The CFA Level I exam consists of 180 multiple-choice questions administered in two 135-minute sessions, one in the morning and one in the afternoon.

 

There is an optional break between sessions. 

 

Session 1 (2 hours, 15 minutes): 90 multiple-choice questions on the following topics: ethics & professional standards, quantitative methods, economics, and financial statement analysis.

 

Second session (2 hours, 15 minutes): 90 multiple choice questions on the following topics: corporate issuers, equity, fixed income, derivatives, alternative investments and portfolio management.

 

For more information: 

 https://www.cfainstitute.org/en/programs/cfa/exam/level-i

The reading delves into the fundamental concept of the time value of money, which forms the basis of investment mathematics. It covers essential ideas applicable to finance, such as the interest rate (also known as the discount rate or opportunity cost), future value, present value, annuities, and cash flow analysis.

The interest rate consists of the required rate of return and additional premiums compensating for risk factors. Future value is calculated by multiplying the present value by the future value factor. 

Besides, interest rate facilitate the comparison of currency amounts across different time periods. 

The reading also explores the periodic rate, effective annual rate, two types of annuities (annuity due and ordinary annuity), and techniques for handling annuities using annuity factors. 

The present value is determined using the present value factor. Additionally, perpetuities and the cash flow additivity principle are discussed. The reading emphasizes the ability to solve time value of money problems by determining unknown variables based on given information.

The reading introduces a range of tools and techniques that are utilized to organize, visualize, and describe data in order to transform raw information into valuable insights for investmentanalysis.

Data is classified into two main types: numerical data, which represents quantifiable quantities, and categorical data, which describes qualities or characteristics.

Numerical data can further be divided into continuous or discrete, while categorical data can be either nominal or ordinal.

Additionally, data can be classified based on their collection method as cross-sectional, timeseries, or panel, and based on their organization as structured or unstructured.

The reading explores various methods such as frequency distributions, contingency tables, and visualization techniques like histograms, bar charts, scatter plots, and heat maps. It also delves into measures of central tendency, dispersion, skewness, kurtosis, and correlation coefficients, explaining their relevanceand applications within the context of investment analysis.

In this reading, fundamental principles and tools of probability are discussed, focusing on their application in investment scenarios. The reading covers the definitions and characteristics of probability, random variables, events, as well as mutually exclusive and exhaustive events. It explores different types of probabilities, including empirical, subjective, and a priori probabilities, and also delves into odds associated with events.

 

The concepts of conditional and unconditional probabilities, as well as joint and conditional probabilities, are introduced, along with guidelines for calculating probabilities using addition and multiplication rules. The reading investigates the notions of event independence and dependence, and presents the total probability rule.

 

Measures such as expected value, variance, standard deviation, and covariance are explained as important tools for analyzing probability distributions, including their application in calculating portfolio variance and joint probability.

 

Additionally, the reading explores the concept of correlation, discusses Bayes' formula for updating probabilities, and touches upon the multiplication rule of counting. It concludes with an overview of formulas for permutations and combinations.

In this reading, the focus is on the probability distributions commonly used in investment analysis and Monte Carlo simulation. It covers the fundamentals of discrete and continuous random variables, including their probability functions and cumulative distribution functions.

 

The discussed distributions encompass the uniform, binomial, normal, multivariate normal, and lognormal distributions. Additionally, the reading introduces concepts such as shortfall risk and Roy's safety-first criterion. It delves into the application of continuous and discrete compounding and explores statistical distributions like the t-distribution, chi-square distribution, and F-distribution.

 

Monte Carlo simulation is presented as a technique for modeling complex financial systems and generating random samples from probability distributions. The reading concludes by explaining the inverse transformation method, which enables the production of random observations from any distribution.

The main focus of this reading is on the concepts and techniques of sampling and estimation in financial analysis. It stresses the significance of using impartial and random samples to ensure reliable conclusions. Various sampling methods are explored, including simple random sampling, stratified random sampling, convenience sampling, and judgmental sampling.

The reading explains the central limit theorem, which states that when dealing with large sample sizes, the sampling distribution of the sample mean closely follows a normal distribution. It introduces confidence intervals as a means of estimating population parameters with a specified level of confidence.

Furthermore, the reading delves into the characteristics of estimators, such as unbiasedness, efficiency, and consistency. It elucidates both point estimates and interval estimates, with interval estimates offering a range of values that indicate a specific probability level.

Confidence intervals for population means are derived for cases where the population variances are known or unknown. This is accomplished using either the standard normal distribution or the t-distribution. Additionally, the reading mentions the utilization of bootstrap and jackknife methods for statistical inference in situations where analytical formulas are not available.

The reading also sheds light on various biases that can impact data analysis, including data snooping bias, sample selection bias, survivorship bias, self-selection bias, implicit selection bias, backfill bias, look-ahead bias, and time-period bias.

Overall, the reading underscores the importance of employing appropriate sampling techniques, unbiased estimation methods, and being mindful of potential biases when conducting financial data analysis.

This reading delves into the principles and techniques of statistical inference and hypothesis testing. It encompasses the following key aspects:

The reading introduces the concept of hypotheses as statements about one or more populations and outlines the steps involved in hypothesis testing.
It defines two essential hypotheses: the null hypothesis, subject to testing, and the alternative hypothesis, which is accepted if the null hypothesis is rejected.

The reading explores three approaches to formulating hypotheses: a two-sided alternative, a one-sided alternative (right side), and a one-sided alternative (left side).

It explains the test statistic, a computed value used to determine whether to reject or retain the null hypothesis.

The reading sheds light on two potential errors in making a statistical decision: Type I error, which involves rejecting a true null hypothesis, and Type II error, which involves failing to reject afalse null hypothesis.

The concepts of the significance level of a test and the confidence level are introduced.

The reading elucidates the power of a test and the notion of a decision rule.

It demonstrates that the (1 − α) confidence interval denotes the range of values in which the null hypothesis is not rejected.

The p-value is defined as the minimum significance level at which the null hypothesis can be rejected.
Various test statistics and distributional assumptions are examined for distinct types of hypothesis tests, such as means, differences between means, variances, and correlations.

The reading highlights the differentiation between parametric and nonparametric tests, emphasizing that nonparametric tests are suitable when data fail to meet distributional assumptions or when thehypothesis does not concern a parameter.

Specific test statistics and degrees of freedom are provided for correlation tests and tests for independence of categorical variables.

In conclusion, the reading encompasses the fundamental concepts and methodologies employed in statistical inference and hypothesis testing. It offers guidance on formulating hypotheses, selectingappropriate test statistics, interpreting outcomes, and comprehending the implications of various test types.

The reading provides an introduction to linear regression, covering its key components and concepts. It explains that linear regression involves a dependent variable and an independentvariable,andtheregression model is represented by an equation with coefficients representing the intercept and slope.

The assumptions of linearity, homoskedasticity, independence, and normality are discussed.The estimated parameters minimize the sum of squared errors, and the coefficient of determination (R2)measuresthe proportion of variation explained by the independent variable.

Hypothesis testing, using F-tests and t-tests, is used to assess the significance of regression coefficients.

Indicator variables can be included in the model, and prediction intervals can be calculated.

Predictions for the dependent variable are made using the estimated model, and the standard error of the forecast is considered.

Nonlinear relationships can be transformed for linear regression analysis.

Overall, the reading provides to CFA level 1 candidates a comprehensive overview of linear regression and its applications.

The study session commences with an introduction to the fundamental principles of demand and supply analysis, focusing on individual consumers and firms. Additionally, it addresses the different market structures, such as perfect competition, oligopoly, and monopoly, within which firms operate. 

 

Subsequently, the session delves into essential macroeconomic concepts and principles, encompassing the measurement of aggregate output and income, analysis of aggregate demand and supply, and examination of factors contributing to economic growth. Finally, the session concludes by exploring the business cycle and its impact on economic activity.

The reading extensively covers a range of concepts in demand and supply analysis, specifically focusing on their application in determining a firm's breakeven and shutdown points. It delves into demand-related notions such as own-price elasticity, cross-price elasticity, and income elasticity. 

Additionally, it explores supply-related ideas including total, average, and marginal product of labor, as well as total, variable, and marginal cost of labor. The reading also provides insights into total and marginal revenue and their significance in the calculation of breakeven and shutdown points. Moreover, it touches upon key principles such as the law of demand, Giffen goods, Veblen goods, and the law of diminishing returns. It further elucidates various aspects such as production costs, short-run total cost, short-run marginal cost, average variable cost, and average total cost. 

Furthermore, the reading examines revenue, marginal revenue, and economic profit. It culminates with an exploration of economies of scale, diseconomies of scale, and the determination of the minimum efficient scale for a firm.

The reading extensively covers a range of concepts in demand and supply analysis, specifically focusing on their application in determining a firm's breakeven and shutdown points. 

It delves into demand-related notions such as own-price elasticity, cross-price elasticity, and income elasticity. Additionally, it explores supply-related ideas including total, average, and marginal product of labor, as well as total, variable, and marginal cost of labor. 

The reading also provides insights into total and marginal revenue and their significance in the calculation of breakeven and shutdown points. Moreover, it touches upon key principles such as the law of demand, Giffen goods, Veblen goods, and the law of diminishing returns. It further elucidates various aspects such as production costs, short-run total cost, short-run marginal cost, average variable cost, and average total cost.

 Furthermore, the reading examines revenue, marginal revenue, and economic profit. It culminates with an exploration of economies of scale, diseconomies of scale, and the determination of the minimum efficient scale for a firm.

Gross Domestic Product (GDP) represents the market value of all final goods and services produced within a country during a specific period. It can be determined by either looking at the total expenditure on goods and services or the income generated in their production.

 

GDP only includes the final purchases of newly produced goods and services, excluding transfer payments and capital gains to avoid double counting. Intermediate goods are also excluded from GDP calculations.

 

There are two methods to measure GDP: by valuing the final output or by summing the value added at each stage of production and distribution. The sum of value added equals the final selling price of the goods.

 

Nominal GDP is measured using current year prices, while Real GDP uses constant prices from a base year. The GDP deflator is the ratio of nominal GDP to real GDP.

 

Households earn income by providing factors of production (labor, capital, and natural resources) and use that income for consumption, savings, and net taxes. Businesses produce most of the economy's output and invest to maintain and expand production capacity. The government sector collects taxes, purchases goods and services, and plays a role in consumption and investment. International trade involves exports and imports, with net exports reflecting the difference between the two.

 

Capital markets connect saving and investment in the economy. From the expenditure side, GDP includes personal consumption, gross private domestic investment, government spending, and net exports.

 

Short-term fluctuations in GDP are influenced by shifts in aggregate demand and aggregate supply. The level of GDP below potential GDP leads to a recessionary situation, while an overheated situation occurs when GDP exceeds potential GDP. Stagflation, characterized by high inflation and weak economic growth, is caused by a decline in short-run aggregate supply.

 

Growth in real GDP indicates the expansion of the overall economy, while per capita GDP reflects a country's standard of living. Economic growth is driven by factors such as labor supply, physical and human capital, raw materials, and technological knowledge. Total factor productivity (TFP) represents the portion of output growth not explained by changes in capital and labor inputs.

 

Sustainable economic growth is measured by the increase in the economy's productive capacity or potential GDP. Factors influencing growth include population growth, labor force participation rate, investment, human capital, natural resources, technology, and public infrastructure. Externalities and spillover effects, both positive and negative, play a significant role in growth. Climate change is closely linked to economic growth and imposes costs on the global economy.

The sustainable rate of growth in an economy is determined by the growth rate of the labor supply and labor productivity.

Business cycles are repetitive patterns of economic expansion and contraction that affect various sectors of the economy. While these cycles are inherent to market economies, their duration and intensity can vary significantly.

 

The investment industry identifies four distinct phases of the business cycle: recovery, expansion, slowdown, and contraction. The peak of economic output occurs during the slowdown phase, while the trough is observed during the recovery phase.

 

The classical cycle refers to fluctuations in economic activity as measured by GDP. In contrast, the growth cycle focuses on deviations from the long-term trend growth level, analyzing whether economic activity is above or below the trend.

The growth rate cycle examines fluctuations in the rate of economic growth.

 

Credit cycles involve changes in the availability and cost of credit. During periods of economic strength, lenders are more inclined to extend credit on favorable terms.

Conversely, during economic weakness, lenders tighten credit, making it less accessible and more expensive. This dynamic impacts asset values, economic fragility, and default rates.

 

Credit cycles play a significant role in the financing of construction and property purchases, making them crucial in the broader economic context.

 

The interaction between business cycles and credit cycles greatly influences the extent and duration of business cycle fluctuations, including recessions and recoveries. Various economic indicators change throughout the business cycle.

Business investment experiences significant fluctuations, while employment levels follow the cycle with a delay. Consumer spending, particularly on durable goods, services, and essential consumer products, also exhibits cyclical patterns.

Although inventories are relatively small compared to the overall economy, they have a substantial impact on economic growth.

Analysts monitor the inventory-to-sales ratio as an important indicator to assess the economy's position within the cycle.

 

Different economic theories provide perspectives on business cycles. Neoclassical and Real Business Cycle (RBC) theories focus on fluctuations in aggregate supply (AS), suggesting that the economy gradually moves towards a new equilibrium without significant government intervention.

Conversely, Keynesian theories emphasize fluctuations in aggregate demand (AD) and advocate for government intervention to restore full employment and avoid deflationary spirals.

 

Monetarists argue that it is generally preferable to allow the economy to find its equilibrium without extensive government intervention.

However, they highlight the importance of maintaining steady growth in the money supply.

 

Economic indicators play a crucial role in understanding the stage of the business cycle.

Leading indicators provide insights into the future direction of the economy, although no indicator is flawless.

Examples of leading indicators include survey-based indicators, average weekly hours, initial claims for unemployment insurance, new building permits, stock market indices, and yield differentials.

Coincident indicators closely align with the turning points of the overall economy and are valuable for identifying its current state.

These indicators encompass industrial production indexes, sales indexes, real personal income, and employment figures.

 

Lagging indicators change after an established trend and have turning points that occur later than those of the overall economy.

Examples of lagging indicators include average duration of unemployment, inventory-to-sales ratio, unit labor costs, bank prime lending rates, consumer debt-to-income ratio, and changes in the consumer price index for services.

 

Policy makers and market practitioners rely on real-time monitoring of economic and financial variables to assess current conditions and produce nowcasts, which estimate the present state of the economy. 

This real-time analysis is valuable because official data, such as GDP figures, are typically published with a delay.

 

Understanding unemployment involves different categories, including actively seeking employment, long-term unemployment, and frictional unemployment, which pertains to individuals searching for better job matches or transitioning between jobs.

 

Inflation manifests in various forms, such as hyperinflation, deflation, imported inflation, and demand inflation. Consumer price indexes, producer price indexes, and GDP deflators serve as measures of inflation. Price levels are influenced by real factors, including aggregate supply and demand.

In this reading, the practices of monetary and fiscal policy are explained, highlighting their significant impact on economic activity. Therefore, it is crucial for financial analysts to familiarize themselves with the tools, goals, and transmission mechanisms of both policies.

Governments have the ability to influence their economies through a combination of monetary and fiscal policy. Specifically, monetary policy refers to the actions of central banks aimed at controlling the quantity of money and credit in an economy. 

On the other hand, fiscal policy involves government decisions regarding taxation and spending. It is through these policies that governments affect the economy, albeit through different mechanisms.

Money serves important functions as a medium of exchange, a store of wealth, and a unit of account. Furthermore, the banking system's practice of fractional reserve banking allows for the creation of money.

The demand for money represents the amount of wealth individuals choose to hold in the form of money, driven by motives such as transactions, precautionary needs, and speculation.

Additionally, the addition of reserves to a fractional reserve banking system can lead to an expansion of the money supply, as determined by the money multiplier.

When considering interest rates, the nominal rate comprises a real required rate of return, an inflation compensation component, and a risk premium.

Central banks play various roles, including being the sole supplier of currency, lender of last resort, government and interbank bank, and banking supervisors. Most central banks prioritize price stability as their primary objective.

To ensure the effective implementation of monetary policy, central banks should strive for independence, credibility, and transparency in their goals and objectives.

However, central banks face challenges in controlling the amount of money deposited by households and corporations, as well as the willingness of banks to create money through credit expansion. These limitations impose constraints on the power of monetary policy.

While the concept of money neutrality suggests that money does not have a long-term influence on the real economy, central banks aim to impact the real economy through their policy rate's influence on market interest rates, asset prices, exchange rates, and economic agents' expectations.

Inflation targeting is a common monetary policy approach, often used alongside exchange rate targeting, particularly in developing economies. 

Another strategy, known as quantitative easing, involves increasing the money supply to stimulate aggregate demand.

In contrast to monetary policy, fiscal policy involves government spending and taxation to impact various aspects of the economy, including aggregate demand, income distribution, and resource allocation. 

Depending on economic conditions, fiscal policy can be expansionary or contractionary.

The tools used in fiscal policy relate to revenue generation through taxes and various forms of expenditure, such as current spending on goods and services and capital expenditure on infrastructure projects.

Given its potential to stabilize an economy, fiscal policy plays a crucial role. Governments can enact expansionary or contractionary measures based on economic conditions.

It is worth noting that coordination between fiscal and monetary policy is crucial, as they operate through different channels and can potentially work against each other if not aligned.

To fully comprehend the effects of monetary and fiscal policy on the economy, financial analysts must have a solid understanding of their intricacies and interplay.

This reading presents a framework for analyzing how a country's trade and capital flows impact its economy. It explores basic models that explain trade based on comparative advantage and discusses how international trade affects economic growth, investment attractiveness, and resource allocation. The benefits of trade, such as gains from exchange and specialization, economies of scale, product variety, and efficient resource allocation, are highlighted.

 

The concept of comparative advantage is explained, both in terms of absolute advantage and opportunity cost. The Ricardian and Heckscher-Ohlin models are discussed as explanations for trade patterns, emphasizing the complementary nature of technology and factor endowments.

 

The reading also examines trade barriers, their reasons for implementation, and their effects on welfare. It differentiates between small and large countries in terms of their influence on trade prices and welfare outcomes. The impact of import tariffs, quotas, voluntary export restraints, and export subsidies on price, production, and trade is explained.

 

Additionally, the reading covers capital restrictions, regional trading blocs, and the importance of understanding trading relationships for investment purposes. It concludes by introducing the International Monetary Fund (IMF), the World Bank, and the World Trade Organization (WTO) as key organizations that contribute to stability, development, and global trade.

The main focus of this reading lies on the fundamental financial statements and how different accounting methods impact these statements and their analysis.

The analysis of financial statements is crucial in evaluating a company's overall financial position and the associated risks it faces over time. Assessing security and business valuation, conducting credit risk assessments, and performing acquisition due diligence all necessitate an understanding of the primary financial statements, including the underlying principles and reporting approaches. 

Since there is no universally accepted set of accounting standards, companies worldwide may vary in their reporting practices depending on their jurisdiction.

Financial statement analysis entails the ability to examine a company's reported results in light of its economic reality, reconcile disparities in accounting practices to facilitate valid cross-company comparisons, identify potential issues with the quality of reported financial statements, and detect any indications of financial statement manipulation by management.

Financial reports, which encompass financial statements, notes, and management's commentary, play a vital role in evaluating a company's financial position and performance. 

Financial analysts utilize these reports for various analyses such as equity valuation, credit risk assessment, acquisition due diligence, and evaluating subsidiary performance. Key factors considered in both equity and credit analysis involve assessing a company's financial position, profitability, cash flow generation, and potential for future growth.

The primary objective of financial reports is to provide information about a company's financial condition, performance, and trends. The main financial statements include the balance sheet, statement of comprehensive income, statement of changes in equity, and statement of cash flows. The balance sheet provides insights into a company's assets, liabilities, and owners' equity at a specific point in time. The statement of comprehensive income presents revenue, expenses, and net income over a given period. Changes in owners' equity, excluding owner-related transactions, are captured in the statement of comprehensive income. The statement of changes in equity outlines the variations in different components of owners' equity. Cash and cash flow are crucial for a company's long-term success as they impact liquidity, solvency, and financial flexibility.

The accompanying notes in financial statements are essential for comprehending the statements as they provide information regarding alternative accounting methods, estimates, and assumptions. Additionally, analysts should evaluate additional information provided by the company, particularly the management commentary, to gain a comprehensive understanding. Publicly traded companies are required to undergo independent audits of their annual financial statements, providing assurance regarding the fairness of the financial statements and, for US companies, the effectiveness of internal control systems.

To gain perspective and evaluate a company's future, analysts should consider external information about the economy, industry, and peer companies.

The financial statement analysis framework offers a structured approach, involving steps such as defining the purpose and context of the analysis, collecting and processing data, analyzing and interpreting the data, developing conclusions and recommendations, and conducting follow-up procedures.

Understanding financial reporting standards is crucial for security valuation and financial analysis. 

This reading emphasizes the objectives of these standards, the parties involved in their establishment, and the implications for analysts in monitoring them.

The primary aim of financial reporting is to provide valuable financial information to investors, lenders, and creditors to facilitate decision-making regarding resource allocation. 

Since different preparers may make varying policy choices and estimates, standards are necessary to ensure consistency in judgments.

Private sector standard-setting bodies and regulatory authorities have distinct roles in the process.

Standard-setting bodies create rules, while regulatory authorities enforce them. However, regulatory authorities typically possess the legal authority to establish financial reporting standards in their jurisdictions.

The International Financial Reporting Standards (IFRS) framework outlines the fundamental concepts for preparing and presenting financial statements for external users. 

The central objective is to achieve a fair presentation of useful information. Qualitative characteristics of useful information include relevance, faithful representation, comparability, verifiability, timeliness, and understandability.

IFRS financial statements encompass the statement of financial position (balance sheet), statement of comprehensive income, statement of changes in equity, cash flow statement, and accompanying notes. 

These statements should adhere to principles such as fair presentation, going concern, accrual basis, materiality and aggregation, and no offsetting. They must be prepared annually, include comparative information, and maintain consistency.

Presentation requirements involve a classified balance sheet and essential information on the face of the statements and in the notes.

Numerous listed companies worldwide report under either IFRS or US Generally Accepted Accounting Principles (GAAP). Achieving comparability between companies using different accounting standards may necessitate adjustments not readily available to financial statement users. 

Analysts should exercise caution when interpreting comparative financial measures and remain updated on significant developments in financial reporting standards.

To stay informed about ongoing developments, analysts can monitor new products or transaction types, actions of standard-setters and regulators, and company disclosures concerning critical accounting policies and estimates.

In this study session, the main focus is on understanding the key sources of information used to assess a company's financial performance.

 

The primary financial statements, including the income statement, balance sheet, cash flow statement, and statement of changes in equity, are discussed, along with the importance of reviewing accompanying notes and management reporting. The session also provides a general framework for conducting financial statement analysis.

 

Additionally, the roles of financial reporting standard-setting bodies and regulatory authorities are described, highlighting their significance in ensuring transparency and accountability in financial reporting.

 

Financial and other reports, including financial statements, notes, and management's commentary, are essential for financial analysts to evaluate a company's performance and financial position. Analysts perform financial analysis for various reasons, such as valuing equity securities, assessing credit risk, conducting due diligence for acquisitions, and evaluating subsidiary performance. Key considerations in equity and credit analysis involve evaluating a company's financial position, profitability, cash flow generation, and potential for future growth.

 

This reading provides an overview of financial statement analysis, covering the purpose of financial reports, the primary financial statements (balance sheet, income statement, statement of changes in equity, and statement of cash flows), the importance of cash flow analysis, the role of notes in understanding financial statements, and the significance of external information sources.

 

The reading also introduces a framework for financial statement analysis, which includes defining the analysis's purpose, collecting and processing data, analyzing and interpreting the data, drawing conclusions and making recommendations, and following up on the analysis.

The balance sheet is a financial statement that shows an entity's assets, liabilities, and equity at a specific time.

Equity represents the owners' stake in the company's assets after deductingliabilities. It can increase through income or new equity issuance and decrease through losses, dividend payments, or share repurchases.

Understanding the balance sheet helps analyze a company'sliquidity, solvency, and overall financial position.

Assets and liabilities are categorized as current or non-current based on their expected liquidation or settlement timeline.

Trade receivables,inventories, accounts payable, and deferred revenue are examples of items on the balance sheet.

Property, plant, and equipment (PPE) are tangible assets, and intangible assets include patents and trademarks.

Depreciation and amortization methods are used to allocate the cost of long-lived assets over their useful lives.

Goodwill, generated in business combinations, is an intangible asset thatis tested for impairment.

Financial instruments can be measured based on fair value or amortized cost, with different recognition methods for changes in fair value. The owners' equity sectionincludes various components such as contributed capital, retained earnings, and non-controlling interest.

The statement of changes in equity shows the changes in each equity component over a period.

Balance sheet ratios, including liquidity and solvency ratios, help assess a company's ability to meet short-term and long-term obligations.

Vertical common-size analysis expresses each balance sheet items as a percentage of total assets.

This learning module should provide CFA level 1 candidates with a detailed practical description of the balance sheet. 

The cash flow statement is a vital financial statement that offers insights into a company's cash receipts and cash payments during an accounting period. It provides information about the company's operating, investing, and financing activities, complementing the income statement. While the income statement measures a company's success, cash and cash flow are also crucial for its long-term viability.

 

Stakeholders, including creditors, investors, and other users of financial statements, rely on the cash flow statement to evaluate a company's liquidity, solvency, and financial flexibility. They can assess the company's ability to meet financial obligations and make informed investment decisions by examining the sources and uses of cash. Key concepts related to cash flow statement analysis include:

 

The cash flow activities are classified into three categories: operating activities, investing activities, and financing activities. Significant non-cash transactions are disclosed separately in a supplemental note.

 

Under International Financial Reporting Standards (IFRS) and US Generally Accepted Accounting Principles (GAAP), cash flow statements share similarities, but IFRS provides more flexibility in classifying certain cash flow items.

 

Companies can report their operating cash flow using either the direct or indirect method. The direct method presents operating cash inflows and outflows by source and use, respectively. The indirect method reconciles net income to operating cash flow by adjusting for non-cash items and changes in operating working capital accounts.

 

The cash flow statement is interconnected with the income statement and comparative balance sheets, providing a comprehensive view of a company's financial performance.

 

While the indirect method is commonly used, analysts can convert it to an approximation of the direct format through a straightforward three-step process.

 

Analyzing a cash flow statement involves evaluating the sources and uses of cash and understanding the primary drivers of cash flow within each category of activities.

 

Common-size statement analysis can be applied to the cash flow statement using different approaches, such as the total cash inflows/total cash outflows method or the percentage of net revenues method.

 

The cash flow statement allows for the calculation of free cash flow to the firm (FCFF) and free cash flow to equity (FCFE), which are important indicators of a company's financial health.

 

The cash flow statement can also be utilized in financial ratio analysis to measure a company's profitability, performance, and financial strength.

 

In summary, the cash flow statement provides essential information about a company's cash flow activities and their impact on its financial position. Understanding the sources and uses of cash enables stakeholders to assess a company's liquidity, solvency, and financial flexibility. By considering the various aspects of the cash flow statement, stakeholders can gain a comprehensive understanding of a company's financial standing and make informed decisions.

This module should give to candidates  the ability to explain the features of equity investments, security markets, and indexes. 

Additionally, the candidate should be able to  evaluate industries, companies, and equity securities, as well as demonstrating knowledge of basic equity valuation models.

Global equities play a crucial role in achieving long-term growth and diversification goals. They also hold a significant portion of capital markets, which have been growing in terms of both breadth and depth as developing economies enter the equity capital market. 

The module provides an explanation of how the financial system operates and underscores its significance in generating wealth. Financial analysts play a crucial role in understanding the functioning of the system, as their analyses heavily influence trading decisions.

The financial system encompasses various markets and intermediaries that facilitate the exchange of instruments, cash flows, andrisks between buyers and sellers.

The reading covers essential points such as the involvement of investors, borrowers, hedgers, and information-motivated traders. Additionally, it explores primary and secondary markets, pooledinvestment vehicles, forward and futures contracts, financial intermediaries, and margin loans.

The reading emphasizes the importance of transparent contracts,information efficiency, and regulatory oversight.

 It concludes by highlighting the advantages of a well-functioning financial system,including efficient allocation of capital, risk sharing, and access to reliable information.

The module also stresses the importance of regulatory bodies whose role to maintain fair and orderly markets, and mandated financial disclosure programs ensure that financial analysts have access toessential information.

The reading provides an explanation of security market indexes, including their construction, management, and applications. These indexes are valuable tools for investors as they offer a broad selection of options that represent various markets, segments, and asset classes. 

It is crucial for investors to comprehend the construction of indexes and choose the most appropriate one for their specific needs. 

The reading emphasizes several key points:

Security market indexes are designed to measure the values of specific target markets.

Constituent securities are carefully selected to represent the target market within an index.

Price return indexes reflect changes in constituent securities' prices, while total return indexes also consider reinvested income.

Indexes can be weighted using different methods, ranging from simple price and equal weightings to more complex approaches like market capitalization and fundamental weightings.

Index management involves periodic rebalancing and reconstitution to maintain appropriate weightings and accurately represent the desired target market.

Security market indexes serve multiple purposes, such as measuring market sentiment, serving as benchmarks for portfolios, assessing systematic risk and performance, and facilitating assetallocationand investment product models.

Investors have a wide range of options when it comes to security market indexes, covering equity, fixed-income, commodity, real estate, and hedge fund asset classes.

Index providers offer diverse indexes within each asset class, catering to different geographic regions, economic development groups, economic sectors, and other relevant factors.

Proper utilization of security market indexes relies on understanding their construction and management principles.

By grasping these aspects, investors can effectively leverage security market indexes for their investment strategies.

This reading provides a comprehensive overview of market efficiency theory and the evidence surrounding it. It explores the different forms of market efficiency and their implications for fundamental analysis, technical analysis, and portfolio management. The key takeaway is that consistently outperforming the market by generating higher returns for a given level of risk is generally not possible according to the efficient market hypothesis.

 

The reading discusses various factors that impact market efficiency, such as the number of participants, analyst coverage, information availability, and trading limitations. It explains the three forms of efficient markets: weak, semi-strong, and strong, which differ in terms of the information incorporated into asset prices.

 

The concepts of intrinsic value and market value are also explored, emphasizing that in efficient markets, these values should align closely. Empirical evidence largely supports the semi-strong-form efficiency in developed countries, while the strong form is not well-supported. The reading highlights several anomalies that challenge market efficiency, including the size anomaly, January anomaly, and winners-losers anomalies. However, it notes that contradictory evidence both supports and refutes these anomalies.

 

The field of behavioral finance is introduced, which utilizes insights from human psychology and behavioral biases to explain investment decisions. Importantly, even if market participants exhibit seemingly irrational behaviors like herding, a market can still be considered efficient.

Equity securities have a crucial role in investment analysis and portfolio management, gaining increasing importance globally due to factors such as the demand for equity capital, technological advancements, and enhanced information exchange. This reading provides an introduction to equity securities and presents a comprehensive overview of global equity markets. It emphasizes the historical performance of equity securities, demonstrating their superior average real annual returns compared to government bills and bonds, which have merely kept up with inflation.

 

The module examines the different types and characteristics of common and preference equity securities, as well as the key distinctions between public and private equity securities. It further delves into the various types of equity securities traded in global markets, exploring their risk and return characteristics. Additionally, the reading delves into the role of equity securities in generating company value, including the relationship between a company's cost of equity, accounting return on equity, investors' required rate of return, and intrinsic value.

 

The following key points are covered in this reading: the features of common and preference shares, the concept of cumulative and non-cumulative preference shares, participating and non-participating preference shares, callable and putable preference shares, private equity securities (including venture capital, leveraged buyouts, and private investments in public equity), depository receipts (such as American depository receipts and global depository receipts), and the influence of underlying characteristics on the risk and return of equity securities. The reading concludes by highlighting the significance of a company's accounting return on equity and its cost of equity in equity investing.

This reading offers an overview of industry analysis and the commonly employed approaches to examine industries. It emphasizes the interconnectedness of company and industry analysis, showcasing how both provide valuable insights into factors influencing a company's growth and profitability. Industry analysis serves multiple purposes, including understanding the business environment, identifying investment opportunities, formulating sector rotation strategies, and evaluating portfolio performance.

 

The reading explores three main methods of classifying companies based on the products/services they provide, their sensitivity to business cycles, and statistical similarities. It introduces cyclical and non-cyclical companies, along with commercial industry classification systems like the Global Industry Classification Standard (GICS) and the Industry Classification Benchmark (ICB).

The reading acknowledges limitations in peer group comparisons and presents steps for creating an initial list of comparable companies. It emphasizes the importance of industry analysis alongside company analysis, as it helps identify opportunities and threats within the company's specific context. The Porter's five forces framework is introduced as a starting point for strategic analysis, focusing on factors influencing industry profitability.

 

The reading discusses barriers to entry, industry concentration, market share stability, and industry life cycles, while also exploring external influences on industry growth, profitability, and risk. Competitive strategies, such as cost leadership and product/service differentiation, are discussed. A checklist for company analysis is provided, covering aspects such as corporate profile, industry characteristics, demand and supply dynamics, pricing, financial ratios, and sustainability metrics. The reading highlights the use of spreadsheet modeling for financial statement analysis and forecasting, emphasizing the significance of assumptions in the modeling process.

In this module, we delve into equity valuation models used to evaluate intrinsic value and highlight their importance, emphasizing the need for careful implementation. The module presents several key points to consider.

Firstly, valuation models serve as a fundamental basis for analysis and research, but their application requires skill and judgment. Therefore, analysts must exercise caution when using these models.

Secondly, the selection of a valuation model relies on the accessible information and data inputs. Analysts should carefully consider the available data and choose a model that best suits the circumstances.

Moreover, it is often advisable to prefer simple valuation models over complex ones. The principle of simplicity should be taken into account when selecting a model. By doing so, analysts can ensure clarity and ease of interpretation.

It is important to note that valuation is an imperfect practice. Analysts strive to minimize forecast inaccuracies, but it is impossible to eliminate them entirely. Thus, the objective is to make reasonable and informed estimates.

To address concerns regarding model applicability and variations in estimates, analysts often employ multiple valuation models. By using different models, they can cross-validate their findings and gain a more comprehensive understanding of the intrinsic value.

The three primary categories of equity valuation models are present value models, multiplier models, and asset-based valuation models. Each category offers a unique approach to estimating value.

Present value models estimate value based on the present value of anticipated future benefits. By discounting future cash flows, analysts determine the value in today's terms.

Multiplier models estimate intrinsic value by applying multiples of fundamental variables. These multiples, such as price-to-earnings ratio or price-to-sales ratio, help gauge the relative value of the equity.

Asset-based valuation models estimate value by subtracting liabilities from the value of assets. This approach focuses on the underlying tangible and intangible assets of the company.

Within the realm of valuation, dividend valuation models hold particular significance. These models consider cash dividends as a crucial input for estimating value.

Understanding the dividend chronology is essential when applying dividend valuation models. Important dates include the declaration date, ex-dividend date, holder-of-record date, and payment date.

The dividend discount model, a specific type of dividend valuation model, estimates value as the present value of expected future dividends. By discounting these dividends, analysts arrive at the intrinsic value.

Another approach is the free cash flow to equity model. It estimates value as the present value of projected future free cash flow to equity. This model focuses on the cash flows available to equity holders.

A simplified version of the dividend discount model is the Gordon growth model. It estimates value as D1/(r - g), where D1 represents the expected dividend, r is the required rate of return, and g is the expected growth rate.

For more complex situations, analysts may employ the two-stage dividend discount model. This model combines short-term high-growth dividends with a terminal value estimation using the Gordon growth model.

Multiplier models, on the other hand, utilize multiples based on fundamental variables or comparable data. These multiples provide a basis for comparing the equity's value to similar companies in the market.

Lastly, asset-based valuation models estimate the equity value by subtracting liabilities from the value of assets. This approach focuses on the net value of the company's assets and liabilities.

By considering these various valuation models and approaches, analysts can gain a comprehensive perspective on the intrinsic value of the equity.

This module aims to equip the candidate with the necessary skills to evaluate various aspects of a company's operations. 

It covers evaluating corporate governance, capital investment decisions, working capital management, cost of capital estimation, and assessing operational and financial leverage.

Numerous studies have demonstrated a positive correlation between strong corporate governance and improved financial performance. Companies that prioritize effective governance practices tend to exhibit better overall results.

Moreover, there is a growing recognition of the importance of environmental, social, and governance factors in investment approaches. Referred to as ESG, these factors are increasingly considered when making investment decisions.

In addition to governance, management decisions regarding investments and financing have a significant impact on corporate profitability and performance. 

Effective capital investment decisions and appropriate financing strategies are crucial for the long-term sustainability and growth of a company.

To ensure sustained success and enhance shareholder value, management must consistently identify and prioritize profitable long-term capital projects. Simultaneously, they need to carefully consider the cost of capital for financing these projects.

Furthermore, optimizing the use of leverage and managing working capital effectively are essential for daily operations. Maintaining an appropriate balance between debt and equity, as well as managing working capital efficiently, contributes to overall operational effectiveness.

By developing a comprehensive understanding of these topics, candidates will be equipped to evaluate a company's corporate governance practices, make informed capital investment decisions, assess working capital management, estimate the cost of capital, and evaluate operational and financial leverage effectively.

This study session focuses on practical techniques for estimating the cost of capital for companies or projects, which is an important factor in corporate decision-making and investor analysis. It covers methods for estimating the costs associated with different sources of capital.

 

The session also discusses capital structure considerations and explores the Modigliani-Miller propositions, including the factors that influence a company's use of leverage. Examples of potential conflicts among stakeholders related to financing decisions are examined. The session concludes by addressing different types of leverage (operating, financial, total), measures of leverage, and the potential impact of leverage on a company's earnings and financial ratios.

This reading offers an overview of the techniques used to determine the cost of capital for both companies and projects. It covers the concept of weighted average cost of capital (WACC) and explores the common methods employed to estimate the individual costs of capital components and their respective weights.

When it comes to estimating the cost of debt, the yield-to-maturity method and the bond rating method are commonly used. The yield-to-maturity method utilizes the bond valuation equation, while the bond rating method relies on the assigned rating of the bond. The resulting cost of debt can be adjusted to reflect the after-tax cost by considering the tax deductibility of interest payments.

For preferred stock, the cost is calculated by dividing the preferred stock dividend by the current price of the stock. As for equity, the cost is determined using the Capital Asset Pricing Model (CAPM) or alternative approaches. The CAPM requires inputs such as the risk-free rate, equity risk premium, and beta.

In situations where publicly traded equity is not available, an alternative method is to estimate the cost of debt and add a risk premium that accounts for the additional risk associated with equity. Comparable companies operating in the same industry can also be used to estimate the unlevered beta for a company with similar business risk.

It's important to consider flotation costs, which are expenses incurred during the process of raising capital. These costs are typically included as an initial cash flow in valuation analysis.

While the CAPM method is the most popular choice among companies for estimating the cost of equity, particularly for larger publicly traded companies, the complexity and specific circumstances of a private company or project may require additional analyses and assumptions in assessing systematic risk.

The capital structure of a company is determined by factors such as its life cycle stage, cash flow characteristics, and ability to support debt. As companies mature, their business risk decreases and they can leverage their positive and predictable cash flows more effectively. However, according to Modigliani and Miller's research, changing the capital structure alone does not impact the overall value of the firm, as it remains independent of this decision. Nevertheless, increasing leverage can enhance firm value to a certain extent, while also raising the risk of default for capital providers who require higher returns.

 

To optimize firm value, management should strive for an optimal capital structure that minimizes the company's weighted average cost of capital. In practical terms, financing decisions are often linked to investment spending and the company's ability to handle debt based on its specific business characteristics and cash flow situation. Managers may choose a particular financing method to signal information to investors, demonstrating confidence in the company's future prospects. However, it's important to note that capital structure decisions can affect different stakeholders in various ways, and conflicts of interest may arise as management seeks to maximize shareholder wealth or prioritize their own interests over others.

This module provides a comprehensive understanding of business risk, financial risk, and leverage measures. It covers the basics of these concepts and their calculation methods. Here is a summary of the key points covered:

Business risk encompasses sales risk and operating risk. Sales risk is associated with uncertainty in sales price and quantity, while operating risk relates to the use of fixed costs in operations.

Financial risk pertains to how a company finances its operations and the balance between equity and debt financing.

Candidates will learn how to calculate various indicators and ratios to assess these risks effectively.

The degree of operating leverage (DOL) measures the percentage change in operating income relative to the percentage change in units sold. It is calculated using the formula (Q(P - V))/(Q(P - V) - F), where Q represents units sold, P is the price per unit, V is the variable cost per unit, and F is fixed costs.

The degree of financial leverage (DFL) indicates the percentage change in net income resulting from a one percent change in operating income. DFL is computed using the formula (Q(P - V) - F)(1 - t)/((Q(P - V) - F - C)(1 - t)), where C represents financial charges and t is the tax rate.

The degree of total leverage (DTL) combines operating leverage and financial leverage to measure net income sensitivity to changes in unit sales. DTL is calculated as DOL × DFL.

The breakeven point (QBE) is the level of units produced and sold at which a company's net income is zero. It is determined by the formula (F + C)/(P - V), where F is fixed costs, C is total variable costs, P is the price per unit, and V is the variable cost per unit.

The operating breakeven point (QOBE) represents the quantity of units produced and sold at which the company's operating income is zero. QOBE is calculated as F/(P - V), where F is fixed costs, and P and V are the price per unit and variable cost per unit, respectively.

By acquiring knowledge of these measures and their calculations, candidates will develop the skills to evaluate and manage business risk, financial risk, and leverage effectively.

In this study session, the focus is on introducing the process of portfolio planning and construction, which involves creating an investment policy statement (IPS).

Following that, there will be a discussion about risk management, encompassing different types and measures of risk, and presenting a risk management framework.

The session will then delve into the examination of technical analysis, which involves utilizing asset price, trading volume, and similar data to make investment decisions. Finally, the session will wrap up by exploring the influence of financial technology (fintech) on various aspects of the investment industry, such as investment analysis, automated advice, and risk management.

This study session provides an overview of the portfolio planning and construction process, emphasizing the importance of developing an investment policy statement (IPS).

 It further explores risk management by discussing different types and measures of risk, and presents a risk management framework.

The module also delves into technical analysis, which involves using asset price, trading volumes, and related data to guide investment decisions.

Lastly, the impact of financial technology(fintech) on various aspects of the investment industry, including investment analysis, automated advice, and risk management, is discussed.

This reading focuses on two main topics: the construction of an investment policy statement (IPS) for clients and the process of portfolio construction. The IPS serves as a fundamental document that outlines the client's objectives, constraints, and other relevant factors that shape the investment strategy. 

It covers aspects such as risk and return objectives, liquidity requirements, time horizon, regulatory considerations, tax status, and unique client needs.

A significant emphasis is placed on incorporating environmental, social, and governance (ESG) considerations within the IPS. 

This can be achieved through different approaches such as negative screening, positive screening, ESG integration, thematic investing, engagement/active ownership, and impact investing.

Risk objectives are specified to align with the client's risk tolerance, which can be expressed as absolute, relative, or a combination of both measures. Return objectives, on the other hand, can be absolute targets or relative to a benchmark.

The IPS also addresses liquidity requirements, time horizon, tax status, legal and regulatory restrictions, and any unique circumstances that could impact the portfolio composition. 

Asset classes are regarded as the foundational components for asset allocation, and a strategic asset allocation is determined based on the IPS, constraints, and expectations of the capital markets.

It is highlighted that monitoring and maintaining the target asset allocation is crucial, and periodic rebalancing is necessary to align the portfolio with the desired allocation. 

In addition to systematic risk, investment committees may opt to consider tactical asset allocation risk or security selection risk.

ESG considerations are emphasized as a vital aspect of the portfolio planning and construction process, providing guidance to investment managers in selecting securities, exercising shareholder rights, and implementing investment strategies.

n this reading, the influence of behavioral biases on the decisions and behaviors of financial market participants is discussed. These biases can be categorized as either cognitive errors or emotional biases, and having awareness of them can enable individuals to adapt or moderate their impact for better economic outcomes.

 

The reading emphasizes the following key points:

 

Financial market participants are not always rational in their decision-making and are susceptible to behavioral biases. Consequently, these biases can lead to suboptimal decisions.

Cognitive errors stem from statistical, information-processing, or memory errors, while emotional biases arise from impulses and intuition. It is important to note that cognitive errors are easier to rectify as they result from faulty reasoning, whereas emotional biases are more resistant to change due to their emotional foundation.

 

Adapting to a bias involves recognizing its presence and making necessary adjustments. On the other hand, moderating a bias aims to reduce or eliminate its influence.

 

Cognitive errors can be classified as belief perseverance biases and information-processing biases. Belief perseverance biases involve maintaining beliefs despite statistical or memory errors and are connected to cognitive dissonance. In contrast, information-processing biases involve the illogical or irrational use of information.

 

Emotional biases encompass biases such as loss aversion, overconfidence, self-control, status quo, endowment, and regret aversion. These biases are driven by emotions and can significantly impact decision-making processes.

 

Recognizing and understanding biases is the initial step in mitigating their impact on financial decisions. By being aware of their existence, individuals can take necessary measures to counteract their effects and make more informed choices.

 

The field of behavioral finance helps explain market anomalies and deviations from the theory of market efficiency. It provides valuable insights into the psychological aspects of financial decision-making and sheds light on the factors that influence market behavior.

 

Studying behavioral biases enables financial market participants to improve decision-making and achieve better economic outcomes. By gaining a deeper understanding of these biases, individuals can develop strategies to minimize their negative impact and enhance their overall financial performance.

This reading highlights the significance of risk management in business and investing, emphasizing that it goes beyond simply avoiding risks. Instead, it involves understanding, carefully selecting, and managing risks. The reading explores different aspects of risk management, including risk exposure, risk tolerance, and the components of a risk management framework.

The key points from the reading are as follows:

Risk management is a comprehensive process that establishes risk tolerance and encompasses the measurement, monitoring, and modification of risks.

A risk management framework comprises risk governance, risk identification and measurement, risk infrastructure, risk policies and processes, risk mitigation and management, communication, and strategic risk analysis and integration.

Risk governance involves top-level oversight and the establishment of risk tolerance for the organization.

Risk identification and measurement involve evaluating both quantitative and qualitative aspects of potential risks and the organization's exposure to them.

Risk infrastructure encompasses the necessary resources and systems for tracking and assessing the organization's risk profile.

Risk policies and processes complement risk governance at the operational level.

Risk mitigation and management entail actively monitoring and adjusting risk exposures while integrating all elements of the risk management framework.

Communication includes risk reporting and feedback loops to enhance decision-making.

Strategic risk analysis and integration utilize risk tools to identify factors that add value and incorporate the analysis into management decisions.

Implementing a risk management committee and a chief risk officer (CRO) demonstrates a robust risk governance framework.

Risk tolerance delineates which risks are acceptable and unacceptable, determining the overall level of risk exposure for the organization.

Financial risks encompass market risk, credit risk, and liquidity risk, while non-financial risks encompass settlement risk, legal risk, regulatory risk, and operational risk, among others.

Risks can be modified through prevention, avoidance, risk transfer (insurance), or risk shifting (derivatives).

Internally, risk can be mitigated through self-insurance or diversification.

Risk drivers are fundamental factors, such as macroeconomic and industry variables, that give rise to risks.

Common risk measures include standard deviation, beta, value at risk, and expected loss given default.

Ultimately, effective risk management enhances decision-making and aids in maximizing value for businesses and investors

Technical analysis is a strategy for examining securities by analyzing their price and volume data presented in charts, and it utilizes indicators to offer investment recommendations. 

The fundamental principles of technical analysis are that the market incorporates all available information, prices move in trends, and price behavior tends to repeat with recognizable patterns. 

The growing trend among analysts and investors is to study technical analysis as a means to enhance decision-making, particularly in light of the impact of psychology on investor behavior. 

While technical analysis is applicable to various financial instruments, it is most effective in liquid markets. 

The methodology involves the use of charts and indicators, with charts providing insights into past price movements and future price expectations.

 Key concepts in technical analysis encompass relative strength analysis, trend identification, consolidation patterns, support and resistance levels, and chart patterns. 

Technical indicators, such as moving averages and Bollinger Bands, provide supplementary information. 

Momentum oscillators and sentiment indicators help assess market sentiment and identify situations of excessive buying or selling. Intermarket analysis examines trends across different types of securities and sectors. 

Technical analysis can be approached from either a top-down or bottom-up perspective, and it brings value to investment teams by generating trading ideas and assisting with timing decisions for securities.

Fintech refers to the application of technology in order to revolutionize financial services and products. 

It encompasses a wide range of areas such as analyzing data, automating trading activities, providing automated financial advice, and maintaining financial records. 

The utilization of Big Data is integral to fintech, involving large datasets characterized by their size, speed, and diversity, which includes both traditional and non-traditional data sources. 

Artificial intelligence empowers computer systems to perform tasks that traditionally required human intelligence, while machine learning enables the extraction of knowledge from data to make predictions and identify patterns. 

Natural language processing is employed to analyze and interpret text and voice-based data. Robo-advisory services deliver automated financial advice to retail investors, encompassing tasks like asset allocation and portfolio optimization. 

The integration of Big Data and machine learning can facilitate the identification of market trends and enhance risk management practices. Algorithmic trading utilizes automated programs to execute trades based on predetermined rules and prevailing market conditions. 

Blockchain and distributed ledger technology present a secure and decentralized approach to storing, tracking, and recording financial assets, with applications extending to cryptocurrencies and post-trade processes.

This study session begins by introducing the unique features that distinguish fixed-income securities, followed by an overview of global debt markets. It explains the primary issuers, sectors, and various types of bonds.

 

The session covers important concepts related to the calculation and interpretation of bond prices, yields, and spreads. Furthermore, it addresses interest rate risk and relevant risk measures. Finally, the session explores securitization, which involves creating fixed-income securities backed by specific assets, and discusses the different types, characteristics, and risks associated with these investments.

 This reading serves as an introduction to fixed-income securities, highlighting their key features and the variations among different types of securities. It covers important points and establishes connections between them:

Firstly, investors need to understand the bond's features, which determine cash flows and returns. Additionally, they should consider legal, regulatory, and tax aspects of the contractual agreement, along with contingency provisions that may affect cash flows.

Moving on, the basic features of a bond include the issuer, maturity, par value, coupon rate and frequency, and currency denomination. Bonds can be issued by various entities, such as supranational organizations, sovereign governments, non-sovereign governments, quasi-government entities, and corporate issuers.

 

Considering the risks, investors are exposed to credit risk when holding bonds. Therefore, they rely on bond credit ratings to assess the credit quality of a bond. It's important to note that the principal refers to the amount the issuer agrees to pay the bondholder at maturity.

The coupon rate represents the annual interest rate paid to bondholders.

It can be either fixed or floating, and the frequency of coupon payments may vary depending on the bond type and place of issuance.

 

Furthermore, bonds can be denominated in any currency, including dual-currency bonds and currency option bonds, which are linked to two currencies.

To estimate the bond's return, investors consider the yield-to-maturity, a crucial metric that equates the present value of a bond's future cash flows to its price. This provides an estimate of the market's expectation for the bond's return.

Regarding bond characteristics, plain vanilla bonds have a known cash flow pattern, fixed maturity date, and pay a fixed rate of interest over their life.

The bond indenture or trust deed, which is usually held by a trustee, serves as the legal contract outlining the bond's form, issuer's obligations, and investor's rights.

The trustee performs specified duties according to the indenture.

 

Moving to asset-backed securities, they involve a separate legal entity that uses underlying assets as guarantees to repay bondholders.

To mitigate credit risk, collateral backing is employed, where secured bonds are backed by assets or financial guarantees.

Bond covenants are enforceable rules agreed upon at the time of bond issuance. Affirmative covenants enumerate what issuers are required to do, whereas negative covenants enumerate what issuers are prohibited from doing.

Considering the jurisdiction, where bonds are issued and traded is an important consideration as it affects applicable laws, regulations, and tax treatment.

Bonds can be domestic, foreign, or issued internationally as Eurobonds or global bonds.

Regarding tax treatment, interest on bonds is generally taxed at the ordinary income tax rate, although specific tax provisions may apply to discounted or premium issuance.

Moving on to different bond structures, amortizing bonds require periodic principal payments, sinking fund agreements facilitate principal retirement, and floating-rate notes (FRNs) have coupon rates based on market reference rates.

Bonds can have various coupon payment structures, such as step-up coupons, credit-linked coupons, payment-in-kind coupons, and deferred coupons.

Index-linked bonds, including inflation-linked bonds, tie coupon payments and principal repayments to a price index.

 

Embedded options in bonds, such as callable bonds, putable bonds, and convertible bonds, grant certain rights to the issuer or bondholder affecting the bond's disposal or redemption.

For instance, callable bonds offer the issuer the right to buy back bonds prior to maturity, while putable bonds allow the bondholder to sell bonds back to the issuer. Convertible bonds give the bondholder the option to convert the bond into common shares of the issuing company.

Debt financing plays a critical role in securing funds for a wide range of entities, including households, governments, financial institutions, and non-financial companies. The effective operation of fixed-income markets is vital for ensuring efficient global allocation of capital. Key aspects of debt financing involve classifying fixed-income markets based on factors such as issuer type, credit quality, maturity, currency denomination, and coupon type.

 

The major bond market sectors encompass households, non-financial corporations, governments, and financial institutions. Investors distinguish between investment-grade and high-yield bond markets based on credit quality. Short-term securities are traded in money markets, while capital markets handle longer-term securities.

 

The majority of bonds are denominated in euros or US dollars. Bonds can feature fixed or floating interest rates, often referencing rates like Libor.

 

Bond markets can be domestic or international, with the Eurobond market offering fewer constraints. Fixed-income indexes are employed to describe markets and assess investment performance. 

Noteworthy bond investors include central banks, institutional investors, retail investors, and banks.

Bonds are initially issued in primary markets and subsequently traded in secondary markets. Various mechanisms facilitate bond issuance, including public offerings, private placements, underwritten offerings, best-efforts offerings, shelf registrations, and auctions.

Most bond trading occurs over-the-counter, and sovereign bonds are primarily issued by national governments.

Companies raise debt through diverse instruments like commercial paper, notes, and bonds. Structured finance encompasses asset-backed securities, collateralized debt obligations, and other related instruments that repackage risks.

Financial institutions have additional funding sources at their disposal, including retail deposits, central bank funds, and repurchase agreements.

In this study session, the primary focus is on analyzing the essential factors that influence bond returns and risks.

Specifically, it delves into the examination of interest rate risk and credit risk. The session introduces important measures like duration and convexity, which aid in evaluating a bond'ssusceptibility to interest rate fluctuations.

 Furthermore, it concludes by explaining credit risk and the application of credit analysis in assessing bonds with higher risk levels.

The reading provides an overview of fixed-rate bonds and their risk and return characteristics. It focuses on two important measures of interest rate risk: duration and convexity. 

The key points covered include the following:

Fixed-rate bonds generate returns through coupon and principal payments, as well as potential capital gains or losses upon selling the bond. 

The total return of a bond includes reinvested coupon interest payments and the sale price if the bond is sold before maturity. The horizon yield represents the internal rate of return between the total return and the bond's purchase price.

Coupon reinvestment risk increases with higher coupon rates and longer reinvestment periods. Capital gains and losses are measured based on the carrying value of the bond, considering any discount or premium if the bond is purchased below or above par value.

Fixed-rate bonds have two types of interest rate risk: coupon reinvestment risk and market price risk. These risks partially offset each other, with market price risk dominating for short-term investors and coupon reinvestment risk dominating for long-term buy-and-hold investors.

Duration measures the sensitivity of a bond's full price, including accrued interest, to changes in interest rates. Different duration statistics, such as Macaulay duration, modified duration, money duration, and price value of a basis point, assess a bond's sensitivity to its own yield-to-maturity or the benchmark yield curve.

Effective duration is similar to approximate modified duration but assumes a parallel shift in the benchmark yield curve when measuring interest rate risk. Key rate duration measures a bond's sensitivity to changes in specific maturity segments of the benchmark yield curve. Bonds with embedded options require effective duration as the appropriate measure of interest rate risk.

Duration and convexity are inversely related to coupon rates and yield-to-maturity. Time-to-maturity and duration are usually positively related, except for certain long-term, low-coupon bonds. Embedded call or put options affect a bond's effective duration, reducing it compared to non-callable or non-putable bonds.

Bond portfolio duration can be calculated based on aggregate cash flows or the weighted average of individual bond durations. Money duration measures the price change in the bond's currency units, while the price value of a basis point estimates the change in the bond's full price with a 1 basis point yield-to-maturity change.

Modified duration captures the primary effect of a bond's percentage price change, while convexity represents the secondary effect. The investment horizon plays a crucial role in measuring interest rate risk, with different risks dominating based on the duration gap between the investment horizon and Macaulay duration.

Credit risk involves default probability and recovery, while liquidity risk relates to transaction costs in bond selling. Changes in benchmark yields and spreads interact, affecting duration and convexity. 

Empirical duration utilizes statistical methods and historical bond prices to determine the price-yield relationship for specific bonds or portfolios.

The reading provides an overview of credit analysis, emphasizing the importance of credit markets, credit ratings, and credit-related risks. It discusses the components of credit risk, including default risk and loss severity. 

 

The reading also covers factors such as downgrade risk and market liquidity risk that can impact yield spreads and bond prices. It highlights the role of credit rating agencies and the limitations of relying solely on credit ratings. 

 

The "4 Cs" framework (capacity, collateral, covenants, and character) is introduced for evaluating credit risk. 

 

The reading explores the impact of credit risk on yields, spread changes, and holding period returns. It discusses credit analysis considerations for high-yield companies, sovereign borrowers, and non-sovereign government bonds. 

 

The analysis of general obligation and revenue-backed bonds is also covered.

The objective of this reading is to equip CFA level 1 candidates with a practical comprehension of derivative analysis, encompassing forwards, futures, options, and swaps.

Derivatives, which obtain their value from underlying assets, have become increasingly important in the management of financial risk, capitalizing on investment opportunities, and creating synthetic exposure to various asset classes.

Similar to other financial markets, the concepts of arbitrage and market efficiency play a crucial role in establishing the prices of these securities.

This study session aims to establish the necessary conceptual framework for understanding the fundamental aspects of derivatives and derivative markets. 

It introduces the essential characteristics and valuation principles associated with forward commitments (forwards, futures, and swaps) as well as contingent claims (options).

A derivative is a financial agreement that gains or loses value based on the performance of an underlying asset, which can be either a firm commitment or a contingent claim.

The derivative markets offer a range of possibilities for investors to create or alter their exposure to an underlying asset, beyond those available in the cash market. The most common underlying assets for derivatives include equities, fixed income and interest rates, currencies, commodities, and credit.

Over-the-counter (OTC) derivative markets allow for flexible, tailored contracts between end users and financial intermediaries.

Exchange-traded derivatives (ETDs) are standardized contracts traded on an organized exchange, requiring collateral to guard against counterparty default.

In cases where derivatives are centrally cleared, a central counterparty (CCP) assumes the credit risk of derivative counterparties and provides clearing and settlement services.

Firm commitments in the form of derivative contracts, such as forwards, futures, and swaps, involve an agreement between counterparties to exchange an underlying asset at a predetermined price in the future.

Moreover, forwards are flexible derivative instruments that are traded over-the-counter (OTC), while futures are standardized contracts traded on an exchange, necessitating daily settlement of gains and losses.

Similarly, swap contracts also represent firm commitments, entailing the exchange of a series of cash flows at a later date. The most common type of swap is the interest rate swap, wherein fixed interest payments are exchanged for floating interest payments.

In contrast, option contracts serve as contingent claims where one counterparty possesses the right to determine the settlement of the trade at a specified exercise price. Consequently, the option buyer pays a premium to the seller for this right.

Furthermore, credit default swap (CDS) contracts serve the purpose of managing the risk of loss from issuer default separately from a cash bond.

Considering these aspects, market participants frequently employ firm commitments and contingent claims to generate comparable exposures to underlying assets. Nevertheless, it is crucial to acknowledge that these derivative instrument types entail distinct payoff and profit profiles.

The one-period binomial model is utilized to evaluate the worth of contingent claims, such as options. It operates under the assumption that the underlying asset will experience either an increase represented by Ru (up gross return) or a decrease denoted by Rd (down gross return) over a single period, which aligns with the expiration of the derivative contract.

 

Within the binomial model, a risk-free portfolio is constructed by combining the option with the underlying asset. The proportion of the option to the underlying security is determined by a hedge ratio. It is crucial for the hedged portfolio to generate the prevailing risk-free rate of return to prevent the existence of riskless arbitrage opportunities.

 

When employing the one-period binomial model to determine the value of a derivative, the focus lies on computing the discounted expected payoff of the option. This is accomplished by employing risk-neutral probabilities instead of actual probabilities. It is noteworthy that there is no need to possess knowledge of the actual probabilities of underlying price movements or the expected return of the underlying asset in order to price an option.

 

Furthermore, the versatility of the one-period binomial model allows for its extension to multiple periods, facilitating the valuation of more intricate contingent claims.

In this study session, alternative investments are introduced, including hedge funds, private capital, real estate, natural resources, and infrastructure. 

The focus is on understanding their unique characteristics, potential advantages, and risks. 

A comparison is made between these alternative investments and traditional investments such as stocks and bonds, highlighting their similarities and differences. 

The goal is to provide an overview that helps in comprehending the nature of alternative investments.

This reading serves as a comprehensive introduction to alternative investments. It covers various categories such as hedge funds, private capital, natural resources, real estate, and infrastructure, highlighting their characteristics, benefits, and risks. Alternative investments are seen as supplementary strategies to traditional investments and often involve active management and distinct risk profiles. Key considerations include lower liquidity, less regulation, higher fees, and limited historical data. Due diligence is essential before investing, and risks such as operational, financial, counterparty, and liquidity risks should be analyzed.

Alternative investments often use partnership structures and have specific fee arrangements.

Various ratios can be computed to assess the performance of alternative investments, such as the Sharpe ratio, Sortino ratio, Treynor ratio, Calmar ratio, and MAR ratio. Additionally, metrics like batting average and slugging percentage can be utilized. Private equity investments are commonly evaluated using the internal rate of return (IRR) calculation, while real estate investments are often assessed using the capitalization rate (cap rate).

Performance appraisal can be challenging due to complexity and limited transparency, requiring alternative measures and ratios. Analysts should be cautious of biases in indexes and consider custom fee arrangements.

Private equity involves investing in privately owned companies or acquiring public companies with the intention of making them private. Key strategies in private equity include leveraged buyouts (MBOs and MBIs) and venture capital. Common ways to exit private equity investments include selling the company to another business (trade sale), taking the company public through an initial public offering (IPO), or restructuring the company's capital (recapitalization).

Private debt refers to various forms of debt provided by investors to private entities. Key strategies in private debt include direct lending, mezzanine debt, and venture debt. 

 Private debt also encompasses specialized strategies such as collateralized loan obligations (CLOs), unitranche debt, real estate debt, and infrastructure debt.

Natural resources encompass a range of assets including commodities (both hard and soft), agricultural land (farmland), and timberland.

Commodity investments involve investing in physical commodities or companies involved in commodity production, although commodity derivatives such as futures or swaps are more commonly used. Commodity investments can also be made through commodity trading advisors (CTAs) often found in hedge funds.

Returns from commodity investing are primarily based on price changes and typically do not include income streams like dividends, interest, or rent (with the exception of income derived from collateral). However, timberland investments offer an income stream through the sale of trees, wood, and other products. 

Timberland can be seen as both a productive facility and a storage facility, providing a sustainable investment that helps mitigate climate-related risks.

Farmland, similar to timberland, generates income based on crop yields and agricultural commodity prices. However, farmland lacks the production flexibility of timberland since crops must be harvested at specific times when they are ripe.

Real estate encompasses two main sectors: residential and commercial. Residential real estate is the largest sector, representing approximately 75% of the global market. Commercial real estate primarily includes office buildings, shopping centers, and warehouses.

 Real estate possesses unique characteristics compared to other asset classes, such as the heterogeneity of properties (no two properties are identical) and their fixed locations.

Investments in real estate can be made directly or indirectly through various means, including public market investments such as real estate investment trusts (REITs) or private transactions involving equity or debt.

Infrastructure investments involve assets that are tangible, require significant capital investments, and have long lifespans. These assets are intended for public use and provide essential services. Examples of infrastructure assets include airports, healthcare facilities, and power plants. 

Financing for infrastructure projects often occurs through partnerships between the public and private sectors.

Social infrastructure assets are designed to support human activities and include educational institutions, healthcare facilities, social housing, and correctional facilities. The focus is on providing, operating, and maintaining infrastructure assets to fulfill these needs.

Infrastructure investments can also be classified based on the stage of development of the underlying asset. Investments in infrastructure projects that are in the construction phase are typically referred to as greenfield investments, while investments in existing infrastructure assets are known as brownfield investments.