CFA Level 1 Portfolio Management: Our Cheat Sheet

Note: this cheat sheet is updated for the latest 2023’s curriculum.

It is probably no surprise that portfolio management is the most popular career current CFA candidates are interested in exploring further.

Portfolio management is the heart of the CFA program – and they start you light and gentle in Level 1 with a broad strokes introduction, gradually increasing in difficulty and topic weight as you advance to Level 3.

Hence, building a solid foundation in CFA Level 1 Portfolio Management is crucial to getting your CFA charter. That’s why we decided to create our 300 Hours Cheat Sheet series of articles, which focuses on one specific topic area for one specific CFA Level. ☕

More Cheat Sheets will be published in the coming weeks, sign up to our member’s list to be notified first.

By referring to the CFA curriculum’s Learning Outcome Statements (LOS), we prioritize and highlight the absolute key concepts and formula you need to know for each topic. With some tips at the end too!

Use the Cheat Sheets during your practice sessions to refresh your memory on important concepts.

Let’s go! Don’t forget to bookmark this page and (re)visit often! 🙂

CFA Level 1 Portfolio Management: Summary

Portfolio management is really the end game for the CFA program.

However, this topic’s weighting in Level 1 is deceptively light. Portfolio Management will become exponentially more important as you advance in the CFA program, especially in Level 3 where it accounts for 35-40% of the entire exam. Nearly half!

2023’s CFA Level 1 Portfolio Management’s topic weighting is 5-8%, which means 9-14 questions of the 180 questions of CFA Level 1 exam are centered around this topic.

It is covered in 2023’s Topic 9 with 8 Learning Modules (LMs).

Here’s a summary of Level 1 Portfolio Management chapter readings:

Once you’ve learnt to value individual securities, evaluating them as a combined portfolio is essential to your capability as an asset or wealth manager. Not only that, but knowing how to tailor the combination of securities to suit different clients’ risk profiles is important to being a good financial advisor.

In short, the CFA Level 1 Portfolio Management readings teaches you:

– How investing via building a portfolio works;
– How to measure how well you’re doing;
– How to be aware of the scale and type of risks your’e taking;
– How to adapt portfolio investment strategies to different types of investor profiles.

LM1: Portfolio Management: An Overview

Steps in portfolio management process

• Planning: List client’s objectives and constraints in IPS
• Execution: This includes asset allocation, security analysis and portfolio construction.
• Feedback: This includes monitoring/rebalancing and performance measurement and reporting.

Types of investors

Defined benefit (DB) vs defined contribution (DC) pension plans

• Defined benefit (DB) plan is where a company promises to makes a pre-defined future benefit payments to the employees. The company bears the investment risk.
• Defined contribution (DC) plan is where a company contributes an agreed amount to the plan and employees invest part of their wages to the plan. In a DC plan, investment and inflation risk is borne by the employee.

LM2: Portfolio Risk and Return: Part I

Risk aversion

• Risk aversion is the degree of an investor’s inability and unwillingness to take risk.
• Risk neutral: an investor who is indifferent about the gamble or a guaranteed outcome, as the investor is only concerned about returns.
• Risk-seeking: an investor who prefers a gamble, where the indifference curve is downward sloping as the expected return decreases for higher levels of risk. This is uncommon.
• Risk averse: an investor who expects additional return for taking additional risks, i.e. the indifference curve is upward sloping. Most investors are risk averse, the degree of risk aversion varies. The steeper the indifference curve, the more risk averse they are.

Minimum variance portfolio

• Minimum variance frontier is a line combining all portfolios with a minimum level of risk given a rate of return.
• Global minimum variance portfolio is the portfolio with the lowest variance amongst the portfolio of all risky assets.
• The efficient frontier is the part of the minimum variance frontier that is above the global minimum variance portfolio, since it gives the highest return for a given level of risk. Note that efficient frontier only consists of risky assets, there are no risk-free assets here.

Capital allocation line (CAL)

CAL overcomes the shortfall of efficient frontier by showing a line representing possible combinations of risk-free assets and optimal risky asset portfolio.

E[R_p]=R_f+\Big(\frac{E[R_i]-R_f}{\sigma_i}\Big)\sigma_p

Optimal investor portfolio is the point where an investor’s indifference curve is tangential to the optimal CAL.

LM3: Portfolio Risk and Return: Part II

Capital market line (CML)

If all investors have the same expectations, the capital market line (CML) becomes a special case of optimal CAL, where the tangent portfolio is the market portfolio.

CML is a special case of CAL whereby

E[R_p]=R_f+\Big(\frac{E[R_m]-R_f}{\sigma_m}\Big)\sigma_p

Slope of CML line is the market price of risk, i.e. Sharpe ratio.

Systematic vs non-systematic risk

• Systematic risk is a non-diversifiable, market risk. Investors should get compensated for taking on systematic risk.
• Non-systematic risk is a local risk that can be diversified away, investors are not compensated for taking on this risk.
• A risk-free asset has zero systematic and non-systematic risk.

Beta

Beta is a measure of an asset’s systematic (market) risk, relative to the risk of the overall market.

\beta=\frac{Cov(R_i,R_m)}{\sigma^2_m}=\frac{\rho_{i,m}\sigma_i\sigma_m}{\sigma^2_m}=\frac{\rho_{i,m}\sigma_i}{\sigma_m}

Capital asset pricing model (CAPM)

CAPM is used to calculate an asset’s required return given its beta.

E[R_i]=R_f+ \beta_i [{E(R_m)-R_f}]

CAPM assumptions:

1. Investors are rational, risk-averse and utility maximizing individuals.
2. Frictionless markets
3. All investors plan for the same holding period
4. Investors have homogenous expectations
5. Investors are infinitely divisible
6. Investors are price takers.

CAPM limitations:

• Only systematic risk are included
• Does not consider multi-period implications

Security market line (SML)

SML is a graphical representation of CAPM, which applies to all securities, whether they are efficient or not.

Slope of the SML is market risk premium, E(R_m) – R_f

If an asset’s expected return forecast is higher (lower) than its CAPM required return, the asset is undervalued (overvalued).

Other portfolio performance evaluation measures

Sharpe ratio (total risk)

Sharpe \thickspace ratio=\frac{R_p-R_f}{\sigma_p}

M-squared (total risk)

M \thickspace squared=(R_p=R_f)\Big(\frac{\sigma_m}{\sigma_p}\Big)-(R_m-R_f)

Treynor ratio (systematic risk)

Treynor \thickspace ratio=\frac{R_p-R_f}{\beta_p}

Jensen’s alpha (systematic risk)

Jensen's \thickspace alpha = R_p-[R_f+\beta_p(R_m-R_f)]

LM4: Basics of Portfolio Planning and Construction

Investment policy statements (IPS)

IPS is a written document detailing the portfolio construction process designed to satisfy a client’s investment objectives.

Major components of an IPS are:

• Introduction
• Statement of purpose
• Statement of duties and responsibilities
• Procedures
• Investment objectives
• Investment constraints
• Investment guidelines
• Evaluation of performance
• Appendices

Assessing overall risk tolerance

• Usually expressed as average, above average, below average.
• 2 factors affect investor’s overall risk tolerance:
  • willingness (investor’s intent towards risk)
  • ability to take risk (investor’s capability to take risk, independent of intent)

Investment constraints

Check out this useful forum post about how to tackle IPS questions too, as we discuss the acronym “RRTTLLU” to remember the investor objectives and constraints.

ESG constraints

Note that IPS may also include a policy regarding responsible investing which takes into account Environmental, Social and Governance (ESG) factors.

The 6 main ESG investment approaches are:

LM5: The Behavioural Biases of Individuals

Cognitive errors

Emotional biases

LM6: Introduction to Risk Management

Risk management framework

• Risk governance: a top-down process that defines risk tolerance and provides guidance to align risk with company goals
• Risk identification and measurement
• Risk infrastructure
• Defined policies and processes
• Risk monitoring, mitigation and management
• Communications
• Strategic analysis or integration

Other risk definitions

• Risk tolerance: what risks are acceptable and how much risk should be taken
• Risk budgeting: how and where the risks are taken and quantifies tolerable risk by specific metrics
• Financial risk: risks that originate from financial markets such as change in interest rates. 3 major types of financial risk are market risk, credit risk and liquidity risks.
• Non-financial risk: risks that arise from within an entity or externally. Examples of non-financial risks are: operational risk, solvency risk, settlement risk, legal risk, regulatory, accounting and tax risk, model risk, tail risk, political risk.
• Methods of risk measurements: standard deviation, beta, duration, delta, gamma, VaR, CVaR, etc.
• Methods of risk modification: risk prevention/avoidance, risk acceptance (self-insurance and diversification), risk transfer (insurance), risk shifting/modification (via derivatives).

LM7: Technical Analysis

Technical analysis assumptions

• Supply and demand determine prices.
• Changes in supply and demand can cause changes in prices.
• Prices can be projected with charts and other technical tools.
• Investors are often irrational, hence preventing market efficiency.

Technical analysis tools

Charts

Trend analysis

Common chart patterns

Reversal patterns (signalling the end of a trend):

Continuation patterns (signals a temporary pause in the trend):

Technical indicators

Price-based indicators

Momentum oscillators

Sentiment indicators

LM8: Fintech in Investment Management

• Fintech refers to the technological innovation in the design and delivery of financial products and services.
• Big data refers to a mix of structured and unstructured datasets that can come from a variety of sources such as individuals, business processes and sensors.
• Artificial intelligence (AI) computer systems perform tasks that traditionally required human intelligence. They display cognitive and decision-making ability comparable or superior to humans. E.g. Apple’s Siri digital assistant.
• Machine learning (ML) is a computer-based technique that extracts knowledge and learns from a large amount of dataset, then applying this pattern to generate predictions on another dataset.
• 3 main approaches to ML:
  • Supervised learning: inputs and outputs are identified and labelled.
  • Unsupervised learning: inputs and outputs are not labelled. ML algorithm will seek or identify the relationships by itself.
  • Deep learning: neural networks are used by computers to perform multi-stage, non-linear data processing to identify patterns and relationships.
• Fintech applications:
  • robo-advisory services: low cost, automated advice process for investments
  • risk analysis: monitoring risks in real time
  • algorithmic trading: automated trading based on pre-specified rules
• Financial applications of distributed ledger technology (DLT):
  • Cryptocurrencies
  • Tokenization: the process of representing ownership rights to physical assets on a blockchain. DLT can streamline this process of physical asset verification (e.g. real estate) by creating a single digital record of ownership.
  • Post-trade clearing and settlement: DLT can simplify the currently cumbersome post-trade clearing and settlement process by providing near real-time trade verification, reconciliation and settlement.
  • Compliance: stricter regulatory reporting requirements have made the cost of compliance higher. DLT can streamline the compliance process by providing near real-time access to transaction and compliance data.

CFA Level 1 Portfolio Management Tips

Know your terms and definitions

There are a wide range of definitions to be learnt in Portfolio Management.

Investment policy statement (IPS) objectives and constraints, risk types, asset classes – make sure you note and memorize them, as exam questions can baldly ask about any term.

Know your lines (CAL, CML, SML) and CAPM

The security market line (SML) and how it relates to capital asset pricing model (CAPM) calculations is a popular question topic, so make sure you’re very familiar with that.

Be sure to also know how to explain the capital allocation line (CAL) and the capital market line (CML), and how the SML is derived from the CML.

Calculation, calculation, calculation

Portfolio management questions can contain calculation-heavy questions, usually centering around risk or return calculations.

Make sure you get lots of practice on calculating and comparing returns (such as expected return), as well as calculating risk metrics (such as variance, covariance, standard deviation, beta).

More Cheat Sheet articles will be published over the coming weeks. Get ahead of other CFA candidates by signing up to our member’s list to get notified.

Meanwhile, here are other related articles that may be of interest:

• CFA Level 1 Cheat Sheets series: Quant Methods | Economics | Corporate Finance | Fixed Income | FRA | Equity Investments | Ethics | Alt Investments | Derivatives
• CFA Level 1: How to Prepare and Pass CFA in 18 Months
• CFA Level 1 Tips: Top 10 Advice from Previous Candidates
• What Is the Best CFA Level 1 Topic Study Order?
• 18 Actionable Ways to Improve Your Study Memory
• How to Study Effectively: Proven Methods that Work for CFA, FRM and CAIA
• The Ultimate Guide to CFA Practice Questions