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Capital market expectation > INtroduction & framework > Flashcards

INtroduction & framework Flashcards

1
Q

cross-sectional consistency

A

ensure internal consistency across asset classes

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2
Q

intertemporal consistency

A

ensure internal consistency across time horizons

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3
Q

Framework for Developing CME

A

(1) Specify expectations needed + time horizon
(2) Research the historical record
(3) Specify the method(s) + model(s)
(4) Determine the best sources for information needs.
(5) selected data and methods -> Interpret the current investment environment -> applying experience and judgment
(6) Provide the set of expectations needed, documenting conclusions
(7) Monitor actual outcomes and compare them with expectations, providing feedback to improve the expectations-setting process

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4
Q

3 Data Measurement Errors and Biases

A

(1) Transcription errors
(2) Survivorship bias
(3) Appraisal (smoothed) data

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5
Q

role of CME in long-term

A

(1) Formulate SAA
(2) Long-term expectations for allowable asset classes

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6
Q

role of short term of CME

A

making active investment decision

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7
Q

Limitations to using economic data

A

+ time lag (collection - distribution)
+ often revised
+ Data index re-base

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8
Q

Data measurement errors and biases

A

(1) Transcription errors
(2) Survivorship bias
(3) Appraisal (smoothed) data

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9
Q

Characteristic of historical estimates (da hoi trong mock test)

A
  1. Limitation:
    + regime changes
    + longer time period preferable
    () Adv: statistical required
    (    ) Disadv: asynchronous: (data points for different variables may not reflect exactly the same period even though they are labeled as if they do)
  2. Chatacteristic:
    + sample statistics from a longer history are more precise
    + using higher-frequency data improve the precision of sample var, cov, and correlation, but not precision of the sample mean
    + When many variables are considered, a large number of observations may be a
    statistical necessity (dat den tieu chuan thong ke can thiet).
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10
Q

Psychological Biases of forecasting in CME

A

(1) Anchoring
(2) Status quo
(3) Confirmation bias
(4) Overconfidence
(5) Prudence bias (over cautions in forecasting)
(6) Availability bias

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11
Q

3 kinds of Model Uncertainty

A

(1) Model uncertainty
(2) Parameter uncertainty
(3) Input uncertainty

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12
Q

Role of Economic Analysis

A

Connection btw Investment Outcome & Economic Output

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13
Q

Exogenous Shocks to Growth

A

events that occur outside the normal course of an economy
(1) Policy Changes
(2) New products and technologies
(3) Geopolitics
(4) Natural disasters
(5) Natural Resources/ Critical Inputs
(6) Financial Crises

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14
Q

Approaches to Economic Forecasting, Econometric Models: Advantages

A

+ Incorporate many variables
+ Can be reused (when specified)
+ Quantifiable Output (consistent relationship)

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15
Q

Approaches to Economic Forecasting, Econometric Models: disadvantages

A

+ Complex, time-consuming
+ Data may be difficult to forecast, changeable relationship
+ Output require interpretation or unrealistic
+ Not work well to forecasrt turning points
+ May give false sense of precision

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16
Q

Approaches to Economic Forecasting, Indicators: Advantages

A

+ Simple, Intuitive, Easy to interpret
+ Available Data
+ Customize Indicators to Forecasting needs

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17
Q

Approaches to Economic Forecasting, Indicators: disadvantages

A

+ inconsistent forecasting results
+ can provide false signals (da hoi mock test)
+ data revised frequently to fit business cycle better

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18
Q

Approaches to Economic Forecasting, Indicators: advantages

A

+ Less complex than econometrics
+ Flexible in mixing objective statistical analysis

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19
Q

Approaches to Economic Forecasting, Indicators: disadvantages

A

+ Subjective
+ Time-consuming
+ Complexity
+ Inconsistent view (through time)

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20
Q

transcription errors

A

errors in gathering and recording data

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21
Q

in lieu

A

= in stead of

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22
Q

Appraisal (smoothed) data characteristics:

A

+ less volatile than market-determined values
+ biased downward and correlations with other assets tend to be understated

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23
Q

model uncertainty

A

whether a selected model is structurally and/ or conceptually correct

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24
Q

Parameter uncertainty

A

quantitative model’s parameters are invariably estimated with error

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25
Q

Input uncertainty

A

whether the inputs are correct

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26
Q

data mining bias

A

repeatedly searching a dataset until a statistically significant pattern emerges.

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27
Q

Ex Post Risk

A

risk in the past

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28
Q

ex ante risk

A

risk in predict in the future

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29
Q

smoothed data

A

the unfrequent trading data

30
Q

Econometric analysis

A

the method uses statistical methods to formulate forecasting models.

31
Q

Leading indicators

A

indicators that move ahead of the business cycle with a reasonable stable lead time. >< lagging indicator (coincident)

32
Q

3 types of Economic indicators

A

(1) lagging indicators.
(2) coincident indicators (reflect current economic activity)
(3) leading indicators.

33
Q

5 phases of business cycle

A

(1) initial recovery,
(2) early expansion,
(3) late expansion,
(4) slowdown, and
(5) contraction

34
Q

initial recovery

A

(1) Duration: of a few months
(2) Business confidence: rising
(3) Government stimulus provided by low interest rates and/or budget deficits
(4) Inflation: Decelerating
(5) Output gap: but negative, Large
(6) short-term interest rates: Low or falling
(7) Bond yields: bottoming out
(8) Stock prices: Rising
(9) Cyclical, riskier assets such as small-cap stocks and high yield bonds: doing well
(10) Moneytary: stimulative, transition to tightening

35
Q

Early expansion

A

(1) Duration: a year to several years.
(2) inflation: Increasing growth with low
(3) confidence: Increasing
(4) short-term interest rates: Rising
(5) Output gap: is narrowing
Stable or rising bond yields.
Rising stock prices

36
Q

Late expansion

A

High confidence and employment
Output gap eliminated and economy at risk of overheating
Increasing inflation
Central bank limits the growth of the money supply
Rising short-term interest rates
Rising bond yields
Rising/peaking stock prices with increased risk and volatility.

37
Q

Slowdown

A

Duration of a few months to a year or longer
Declining confidence
Inflation still rising
Short-term interest rates at a peak
Bond yields peaking and possibly falling, resulting in rising bond prices
Possible inverting yield curve.
Falling stock prices.

38
Q

Contraction

A

Duration of 12 to 18 months
Declining confidence and profit
Increase in unemployment and bankruptcies.
Inflation topping out
Falling short-term interest rates.
Falling bond yields, rising prices
Stock prices increasing during the latter stages, anticipating the end of the recession

39
Q

7 steps to formulate capital market expectations,

A

(1) Specify asset classes & time horizon
(2) Research historical record -> driver affect past performance
(3) Identify Valuation Model
(4) Determine the best information sources
(5) Interpret current investment environment
(6) Provide necessary expectations, documenting conclusions
(7) Monitor actual outcomes and compare them with expectations

40
Q

9 problems in forecast CME

A

(1) limitations to using economic data:
(2) data measurement errors and biases
(3) limitations of historical estimates
(4) Using ex post data (after the fact) to determine ex ante (before the fact) risk and return can be problematic
(5) Biases in Analysts’ Methods
(6) Fail to account for conditioning information
(7) Misinterpretation of correlation
(8) Psychological Biases
(9) Model Uncertainty

41
Q

asynchronous data

A

du lieu ko dong bo

42
Q

2 types of Biases in Analysts’ Methods

A

(1) Data-mining bias: repeated research until statistical significant pattern
(2) Time period bias.
Eg: Evidence suggesting that small-cap stocks outperform large-cap stocks over time is very sensitive to the choice of sample period.

43
Q

time period bias

A

For example, small-cap U.S. stocks are widely thought to outperform large-cap stocks, but their advantage disappears when data from the 1970s and 1980s are excluded.

44
Q

fail to account for conditioning information

A

analysts should account for current conditions in their forecasts

45
Q

twin deficit problem

A

(1) government budget deficit
(2) current account deficit

46
Q

Application of forecast trend growth

A

(1) Forecasting returns with DCF models: incorporate the trend rate of growth
(2) Stock reuturn: Higher trend growth rates may lead to higher stock returns assuming the growth is not already reflected in stock price
(3) When we speak of higher trend growth rates, we mean the economy can grow at a faster pace before inflation becomes major concern
(4) Higher gov bond yield: Higher trend growth rates tend to generate higher government bond yields.

47
Q

3 approach to economic forecast

A

(1) Econometric Models
(2) Indicators
(3) Check list

48
Q

Advantages & Dis of econometric approach

A

Adv:
(1) Modeling can incorporate many variables.
(2) Once the model is specified, can be reused
(3) Output is quantified & base on a consistent set of relationships
Disadv:
(1) complex and time-consuming to construct
(2) dificult to forecast and relationship can change
(3) Output may require interpretation or be unrealistic
(4) It does not work well to forecast turning points.

49
Q

diffusion index

A

it is composite - a group of indicator

50
Q

Adv & Dis adv indicators

A

Adv:
(1) Economic indicators are simple, intuitive, and easy to interpret
(2) Data are often readily available from third parties
(3) Focuses primarily on identifying turning points
Disadv:
(1) History subject to frequent revision
* Current” data not reliable as input for historical analysis.
* Overfitted in-sample. Likely overstates forecast accuracy.
(2) Can provide false signals of economic outlook
(3) May provide little more than binary (no/yes)

51
Q

Description, Adv and disadv of Checklist approach

A
  1. Description: an analyst considers a series of questions.
    For example, to forecast GDP:
    + What was the latest employment report?
    + What is the central bank’s next move, given the latest information
    released?
    + What is the latest report on business investment?”
    Then the analyst uses judgment and perhaps some statistical modeling to interpret the answers and formulate a forecast. Judgment is required both in determining which factors to consider and how to interpret them.
  2. Advantage:
    + Less complex than econometrics.
    + Flexible:
    • Structural changes easily incorporated
    • Items easily added/dropped
    • Can draw on any information, from any source, as desired
      + Breadth: Can include virtually any topics
  3. Disadvantage:
    + Time-consuming
    + Subjective
52
Q

out put gap

A

= actual growth - sustainable growth

53
Q

what discount rate use when negative interest rate

A

use Taylor rate (instaed of risk free) for build up model

54
Q

effect of FP and MP to yield curve

A

Ease - ease -> steepen
Tight - ease -> less clear
Tight - tight -> Contract

55
Q

Country effects (da hoi trong Mock)

A

should capture systematic differences in the financial environment across countries

56
Q

industry effects

A

control for systematic differences in risk & performance across sector types

57
Q

characteristics of Risks in Emerging Market Equities (da hoi trong mock)

A

(1) country effects still tend to be more important than (global) industry
effects
(2) Local economic and market factors exert greater influence on risk and return
(3) the emerging market debt investor needs to focus on ability and willingness to pay specific obligations, emerging market equity investors need to focus on the many ways that the value of their ownership claims might be expropriated by the government, corporate insiders, or dominant shareholders

58
Q

Liability - relative approaches

A

(1) Liability - hedging portfolio
(2) Surplus optimization

59
Q

Transcription error

A

Errors in gathering and recording data

60
Q

GTAA

A

seeks to take advantage of pricing or valuation anomalies across multiple asset classes, typically equities, fixed income, and currencies

61
Q

What out put high-frequency data can improve ?
+ The precision of sample variances
+ covariances
+ correlations
+ Sample mean

A

Can improve:
+ The precision of sample variances
+ covariances
+ correlations
Can not improve sample mean

62
Q

when the frequency of observations increases, why the likelihood increases that data may
be asynchronous across variables ?

A

data points for different variables may not reflect exactly the same period even though they are labeled as if they do. Eg: time zone differences

63
Q

what is most serious ?
+ Model uncertainty
+ Parameter uncertainty
+ Input uncertainty

A

Model uncertainty

64
Q

Luu y cac chinh sach anh huong den Oil -> deu la Exogenous Shocks to Growth vi Oil la impotant resource

A
65
Q

Diffusion index

A

which measures how many indicators are pointing
up and how many down
Diffusion Index (DI)=(Advances−Declines)+PDIV
where:
Advances=Number of stocks moving higher
Declines=Number of stocks moving lower
PDIV=Previous DI value
​

66
Q

How fiscal policy and monetary policy mix affect nominal rate

A

+ Fiscal policy: affect real rate (tight -, loose +)
+ Money policy: affect inflation (tight -, loose +)
-> nominal interest = real rate + inflation

67
Q

inflation tăng mạnh nhất giai đoạn nào

A

chuyển từ slowdown sang contraction
Lạm phát cao kỷ lục là dấu hiệu bắt đầu của 1 cuộc suy thoái (giống như hiện tại)

68
Q

when is short term interest rate highest

A

in slowdown stage
Giống giai đoạn VN hiện tại, lãi suất huy động tăng cao kỷ lục

69
Q

early extention of yield curve

A

+ Front section: steepening
+ Back half: flattening

70
Q

contraction of yield curve

A

+ first: contraction
+ after: steepening

Capital market expectation (2 decks)

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