CFA Level I quantitative methods and fixed income practice: cram pack

Formula sheets, the key method steps for every topic and 20 practice problems, with full solutions at the back.

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1Formulas and methods

Time value of money

Future value
FV = PV·(1 + i)n
Present value
PV = FV/(1 + i)n
Several periods per year
i = r/m, N = m·n
Annuity, present value
PV = PMT·[1 − (1 + i)−n]/i
Annuity, future value
FV = PMT·[(1 + i)n − 1]/i

Method

  1. Draw a timeline with every cash flow and its timing.
  2. Match the rate to the period: a monthly rate for monthly payments.
  3. Use FV = PV·(1 + i)ⁿ for single amounts and the annuity formulas for equal payments.
  4. Check the sign and the order of magnitude of the answer.

NPV & IRR

Net present value
NPV = −C0 + Σ CFt/(1 + r)t
Equal cash flows
NPV = −C0 + CF·[1 − (1 + r)−n]/r
Internal rate of return
the r at which NPV = 0
Decision
accept when NPV > 0 (or IRR > required return)

Method

  1. List all cash flows with their year; the investment at year 0 is negative.
  2. Discount each cash flow: CFt/(1 + r)t.
  3. Add them up to get the NPV. Positive means the project earns more than r.
  4. For the IRR, find the rate that makes NPV zero by trial or interpolation.

Bond pricing & yield

Bond price
P = C·(1 − (1 + y)−n)/y + F/(1 + y)n
Semi-annual
C/2, y/2 and 2n periods
Current yield
C/P
Price and yield
yield up → price down

Method

  1. Find the coupon per period and the yield per period.
  2. Price = present value of the coupons (an annuity) + present value of the face value.
  3. For semi-annual coupons use half the coupon, half the yield and twice the periods.
  4. Check: if the yield is above the coupon rate, the price is below face value.

CAPM & WACC

CAPM
re = rf + β·(rm − rf)
WACC
E/V·re + D/V·rd·(1 − T)
Firm value
V = E + D

Descriptive statistics

Mean
x̄ = Σx/n
Sample standard deviation
s = √(Σ(x − x̄)²/(n − 1))
Median
middle value of the sorted data
z-score
z = (x − μ)/σ
Normal distribution
68% within ±1σ, 95% within ±2σ

Probability

Complement
P(not A) = 1 − P(A)
Addition rule
P(A ∪ B) = P(A) + P(B) − P(A ∩ B)
Independent events
P(A ∩ B) = P(A)·P(B)
Conditional probability
P(A|B) = P(A ∩ B)/P(B)
Binomial
P(X = k) = C(n,k)·pk(1 − p)n−k

Normal distribution

z-score
z = (x − μ)/σ
Below x
P(X < x) = Φ(z)
Above x
P(X > x) = 1 − Φ(z)
Between
Φ(z2) − Φ(z1)
Percentile
x = μ + z·σ

Method

  1. Convert the value to a z-score: z = (x − μ)/σ.
  2. Look up Φ(z), the area to the left of z.
  3. For the area to the right use 1 − Φ(z); for an interval subtract the two left areas.
  4. For a percentile, work backwards: find z for the area, then x = μ + z·σ.

Confidence intervals

σ known
x̄ ± z·σ/√n
σ unknown
x̄ ± t·s/√n, df = n − 1
Critical z
90%: 1.645, 95%: 1.96, 99%: 2.576
Sample size
n = (z·σ/E)², rounded up

Method

  1. Decide between z (population σ known) and t (only the sample s, with n − 1 degrees of freedom).
  2. Find the critical value for the confidence level.
  3. Margin of error: E = critical value × standard deviation/√n.
  4. Interval: x̄ ± E.

Hypothesis tests & confidence intervals

z-test for a mean
z = (x̄ − μ0)/(σ/√n)
t-test for a mean
t = (x̄ − μ0)/(s/√n), df = n − 1
Two-sided at 5%
reject H0 if |z| > 1.96
Confidence interval
x̄ ± z·σ/√n

Method

  1. State H₀ and H₁ and decide whether the test is one- or two-sided.
  2. Calculate the test statistic: (x̄ − μ₀)/(σ/√n), or with s and t.
  3. Compare with the critical value, or find the p-value.
  4. Reject H₀ if the statistic is beyond the critical value (p below α), and state the conclusion in words.

Linear regression & correlation

Sums of squares
Sxx = Σ(x − x̄)² = Σx² − (Σx)²/n, Sxy = Σxy − ΣxΣy/n
Slope
b = Sxy/Sxx
Intercept
a = ȳ − b·x̄
Correlation
r = Sxy/√(SxxSyy)
Residual
e = y − ŷ

2Practice problems

1.Time value of moneyMedium
years0123…11€20 000FV = ?

You invest €20 000 at 7% per year with continuous compounding. Find the value FV after 11 years.

PV = €20 000r = 7%t = 11
FV = €
2.Time value of moneyHard
months0123…36€25 000A?AAA

A loan of €25 000 is repaid with equal monthly payments over 3 years. The interest rate is 5.4% per year, compounded monthly. Find the monthly payment A.

P = €25 0005.4% / 12N = 36
A = €
3.NPV & IRRMedium
years0123−75 00030 00033 00022 000

An investment of €75 000 gives these cash flows at the end of years 1 to 3: €30 000, €33 000, €22 000. The cost of capital is 6%. Find the net present value NPV.

r = 6%CF0 = −75 000CF1 = 30 000CF2 = 33 000CF3 = 22 000
NPV = €
4.NPV & IRRHard
years012−20 0008 50013 000

A project costs €20 000 and returns €8 500, €13 000 at the end of years 1 to 2. Find its internal rate of return IRR in percent.

CF0 = −20 000CF1 = 8 500CF2 = 13 000
IRR = %
5.Bond pricing & yieldMedium
years0123…8P€60€60€60 + €1 000

A bond with a face value of €1 000 pays an annual coupon of 6% and matures in 8 years. Its yield to maturity changes from 9% to 8%. By how much ΔP does the bond price change?

F = €1 000coupon = 6%n = 8y1 = 9%y2 = 8%
ΔP = €
6.Bond pricing & yieldHard
years0123€1 154€70€70€70 + €1 070

A bond with 10 years to maturity (face value €1 000, annual coupon 7%) sells for €1 154. The issuer can call it in 3 years at a call price of €1 070. Find the yield to call YTC in percent.

F = €1 000coupon = 7%P = €1 154call price = €1 070call in 3 years
YTC = %
7.CAPM & WACCMedium
WACC = ?equity€10 000 000re​ = 10%debt€6 000 000rd​ = 3.5%T = 28%

A company has equity worth €10 000 000 and debt worth €6 000 000. Its cost of equity is 10%, its pre-tax cost of debt is 3.5% and the tax rate is 28%. Find the WACC.

E = €10 000 000D = €6 000 000re = 10%rd = 3.5%T = 28%
WACC = %
8.CAPM & WACCHard
WACC = ?equity2 000 000 × €28.00D0​ = €1.90g = 2%debt€56 000 000rd​ = 6%T = 20%

A company has 2 000 000 shares trading at €28.00; the book value of its equity is €22 400 000. It just paid a dividend of €1.90 per share, and dividends grow by 2% per year. Its debt has a market value of €56 000 000 and a pre-tax cost of 6%. The tax rate is 20%. Find the WACC, using the dividend growth model for the cost of equity.

N = 2 000 000P0 = €28.00book equity = €22 400 000D0 = €1.90g = 2%D = €56 000 000rd = 6%T = 20%
WACC = %
9.Descriptive statisticsMedium
25303540455055

Find the sample standard deviation s of the data: 26, 57, 39, 25, 59, 35.

n = 6
s =
10.Descriptive statisticsHard
z −2−1012

Exam scores are normally distributed with mean 100 and standard deviation 20. Find the z-score z of a score of 90.

μ = 100σ = 20x = 90
z =
11.ProbabilityMedium
xp(x)10.320.230.3540.15μ = 2.35

For the distribution shown, find the variance Var(X) of X.

x: 1, 2, 3, 4p(x): 0.3, 0.2, 0.35, 0.15
Var(X) =
12.ProbabilityHard
n = 12, p = 0.25: P(X ≤ 1) = ?k0123456789101112

12 components are tested, and each one fails with probability 0.25, independently. What is the probability P that at most one fails?

n = 12p = 0.25
P =
13.Normal distributionMedium
454534P = ?

The battery lifetimes are normally distributed with mean 500 h and standard deviation 40 h. What fraction lies between 454 and 534 h? Give P as a decimal.

μ = 500σ = 40x1 = 454x2 = 534
P =
14.Normal distributionHard
157164171178185192199cmtop 5%

The heights of adult men are normally distributed with mean 178 cm and standard deviation 7 cm. Drag the cut-off so the shaded top 5% is to the right of it. Find the cut-off x.

μ = 178 cmσ = 7 cm5%
x = cm
15.Confidence intervalsMedium
n = 6, s = 18.5LU = ?x̄ = 54E99%

A sample of 6 items has mean 54 and standard deviation s = 18.5. The population is roughly normal. Find the upper limit of the 99% confidence interval for the mean.

n = 6x̄ = 54s = 18.599%t(5) = 4.032
upper limit =
16.Confidence intervalsHard
σ = 12, n = ?x̄ − Ex̄ + Ex̄E = 199%

The population standard deviation is 12. How large a sample n do you need so that a 99% confidence interval for the mean has a margin of error of at most 1?

σ = 12E = 199%
n =
17.Hypothesis tests & confidence intervalsMedium
−2.0932.093t = ?df = 19

20 employees take a typing test before and after a training course. For each person the difference d = after − before (words per minute) is recorded. The mean difference is 1.45 and the standard deviation of the differences is 3.6. Find the paired test statistic t for H₀: μd = 0.

n = 20d̄ = 1.45sd = 3.6
t =
18.Hypothesis tests & confidence intervalsHard
σ = 10, n = ?x̄ − Ex̄ + Ex̄E = 2.595%

How large must a sample be so that the 95% confidence interval for a mean has a margin of error of at most 2.5? The standard deviation is 10. Find the smallest sample size n.

σ = 10E = 2.595%
n =
19.Linear regression & correlationMedium
xy14471759207723962610629122xy1520253050100

The table gives 6 paired observations of x = temperature in °C and y = ice creams sold. Their sums are given. Find Pearson's correlation coefficient r from these sums.

n = 6Σx = 129Σy = 507Σx² = 2931Σy² = 46955Σxy = 11703
r =
20.Linear regression & correlationHard
xy2454476468571056xy510455055x = 3

The table gives 5 paired observations of x = advertising spend in k€ and y = sales in k€. Use the least-squares line ŷ = a + b·x. Predict ŷ for x = 3.

n = 5x = 3
ŷ =

3Solutions

1.Time value of money

Answer: FV = 43195 €

Time value of money: money today is worth more than the same amount later, because it can earn interest. With interest rate i per period, an amount grows as FV = PV·(1 + i)n. A series of equal payments (an annuity) is valued by adding up each payment, which gives the annuity formulas.

Exponent

r·t = 0.07·11 = 0.77
e0.77 = 2.16

Future value

FV = 20 000·2.16 = €43 195.33

Answer

FV = €43 195.33
2.Time value of money

Answer: A = 753.8 €

Time value of money: money today is worth more than the same amount later, because it can earn interest. With interest rate i per period, an amount grows as FV = PV·(1 + i)n. A series of equal payments (an annuity) is valued by adding up each payment, which gives the annuity formulas.

Monthly rate and number of payments

i = 0.054000000000000006/12 = 0.0045
N = 12·3 = 36

Payment

The present value of N equal payments A is A·(1 − (1 + i)⁻ᴺ)/i. Set it equal to the loan and solve for A.

(1 + i)−N = 0.8508
A = 25 000·0.0045/(1 − 0.8508) = €753.77

Answer

A = €753.77
3.NPV & IRR

Answer: NPV = 1143 €

Net present value: discount every cash flow back to today with the required rate of return r, then add them up: NPV = Σ CFₜ/(1 + r)ᵗ. A project with NPV > 0 earns more than r and adds value. The internal rate of return (IRR) is the rate at which NPV = 0.

Present value of each cash flow

CF0 = −75 000
CF1/(1 + 0.06)1 = 30 000/1.06 = 28 301.89
CF2/(1 + 0.06)2 = 33 000/1.124 = 29 369.88
CF3/(1 + 0.06)3 = 22 000/1.191 = 18 471.62

Add them up

NPV = €1 143.39

Answer

NPV = €1 143.39

NPV is positive, so the project earns more than the required return.

4.NPV & IRR

Answer: IRR = 4.626 %

Net present value: discount every cash flow back to today with the required rate of return r, then add them up: NPV = Σ CFₜ/(1 + r)ᵗ. A project with NPV > 0 earns more than r and adds value. The internal rate of return (IRR) is the rate at which NPV = 0.

Bracket the IRR

NPV falls as the rate rises, so the IRR lies between a rate with positive NPV and one with negative NPV.

NPV(0%) = 1 500.00
NPV(5%) = −113.38

Narrow down

Linear interpolation gives a first estimate; repeating it (or a calculator's IRR function) gives the exact rate.

IRR ≈ 0 + 5·1 500.00/(1 500.00 − (−113.38)) = 4.649%
exact: NPV(4.626%) = 0 → IRR = 4.626%

Answer

IRR = 4.626%
5.Bond pricing & yield

Answer: ΔP = 51.11 €

Bond pricing: a bond’s price is the present value of its cash flows, discounted at the yield to maturity (YTM): the coupons form an annuity and the face value is paid back at maturity. P = C·(1 − (1 + y)⁻ⁿ)/y + F/(1 + y)ⁿ. When the yield is above the coupon rate the bond trades below face value, and the other way round.

Price at the old yield

C = €60.00, i = 0.09, N = 8
€60.00·(1 − 0.5019)/0.09 + €1 000·0.5019 = €332.09 + €501.87 = €833.96

Price at the new yield

C = €60.00, i = 0.08, N = 8
€60.00·(1 − 0.5403)/0.08 + €1 000·0.5403 = €344.80 + €540.27 = €885.07

Change

ΔP = 885.07 − 833.96 = €51.11

Answer

ΔP = €51.11
6.Bond pricing & yield

Answer: YTC = 3.728 %

Bond pricing: a bond’s price is the present value of its cash flows, discounted at the yield to maturity (YTM): the coupons form an annuity and the face value is paid back at maturity. P = C·(1 − (1 + y)⁻ⁿ)/y + F/(1 + y)ⁿ. When the yield is above the coupon rate the bond trades below face value, and the other way round.

Equation for the yield

1154 = 70·(1 − (1 + y)−3)/y + 1070/(1 + y)3

Solve numerically

y = 3%: €1 177.20
y = 4%: €1 145.48
YTC = 3.728%

Answer

YTC = 3.728%

The yield to maturity is 5.005%. Investors in a premium bond expect it to be called, so the lower yield to call is the more realistic one.

7.CAPM & WACC

Answer: WACC = 7.195 %

Cost of capital: CAPM gives the return shareholders require: re = rf + β·(rm − rf). The weighted average cost of capital mixes equity and debt by their market values: WACC = E/V·re + D/V·rd·(1 − T), with V = E + D. Interest is tax-deductible, hence the (1 − T).

Weights

V = €16 000 000, E/V = 0.625, D/V = 0.375

WACC

WACC = 0.625·10% + 0.375·3.5%·(1 − 0.28) = 7.195%

Answer

WACC = 7.195%
8.CAPM & WACC

Answer: WACC = 6.861 %

Cost of capital: CAPM gives the return shareholders require: re = rf + β·(rm − rf). The weighted average cost of capital mixes equity and debt by their market values: WACC = E/V·re + D/V·rd·(1 − T), with V = E + D. Interest is tax-deductible, hence the (1 − T).

Cost of equity

D1 = 1.9·1.02 = €1.94
re = 1.938/28 + 0.02 = 8.921%

Market values

E = 2 000 000·€28.00 = €56 000 000
V = €112 000 000, E/V = 0.5, D/V = 0.5

WACC

WACC = 0.5·8.921% + 0.5·6%·(1 − 0.2) = 6.861%

Answer

WACC = 6.861%
9.Descriptive statistics

Answer: s = 14.81

Descriptive statistics: the mean is the sum divided by n; the median is the middle value of the sorted data (the average of the two middle values when n is even). The sample standard deviation is s = √(Σ(x − x̄)²/(n − 1)). A z-score z = (x − μ)/σ says how many standard deviations a value lies from the mean.

Mean

x̄ = 241/6 = 40.17

Squared deviations

Σ(x − x̄)² = (−14.17)² + 16.83² + (−1.167)² + (−15.17)² + 18.83² + (−5.167)² = 1097

Standard deviation

s = √(1097/5) = 14.81

Answer

s = 14.81
10.Descriptive statistics

Answer: z = −0.5

Descriptive statistics: the mean is the sum divided by n; the median is the middle value of the sorted data (the average of the two middle values when n is even). The sample standard deviation is s = √(Σ(x − x̄)²/(n − 1)). A z-score z = (x − μ)/σ says how many standard deviations a value lies from the mean.

Standardise

z = (90 − 100)/20 = −0.5

Answer

z = −0.5
11.Probability

Answer: Var(X) = 1.128

Discrete random variables: a probability distribution lists every value x a variable can take with its probability p(x); the probabilities are between 0 and 1 and add up to 1. The expected value (mean) is E(X) = Σx·p(x), the long-run average. The variance is Var(X) = Σ(x − μ)²·p(x) = E(X²) − μ², and the standard deviation σ = √Var(X). For a linear change Y = aX + b: E(Y) = a·E(X) + b, Var(Y) = a²·Var(X) and σY = |a|·σX; adding a constant does not change the spread.

Mean

μ = 1·0.3 + 2·0.2 + 3·0.35 + 4·0.15 = 2.35

Mean of the squares

E(X²) = 1·0.3 + 4·0.2 + 9·0.35 + 16·0.15 = 6.65

Variance

Var(X) = 6.65 − 2.35² = 1.128

Answer

Var(X) = 1.128
12.Probability

Answer: P = 0.1584

Probability: with equally likely outcomes, P(A) = favourable/total. For independent events multiply: P(A and B) = P(A)·P(B). The complement often helps: P(at least one) = 1 − P(none). Binomial: in n independent trials with success probability p, P(X = k) = C(n, k)·pᵏ·(1 − p)ⁿ⁻ᵏ.

Zero and one failure

P(X = 0) = 0.7512 = 0.03168
P(X = 1) = 12·0.25·0.7511 = 0.1267

Add them

P = 0.03168 + 0.1267 = 0.1584

Answer

P = 0.1584
13.Normal distribution

Answer: P = 0.6773

Normal distribution: convert a value x to a z-score, z = (x − μ)/σ, which counts standard deviations from the mean. A z-table (or Φ(z)) gives the area to the left of z, which is P(X < x). The area to the right is 1 − Φ(z), and the area between two values is the difference of their two areas.

z-scores

z₁ = (454 − 500)/40 = −1.15
z₂ = (534 − 500)/40 = 0.85

Area between

P = Φ(0.85) − Φ(−1.15) = 0.8023 − 0.1251 = 0.6773

Answer

P = 0.6773
14.Normal distribution

Answer: x = 189.5 cm

From an area back to z: Φ(z) is the area to the left of z. For a left-tail area A, find z with Φ(z) = A in the table. A right-tail area A means Φ(z) = 1 − A. A central area A between −z and z leaves (1 − A)/2 in each tail, so Φ(z) = (1 + A)/2. For a value x, use x = μ + zσ.

Area to the left

Φ(z) = 0.95

z from the table

z ≈ 1.64

Back to the original units

x = 178 + 1.64·7 = 189.5 cm

Answer

x = 189.5 cm
15.Confidence intervals

Answer: upper limit = 84.45

Confidence interval for a mean: x̄ ± margin of error. With a known population σ the margin is z·σ/√n; with only the sample standard deviation s, use t with n − 1 degrees of freedom: t·s/√n. Critical values: z = 1.645 (90%), 1.96 (95%), 2.576 (99%). To get a margin E or smaller, you need n ≥ (z·σ/E)², rounded up.

Critical value

df = n − 1 = 5, t = 4.032

Margin of error

E = 4.032·18.5/√6 = 30.45

Interval

54 ± 30.45 → [23.55, 84.45]

Answer

upper limit = 84.45
16.Confidence intervals

Answer: n = 956

Confidence interval for a mean: x̄ ± margin of error. With a known population σ the margin is z·σ/√n; with only the sample standard deviation s, use t with n − 1 degrees of freedom: t·s/√n. Critical values: z = 1.645 (90%), 1.96 (95%), 2.576 (99%). To get a margin E or smaller, you need n ≥ (z·σ/E)², rounded up.

Solve for n

n = (2.576·12/1)² = 955.6

Round up

A sample size is a whole number, and rounding down would make the margin too large.

n = 956

Answer

n = 956
17.Hypothesis tests & confidence intervals

Answer: t = 1.801

Testing a mean: the test statistic measures how many standard errors the sample mean lies from the value claimed in H₀: z = (x̄ − μ₀)/(σ/√n) when σ is known, t = (x̄ − μ₀)/(s/√n) when it is estimated from the sample. A confidence interval is x̄ ± (critical value)·(standard error).

Standard error of the mean difference

SE = 3.6/√20 = 0.805

Test statistic

t = 1.45/0.805 = 1.801

Answer

t = 1.801

With df = 19, the two-sided 5% critical value is 2.093; |t| is smaller, so H₀ is not rejected.

18.Hypothesis tests & confidence intervals

Answer: n = 62

Testing a mean: the test statistic measures how many standard errors the sample mean lies from the value claimed in H₀: z = (x̄ − μ₀)/(σ/√n) when σ is known, t = (x̄ − μ₀)/(s/√n) when it is estimated from the sample. A confidence interval is x̄ ± (critical value)·(standard error).

Solve for n

n = (1.96·10/2.5)² = 61.47

Round up

n = 62

Answer

n = 62
19.Linear regression & correlation

Answer: r = 0.997

Least-squares regression: with x̄ and ȳ the means, Sxx = Σ(x − x̄)², Syy = Σ(y − ȳ)² and Sxy = Σ(x − x̄)(y − ȳ), the line ŷ = a + b·x has slope b = Sxy/Sxx and intercept a = ȳ − b·x̄, so it always passes through (x̄, ȳ). Pearson's correlation coefficient r = Sxy/√(Sxx·Syy) lies between −1 and 1; r² is the fraction of the variation in y explained by the line.

Centred sums

Sxy = 11703 − 129·507/6 = 802.5
Sxx = 2931 − 129²/6 = 157.5
Syy = 46955 − 507²/6 = 4114

Correlation coefficient

r = 802.5/√(157.5·4114) = 0.997

Answer

r = 0.997
20.Linear regression & correlation

Answer: ŷ = 45.4

Least-squares regression: with x̄ and ȳ the means, Sxx = Σ(x − x̄)², Syy = Σ(y − ȳ)² and Sxy = Σ(x − x̄)(y − ȳ), the line ŷ = a + b·x has slope b = Sxy/Sxx and intercept a = ȳ − b·x̄, so it always passes through (x̄, ȳ). Pearson's correlation coefficient r = Sxy/√(Sxx·Syy) lies between −1 and 1; r² is the fraction of the variation in y explained by the line.

Means

x̄ = 30/5 = 6
ȳ = 251/5 = 50.2

Sums of squares and products

Sxx = Σ(x − x̄)² = 40
Sxy = Σ(x − x̄)(y − ȳ) = 64

Regression line

b = 64/40 = 1.6
a = 50.2 − 1.6·6 = 40.6
ŷ = 40.6 + 1.6·x

Prediction

ŷ = 40.6 + 1.6·3 = 45.4

Answer

ŷ = 45.4

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