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CFA > SS 3. Quantitative Methods: Application > Flashcards

SS 3. Quantitative Methods: Application Flashcards

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1
Q

1 - the probability of a Type II error is:

A

The power of test

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2
Q

The p-value approach is:

A

The smallest level of significance at which the null hypothesis can be rejected

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3
Q

A t-distribution has (fatter/thinner) tails than a normal distribution

A

Fatter (because the t-distribution has a standard deviation greater than 1)

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4
Q

99% probability that any sample mean obtained is within ____ standard errors of the population mean

A

Two sided: 2.58

One sided: 2.33

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5
Q

What is the major difference when using technical analysis for the bond market compared to equities?

A

Trading volume for bonds is harder to obtain

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6
Q

90% probability that any sample mean obtained is within ____ standard errors of the population mean

A

Two sided: 1.645

One sided: 1.28

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7
Q

An uptrend line can be constructed by drawing a line that connects the:

A

lows of a price chart

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8
Q

When the sample data is dependent, we need to use what kind of test?

A

A paired comparison test

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9
Q

If population standard deviation is NOT KNOWN:

Standard Error =

A

SAMPLE standard deviation
/
square root of n (sample size)

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10
Q

A downtrend line can be constructed by drawing a line that connects the:

A

Highs of the price chart

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11
Q

The sampling distribution of the sampling mean is:

A

the distribution of the means of all possible samples of a given size from a given population

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12
Q

Type I Error:

A

Rejects a true hypothesis

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13
Q

The hypothesis accepted when null hypothesis is rejected is the:

A

alternative hypothesis

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14
Q

What are the formal steps in hypothesis testing? (7)

A
  1. Stating the null hypothesis and the alternative hypothesis
  2. Identifying the appropriate test statistic and its probability distribution
  3. Specifying the significance level
  4. Stating the decision rule
  5. Collecting the data and calculating the test statistic
  6. Making the statistical decision
  7. Making the economic or investment decision
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15
Q

‘Observations that represent a characteristic of individuals, groups, geographical regions, or companies at a single point in time’ describes:

A

Cross sectional data

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16
Q

The general target price for a ‘head and shoulders’ pattern is:

A

The neckline minus the amplitude of the head over the neckline

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17
Q

Test statistic =

A

(sample statistic - hypothesised value)
/
standard error of the sample statistic

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18
Q

Test statistic for F-distribution:

A

F = s1^2 / s2^2 (larger/smaller)

s^2 = sample variance

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19
Q

Define ‘Sampling Error’:

A

The difference between the observed value of a statistic and the quantity it is supposed to estimate

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20
Q

The short interest ratio =

A

the amount of short interest
/
average daily volume

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21
Q

The major cycles under Elliot Wave Theory are (9):

A 
Grand supercycle
supercycle
cycle
primary
intermediate
minor
minute
minuette
subminuette
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22
Q

An estimator is:

A

a formula to calculate sample statistics

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23
Q

A sequence of data occuring at discrete and uniformly-spaced intervals is called:

A

a time series

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24
Q

Tracking risk is defined as:

A

The standard deviation of the difference between portfolio and benchmark returns

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25
Q

‘A formula to calculate sample statistics’ describes:

A

An estimator

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26
Q

A price range in which buying activity is sufficient to stop the decline in price of a security defines:

A

Support

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27
Q

For F-Test, the larger sample variance is placed on the:

A

numerator

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28
Q

Test statistic for Chi Squared distribution:

A

[(n-1) * sample variance]
/
Hypothesised variance

n-1 = degree of freedom

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29
Q

A company’s predicted stock price from an equity analysts model is a good example of:

A

A continuous random variable

A company’s predicted share price from a model could take on any value, thus is a continuous random variable. (note, a company’s share price on the stock exchange is limited to $0.01 movements, and is thus a discrete random variable).

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30
Q

The power of the test is:

A

1 - (probability of a Type II error)

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31
Q

Sampling from a database that only tracks companies currently in existence is an example of:

A

Sample selection bias (Survivorship bias)

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32
Q

As a technical analyst you are set the task of trying to identify intermarket relationships, what are you most likely to use to identify these relationships?

A

Relative Strength Analysis

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33
Q

The level of significance and the confidence level are:

A

Indirectly proportional

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34
Q

A common flow of funds indicator is the Arms Index, also called the TRIN. A value of less than 1 indicates:

A

There is more trading activity in rising stocks

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35
Q

1 - confidence level =

A

Probability of a Type 1 error

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36
Q

Sample mean - hypothesized mean
/
standard error
=

A

z-statistic

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37
Q

To standardize a random variable X, you should:

A

subtract the mean of X from X, then divide the result by the standard deviation of X

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38
Q

The power of test is the probability of:

A

rejecting the false null hypothesis

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39
Q

Name 3 Continuation patterns:

A

Triangle patterns
Rectangle patterns
Flags and pennants (minor continuation pattern)

40
Q

What is the definition of retracement in the context of technical analysis?

A

The reversal in the movement of a security’s price such that it is counter to the prevailing longer-term price trend.

41
Q

Doji:

A

A bar on a candlestick chart where the opening and closing price is the same.

42
Q

Describe the Central Limit Theorem:

A

The population mean can be statistically described by the sample mean, as long as the sample size is large

43
Q

If the level of confidence is lowered from 95% to 90%, but the allowable error and the standard deviation remain the same, what happens to the required sample size?

A

It decreases

44
Q

A multivariate normal distribution is most likely to be defined by its constituents’ means, variances and:

A

Pairwise correlations

45
Q

The t-distribution is used when the population variance is:

A

Unknown

46
Q

How many pairwise return correlations does a 20 stock portfolio have?

A

190

20 choose 2

47
Q

Formula for construction of confidence intervals:

A

Sample mean +/- z-score * Standard error

48
Q

List the 5 biases in sampling that will cause an analyst’s conclusions to be in error:

A
  1. Data mining (or data snooping)
  2. Sample Selection
  3. Time Period Bias
  4. Look Ahead Bias
  5. Survivorship bias
49
Q

95% probability that any sample mean obtained is within ____ standard errors of the population mean

A

Two sided: 1.96

One sided: 1.645

50
Q

If sampling from a NONNORMAL distribution with an UNKNOWN variance, use a:

A

t-statistic or z-statistic (large sample size only)

51
Q

What do we call the conditions under which the null hypothesis is not rejected?

A

Decision rule

The decision rule lays out the conditions under which we may compare the z values and decide whether or not to reject the hypothesis.

52
Q

In the case of a test of the difference in means of two independent samples, we use a:

A

t-distributed statistic

53
Q

Tracking error is defined as:

A

A portfolio’s gross return minus the benchmark return

54
Q

Give 4 examples of Momentum Oscillators:

A
  1. Rate of change oscillator
  2. Relative strength index
  3. Stochastic oscillator
  4. Moving average convergence/divergence oscillator (MACD)
55
Q

The probability of success of a Bernoulli random variable:

A

Stays the same with each trial

The trials are independent of each other
e.g. coin toss

56
Q

The hypothesis to be tested is the:

A

null hypothesis

57
Q

1 - significance level =

A

Degree of confidence

58
Q

The distribution of all the distinct values a statistic can have when drawn form samples of the same size from the same population is the:

A

Sampling distribution

59
Q

If sampling from a normal distribution with a KNOWN variance, use a:

A

z-statistic

60
Q

The significance level of the test (alpha) is:

A

The probability of making a Type 1 error.

61
Q

Identifying trading strategies by P/BV when BS is not available until later is an example of:

A

Look-ahead bias

62
Q

Short time periods are likely to give results that may not reflect a longer time period

Long time periods are distortive if there has been a structural change

These are examples of:

A

Time-period bias

63
Q

The _______ ______ _______ states that the sampling distribution of the mean of any independent, random variable will be normal or nearly normal, if the sample size is large enough

A

Central Limit Theroem

64
Q

Type II Error:

A

Fails to reject a false hypothesis

65
Q

The difference between statistic and estimated parameter (eg sample mean - population mean) is:

A

Sampling Error

66
Q

A quantity from or describing a population (eg population mean) is a:

A

Parameter

67
Q

A price range in which selling activity is sufficient to stop the rise in price of a security defines:

A

Resistance

68
Q

In the test comparing variances of two normally distributed populations, we use:

A

An F-distributed test statistic

69
Q

Technical traders tend to believe that the market is (efficient/not efficient)

A

Not efficient

70
Q

To draw a downtrend line, the analyst has to draw a line that connects all the prior:

A

Highs of the trend period

71
Q

If population standard deviation is KNOWN:

Standard Error =

A

POPULATION standard deviation
/
square root of n (sample size)

72
Q

For F-Test, the larger sample variance is placed on the:

A

numerator

73
Q

A function that determines the probability a random variable takes on a specific value is:

A

A probability function

E.g.
P(x) = x/5 if X = (1,2,3,4,5)
so
p(1) = 1/5 = 0.2

74
Q

A 1-sample t-test uses a t-distribution with ____ degrees of freedom

A

n - 1

75
Q

To standardise a random variable you are most likely to:

A

Subtract its mean from it and divide by one standard deviation

76
Q

If sampling from a normal distribution with an UNKNOWN variance, use a:

A

t-statistic for small sample size

t-statistic or z-statistic for large sample size

77
Q

What is it called when all the items in the population have the same chance of being selected for the sample?

A

Simple Random sampling

78
Q

_____ sampling is a modified form of stratified random sampling used to reduce sampling costs when the population is scattered over a large geographic area.

A

Cluster sampling

79
Q

The process of standardizing a normally distributed variable is:

A

Dividing the difference of mean and random variable by standard deviation.

80
Q

If sampling from a NONNORMAL distribution with a KNOWN variance, use a:

A

z-statistic (large sample size only)

81
Q

TRIN ratio =

A

(Number of advancing issues / number of declining issues)
/
(volume of advancing issues / volume of declining issues

82
Q

The Kurtosis of a normal distribution is:

A

3

83
Q

Statistical Inference is:

A

drawing conclusions about the entire population based on the statistical characteristics of a sample

84
Q

A large sample size has at least:

A

30 observations

85
Q

Drilling into data until you find something that appears to work is an example of:

A

Data-mining bias

86
Q

Name 4 Reversal patterns:

A

Head and Shoulders
Inverse Head and Shoulders
Double tops and bottoms
Triple tops and bottoms

87
Q

Give 2 examples of price-based indicators:

A
  1. Moving average

2. Bollinger bands

88
Q

Chart patterns can be categorised into two main areas, namely:

A

Reversal and Continuation

89
Q

In the context of technical analysis, the principle that states that ‘once a support level is breached, it becomes a resistance level’ is known as the:

A

change in polarity principle

90
Q

‘One particular value that is used to estimate the underlying population parameter’ describes:

A

the point estimate

91
Q

A distribution that explains the behavior of two or more dependent variables is referred to as:

A

A multivariate distribution

92
Q

As n becomes large, t-distribution approaches:

A

normal distribution

93
Q

A decrease in significance level reduces Type _ error, but increases chances of Type _ error

A

I, II

94
Q

Name 3 situations when nonparametric tests are used:

A

When the data we use do not meet distributional assumptions

When the data are given in ranks

When the hypothesis we are addressing does not concern a parameter

95
Q

Desirable properties of an estimator (3)

A

Unbiased
Efficient
Consistent

96
Q

Elliott wave theory discusses how markets move. The key elements that R. N. Elliott proposes affect the way the market moves are in waves, that are described by:

A

Fibonacci ratios

CFA (20 decks)

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