Topic 3. Overview of company analysis

Company analysis is a detailed examination of a specific business entity to assess its financial health, operational performance, competitive position and overall potential as an investment

Elements that should be covered in thorough company analysis

Thorough company analysis involves a comprehensive examination of various aspects of a business to understand its current state and SWOT

Here are the key elements that should be covered in a thorough company analysis:

• Forecasting cost of goods sold (COGS)

The cost of goods sold (COGS) includes raw materials, direct labor and overhead costs used in producing the goods. COGS is directly related to sales and forecasted as a percentage of sales. Historical data on a company’s COGS as a percentage of sales provides a starting point for estimates.

Since COGS is a relatively high cost, a small error in this item can significantly impact the forecasted operating profit.

• Forecasting Selling, general, and administrative (SG&A)

Selling, general and administrative (SGA) expenses have a less direct relationship with a company’s revenue. Certain expenses within SG&A are more variable than others, e.g., selling and distribution expenses have a significant variable component and can be estimated as a percentage of sales.

To benchmark a company against its competitors, it is imperative to analyze the historical relationship between its sales and operating expenses. This can be used to compare a company’s efficiency and margin potential compared to its peers.

Comparing estimated values and market prices; information efficiency and efficient market hypothesis
Comparing Estimated Values and Market Prices:

1. Estimated Values:

Estimated values are assessments made by analysts or investors about the intrinsic worth of an asset or a security. They are calculated using various methods such as discounted cash flow analysis, comparative market analysis, or other valuation models.

1. Market Prices:

Market prices, on the other hand, are the actual prices at which assets or securities are traded in the market. They are determined by the interactions of buyers and sellers, influenced by factors like supply, demand, investor sentiment, and market conditions.

1. Factors Influencing Discrepancies between market prices and estimated values
   • Information Availability
   • Emotions and Sentiments
   • Market Dynamics
   • Investment Strategies

Information Efficiency and Efficient Market Hypothesis (EMH)

1. Information Efficiency:
   • Information efficiency refers to how quickly and accurately information is reflected in asset prices. In an informationally efficient market, prices fully reflect all available information.
   • There are three forms of information efficiency:
     • Weak Form Efficiency: Assumes that all past trading information is already reflected in stock prices.
     • Semi-Strong Form Efficiency: Implies that all publicly available information, including news and reports, is already reflected in stock prices.
     • Strong Form Efficiency: Suggests that all information, both public and private, is fully reflected in stock prices.
2. Efficient Market Hypothesis (EMH):

The Efficient Market Hypothesis is a theory that states that financial markets are informationally efficient. This means that at any given time, asset prices reflect all available information.

1. • EMH implications for investors:
     • It suggests that it is difficult to consistently outperform the market through stock selection or market timing.

Approaches to balance sheet modelling
Balanced sheet modeling involves creating a financial model that represents a company’s balance sheet, which is a snapshot of its financial position at a specific point in time.

1. Historical Approach:

1. • Method: This approach involves using historical data from the company’s financial statements to create the balance sheet model.
   • Advantages: It provides a baseline for understanding how the company’s financial position has evolved over time.
   • Limitations: It may not capture future changes or unexpected events that can impact the balance sheet.
2. Forecasted Approach:
   • Method: This approach involves projecting future financials based on assumptions and expectations
   • Advantages: It allows for forward-looking analysis and can help in scenario planning.
   • Limitations: The accuracy of forecasts heavily relies on the quality of assumptions made.
3. Stress Testing and Sensitivity Analysis:
   • Method: This approach involves subjecting the balance sheet to various stress scenarios or changes in key assumptions to understand how the financial position may be impacted.
   • Advantages: It helps identify vulnerabilities and assesses the company’s resilience to adverse conditions.
   • Limitations: It may not capture all possible scenarios, and the impact of stress scenarios may not always be straightforward to predict.
4. Scenario Analysis:
   • Method: This approach involves constructing multiple balance sheet scenarios based on different sets of assumptions.
   • Advantages: It provides a more comprehensive view of potential future states and helps in decision-making under uncertainty.
   • Limitations: It can be time-consuming and complex, especially when dealing with a large number of variables.
5. Monte Carlo Simulation:
   • Method: This involves running thousands or millions of simulations using random variables within specified ranges to generate a range of potential balance sheet outcomes.
   • Advantages: It accounts for uncertainty and variability in a more sophisticated way than traditional scenario analysis.
   • Limitations: It can be computationally intensive and requires a good understanding of statistical modeling.
6. Econometric Modeling:
   • Method: This involves using statistical methods to model the relationship between different economic variables and the company’s balance sheet items
   • Advantages: It provides a structured way to incorporate macroeconomic factors into balance sheet projections.
   • Limitations: It relies on the accuracy of economic forecasts and assumes that historical relationships will hold in the future.
7. Machine Learning and Artificial Intelligence:
   • Method: Advanced techniques like machine learning can be used to build predictive models based on historical data.
   • Advantages: ML models can capture non-linear relationships and patterns that may be difficult to identify through traditional methods.
   • Limitations: They may require a significant amount of data and can be complex to implement and interpret.

Understanding different types of companies and stocks is crucial for investors to make informed decisions. Here are definitions and characteristics of various types:

1. Growth Companies and Growth Stocks:

Growth Companies These are companies that are expected to have higher-than-average revenue and earnings growth compared to their industry or the overall market.

Characteristics:

1. • They may not prioritize paying dividends, preferring to reinvest profits for growth.
   • Often operate in industries with high potential for expansion or emerging technologies.
   • Typically have high price-to-earnings (P/E) ratios, reflecting investor optimism about future earnings.
2. Defensive Companies and Defensive Stocks:

Defensive Companies: These are companies that tend to be less sensitive to economic cycles and are considered more stable.

Characteristics:

• They often operate in industries like healthcare, utilities, or consumer staples (e.g., food, household goods) which tend to have stable demand.
• May offer consistent dividends as they generate steady cash flows.
• They tend to have lower beta values, indicating lower sensitivity to market fluctuations.

1. Cyclical Companies and Cyclical Stocks:

Cyclical Companies: These companies are highly sensitive to economic cycles. Their performance tends to correlate with the overall health of the economy. They thrive during periods of economic expansion but struggle during downturns.

Characteristics:

• Often belong to industries like automotive, construction, or luxury goods, which are highly dependent on consumer spending and economic activity.
• Earnings and revenue may fluctuate significantly with economic conditions.
• They may have higher beta values, indicating higher sensitivity to market movements.

1. Speculative Companies and Speculative Stocks:

Speculative Companies: These are companies that have high uncertainty and risk associated with their business models, products, or technologies.

Characteristics:

• They may be pre-revenue or have limited financial history, making them riskier investments.
• Often involved in research, development, or early-stage commercialization of new technologies.
• May have high volatility and are susceptible to large price swings.

The elements of a competitive analysis for a company.
A competitive analysis should examine your competitors’ features, market share, pricing, marketing, differentiators, strengths, weaknesses, geography, culture and customer reviews.

A competitive analysis typically includes the following elements:

• Identifying Competitors
• Analyzing Competitor’s Products/Services
• Assessing Competitor’s Market Positioning
• Understanding Competitor’s Pricing Strategies
• Analyzing Competitor’s Marketing and Sales Strategies
• Assessing Competitor’s Financial Performance
• Identifying Opportunities and Threats

Contrast top-down and bottom-up approaches to economic forecasting.
Top-down usually encompasses a vast universe of macro variables while bottom-up is more narrowly focused.

The bottom-up analysis takes a completely different approach. Generally, it focuses its analysis on specific characteristics and micro attributes of an individual stock.

The importance of quality of earnings analysis

Quality of earnings analysis is a critical aspect of financial evaluation for investors, analysts, and stakeholders. It provides insights into the sustainability, reliability and transparency of a company’s reported earnings.

Quality earnings analysis helps in;

• Exposing accounting issues.
• Expediting the transaction process
• Controlling processes
• Enhancing credibility.
• Avoid future price renegotiations

 

Quality of earnings indicators and risk factors

Quality of Earnings Indicators (QEI) are financial metrics that are used to assess the underlying profitability and sustainability of a company’s earnings.

Quality of Earnings Indicators

They include;

• Gross Margin: This measures the proportion of revenue that a company retains after accounting for the cost of goods sold
• Operating Margin: This measures the proportion of revenue that a company retains after accounting for all operating expenses.
• Net Margin: This measures the proportion of revenue that a company retains after accounting for all expenses, including taxes.
• Return on Equity (ROE): This measures the amount of net income that a company generates in relation to its shareholder equity.
• Free Cash Flow: This measures the amount of cash that a company generates after accounting for capital expenditures.

Risk Factors include;

• Economic risks
• Competitive risks
• Regulatory risks
• Financial risks
• Operational risks