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CFA Level 2 Notes
Ethics and Professional standards
Reading 1: Code of Ethics and Standards of Professional Conduct
6 components of the Code of Ethics
- Act with integrity , competence , diligence and respect
- Place integrity of profession and clients above personal interests
- Reasonable care and exercise independent professional judgment when making investment recommendations
- Practice and encourage others to practice in ethical manner
- Promote integrity and viability of global capital markets for ultimate benefit of society
- Maintain and improve professional competence
Disciplinary Review Committee (DRC) responsible for the enforcement of Code and Standards
Professional Conduct inquiries come from number of sources:
- Self-disclose on annual Professional Conduct Statement
- Written complaints received by Professional Conduct staff about investigation
- Media, regulatory notices or public sources
- Monitored by proctors who complete report on candidates who violated exam day
Sanctions include:
- Public censure
- Membership suspension and use of CFA designation
- Revocation of CFA charter
7 standards of Professional Conduct
1. PROFESSIONALISM A. Knowledge of the law (including code of ethics and standards of professional conduct) – in the event of a conflict, the stricter law, rule or regulation applies. B. Independence and objectivity – not offer or accept gift or compensation that would compromise independence/objectivity C. Misrepresentation – not make any in regards to analysis, recommendations or actions § Crediting source not required when using statistics, tables and projections from recognised financial and statistical reporting services D. Misconduct – not engage in conduct involving dishonesty, fraud, deceit
2. INTEGRITY OF CAPITAL MARKETS
A. Material nonpublic info – that could affect value of investment § Public once it is announced to the marketplace § Mosaic theory = reaching investment conclusion through analysis of public info + non-material nonpublic info § Members should make effort to achieve public dissemination by the firm of information they possess. Firms should review employee trades and maintain watch lists. B. Market manipulation – not distort prices or artificially inflate trading volume à only if there is INTENT to mislead.
3. DUTIES TO CLIENTS
A. Loyalty, Prudence and Care – act in benefit of client, place clients interest before employer’s/own interest § Submit at least quarterly statements showing securities in custody and all debits, credit and transactions. Not vote on all proxies. B. Fair Dealing – dealing with clients when making analysis, recommendations, engagement § E.g. do not take shares of an oversubscribe IPO C. Suitability – risk and return objectives, suitable investments, consistent with objectives and constraints of portfolio § Members gather info at beginning of relationship in the form of an investment policy statement (IPS) D. Performance presentation – fair, accurate and complete § Include terminated accounts and state when terminated E. Preservation of confidentiality – keep info about clients (current and past) confidential unless 3 exceptions: illegal activities, disclosure required by law, client permits disclosure
4. DUTIES TO EMPLOYERS
A. Loyalty – act for benefit of employer and not divulge confidential info § No requirement to put employer interests ahead of family and personal obligations § Violations include misappropriation of trade secrets and client lists, misuse of confidential info, soliciting employer’s clients, self-dealing. B. Additional Compensation Arrangements – not accept gifts, benefits that might create conflict of interest unless obtain written consent from all parties involved § If client offers bonus depending on future performance, this is an compensation arrangement à requires written consent in advance § If client offers bonus depending on past performance, this is a gift à requires disclosure to employer to comply with Standard I(B) Independence and Objectivity C. Responsibilities of Supervisors – make sure people comply with laws, regulation and Code and Standards
5. INVESTMENT ANALYSIS, RECOMMENDATIONS AND ACTIONS
A. Diligence and Reasonable Basis – reasonable basis supported by research and investigation for analysis, recommendation § Application depends on investment philosophy adhered to, members’ roles in investment decision making process, and resources and support provided by employer § Considerations include economic conditions, firms financial results/operating history, fees and historical results, limitations of quant models, peer group comparisons for valuation are appropriate § Members should encourage firm to adopt policy for periodic internal review of quality of 3 rd^ party research B. Communication with Clients – disclose basic principles of investment process and construct portfolios and any changes that might materially affect processes, significant limitations and risks, identifying important factors and communicate them, distinguish between fact and opinion. § Expectations based on modeling/analysis are not facts § Communicate gains/losses in terms of total returns § Explain limitations of model/assumptions used and of the investment itself – e.g. liquidity and capacity C. Record Retention – develop and maintain records to support analysis and recommendation with clients (e.g. documenting details of convo) § Member who changes firms must re-create analysis documentation supporting recommendation and must not rely on material created at previous firm § If no regulatory standards/firm policies in place, recommends 7-year minimum holding period
6. CONFLICT OF INTEREST
Investment Banking (IB) Requirements Recommended
- Separate research analysts from IB dept
- Analyst NOT supervised by IB personnel
- Prevent IB from reviewing or approving research reports and recommendations - Not sharing report with IB until publication - IB personnel only review to verify factual info or identify possible conflict of interest - Analyst not allowed to participate in roadshow
Research Analyst Compensation Requirements Recommended
- Comp directly related to quality of research and recommendations, and NOT linked to IB or corporate finance activities - Measurable criteria consistently applied to all analysts - Disclose extent to which compensation is dependent on IB revenue
Relationship with Subject Companies Requirements Recommended
- Analyst not allow subject company to see any part of research that might signal recommendation or make promises - Governing r/ship with companies (e.g. gifts) - Check facts contained before publication - Legal dept receive draft before shared
Personal Investment and Trading Requirements Recommended
- Policies addressing personal trading of employees
- Ensuring employees do not share info with any one who could trade ahead
- Prohibit employees and family from trading contrary to recommendations - Interests of client ahead of personal & firm - Obtain approval from legal/compliance department in advance of any trading - Restricted periods for employee trading - Contrary investment due to financial hardship - Provide list of personal holdings
Timeliness of Research Reports and Recommendations Requirements Recommended
- Regularly issue research reports on subject companies on a timely basis - Regular updates on research e.g. quarterly - If company coverage discontinued, issue a “final” research report
Compliance and Enforcement Requirements Recommended
- Disciplinary action, monitoring effectiveness, maintain records for audit - Distribute client list of activities which are violations and include disciplinary sanctions
Disclosure Requirements Recommended
- Disclose conflict of interest related to covered employees or firm as a whole - Disclosures complete & easy to understand - Disclose valuation methods for price tgts
Rating System Requirements Recommended
- Must have rating system that investors find useful for investment decision that determines suitability of investment - Avoid 1-dimensional ratings à Need more info + description of system
- Absolute (buy/hold/sell) or relative (outperform/underperform) categories recommended
Reading 7: Trade Allocation: Fair Dealing and Disclosure
Evaluate trade allocation practices and determine if comply with Standards
- Allocation of client trades on ad-hoc basis lends itself to fairness problems: o Allocation may be based on compensation arrangements § E.g. allocating disproportionately trades to performance-based fee accounts à breaches III(A) as this increases fees at expense of asset-based fee accounts o Allocation may be based client relationships with firm § E.g. allocating disproportionate share of profitable trades to favored clients
Describe appropriate actions to take in response to trade allocation practices that don’t respect client interests
- Advanced indication of client interest regarding new issues
- Distribute new issues by client , not by PM
- Fair and objective method for trade allocation such as pro rata system
- Execution of trades and price fairly + in a timely and efficient manner
- Keeping records and periodically review to ensure clients treated equitably
Reading 8: Changing Investment Objectives
Evaluate disclosure of investment objective and policies
- Investment actions consistent with stated objectives and constraints of the fund
- Material deviation from process in absence of client approval violates III(C) Duties to Clients
- Investment must fit within mandate or within realm of investment that’s allowed according to fund’s disclosure (e.g. prospectus or PDS)
Actions needed to ensure adequate disclosure of investment process
- Determine clients financial situation, investment objectives and level of investing expertise
- Adequacy disclose security selection and portfolio construction process
- Conduct regular internal checks for compliance with these processes
- Stick to stated investment strategy if managing specific mandate or strategy
- Notify investors of potential change in process and secure documentation of authorization for proposed changes
- Residual term independently distributed à residual not correlated with any other observations
- Residual term normally distributed
SIMPLE LINEAR REGRESSION MODEL: Y i = b 0 + b 1 Xi + ε i ,
b 1 is the slope coefficient à
- Predicted change in dependent for 1 unit change in independent
- i.e. beta à measures systematic risk
b 0 is intercept term à
- i.e. ex-post alpha à measures excess risk-adjusted return
Error term ( ε i ) represents portion of dependent variable that cannot be explained by independent variable
Regression is a line of best fit. It is the line for which estimates of b 0 and b 1 are such that sum of squared differences between estimated Y-values and actual Y-values is minimized à Sum of squared errors (SSE)
- Simple linear regression = ordinary least squares (OLS) regression
Note: Hypothesis test or confidence interval needed to assess importance of variable
Standard error of estimate, coefficient of determination, and confidence interval for regression coefficient Standard error of estimate (SEE) measures the degree of variability of the actual Y-values relative to the estimated Y-values
- Measures how well regression model “fits” the data à the smaller the SE the better the fit
- SEE is the SD of error terms in regression à also referred to as “standard error of regression/residual”
- SEE will be LOW if r/ship b/w dependent and independent is STRONG (e.g. r/ship b/w treasury yield bond and mortgage rates)
- SEE
Coefficient of Determination (R 2 ) is the % of total variation in dependent explained by independent
- R 2 of 0.63 means variation of independent explains 63% of variation in dependent variable
- R 2 may be computed by squaring correlation coefficient (r) for a regression with 1 variable o R 2 =r 2
- Note: correlated b/between predicted and actual values is square root of R 2
- If more than 1 variable à multiple regression techniques needed (e.g. ANOVA) o E.g. 𝑅 $^ = 789:;<=7> ?;@<;A<B= ABA;: ?;@<;A<B= = 1 −^
D=789:;<=7> ?;@<;A<B= ABA;: ?;@<;A<B=
Confidence interval for regression coefficient
- à i.e. Coefficient Estimate ±t * SE o t (^) c = critical two tailed t-value à note: n- o s (^) b1 = standard error of regression coefficient
- SEE = s (^) b1 = wider confidence interval
Null and alternative hypothesis about pop regression coefficient and appropriate test statistic
t-test for true slope coefficient (b 1 ) is equal to hypothesized value:
- Reject H 0 if t > CV or if t < -CV o If reject à slope coefficient different from hypothesis
t-stat = Coefficient estimate/SE
Predicted value for dependent variable Predicted values – values predicted by regression equation, given an estimate of independent variable
o Y = predicted value of dependent o X (^) p = forecasted value of independent Confidence Interval for predicted value of dependent variable
- Confidence interval: o S (^) f = SE of forecast § à note: will most likely be given S (^) f in exam
Analysis of variance (ANOVA) in regression analysis, and calculate F-statistics Analysis of variance (ANOVA) – statistical procedure for dividing total variability of variable into components that can be attributed to different sources. Analysing total variables of dependent variable
Total sum of squares (SST) measures total variation in dependent variable à sum of squared differences between actual and mean value of Y
Regression sum of squares (RSS) measures variation in dependent variable explained by independent à sum of squared distances between predicted Y and mean of Y
Sum of squared errors (SSE) measures unexplained variation in dependent variable à (aka sum of squared residuals) à sum of squared vertical distances between actual Y and predicted Y on regression line
Note: memorizing formula not important. Need to know what they measure to construct ANOVA
Total Variation = explained variation + unexplained variation à SST = RSS + SSE
R 2 =
EBA;: ?;@<;A<B= FFE – D=789:;<=7>?;@<;A<B= (FFI) EBA;: ?;@<;A<B= (FFE) =^
I89:;<=7> ?;@<;A<B= (KFF) EBA;: ?;@<;A<B= (FFE)
- R 2 is the correlation squared
SEE = 𝑀𝑆𝐸 =
FFI =N$
- MSE = mean squared error
- SSE is sum of squared residuals. SEE is the SD of the residual
F-test assesses how well set of independent variables, as a group, explains variation in dependent variable
- Tests whether all slope coefficients are equal to 0
- Used to test whether at least one independent variable explains significant portion of variation
- F-statistic: F = OFK OFI =^
KFF/Q FFI/=NQN" MSR = mean regression sum of squares ALWAYS 1 TAILED TEST k is number of slope parameters estimated (i.e. df = k) k(numerator) = 1 k (^) (denominator) = n-
Multiple regression à F-stat tests all independent variables Simple linear regression à only 1 independent variable
Reject null if F(test-statistic) > F (^) c (critical value) à independent variable sign diff from 0 à makes sign contribution to explanation of dependent variable
Limitations of regression analysis
F-statistic and how it used in regression analysis
- F-test assesses how well set of independent variables explains variation in dependent
- i.e. whether at-least one independent variable explains significant portion of variation in dependent
- Same formula as simple linear regression: F = OFK OFI =^
KFF/Q FFI/=NQN"
- Reject hypothesis if F(test-stat) > F(critical value) o Rejection à at least one coefficient significantly different à at least 1 independent variables makes significant contribution to explanation of dependent variable R 2 vs adjusted R 2 in multiple regression Coefficient of determination (R 2 ) used to test overall effectiveness of entire set of independent variables in explaining the dependent variable
Same calc as simple linear regression: R 2 = EBA;: ?;@<;A<B= FFE – D=789:;<=7>?;@<;A<B= (FFI) EBA;: ?;@<;A<B= (FFE) =^
I89:;<=7> ?;@<;A<B= (KFF) EBA;: ?;@<;A<B= (FFE)
Unfortunately R 2 may not be reliable measure of explanatory power of multiple regression model à because R 2 almost always increases as variables added to the model à high R 2 may reflect impact of large set of independent variables rather than how well set explains dependent variable à overestimating regression
- R 2 of at least 30% is considered reasonable fit
To overcome problem, recommend used adjusted R 2 à 𝑹 (^) 𝒂𝟐^ = 𝟏 − 𝒏N𝟏 𝒏N𝒌N𝟏 ×^ 𝟏 − 𝑹^
𝟐 n is # observations. K is # independent variables
- 𝑹 (^) 𝒂𝟐^ £ R 2 à adding new independent variables will increase R 2 but may either increase or decrease 𝑹 (^) 𝒂𝟐 o if new variable has small effect on R 2 , value of 𝑹 (^) 𝒂𝟐^ may decrease
- 𝑹 (^) 𝒂𝟐^ may be less than 0
Multiple regression equation using dummy variables When independent variable is binary (on or off), they are called dummy variables à used to quantity impact of qualitative events
- assigned value of 0 or 1
- if want to distinguish n classes à use n-1 dummy variables
Types of heteroskedasticity and how serial correlation affects statistical inference Heteroskedasticity occurs when variance of residuals is not the same across all observations in the sample. This happens when there are subsamples that are more spread out than the rest of the sample à i.e. variance of errors increases magnitude (i.e. as x increases, variances increase)
- Unconditional heteroskedasticity : not related to level of independent variables (function of x) à doesn’t systematically increase/decrease with changes in value of independent variables o Violation of equal variance assumption. Usually causes no major problems with regression
- Conditional heteroskedasticity: related to level of independent variable (depends on x) o E.g. variance of residual term increases as value of independent variable increases o Creates significant problems for statistical inference o Chi-square used as test à if t > cv reject null
Note: homoscedasticity is if variance of residuals stays the same.
Effects of Heteroskedasticity on regression analysis:
- F-test for overall significant of regression is unreliable
- Coefficient estimates are not affected
- Standard Errors (SE) are unreliable estimates
o If SE is understated à T-stat overstated à problem that will incorrectly reject null
hypothesis
