Lec 1 - research in finance and essentials of econometrics Flashcards

1
Q

What is theoretical research?

A

A system of ideas trying to explain something, especially one based on general principles of the objects trying to be explained:
- On average
- In principle
- Probability

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

What are examples of theoretical research in the real world?

A

Relation between individual stock return and market return
CAPM

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

What is empirical research?

A

Empirical means verifiable by observations, experiences, and evidence (rather than theory)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

What do you test in empirical analysis?

A

Predictions of a theory
- When findings are consistent with theory’s predictions, you have good level of confidence to believe the theory is right
- When findings are inconsistent with predicitions, a theory is rejected

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

What is a clinical study?

A

A study based on 1 case (you can have more than once company e.g a takeover has 2)
- Disney’s takeover of Marvel
- Marvel’s IPO
- Steve Job’s death in 2012

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

What are the benefits and drawbacks of clinical study?

A

Benefit:
- In-depth analysis is possible
Drawback:
Difficult to generalise to a broader group

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

What is a good example of a clinical study?

A

Lys and Vincent 1995

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

What is a large sample study?

A

Based on a large sample of similar cases
- Sample of IPO companies
- Sample of bidders in M&A transactions
Answers questions:
- What’s the average long-term performance of IPO firms?
- On average do bidders gain or lose?

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

What are the benefits and drawbacks of large sample study?

A

Benefit:
- Can make general conclusions
Drawback:
- Costly to conduct very detailed analyses of each case

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

What is a good example of a large sample study?

A

Gregory 1999 and Gao 2011

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

What is a Steve Jobs example of hypothesis testing?

A

The event would have negative impact on share price
Null: Apple’s (abnormal) share return on 5th Oct is non-negative
Alternative: Apple’s (abnormal) share return on 5th Oct is negative

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

How to test the Steve Jobs hypothesis?

A

Event study methodology
- Reject null in favour of alternative hypothesis, if Apple’s abnormal return is significantly negative upon the announcement
- Fail to reject the null hypothesis, if Apple’s abnormal return is insignificant or significantly positive upon the announcement
- One-tailed test

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

When do you perform a one-tailed test?

A

When the hypotheised value deviates from the null in only one direction

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

When do you perform a two-tailed test?

A

If the hypothesised value may deviate from the null in either direction

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

What are the characteristics of a two-tailed test?

A
  • Stricter
  • Fixed significance level - if a hypothesis is rejected in a two-tailed test, it must be rejected in a one-tailed test, ceteris parabus (this doesn’t work the other way)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

When can a null hypothesis get rejected?

A

With a confidence level less than 100%
- Required level of confidence is 95% or 99% (99% being higher)

17
Q

What is a random variable?

A

Numerical realisation of an underlying distribution
- Distribution that consists of the possible outcomes and their respective probabilities (stock return of the next day)
- Beta and abnormal returns are random variables

18
Q

What is statistical significance?

A

Level of signifiance = 1 - level of confidence
E.g:
Statistical significance 1% = 99% level of confidence
Statistical signifiance 5% = 95% level of confidence
1% is a higher level of statistical significance

19
Q

How do you test statistical significance?

A

Compare the test statistic and the critical value

20
Q

What are the test statistics for a random variable?

A

A figure that summarises the information in the data on the random variable
- Reduces all information to a figure to draw inferences
- Is also a random variable
- Formula given by staticians

21
Q

What is the critical value?

A

A specific value on the support of the distribution of the test statistic

22
Q

What happens when a test statistic falls beyond a critical value?

A
  • Reject the null hypothesis at the corresponding level of significance
23
Q

Why does the critical value vary?

A
  • Type of distributions random variable follows
  • Type of test (one or two-tailed)
  • Degrees of freedom of data
24
Q

What is a type 1 error?

A

When you reject a null hypothesis that is true

25
Q

What is a type 2 error?

A

When you fail to reject a null hypothesis that is false

26
Q

What is the power of test?

A

Measures the power of test in picking up the hypothesised effect
If a test has high (low) power, it has a low (high) probability of making a type 2 error

27
Q

How is the power of test measured?

A

Measured by 1 - Probability of making a type 2 error