is taken as the base date was seen as a very positive result. All in all, in developed financial markets, meeting the performance of a major market index is seen as success. The same analysis is also carried out for the non-zero portfolio and following results are obtained: Table 5: ‘Non-Zero Portfolio’ ISE100 Relative Returns Base Date Month 28-Dec-2001 15-Mar-2002 1 57 -21 2 45 1
  11. 11. 3 0 54 4 31 72 5 39 82 6 53 74 7 66 69 8 68 52 9 57 59 10 48 47 11 54 38 12 42 35 Average 47 47 When the two tables are compared (Table 4 and Table 5), the second portfolio performed much better than the first one. Besides the second portfolio produced the same index-relative results for both base dates, hence the base date lost its importance again. A 50% index-relative return over a major market index should be seen as a huge success for any portfolio manager. Finally, when the performances of the two portfolios are compared, it is seen that there is a high value attached to the ‘HOLD’ recommendations. 7. Empirical Results and Conclusions During the application phases of the quantitative valuation technique, the first step was the construction of the proforma statements and estimation of the fundamental cash flows using these proforma statements. Then the costs of capital are synthesised to discount these cash flows and the intrinsic values of the companies are revealed. These values, in turn, are compared to the actual prices established in the stock market. Another step forward was taken by assuming that the market prices would reach to the level of theoretical prices hence the system produced respective investment recommendations. The portfolios constructed according to the recommendations are seen to considerably outperform the ISE100 index. The empirical findings of this research can be listed as: 1. The discounted cash flow method for valuation is better suited for practical applications than the asset based valuation method. 2. In the application of the QVT, either fundamental cash flows (Free Cash Flow to Equity of Free Cash Flow to Firm) could be employed. The corresponding discount rate should be determined adequately. Free Cash Flow to Equity should be discounted at Return on Equity, while Free Cash Flow to Firm should be discounted using Weighted Average Cost of Capital. 3. The first phase of the QVT is the determination of proforma financial statements. Using multiple regression instead of simple regression to forecast net sales (the first element in the proforma cycle) generates better results. The multiple regression model recommended in this study is the one that incorporates the internal sales dynamics (the year) and annual WPI inflation of Turkey. 4. During the proforma creation process, focusing on earnings before interest and taxes instead of net income would reduce the error margin to a great extent. * Yazışmaların yapılacağı yazar: Derin Orhon, dorhon@ins.itu.edu.tr. Tel: (212) 285 38 55
  12. 12. 5. When synthesising the costs of capital to discount the cash flows, using the average of annual deposit rates offered by Turkish banks is more appropriate. At the end there is high inconsistency in the history of maturities for Treasury debt securities and CBT’s overnight rates exhibit excessive volatility. 6. The accuracy of quantitative values obtained from QVT in reflecting the true market prices is 36%. Considering that the input date set is very limited, even this result is encouraging. The accuracy is expected to improve with increasing number of observations, i.e. with additions of financial statements. 7. The two portfolios constructed by assuming that the theoretical values given by the QVT better reflect the true values of the companies considerably outperform the ISE100 index on annualised returns which are calculated for different holding periods. Especially, the performance of the second portfolio (non-zero portfolio), which gives credibility to hold recommendation, was very successful. Hence, it can be said that there is a high value underlying the hold investment action. References Daniel, K. D., Hirshleifer, D. and Subrahmanyam, A., 2001. Overconfidence, Arbitrage and Equilibrium Asset Pricing. The Journal of Finance, Volume 56, Issue 3, 921-965. Ercel, G., 1999. The Relationship Between Inflation and Growth. ISE Quarterly Review, Volume 3, No 12, 15-28. Ertugrul, A. and Selcuk, F., 2001. A Brief Account of the Turkish Economy, 1980-2000. Departmental Working Papers, Bilkent University, Ankara. Fama, E. F. and French, K. R., 1999. The Corporate Cost of Capital and the Return on Corporate Investment. The Journal of Finance, Volume 54, Issue 6, 1939-1967. Fifield, S.G.M., Power, D.E. and Sinclair, C.D., 2002. Macroeconomic factors and share returns: an analysis using emerging market data. International Journal of Finance & Economics, Volume 7, Issue 1, 51-62. Istanbul Menkul Degerler Borsasi, 1998. Sermaye Piyasalari ve Borsa Temel Bilgiler Kilavuzu, Egitim ve Yayin Mudurlugu, Istanbul. Kim, D., 1997. A Re-examination of Firm Size, Book-to-Market, and Earnings Price in the Cross- Section of Expected Stock Returns. Journal of Financial and Quantitative Analysis, Volume 32, Number 4, 463-489. Malatyali, K., 2000. An Inquiry on The Factors Contributing to the Economic Crisis in Turkey. ISE Quarterly Review, Volume 4, No 15, 53-64.
  13. 13. Pastor, L. L., 2000. Portfolio Selection and Asset Pricing Models. The Journal of Finance, Volume 55, Issue 1, 179-223. Appendix A: Companies Used in QVT Grouped by Sectors Company Name Ticker Sector Weight in Sector (%) 1 Turk Hava Yollari THYA Airlines & Services 83 2 Anadolu Isuzu O ASUZU Automotive 3 3 Ford Otosan FROTO Automotive 45 4 Otokar OTKA Automotive 4 5 Tofas Otomotiv R TOASO Automotive 36 6 Anadolu Efes AEFES Beverages 93 7 Akcansa AKCNS Cement 17 8 Cimsa CIMSA Cement 12 9 Arcelik ARCLK Consumer Durables 48 10 Beko BEKO Consumer Durables 6 11 Turk Demir TDDF Consumer Durables 2 12 Dokum Vestel VESTL Consumer Durables 20 13 Eczacibasi Ilac ECILC Consumer Products 83 14 Ak Enerji AKEN Energy 30 15 Kent Gida R KENT Food 39 16 Tat Konserve TATKS Food 12 17 Trakya Cam TRKC Glass 80 18 Hurriyet Gazete M HURG Media 86 19 Eregli Demir Z EREGL Metals and Steel 74 20 Celik Aksa AKSA Petroleum & 4 21 Aygaz AYGA Derivatives Petroleum & 6 22 Kordsa Z KORDS Derivatives Petroleum & 3 23 Petkim PETKM Derivatives Petroleum & 17 24 Petrol Ofisi PTOFS Derivatives Petroleum & 31 * Derivatives Yazışmaların yapılacağı yazar: Derin Orhon, dorhon@ins.itu.edu.tr. Tel: (212) 285 38 55
  14. 14. 25 Sasa SASA Petroleum & 2 26 Tupras TUPRS Derivatives Petroleum & 30 27 Carsi CARSI Derivatives Retail 3 28 Migros MIGRS Retail 63 29 Alcatel Teletas ALCTL Telecommunications 2 30 Aselsan ASELS Telecommunications 3 31 Netas NETAS Telecommunications 5 32 Turkcell TCELL Telecommunications 89 33 Bossa BOSSA Textile 13 Source: Istanbul Stock Exchange NET (-) (-) Operating & (=) SALES COGS Other EBIT Expenses (/) (-) Appendix B: Proforma Statements Preparation Template Fixed Cost Asset Interest & Turnover Variable Cost Ex.ordinary Ratio Expenses (=) TOTAL EBT ASSETS (*) (-) Past Years’ Taxes Common Base Statements (=) Individual Assets Net Cost of Income Debt Current Assets (/) (-) Dividend Current Payment Ratio (=) Retained Current Earnings Liabilities (*) D/E Ratio for New Equity Target Debt Amount New Debt Required Obligation Capital Increase
  15. 15. Appendix C: Synthesising the Weighted Average Cost of Capital Company ROE D/E Tc WACC Akcansa 120.7 46.0 37.7 96.1 Aksa 117.8 57.4 33.5 91.5 Ak Enerji 118.4 50.2 20.1 97.1 Alcatel Teletas 127.7 332.1 31.3 65.8 Anadolu Efes 115.5 280.6 7.9 76.9 Anadolu Isuzu 124.3 116.9 27.3 84.2 Arcelik 126.0 116.8 26.8 85.2 Aselsan 123.0 243.6 39.7 65.1 Aygaz 119.0 72.9 28.2 89.6 Beko 124.5 262.1 29.1 69.6 Bossa 117.8 116.9 38.9 76.9 Carsi 122.5 514.2 40.5 54.1 Cimsa 118.0 53.4 22.7 95.4 Eczacibasi Ilac 121.5 124.0 41.3 76.5 Eregli Demir Celik 127.9 152.1 25.4 81.6 Ford Otosan 124.9 153.8 26.6 79.7 Hurriyet Gazete 125.5 86.1 18.1 93.4 Kent Gida 107.5 454.6 15.6 66.9 Kordsa 121.9 102.9 35.8 82.4 Migros 117.0 250.0 24.1 70.6 Netas 123.1 95.2 37.9 83.8 * Yazışmaların yapılacağı yazar: Derin Orhon, dorhon@ins.itu.edu.tr. Tel: (212) 285 38 55
  16. 16. Otokar 120.3 228.8 26.3 71.8 Petkim 127.0 27.9 46.7 107.2 Petrol Ofisi 123.2 111.3 41.3 79.5 Sasa 117.7 132.5 26.7 79.3 Tat Konserve 114.9 109.5 28.3 80.5 Tofas Otomotiv 127.2 156.3 25.8 80.7 Trakya Cam 118.8 63.2 18.1 94.5 Tupras 125.5 558.1 29.8 59.9 Turkcell 127.3 942.8 0.0 74.2 Turk Demir Dokum 119.0 219.9 32.5 69.0 Turk Hava Yollari 124.2 186.6 39.6 70.3 Vestel 125.4 326.4 26.9 67.8 Appendix D: Absolute Deviations under Two Different Approaches Based on Dec.28,2001 Based on March 15,2002 Company Absolute Deviations Absolute deviations FCFFs Interm. Term FCFFs Interm. Term Average 54.1% 56.3% 54.1% 65.1% Akcansa 63.4% 58.7% 55.5% 49.9% Aksa 33.3% 21.8% 12.3% 2.8% Ak Enerji 34.4% 45.0% 28.6% 40.1% Alcatel Teletas 5.4% 50.5% 45.1% 107.3% Anadolu Efes 61.2% 62.3% 57.0% 58.2% Anadolu Isuzu 19.5% 36.2% 9.0% 84.5% Arcelik 33.3% 22.0% 3.1% 13.4% Aselsan 106.7% 132.1% 140.3% 169.7% Aygaz 39.4% 30.9% 13.7% 1.5% Beko 65.5% 108.0% 72.4% 116.7% Bossa 31.2% 59.6% 48.1% 80.1% Carsi 21.8% 63.7% 94.3% 161.1% Cimsa 23.0% 23.9% 77.8% 75.9% Eczacibasi Ilac 75.0% 1.2% 65.6% 35.7% Eregli Demir Celik 2.4% 23.5% 14.9% 45.4% Ford Otosan 90.9% 64.9% 90.7% 64.3%
  17. 17. Hurriyet Gazete 43.0% 35.7% 49.7% 43.3% Kent Gida 57.5% 49.2% 17.1% 0.9% Kordsa 76.8% 63.0% 70.5% 52.9% Migros 77.6% 80.1% 68.8% 72.3% Netas 35.0% 16.5% 2.0% 31.1% Otokar 52.5% 34.5% 24.8% 3.8% Petkim 74.1% 64.0% 63.3% 49.1% Petrol Ofisi 82.3% 75.9% 67.7% 56.0% Sasa 94.6% 112.5% 107.1% 126.2% Tat Konserve 20.2% 7.6% 18.6% 37.2% Tofas Otomotiv 85.0% 71.2% 81.1% 64.0% Trakya Cam 21.0% 22.7% 4.0% 6.1% Tupras 21.4% 13.4% 23.5% 36.1% Turkcell 30.3% 20.6% 8.9% 24.1% Turk Demir Dokum 118.2% 192.1% 139.2% 220.2% Turk Hava Yollari 94.1% 93.3% 91.3% 90.1% Vestel 94.3% 102.9% 117.9% 127.5% Appendix E: Summary Performances for QVT’s Investment Recommendations * Yazışmaların yapılacağı yazar: Derin Orhon, dorhon@ins.itu.edu.tr. Tel: (212) 285 38 55
  18. 18. For a portfolio equals to zero at t=0, relative to index and compounded annually: Based on 28-Dec-01: Based on 15-Mar-02: Based on average of 28-Dec/15-Mar '02: Months Method 1 Method 2 Method 1 Method 2 Method 1 Method 2 1 8.2% 21.4% 4.2% 17.8% 2.9% -0.2% 2 14.6% 16.5% -10.4% 8.8% 3.1% 5.1% 3 20.0% 14.1% -13.1% 28.5% -1.2% 8.2% 4 12.2% 17.3% -6.3% 29.4% -8.5% 9.5% 5 1.0% 13.7% 1.1% 38.9% -12.1% 9.8% 6 -18.9% 1.6% 3.3% 34.4% -10.5% 10.5% 7 -9.6% 1.8% 2.2% 32.4% -8.4% 11.2% 8 -5.3% 5.0% 6.3% 31.9% -6.5% 10.7% 9 -3.4% 3.7% 5.3% 35.1% -4.8% 12.1% 10 -1.3% 4.3% 5.2% 28.5% -2.0% 14.3% 11 -2.7% 6.6% 6.2% 25.3% -0.9% 14.9% 12 0.1% 6.0% 4.7% 22.1% 0.0% 13.6% Average 1.2% 9.3% 0.7% 27.8% -4.1% 10.0% For a portfolio does not equal to zero at t=0, relative to index and compounded annually: Based on 28-Dec-02: Based on 15-Mar-02: Based on average of 28-Dec/15-Mar '02: Months Method 1 Method 2 Method 1 Method 2 Method 1 Method 2 1 73.3% 56.7% -21.7% -21.4% -27.1% -23.4% 2 65.4% 44.7% -6.4% 1.1% -25.4% -16.4% 3 15.0% 0.4% 41.2% 53.6% -11.9% -0.9% 4 27.1% 31.0% 72.0% 71.5% 10.6% 22.1% 5 21.8% 38.9% 74.1% 82.2% 32.7% 45.1% 6 21.3% 53.1% 65.3% 74.0% 41.0% 52.9% 7 58.9% 66.2% 62.2% 69.4% 40.8% 53.2% 8 67.2% 68.1% 46.6% 51.5% 35.7% 46.9% 9 58.8% 57.3% 53.6% 58.7% 34.4% 43.5% 10 50.5% 48.3% 45.1% 47.3% 34.0% 41.0% 11 49.3% 54.0% 36.2% 37.9% 33.4% 39.7% 12 40.9% 42.2% 31.6% 34.9% 28.8% 34.3% Average 45.8% 46.8% 41.6% 46.7% 18.9% 28.2%

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