(11-12) CFA 3 - Reading 26 and CFA 2 Reading 27 Flashcards
Reading 26 - Section 2
Introduction to Performance Evaluation and Attribution:
a. Components of Portfolio Evaluation and Their Interrelationships:
Performance Measurement: Determines the portfolio’s performance against a benchmark.
Performance Attribution: Explains how the performance was achieved, analyzing sources of returns or risks.
Performance Appraisal: Evaluates whether the achieved performance was due to managerial skill or chance, providing insights for future expectations.
These components are interconnected and together offer a comprehensive understanding of a portfolio’s performance.
b. Attributes of an Effective Attribution Process:
An effective performance attribution process should:
Account for the portfolio’s complete return or risk exposure.
Reflect the investment decision-making process accurately.
Quantify the active decisions of the portfolio manager.
Offer a comprehensive understanding of the portfolio’s excess return or risk.
Incomplete attribution or a failure to reflect the investment process undermines the quality of the analysis.
c. Contrasts in Attribution and Risk:
Return Attribution vs. Risk Attribution: Return attribution explains active decisions’ impact on returns, while risk attribution evaluates the risk consequences of those decisions.
Macro vs. Micro Return Attribution: Macro attribution assesses asset owner decisions like tactical asset allocation, while micro attribution evaluates portfolio manager decisions affecting the total fund’s performance.
d. Types of Performance Attribution:
Returns-Based Attribution:
Advantages: Easy to implement, suitable for strategies with limited data availability.
Disadvantages: Less accurate, vulnerable to data manipulation, does not use underlying holdings.
Holdings-Based Attribution:
Advantages: Uses beginning-of-period holdings, more accurate with shorter evaluation periods.
Disadvantages: Fails to capture transaction impact, potential discrepancies in actual performance.
Transactions-Based Attribution:
Advantages: Most accurate, includes holdings and transactions, accounts for transaction costs.
Disadvantages: Time-consuming, requires complete and reconciled data, complexity in implementation.
Reading 26 - Section 3
Equity Return Attribution:
e. Interpretation of Portfolio Returns Using Attribution Approach:
Return Attribution Overview:
Evaluates the sources of excess return in a portfolio relative to its benchmark.
Informs management and clients about the active decisions made by portfolio managers.
Utilized retrospectively to assess historical investment decisions.
Common Equity Attribution Approaches:
Brinson-Fachler Model:
Focuses on identifying sources of excess return via sector allocation and security selection.
Modification in asset allocation factor provides adjustments based on overall benchmark return.
Allows calculation of allocation and selection effects to explain differences between portfolio and benchmark returns.
Factor-Based Attribution:
Utilizes factors to attribute returns, often considering systematic risk factors like market, size, value, etc.
Geometric vs. Arithmetic Attribution:
Arithmetic Attribution: Explains excess return between portfolio and benchmark for single periods; results are straightforward but may not sum to total excess return over multiple periods.
Geometric Attribution: Divides the arithmetic excess return by the benchmark’s wealth ratio, allowing compounding across periods; avoids the need for adjustments over time.
A Simple Return Attribution Example:
Portfolio return: 5.24%
Benchmark return: 3.24%
Arithmetic excess return: 2.00% (5.24% - 3.24%)
Return Attribution Analysis:
Security Selection: Reflects performance deviation from benchmark due to individual security choices.
Asset Allocation: Represents performance alteration due to weight adjustments in asset categories.
For instance, a positive excess return might stem from superior security selection (250 bps) compared to a negative impact from allocation decisions (50 bps).
Brinson-Hood-Beebower (BHB) Model:
Focuses on sector-level returns and weights to attribute excess returns.
Allocation, selection, and interaction effects are calculated to explain the difference between portfolio and benchmark returns.
Allocation effect: Reflects the impact of portfolio weight deviations from benchmark sectors.
Selection effect: Represents performance alteration due to portfolio returns in sectors relative to benchmark returns.
Interaction effect: Arises from combined allocation and selection decisions.
Brinson-Fachler Model:
Similar to BHB but modifies allocation calculation to compare returns with the overall benchmark.
Aims to rectify problems related to positive or negative market performances in the BHB model.
Reading 26 - Section 4
Fixed-Income Return Attribution Methods
Exposure Decomposition - Duration Based
What It Does: Analyzes the portfolio’s active management relative to the benchmark, typically based on duration, yield curve positioning, or sector bets.
Interpretation: It breaks down the portfolio’s risk exposures by grouping bonds based on characteristics like duration or bond sector. This approach simplifies data and offers straightforward results for reports.
Yield Curve Decomposition - Duration Based
What It Does: Estimates return of securities or sectors using duration and changes in yield to maturity.
Interpretation: Identifies contributions to total return from changes in yield to maturity factors, such as level, slope, curvature, and spread factors. Offers insights into how yield curve views affect returns.
Yield Curve Decomposition - Full Repricing
What It Does: Reprices bonds from zero-coupon curves and factors in various changes.
Interpretation: Provides precise pricing, covers a broad range of instruments, but demands complex operational administration and can be harder to interpret.
Interpreting Fixed-Income Attribution Results
Exposure Decomposition Analysis
Example Inference: Higher duration than the benchmark might indicate an expectation of falling rates. Overweight in corporate sectors might imply an expectation of narrowing credit spreads.
Outcome Inference: Underperformance relative to the benchmark (-0.20%), effects of duration, yield curve bets, sector overweights, and bond selections.
Yield Curve Decomposition Analysis
Example Inference: Overweighting corporate and longer-term bonds contributed positively to excess returns.
Outcome Inference: Contributions from yield, roll, shift, slope, curvature, spread, and specific bond selections impact the total excess return.
Conclusions from Return Attribution
Comparison: Understanding the portfolio’s under/overperformance relative to benchmarks.
Contributions: Assessing the impact of duration, yield curve positioning, sector bets, and bond selections on returns.
Unaccounted: Recognizing the residual, which might indicate inaccuracies in estimating price variations, especially during significant yield shifts.
Reading 26 - Section 5
Understanding Risk Attribution
Purpose of Risk Attribution
Absolute Mandates: Identifies sources of portfolio volatility.
Benchmark-Relative Mandates: Reveals sources of tracking risk compared to benchmarks.
Integration with Return Attribution: Quantifies contributions to both return and risk from active investment decisions.
Considerations in Risk Attribution Approach
Reflecting Investment Decision Processes: Approach aligns with bottom-up, top-down, or factor-based strategies.
Benchmark-Relative Portfolios: Quantifies contribution of active decisions to tracking risk.
Absolute Mandates: Considers exposures to market, size, style factors, and specific risks due to stock selections.
Attribution Models for Different Investment Processes
Bottom-Up Benchmark-Relative Processes: Measures each position’s contribution to tracking risk based on its marginal contribution and active weight.
Top-Down Benchmark-Relative Processes: Identifies total contribution of allocation and selection to tracking risk.
Absolute Bottom-Up Processes: Evaluates risk contributions by calculating the marginal effect of each asset on portfolio volatility.
Role of Risk Attribution Alongside Return Attribution
Complementary Relationship: Explains where risk was introduced into the portfolio and its consequences.
Integration with Return Attribution: Assesses whether allocation decisions that added to excess return also introduced additional risk.
Selecting a Risk Attribution Approach
Alignment with Investment Strategy
Bottom-Up: Focus on individual security selection.
Top-Down: Macro focus followed by sector selection.
Factor-Based: Different exposures to risk factors driving asset returns.
Mandate Type Consideration
Benchmark-Relative: Quantifies active decisions’ impact on tracking risk against benchmarks.
Absolute Mandate: Evaluates risk from market, size, style factors, and specific stock selections.
Integration with Return Attribution
Combined Insight: Shows both return and risk consequences of investment decisions.
Understanding Full Impact: Assesses if allocation decisions contributing to excess return introduced additional risk.
Reading 26 - Section 6
Return Attribution Analysis at Multiple Levels
Asset Owner vs. Investment Manager Attribution
Macro Attribution: Evaluates decisions made at the asset owner level (e.g., fund sponsor) regarding strategic asset allocation and manager selection.
Micro Attribution: Assesses the impact of portfolio managers’ decisions on total fund performance.
Macro Attribution Example: Fund Sponsor Level
Strategic Asset Allocation: Allocation of weights to different asset classes by the fund sponsor.
Tactical Deviations: Decisions delegated to investment managers.
Manager Selection: Evaluates if managers added value relative to their benchmarks.
Evaluation at Fund Sponsor Level
Value Portfolio Manager’s Decisions:
Allocation Effect: Overweighting value equities added to portfolio return.
Selection + Interaction: Manager outperformance contributed positively.
Growth Portfolio Manager’s Decisions:
Allocation Effect: Underweighting growth equities added to portfolio return.
Selection + Interaction: Manager outperformance contributed positively.
Micro Attribution Example: Portfolio Manager Level
Segment Level Analysis: Evaluates impact at specific equity segments (small-cap value, large-cap value, large-cap growth).
Segment-Level Evaluation
Allocation Effects: Underweighting/overweighting segments impacting overall fund performance.
Selection + Interaction: Manager’s performance compared to segment benchmarks.
Conclusions from Segment-Level Analysis
Total Fund Outperformance: Primarily driven by positive security selection.
Value Portfolio Manager’s Decisions: Underweighting small-cap value detracted from performance; underweighting large-cap value contributed positively.
Further Levels of Analysis
Country and Sector Allocations: Assessing decisions within countries or sectors.
Reflecting Decision-Making Process: Attribution aligned with investment strategy used by the manager.
Security-Level Analysis
Individual Security Decisions: Impact of individual securities on portfolio return.
Transaction Activity: Evaluates trading expenses and timing effects.
Example of Security-Level Attribution
Individual Securities Impact:
Allocation: Measures value added from individual security selection.
Selection Effects: Transaction costs and timing impacts on specific securities.
Key Considerations in Return Attribution at Multiple Levels
Ownership vs. Managerial Attribution: Evaluating decisions made at the fund sponsor level versus those made by portfolio managers.
Macro and Micro Attribution: Analyzing decisions at different levels of the investment process to understand their impact on portfolio performance.
Segment, Security, Country, and Sector Levels: Examining performance and decision-making across various segments and levels to comprehensively evaluate attribution.
Reading 26 - Section 7
Asset-Based and Liability-Based Benchmarks
Uses of Liability-Based Benchmarks
Liability Focus: Tracks the cash flows necessary to meet future obligations, such as in defined benefit pension plans.
Progress Tracking: Monitors the fund’s progress towards meeting liabilities or, if fully funded, tracks asset performance relative to liability changes.
Performance Evaluation: Assesses assets’ performance concerning their ability to meet liabilities rather than market benchmarks.
Aligning Investments: Helps in constructing portfolios in line with future obligations and cash flow requirements.
Types of Asset-Based Benchmarks
Absolute (Target) Return Benchmarks:
Specifies a minimum target return for managers to exceed, often a fixed rate or spread above a market index.
Examples include private equity investments targeting a specific annual return.
Broad Market Indexes:
Represents overall asset class performance (e.g., MSCI World Index for global developed market equities).
Widely available, known, and reported in the media.
Style Indexes:
Represents investment styles within asset classes (e.g., Russell 2000 Value and Russell 1000 Growth Indexes).
Captures variations in stock valuation and market capitalization.
Factor-Model-Based Benchmarks:
Constructed to closely mirror the investment decision-making process.
Utilizes factors influencing returns (e.g., industry exposure, financial leverage) in portfolio return regression analysis.
Returns-Based (Sharpe Style Analysis) Benchmarks:
Relates portfolio returns to various style indexes (e.g., small-cap value, large-cap growth) to create a benchmark mirroring the portfolio’s returns.
Views investment style as a continuum rather than discrete styles.
Manager Universes (Peer Groups):
Broad groups of managers with similar investment disciplines used for comparison purposes.
Not a benchmark but aids in comparing performance among managers with similar strategies.
Custom Security-Based (Strategy) Benchmarks:
Customized to reflect an investment manager’s specific strategy.
Constructed through discussions and analysis of past exposures consistent with the manager’s investment process.
Costly to maintain but aligns closely with the manager’s unique strategy.
Key Points
Liability-Based Focus: Tracks cash flows for future obligations in pension plans, ensuring assets align with future needs.
Asset-Based Variety: Diverse asset-based benchmarks cater to different investment styles and strategies.
Customization vs. Standardization: Custom benchmarks align precisely but come at higher costs, while standard benchmarks offer broader comparability but may not fully represent specific strategies.
Performance Measurement: Asset-based benchmarks vary from reflecting market performance to mirroring investment processes, aiding in performance evaluation and comparisons among managers.
Reading 26 - Section 8
Benchmark Properties, Evaluating Benchmark Quality, and Choosing the Correct Benchmark Tests of Benchmark Quality
Unambiguousness:
Securities and their weights in the benchmark should be clearly identifiable.
Example: Identifying whether specific stocks like Nestlé are part of a global equity benchmark.
Investability:
Benchmark should be replicable and holdable to earn its return (gross of expenses).
Sponsor should have the option to switch assets from active management to the benchmark.
Measurability:
Benchmark’s return must be measurable frequently and in a timely manner.
Appropriateness:
Consistency with the manager’s investment style or area of expertise.
Reflective of Current Opinions:
Managers should be familiar with benchmark securities and their factor exposures.
Pre-specification:
Constructed before the evaluation period to ensure objectivity in assessment.
Accountability:
The manager accepts ownership of the benchmark and its securities, aligning with their investment process.
Impact of Benchmark Misspecification on Attribution and Appraisal Analysis
Quality Evaluation Tests: These examine correlations between portfolio returns, market index returns, style returns, and active management returns.
Biases Identification: Systematic biases between active management and style returns can be identified through correlations.
Correct Benchmark Choice Importance: Incorrect benchmarks distort performance evaluation.
Example Impact: Using the wrong benchmark led to incorrect attribution analysis, where the manager’s underperformance against the wrong benchmark masked their actual outperformance against their normal portfolio.
Peer Group Benchmark Issues: Selection of inappropriate peers can induce herding behavior around median returns, affecting investment decisions.
Ethical Consideration: Managers changing benchmarks to improve measured excess returns can be inappropriate and unethical.
Misspecified Benchmark Impact: Leads to the mismeasurement of value added by portfolio managers, creating style bias and affecting performance appraisal accuracy.
Decomposition Significance: Helps understand the influence of a misaligned benchmark on performance assessment.
Choosing the Correct Benchmark
Mismatch Impact: Mismatch between the broad market benchmark and manager’s “normal” portfolio leads to misfit active return.
Example Impact: Using a broad market index may miss the manager’s style, creating style bias and affecting performance appraisal accuracy.
Understanding True Active Return: The manager’s actual outperformance against their normal portfolio might be obscured when evaluated against an incorrect benchmark.
Reading 26 - Section 9
Benchmarking Alternative Investments: Challenges and Considerations
Problems in Benchmarking Alternative Investments
- Lack of High-Quality, Investible Market Indexes:
Challenges arise due to inadequate indexes that are investible and of high quality.
Limited liquidity and unavailable market values for underlying assets pose challenges.
2. Use of Leverage and Limited Liquidity:
Leverage in many strategies and the complexity of alternative assets add difficulty.
Limited liquidity and lack of readily available market values complicate benchmarking.
3. Time-Weighted Rates and Internal Rates of Return:
Use of internal rates of return rather than time-weighted rates further complicates evaluation.
Specific Challenges in Benchmarking Different Alternative Asset Classes
Hedge Fund Investments (9.1)
Diversity and Complexity: Hedge funds cover a wide range of strategies, making it hard to create a standard benchmark.
Leverage and Complexity: Use of leverage, derivatives, and short positions complicates benchmark selection.
Transparency and Monitoring: Lack of transparency, difficulty in monitoring, and illiquidity hinder benchmark use.
Unsuitability of Broad Market Indexes: Unsuitability of broad market indexes due to weak correlations with hedge fund returns.
Real Estate Investments (9.2)
Subset Representation: Real estate benchmarks represent only subsets of the asset class, lacking full representation.
Correlation with Largest Contributors: Index performance highly correlated with the largest fund contributors.
Biased Reporting: Manager-reported performance data could be biased, affecting benchmark accuracy.
Valuation Challenges: Infrequent valuations, appraisal-based valuations, and limited transaction data affect accuracy.
Private Equity (9.3)
IRR Calculation vs. Peer Group Comparison: Different valuation methodologies affect IRR calculations and comparisons.
Limitations in Comparisons: Differences in valuation methodologies and timing influence returns’ comparability.
Public Market Equivalent (PME): Methodologies like PME allow comparison with public equity indexes, but choosing the appropriate PME is crucial.
Commodity Investments (9.4)
Futures-Based Indexes: Use of futures-based indexes makes representation of actual commodity assets challenging.
Diverse Indexes: Commodity indexes vary widely in composition and weighting, making uniform benchmarks difficult.
Derivative Use and Exposure Weighting: Varying degrees of leverage and discretionary exposure weights complicate benchmarking.
Managed Derivatives (9.5)
Specific Strategy Benchmarks: Derivative benchmarks are specific to particular investment strategies.
Peer Group-Based Benchmarks: Use of peer group-based benchmarks like BarclayHedge faces limitations like survivorship bias.
Distressed Securities (9.6)
Valuation and Liquidity Challenges: Illiquidity and difficulties in valuing distressed securities complicate benchmarking.
Use of Multiple Strategy Indexes: Using indexes from multiple strategies raises challenges in suitability for specific approaches.
Valuation Issues: Random interval valuations might not address the underlying valuation challenges adequately.
Reading 26 - Section 10
Performance Appraisal: Risk-Based Measures
Objective of Investment Performance Appraisal
Investment performance appraisal gauges investment skill by assessing how effectively money is invested relative to the risks undertaken. It primarily focuses on ranking investment managers within similar investment disciplines. This assessment seeks to differentiate between skill and luck in investment outcomes.
Distinguishing Skill from Luck (10.1)
Paradox of Skill: As knowledge and skills increase, differences between the worst and best performers narrow, leading to potential attributions to luck.
Challenges in Evaluation: Evaluating skill based on past returns is challenging due to the randomness of financial market returns and the impact of news, investor emotions, and liquidity-driven trading.
Limited Insights from Historical Performance: Historical performance represents only one outcome among many potential scenarios, making it hard to discern true skill from luck.
Appraisal Measures (10.2)
Several returns-based measures exist to assess active management:
Sharpe Ratio: Measures excess return per unit of return volatility but assumes equal investor indifference between upside and downside volatility.
Treynor Ratio: Evaluates excess return per unit of systematic risk, helpful when assessing portfolios in a well-diversified context.
Information Ratio: Assesses performance relative to the benchmark scaled by risk, assuming a well-matched benchmark.
Appraisal Ratio: Measures annualized alpha divided by annualized residual risk, indicating the reward of active management relative to the risk.
Sortino Ratio: Modifies the Sharpe ratio by penalizing only returns lower than a specified target return (MAR - minimum acceptable return), focusing on return per unit of downside risk.
Limitations of Appraisal Measures
Volatility Assumptions: Sharpe and Sortino ratios assume normal return distributions, impacting their ability to differentiate between asymmetrically distributed returns.
Investor-Specific Nature: Sortino ratio’s reliance on a minimum acceptable return (MAR) makes cross-sectional comparisons challenging as the MAR varies based on investors’ preferences.
Historical Data Reliance: Assessing skill based solely on historical returns is prone to errors due to the randomness of market returns and the impact of various factors beyond manager control.
While these measures provide valuable insights into risk-adjusted performance, their reliance on historical data and assumptions about return distributions poses challenges in accurately determining investment skill, necessitating a holistic approach that considers qualitative factors alongside quantitative metrics.
Reading 26 - Section 11
Performance Appraisal: Capture Ratios and Drawdowns
Objective of Capture Ratios and Drawdowns
Capture ratios and drawdowns are performance measures in investment evaluation. They assist in assessing a manager’s participation in up and down markets and understanding the impact of drawdowns on performance and suitability concerning an investor’s time horizon and risk tolerance.
Capture Ratios (11.1)
Upside and Downside Capture: Measure manager performance relative to the benchmark in positive and negative market conditions, respectively.
Calculations: Upside Capture (UC) and Downside Capture (DC) ratios are calculated using manager and benchmark returns.
Capture Ratio (CR): CR = UC/DC. A ratio >1 indicates a convex return profile (asymmetrically positive), while <1 indicates a concave return profile (asymmetrically negative).
Interpretation of Capture Ratios
Illustration: Higher UC (>100%) in up markets and lower DC (<100%) in down markets suggest outperformance relative to the benchmark.
Graphical Representation: Graphs showing the convex and concave return profiles provide visual insights into how returns change concerning benchmark returns.
Drawdown (11.2)
Definition: Drawdown represents the cumulative peak-to-trough loss during a continuous period.
Drawdown Duration: Total time from start to recovery to zero cumulative return, segmented into drawdown and recovery phases.
Example and Implications of Drawdown
Example Analysis: Illustration of drawdown using the S&P 500 Index shows periods of negative returns, their depths, and the subsequent recovery phases.
Investment Implications: Larger drawdowns might be unsuitable for investors with shorter time horizons as recovery might take longer, impacting risk-adjusted returns.
Effect on Performance and Manager Selection
Asymmetric Returns: Understanding the relationship between capture ratios, drawdowns, and return profiles is crucial for evaluating manager performance.
Investment Strategies: Different strategies like low-beta or positive/negative asymmetry profiles exhibit varying performance concerning drawdowns and capture ratios.
Manager Robustness: Responses to drawdowns reveal the robustness of investment processes and risk management strategies, aiding in evaluating manager consistency.
Limitations of Measures
Investment Horizon and Risk Capacity: Drawdowns have different impacts on investors with varying time horizons and risk capacities.
Investor Behavior: Investor reactions to drawdowns might influence manager selection despite the manager’s consistent discipline during market downturns.
Strategy Evaluation: It’s crucial to discern if the observed asymmetry in returns is inherent to the strategy or reliant on manager skill to avoid misinterpretation.
Understanding the interplay between capture ratios, drawdowns, and investment strategies is crucial for accurate performance appraisal. It allows for a comprehensive evaluation of manager performance concerning risk tolerance, time horizon, and overall suitability for investor needs.
Reading 26 - Section 12
Evaluation of Investment Manager Skill
Manager A’s Performance Assessment
The evaluation of Manager A’s skill against the MSCI Pacific Index involves various tools and analyses to determine if the outperformance was due to skill or luck.
Performance Attribution Analysis (12.1)
Attribution Analysis: The breakdown of outperformance from country allocation and stock selection decisions.
Outcome: Manager A’s overweight in Australia and underweight in Japan led to performance losses due to underperformance and outperformance of these markets, respectively. However, stock selection in Japan and Australia contributed positively, especially in Japanese stocks.
Interpretation from Attribution Analysis
Strengths and Weaknesses: Manager A excels in stock selection but struggles in asset allocation decisions.
Conclusion: The outperformance was influenced more by stock picking skills than market allocation decisions over the five-year period.
Appraisal Measures (12.2)
Risk and Return Analysis: Comparison of Manager A’s performance against other managers (B and C) using various measures.
Sharpe and Treynor Ratios: Manager A’s Sharpe ratio indicates more risk compared to the benchmark and Manager B but lower risk than Manager C. The Treynor ratio signifies higher returns relative to systematic risk for Manager A.
Sortino Ratio: Indicates the ability to generate higher returns relative to downside risk, reflecting a level of proficiency in risk management.
Assessment of Skill (12.3)
Conclusion: Manager A exhibits stock selection skills, generating excess returns without significant excess risk compared to the benchmark and similar managers.
Limitations: The analysis doesn’t address country allocation conclusions and relies on a limited sample period, requiring further study and additional analyses for stronger conclusions.
Considerations: Future evaluations should include qualitative assessments, risk attribution, and a longer track record for increased confidence in conclusions.
Limitations and Conclusion
Limitations Acknowledged: The analysis is limited and doesn’t guarantee future outcomes. Additional studies and qualitative assessments are necessary for a more comprehensive evaluation.
Conclusion: Manager A demonstrates a certain level of skill in stock selection, but further analysis and a more extended track record are needed for a more robust assessment.
Reading 27 - Section 1
Introduction to Private Company Valuation
Comparison: Public vs. Private Company Valuation (a)
Public Companies: Listed on public markets, enabling the valuation through readily available market prices.
Private Companies: Shares not publicly traded, requiring specialized valuation methods due to limited market information.
Uses and Applications of Private Business Valuation (b)
Uses of Valuation:
Transactions: Key area encompassing financing, IPOs, acquisitions, bankruptcy, and share-based compensations.
Compliance: Focuses on financial and tax reporting, especially concerning goodwill impairment and tax obligations.
Litigation: Legal proceedings often requiring valuations related to damages, shareholder disputes, and divorce.
Key Differences between Private and Public Companies
Company-Specific Factors:
Life Cycle Stage: Private companies vary widely from early-stage ventures to stable, successful entities.
Size: Private companies, on average, tend to be smaller, influencing risk levels and growth prospects.
Management and Shareholder Overlap: Private companies often have top management with a significant ownership stake, impacting decision-making.
Quality of Information: Private companies usually have limited financial disclosure, increasing uncertainty and risk for investors.
Stock-Specific Factors:
Liquidity: Shares of private companies are less liquid due to fewer shareholders and limited market access.
Control Concentration: Control of private companies often rests with a small group, affecting decision-making and potential conflicts of interest.
Reasons for Performing Valuations
Transactions: Financing rounds, IPOs, acquisitions, bankruptcy, and share-based compensation.
Compliance: Financial and tax reporting, including goodwill impairment testing and tax obligations.
Litigation: Legal proceedings involving damages, disputes, and divorce settlements.
Specialized Knowledge and Focus
Transaction Focus: Involves investment bankers.
Compliance Valuations: Require expertise in accounting or tax regulations.
Litigation-Related Valuations: Demand effective presentations in a legal setting.
Conclusion:
Private company valuation involves unique challenges due to limited information and diverse company structures. Understanding the nuances between public and private entities is crucial in applying appropriate valuation methods across various contexts, from transactions to compliance and litigation. Specialized knowledge in these areas is fundamental for accurate and contextually relevant valuations.
Reading 27 - Section 2
Private Company Valuation Approaches
Valuation Approaches for Private Companies
Income Approach: Values assets based on the present discounted value of expected income. Corresponds to discounted cash flow models used by public equity analysts.
Market Approach: Values assets based on pricing multiples from similar asset sales, either share price or total company value.
Asset-Based Approach: Values private companies based on underlying assets minus related liabilities.
Factors Influencing Approach Selection
Nature and Stage of Operations: Varying valuation methods based on the company’s development stage, growth prospects, and financial stability.
Size Consideration: Public companies’ multiples may not be suitable for small, mature private firms with limited growth prospects.
Considerations in Valuation
Operating and Non-operating Assets: Valuation includes both, with non-operating assets, like excess cash, impacting the overall value.
Earnings Normalization and Cash Flow Estimation Issues
Earnings Normalization for Private Companies
Adjusted Earnings: Adapting reported earnings to reflect the true potential under new ownership.
Challenges: Adjustments often needed due to discretionary expenses, controlling shareholder actions, and discrepancies in compensation.
Areas for Adjustment: Personal expenses, compensation levels, personal-use assets, and real estate usage need scrutiny and potential adjustment.
Cash Flow Estimation Challenges
Free Cash Flow (FCF): Essential in valuation, particularly FCFF and FCFE for firm and equity valuation, respectively.
Uncertainties: Future cash flow uncertainty due to varying scenarios like IPO, acquisition, or continued private operation poses valuation challenges.
Approaches: Probability-weighted average scenarios or conventional single discount rate models used for valuing various future scenarios.
Managerial Involvement: Private company managers possess more information and biases, impacting cash flow forecasts used in valuation.
Conclusion:
Valuation of private companies involves assessing earnings normalization and cash flow estimation. Adjusting reported earnings for accuracy and estimating future cash flows under different scenarios pose challenges. Managerial involvement, uncertainties, and biases necessitate robust valuation approaches for accurate estimations. The process for estimating cash flows remains similar for both public and private companies, though challenges may vary due to the nature of private company operations.
Reading 27 - Section 3
Income Approach Methods and Required Rate of Return
Income Approach in Valuation
Conceptual Basis: Derives value from future income and cash flow expectations, converting them into present value.
Three Main Forms:
Free Cash Flow Method: Discounts future cash flows using an appropriate rate reflective of associated risks.
Capitalized Cash Flow Method: Uses a single estimate of economic benefits divided by a capitalization rate.
Residual Income Method: Estimating intangible asset value by capitalizing future earnings exceeding return requirements.
Estimating Required Rate of Return
Challenges in Estimation:
Size Premiums: Private company valuations often utilize size premiums, more common in private than public company valuations. The relevance of size premiums from public companies might not align well with smaller private companies.
CAPM Suitability: Questioning the suitability of the CAPM for small private company valuations due to lack of comparability with public companies.
Expanded CAPM: Adapting CAPM by including premiums for small size and company-specific risk. Subjective estimation of company-specific risk remains a challenge.
Build-up Approach: A method for return estimation based on adding premia to the risk-free rate. It includes factors like size and company risk but doesn’t use beta for equity risk premium.
Debt Availability and Cost: Estimating a private company’s debt capacity and cost is challenging. Private firms might have limited access to debt financing, increasing reliance on equity and subsequently increasing WACC.
Discount Rates in Acquisitions: Buyer’s cost of capital might differ in acquisition contexts, leading to potential value transfer from buyer to seller.
Projection Risk Adjustment: Less information on private company operations introduces more uncertainty in projections, potentially requiring a higher rate of return. Managerial inexperience in forecasting could impact projections.
Comparison of Models for Required Rate of Return
CAPM: Standard model for determining an asset’s expected return based on risk and market return.
Expanded CAPM: Augmented version adding premiums for small size and company-specific risk.
Build-up Approach: Comprises various premia added to the risk-free rate, excluding beta for equity risk premium.
Estimating the required rate of return for private company equity involves complexities due to size premiums, suitability of models like CAPM, challenges in debt estimation, and projection risk, among other factors. The valuation process necessitates a nuanced approach considering the unique nature of private companies and their financial dynamics.
Reading 27 - Section 4
Free Cash Flow, Capitalized Cash Flow, and Excess Earnings Methods
Approaches to Private Company Valuation
Income Approach: Based on future income expectations, includes:
Free Cash Flow (FCF) Method: Projects future cash flows discounted to present value.
Capitalized Cash Flow Method (CCM): Valuates using a stable growth single-stage model.
Excess Earnings Method (EEM): Estimates intangible asset value from residual earnings after required returns to tangible assets.
Factors Relevant to Approach Selection
Free Cash Flow Method: Preferred when discrete cash flow forecasts are available till stabilization.
Capitalized Cash Flow Method: Suitable for companies with stable future operations or limited projections.
Excess Earnings Method: Used for valuing intangible assets or smaller businesses when market approach methods are infeasible.
Valuation using Methods
Free Cash Flow (FCF) Method:
Involves projecting cash flows over a defined period and a terminal value estimation.
Capitalized Cash Flow Method (CCM):
Calculates value by dividing Free Cash Flow to the Firm (FCFF) by the difference between WACC and sustainable growth rate (gf).
Direct equity valuation substitutes FCFF with Free Cash Flow to Equity (FCFE) and the equity return requirement for WACC.
Excess Earnings Method (EEM):
Estimates intangible asset value after deducting required returns for working capital and fixed assets.
Calculates residual income, capitalizes it using a growing perpetuity formula for intangibles’ value.
Sums working capital, fixed assets, and intangibles to obtain the business value.
Challenges and Usage of EEM
Application: EEM typically used for valuing intangible assets or very small businesses when other approaches are impractical.
Estimation Challenges: Determining return requirements for various assets (working capital, fixed, intangible) involves significant judgment.
Residual Income in Financial Reporting: Residual income plays a crucial role in valuing intangible assets for financial reporting and purchase price allocation pursuant to accounting standards like IFRS 3 or ASC 805.
The EEM offers a unique perspective in valuing intangible assets or smaller businesses, necessitating nuanced estimation of return requirements for different asset types. Its application extends to financial reporting, particularly in valuing intangible assets and goodwill impairment testing, serving as a vital concept in such assessments.