INtroduction & framework Flashcards
cross-sectional consistency
ensure internal consistency across asset classes
intertemporal consistency
ensure internal consistency across time horizons
Framework for Developing CME
(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
3 Data Measurement Errors and Biases
(1) Transcription errors
(2) Survivorship bias
(3) Appraisal (smoothed) data
role of CME in long-term
(1) Formulate SAA
(2) Long-term expectations for allowable asset classes
role of short term of CME
making active investment decision
Limitations to using economic data
+ time lag (collection - distribution)
+ often revised
+ Data index re-base
Data measurement errors and biases
(1) Transcription errors
(2) Survivorship bias
(3) Appraisal (smoothed) data
Characteristic of historical estimates (da hoi trong mock test)
- 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) - 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).
Psychological Biases of forecasting in CME
(1) Anchoring
(2) Status quo
(3) Confirmation bias
(4) Overconfidence
(5) Prudence bias (over cautions in forecasting)
(6) Availability bias
3 kinds of Model Uncertainty
(1) Model uncertainty
(2) Parameter uncertainty
(3) Input uncertainty
Role of Economic Analysis
Connection btw Investment Outcome & Economic Output
Exogenous Shocks to Growth
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
Approaches to Economic Forecasting, Econometric Models: Advantages
+ Incorporate many variables
+ Can be reused (when specified)
+ Quantifiable Output (consistent relationship)
Approaches to Economic Forecasting, Econometric Models: disadvantages
+ 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
Approaches to Economic Forecasting, Indicators: Advantages
+ Simple, Intuitive, Easy to interpret
+ Available Data
+ Customize Indicators to Forecasting needs
Approaches to Economic Forecasting, Indicators: disadvantages
+ inconsistent forecasting results
+ can provide false signals (da hoi mock test)
+ data revised frequently to fit business cycle better
Approaches to Economic Forecasting, Indicators: advantages
+ Less complex than econometrics
+ Flexible in mixing objective statistical analysis
Approaches to Economic Forecasting, Indicators: disadvantages
+ Subjective
+ Time-consuming
+ Complexity
+ Inconsistent view (through time)
transcription errors
errors in gathering and recording data
in lieu
= in stead of
Appraisal (smoothed) data characteristics:
+ less volatile than market-determined values
+ biased downward and correlations with other assets tend to be understated
model uncertainty
whether a selected model is structurally and/ or conceptually correct
Parameter uncertainty
quantitative model’s parameters are invariably estimated with error
Input uncertainty
whether the inputs are correct
data mining bias
repeatedly searching a dataset until a statistically significant pattern emerges.
Ex Post Risk
risk in the past
ex ante risk
risk in predict in the future
smoothed data
the unfrequent trading data
Econometric analysis
the method uses statistical methods to formulate forecasting models.
Leading indicators
indicators that move ahead of the business cycle with a reasonable stable lead time. >< lagging indicator (coincident)
3 types of Economic indicators
(1) lagging indicators.
(2) coincident indicators (reflect current economic activity)
(3) leading indicators.
5 phases of business cycle
(1) initial recovery,
(2) early expansion,
(3) late expansion,
(4) slowdown, and
(5) contraction
initial recovery
(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
Early expansion
(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
Late expansion
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.
Slowdown
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.
Contraction
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
7 steps to formulate capital market expectations,
(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
9 problems in forecast CME
(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
asynchronous data
du lieu ko dong bo
2 types of Biases in Analysts’ Methods
(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.
time period bias
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.
fail to account for conditioning information
analysts should account for current conditions in their forecasts
twin deficit problem
(1) government budget deficit
(2) current account deficit
Application of forecast trend growth
(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.
3 approach to economic forecast
(1) Econometric Models
(2) Indicators
(3) Check list
Advantages & Dis of econometric approach
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.
diffusion index
it is composite - a group of indicator
Adv & Dis adv indicators
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)
Description, Adv and disadv of Checklist approach
- 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. - 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
- Disadvantage:
+ Time-consuming
+ Subjective
out put gap
= actual growth - sustainable growth
what discount rate use when negative interest rate
use Taylor rate (instaed of risk free) for build up model
effect of FP and MP to yield curve
Ease - ease -> steepen
Tight - ease -> less clear
Tight - tight -> Contract
Country effects (da hoi trong Mock)
should capture systematic differences in the financial environment across countries
industry effects
control for systematic differences in risk & performance across sector types
characteristics of Risks in Emerging Market Equities (da hoi trong mock)
(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
Liability - relative approaches
(1) Liability - hedging portfolio
(2) Surplus optimization
Transcription error
Errors in gathering and recording data
GTAA
seeks to take advantage of pricing or valuation anomalies across multiple asset classes, typically equities, fixed income, and currencies
What out put high-frequency data can improve ?
+ The precision of sample variances
+ covariances
+ correlations
+ Sample mean
Can improve:
+ The precision of sample variances
+ covariances
+ correlations
Can not improve sample mean
when the frequency of observations increases, why the likelihood increases that data may
be asynchronous across variables ?
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
what is most serious ?
+ Model uncertainty
+ Parameter uncertainty
+ Input uncertainty
Model uncertainty
Luu y cac chinh sach anh huong den Oil -> deu la Exogenous Shocks to Growth vi Oil la impotant resource
Diffusion index
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
How fiscal policy and monetary policy mix affect nominal rate
+ Fiscal policy: affect real rate (tight -, loose +)
+ Money policy: affect inflation (tight -, loose +)
-> nominal interest = real rate + inflation
inflation tăng mạnh nhất giai đoạn nào
chuyển từ slowdown sang contraction
Lạm phát cao kỷ lục là dấu hiệu bắt đầu của 1 cuộc suy thoái (giống như hiện tại)
when is short term interest rate highest
in slowdown stage
Giống giai đoạn VN hiện tại, lãi suất huy động tăng cao kỷ lục
early extention of yield curve
+ Front section: steepening
+ Back half: flattening
contraction of yield curve
+ first: contraction
+ after: steepening
