Level I CFA Curriculum - Volume 1
Location: 2027\L1\Vol-1\Pg.95: Beginning of the second paragraph:
Textbook Quote: The primary advantage of using market-capitalization weighting is that even as the price of each security fluctuates, its share of the total market capitalization stays constant.
Correction: A change in price will automatically imply a change in market cap, and therefore the constituent’s weight in the index will not stay constant.
Coach's Explanation: Market Cap = [(Stock Price) x (Number of Shares)]
An increase in price will automatically result in an increase in market cap, and therefore a greater weighting in the index.
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Location: 2027\L1\Vol-1\Pg.117: Question6:
Textbook Quote: ‘A significant increase in the value of Company A is announced’
Correction: The author should instead state: Company A makes an announcement that results in an increase in its valuation.
Coach's Explanation: For example, if a company announces that their earnings have beat expectations, then their stock price should appreciate upon the announcement.
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Location: 2027\L1\Vol-1\Pg.128: Case Study:
Coach's Explanation: Annualizing returns was already covered on: 2027\L1\Vol-1\Pg.16; in fact, the example on Pg.127 is exactly identical to 2027\L1\Vol-1\Pg.16. They should at least change the numbers in the examples.
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Location: 2027\L1\Vol-1\Pg.153: Case Study:
Textbook Quote: At the height of the COVID-19 pandemic, the Government of Greece issued a 2% annual coupon bond maturing in seven years.
Correction: Although implied, the question does not explicitly point out that the bond was issued at par.
Coach's Explanation: A bond may not necessarily be issued at par. For example, if the yield upon issue is higher than the coupon, then the bond will be issued at a discount, whereas if the yield is lower than the coupon, the bond will be issued at a premium.
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Location: 2027\L1\Vol-1\Pg.180: Question 4:
Textbook Quote: LVMH pays an annual dividend of EUR12.50
Correction: The question should indicate that LVMH just paid a dividend of EUR12.50 per share.
Coach's Explanation: When earnings and dividends are growing, the timing of the base dividend is critical. For example, if the EUR12.50 is the dividend payable at the end of the current year, then it would be DIV(1), on the other hand, if it was the dividend that was just paid, then it would be DIV(o). There’s an entire year’s worth of growth in-between these values.
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Location: 2027\L1\Vol-1\Pg.189: Solution to Part3:
Textbook Quote: The negative skewness indicates a tendency for more frequent negative returns..
Correction: The negative skewness indicates a tendency for larger (rather than more frequent) negative return.
Coach's Explanation: Frequency of outliers affects Kurtosis. Skewness on the other hand is caused by the size of these outlier value (rather than frequency).
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Location: 2027\L1\Vol-1\Pg.191: Solution to Part6:
Textbook Quote: The risk adjusted return for Fund X is 3.125% and for Fund Y is 3.086%
Correction: In explaining why PartA is incorrect, the 3.125 and 3.086 should not be accompanied by % sign.
Coach's Explanation: Risk adjusted return is a factor (i.e. multiple), rather than a percent. For example, the 3.125 should be interpreted as the fund yielding 3.125% return for every unit (1%) of risk.
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Location: 2027\L1\Vol-1\Pg.217:
Textbook Quote: Description regarding Negative Skewness and Positive Skewness
Correction: Outlier frequency and tail fatness affects kurtosis; however, this is mixed in with the description for positive and negative skew.
Coach's Explanation: Skewness is caused by the size of the outlier observations. To illustrate, suppose that Bill Gates moves into your neighborhood. This would cause the income distribution in your neighborhood to skew to the right (due to Mr. Gates extreme high net worth). However, since Mr. Gates is just one individual, it would hardly impact the frequency of outliers (i.e. tail fatness).
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Location: 2027\L1\Vol-1\Pg.224: Question4:
Textbook Quote: In the response to PartC: The mode.. might not adequately represent the central tendency in a highly skewed or kurtotic distribution
Correction: While the mode would be affected by a skewed distribution; a kurtotic distribution may not necessarily affect the mode, particularly if its Leptokurtic.
Coach's Explanation: Even if you look at Exhibit 23 on Pg220, you can see that irrespective of the kurtosis, the mode (i.e. the hump of the bell curve) stays centered. On the other hand, if the distribution is skewed (see Exhibit 20 on Pg.217), then the mode will be off center.
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Location: 2027\L1\Vol-1\Pg.234/235:
Textbook Quote: The question sequencing is off. The entire content on P234 relates to Q3.
Correction: Therefore, on P235, the Question number should be 4, not 5.
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Location: 2027\L1\Vol-1\Pg.273: Below Exhibit 14
Textbook Quote: The average simulated final price is 11.09, implying an 11.09% return
Correction: A final price of 11.09 would imply a return of 10.9%, and not 11.09%.
Coach's Explanation: From Exhibit 14, we can see that the starting price as $10. Therefore, and ending price of $11.09 would result in a 10.9% return.
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Location: 2027\L1\Vol-1\Pg.277: Part2
Textbook Quote: What characteristic of the log-normal distribution makes it suitable for modeling asset returns over time?
Correction: Log-normal distribution is suited for modelling asset prices, rather than returns.
Coach's Explanation: Log-normal distribution will have zero as its lowest possible value, mirroring that of for asset prices.
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Location: 2027\L1\Vol-1\Pg.291:
Textbook Quote: The conditional variance given P1:
Correction: The figures in the solution are all wrong.
Coach's Explanation: See the conditional variance computation at the bottom of Pg291 for the correct approach in computing conditional variance.
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Location: 2027\L1\Vol-1\Pg.305: Solution to Q5
Textbook Quote: The -λ in the solution is multiplied by 1
Correction: It should be multiplied by 5.
Coach's Explanation: The term in the question is 5 years.
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Location: 2027\L1\Vol-1\Pg.312: Question 6:
Textbook Quote: According to the central limit theorem, does the sample variance change as the sample size increases.
Correction: It should read: According to the central limit theorem, does the variance of the sample mean change as the sample size increases?
Coach's Explanation: Variance of the sample mean = [(Sample Variance) / (Sample Size)]
Therefore, as the sample size increases, the variance of the sample means decreases. In other words, with larger samples, the means of the those samples will deviate less from each other.
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Location: 2027\L1\Vol-1\Pg.319: Percentage of Return
Textbook Quote: A one-day VaR of 5% at a 95%n confidence level means there is a 95% chance that the portfolio will not lose more than 5% of its value in one day.
Correction: The author should have used a return figure other than 5% when illustrating a 95% VaR.
Coach's Explanation: The author’s example may be interpreted as indicating that downside risk is simply equal to: [1 – (VaR Confidence level)] = [(1 - .95)] = (.05). However, that is not so, the 95% VaR could have been -30%, implying that there is a 5% probability that we will not a see a loss that is greater than 30%.
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Location: 2027\L1\Vol-1\Pg.343: Top of page:
Textbook Quote: The X2 is given as 40.8237.
Correction: The X2 should be 40.856
Coach's Explanation: [(44-1) x (.0362) / (.0381)] = 40.856
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Location: 2027\L1\Vol-1\Pg.345: Bottom of page:
Textbook Quote:
At α = .05, reject H(o) if t < -1.6628
At α = .01, reject H(o) if t < -2.3705
Correction:
This is a right tail test. Therefore, the rejection points should be:
At α = .05, reject H(o) if t > 1.6628
At α = .01, reject H(o) if t > 2.3705
Coach's Explanation: The rejection range in the distribution coincides with the alternative hypothesis. Since the alternative hypothesis has a greater than sign (>), the rejection area will be in the right tail (i.e. positive critical values). Consequently, since the t-stat of 0.3805 is less than both critical values, the Null cannot be rejected. As well, the rejection area depicted in Exhibit 20 should be on the right tail (and not the left).
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Location: 2027\L1\Vol-1\Pg.359: Solution to Part4:
Textbook Quote: The standard error is divided by the square root of 130, which is (n-1)
Correction: The standard error is should be divided by the square root of 131, which is (n).
Coach's Explanation: We use (n-1) when determining the degrees of freedom, which is in turn used to compute the critical values in a hypothesis test. On the other hand, standard error is found by dividing the sample standard deviation by the square root of sample size (n). This is clearly stated on Pg.350 of Volume 1; but for some reason, the solution to Part4 used (n-1).
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Location: 2027\L1\Vol-1\Pg.375: Question 12:
Textbook Quote: The question asks for the confidence interval for monthly returns.
Correction: The question is really asking for the confidence interval for the mean monthly return.
Coach's Explanation: When computing the confidence interval for individual observations, we use the sample standard deviation. However, when computing the confidence interval for the mean, we use standard error of the sample mean, which is sample standard deviation divided by the square root of the sample size.
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Location: 2027\L1\Vol-1\Pg.381: Module 8
Textbook Quote: The Return and Risk of a Financial Portfolio
Coach's Explanation: There is an incredible amount of duplication between this module and Modules 1 & 2 of Volume9.
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Location: 2027\L1\Vol-1\Pg.393: Bottom of Exhibit 8
Textbook Quote: As the weight of the MSCI Emerging Markets Index increases…portfolio risk and return decrease first …
Correction: As the weight of the MSCI Emerging Markets Index increases…portfolio risk decreases whereas portfolio return increases first…
Coach's Explanation: As we move from P11 to P9, we can see clearly that return increases. In fact, the return increases continuously as we the weight of the MSCI Emerging Market Index increases. However, it’s portfolio risk that initially decreases, and then begins to increase beyond P9.
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Location: 2027\L1\Vol-1\Pg.394: Top of page:
Textbook Quote: As we move along the frontier, portfolio risk decreases more than the decrease in portfolio return.
Correction: The statement should be more specific
Coach's Explanation: As we move left along the frontier, portfolio risk decreases more than the decrease in portfolio return.
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Location: 2027\L1\Vol-1\Pg.432/433: Part1
Textbook Quote: The answer selects Investment A because it yields the lowest negative utility.
Correction: Even if the utility is least negative, the fact that its negative would not make it eligible for a risk averse investor.
Coach's Explanation: Since all the investments in this question yield a negative utility, none should be selected. The investor would be better off holding cash, where utility is zero.
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Location: 2027\L1\Vol-1\Pg.443: Part1
Textbook Quote: The line depicting the total risk and expected return of portfolio combinations of a risk-free asset and any risky asset..
Correction: The Capital Allocation Line combines the risk-free asset with the Optimal Risky Portfolio, and not just any risky asset.
Coach's Explanation: The whole point of the Capital Allocation Line is to identify the optimal risky portfolio, which when combined with the risk-free asset, will yield the highest return per unit of risk (i.e. highest Sharpe).
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Location: 2027\L1\Vol-1\Pg.447: Question1
Coach's Explanation: This is an exact replication of 2027\L1\Vol-1\Pg.411\Part5. They should at least change the numbers.
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Location: 2027\L1\Vol-1\Pg.449: Question 9:
Textbook Quote: The answer depicts variance as a percent (%)
Correction: (%) applies to standard deviation, not variance figures.
Coach's Explanation: After we take the square root of variance, the resulting standard deviation will be in the same format as the underlying variable. For example, if the variable being analyzed is return (%), then the standard deviation will be in (%), whereas if the variable being analyzed is price ($), then standard deviation will be in ($) as well.
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Location: 2027\L1\Vol-1\Pg.463: Bottom of page:
Textbook Quote: The 95% confidence level parametric VaR, assuming normal distribution, uses a critical value of 1.96.
Correction: A 95% VaR results in a single tail area of 5%, which corresponds with a critical value of 1.65, not 1.96.
Coach's Explanation: VaR is a measure of downside risk; therefore, it only looks at the left tail. Therefore, with a 95% VaR, the entire 5% is allotted to the left tail. Consequently, a 5% left tail occurs (-1.65) standard deviations below the mean. The 1.96 represents critical values for a two-tailed 95% confidence interval (which is different from VaR).
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Location: 2027\L1\Vol-1\Pg.511: Question 5:
Textbook Quote: Find the coefficient of determination
Correction: The coefficient of determination is already given in the case.
Coach's Explanation: This is a weak effort in coming up with good practice questions.
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Location: 2027\L1\Vol-1\Pg.567: Question 9:
Textbook Quote: If energy prices decrease by 1.0%...
Correction: The question should be more specific with regards to whether it is referring to the price of renewable or non-renewable energy (as both are mentioned in the case).
