Masterarbeit, 2012
89 Seiten, Note: 1
1.Introduction
2. Literature review
2.1 Distinction between equity and entity level valuation
2.2 Multiples based valuation
2.2.1 Accuracy of multiples
2.2.2 Selecting comparables
2.2.3 Choosing multiples
2.3 Accounting flows based
2.3.1 Dividend discount model
2.3.2 Free cash flow model
2.3.3 Residual income valuation model
2.3.3.1 Derivation
2.3.3.2 Benefits of the model
2.3.3.3 Performance
2.3.3.4 Implementation issues
2.3.4 Abnormal earnings growth model
2.3.4.1 Derivation
2.3.4.2 AEGM versus the RIVM
2.4 Valuation of defensive and cyclical firms
2.5 Concluding remarks
3. Large sample analysis
3.1 Research question
3.2 Sample selection
3.3 Methodology
3.3.1 Multiples based valuation
3.3.1.1 Selected value driver
3.3.1.2 Identification of comparable companies
3.3.1.3 Estimation of value
3.3.2 Accounting flows based valuation
3.3.2.1 Cost of equity capital
3.3.2.2 Dividend payout rate
3.3.2.3 Forecasted earnings
3.3.2.4 Forecast horizons and continuing value assumptions
3.4 Results and analysis
3.4.1 Sample descriptive statistics
3.4.2 Valuation errors
3.4.2.1 Descriptive statistics of valuation errors
3.4.2.2 Cross sample comparison of valuation errors
3.4.2.3 Comparison of valuation errors within each sample
3.4.3 Interaction between cyclicality and economic state
3.4.4 Price explainability
3.5 Sensitivity tests
3.5.1 Multiples based valuation
3.5.2 Flow based valuation
3.5.2.1 CAPM assumptions
3.5.2.2 Terminal value
3.6 Concluding remarks
4. Small sample analysis
4.1 Research question and hypothesis development
4.1.1 Target prices (Hypothesis 1)
4.1.2 Earnings (Hypothesis 2)
4.1.3 Flow models (Hypothesis 3)
4.1.4 Investment recommendations (Hypothesis 4)
4.2 Sample selection
4.3 Results and analysis
4.3.1 Industry characteristics
4.3.1.1 Education services
4.3.1.2 Tobacco products manufacturing
4.3.1.3 Food products manufacturing
4.3.1.4 Health services
4.3.1.5 Utilities
4.3.1.6 Housing contractors
4.3.1.7 Primary metal manufacturing
4.3.1.8 Automobile manufacturing
4.3.1.9 Airlines
4.3.1.10 Paper manufacturing
4.3.2 Tests of Empirical Hypothesis
4.3.2.1 Target prices versus actual price (Hypothesis 1)
4.3.2.2 Earnings as a value driver (Hypothesis 2)
4.3.2.3 Use of flow based models (Hypothesis 3)
4.3.2.4 Analyst investment ratings (Hypothesis 4)
4.4 Concluding remarks
5. Conclusion
This thesis investigates the performance of diverse accounting-based valuation models across varying economic conditions (growth vs. recession) and industry types (cyclical vs. defensive). It aims to assess how these models behave and how analysts employ them to formulate investment recommendations.
2.3.3 Residual Income Valuation Model
The concept of residual income is not a recent discovery; it can be attributed to papers from Preinreich (1938), Edwards and Bell (1961), and Peasnell (1982). Contemporary research on the residual income valuation model, however, can be attributed to Ohlson (1995). The RIV model estimates value of equity as the book value of equity plus the present value of future residual income. Residual income is defined by Ohlson (1995: 667) as return on the capital invested at the beginning of the period minus a charge for the use of that capital. Equation 9 shows the residual income equation from an equity perspective:
REt = Bt + dt - Bt-1 - (ρE - 1)Bt-1 (9)
Where:
Bt + dt - Bt-1 = clean surplus earnings
Bt = closing book value
Bt-1 = opening book value
dt = dividends
The residual income valuation relationship is a forward-looking relationship that links economic value, book value, and expected future residual incomes to firm value. It does not encompass backward-looking accounting numbers and value creation. However, consulting firm Stern Stewart & Co. propose an economic value added (EVA™) approach which does take into account historical performance (O’Hanlon and Peasnell, 2002). This dissertation will not examine EVA™ in any detail, but it is important to note that there are variations to the RIV model.
1. Introduction: This chapter contextualizes the research within the economic landscape since 2007 and defines the core focus on cyclical and defensive industry valuation.
2. Literature review: This section critically examines existing academic debates regarding accounting-based valuation, specifically comparing multiples and flow-based models.
3. Large sample analysis: This chapter empirically tests the performance of chosen valuation models across extensive datasets covering different market conditions.
4. Small sample analysis: This part connects the theoretical findings to real-world analyst reports to observe practical application and investment justification.
5. Conclusion: This chapter synthesizes the findings, confirming that valuation model effectiveness is highly dependent on industry cyclicity and economic state.
Equity Valuation, Accounting Numbers, Cyclical Industries, Defensive Industries, Economic Recession, Valuation Models, Residual Income, Earnings Volatility, Financial Analysts, Investment Recommendations, Market Volatility, CAPM, Multiples, Forecasting, Valuation Accuracy.
The thesis focuses on analyzing how various accounting-based valuation models perform when applied to different industry types, specifically cyclical and defensive, during periods of economic growth or recession.
The study differentiates between cyclical industries (e.g., car manufacturers, airlines) and defensive industries (e.g., utility companies, food products) based on how their cash flows and earnings react to economic cycles.
The research evaluates the "one-year forward earnings to price" multiple, the "Residual Income Valuation" (RIV) model, and the "Abnormal Earnings Growth" (AEG) model.
The thesis uses a dual-methodology approach: a quantitative large-sample analysis to test model accuracy across different economic states, followed by a qualitative small-sample analysis of actual analyst reports.
The research asks if there is a significant performance difference in accounting-based valuation models across cyclical and defensive industries in growth versus recessionary economic states.
Analysts are analyzed to determine whether they utilize valuation models to justify their investment recommendations and if their preferences for specific models change based on industry characteristics and market conditions.
The findings indicate that while simple earnings-based models perform well in most environments, flow-based models provide significant complementary value, particularly for cyclical stocks during volatile recessionary periods.
Economic volatility, especially in recessions for cyclical stocks, increases valuation errors. The study finds that analysts often adjust their approaches or shift valuation models to mitigate these risks when earnings become unreliable.
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