nominal A nominal B = Einflation.v A' EinflationB Relative Purchasing Power Parity: High inflation rates leads to currency depreciation.. %ASA/B = inflation Xj - inflation,B Profit on
Trang 1LEVEL II SCHWESER'
ETHICAL AND PROFESSIONAL
STANDARDS
I
I (A)
I (B)
I (C )
I (D)
II
II (A)
II (B)
III
HI (A)
HI (B)
HI (C)
HI (D)
HI (E)
IV
IV (A)
IV (B)
IV (C)
V
v (A)
V (B)
V (C)
VI
VI (A)
VI (B)
VI (C)
VII
VII (A)
VII (B)
Professionalism
Knowledge of the Law
Independence and Objectivity
Misrepresentation
Misconduct
Integrity of Capital Markets
Material Nonpublic Information
Market Manipulation
Duties to Clients
Loyalty, Prudence, and Care
Fair Dealing
Suitability
Performance Presentation
Preservation of Confidentiality
Duties to Employers
Loyalty
Additional Compensation Arrangements
Responsibilities of Supervisors
Investment Analysis, Recommendations,
and Action
Diligence and Reasonable Basis
Communication with Clients and
Prospective Clients
Record Retention
Conflicts of Interest
Disclosure o f Conflicts
Priority of Transactions
Referral Fees
Responsibilities as a CFA Institute
Member or CFA Candidate
Conduct in the CFA Program
Reference to CFA Institute, CFA
Designation, and CFA Program
QUANTITATIVE METHODS
Simple Linear Regression
Correlation:
covXY
rXY =
(s x)(s y)
t-test for r (n - 2 d f): t = rVn — 2
Estimated slope coefficient:
covxy
<J\
Estimated intercept: b0 = Y — bjX
Confidence interval for predicted Y-value:
A
Y ± tc x SE of forecast
M ultiple Regression
Yi = b0 +( b 1x X l i) + (b2 x X 2l)
+ (b3 X X 3i) + £;
• Test statistical significance of b; H (): b = 0,
A /
t = y , n — k — 1 df
Reject if |t| > critical t or p-value < a
Confidence Interval: bj ± |tc X sg
SST = RSS + SSE
M SR = RSS / k
M SE = SSE / ( n - k - 1)
Test statistical significance of regression:
F = M SR / M SE with k and n — k — 1 df (1-tail)
Standard error of estimate (SEE = VM SE )
Smaller SEE means better fit
• Coefficient of determination (R2 = RSS / SST)
% of variability of Y explained by Xs; higher R2 means better fit
Regression Analysis— Problem s
• Heteroskedasticity Non-constant error variance
Detect with Breusch-Pagan test Correct with White-corrected standard errors
• Autocorrelation Correlation among error terms Detect with Durbin-Watson test; positive autocorrelation if D W < d( Correct by adjusting standard errors using Hansen method
• Multicollinearity High correlation among Xs
Detect if F-test significant, t-tests insignificant
Correct by dropping X variables
M odel M isspecification
• Omitting a variable
• Variable should be transformed
• Incorrectly pooling data
• Using lagged dependent vbl as independent vbl
• Forecasting the past
• Measuring independent variables with error
Effects o f M isspecification Regression coefficients are biased and inconsistent, lack of confidence in hypothesis tests of the coefficients or in the model predictions
Linear trend model: yt = b0 + b,t + £t Log-linear trend model: ln(yt ) = b0 + b,t + £t Covariance stationary: mean and variance don’t change over time To determine if a time series is covariance stationary, (1) plot data, (2) run an AR model and test correlations, and/or (3) perform Dickey Fuller test
Unit root: coefficient on lagged dep vbl = 1 Series with unit root is not covariance stationary First differencing will often eliminate the unit root
Autoregressive (AR) model: specified correctly if autocorrelation of residuals not significant
Mean reverting level for A R(1):
bo (1 — b j)
RM SE: square root of average squared error
Random W alk T im e Series:
xt = xt-i + £t Seasonality: indicated by statistically significant lagged err term Correct by adding lagged term
ARCH: detected by estimating:
= ao + ai^t-i + Bt Variance of ARCH series:
A 2 A A A 2 CTt+l = a0 + al£t Risk Types:
Appropriate
m ethod Distribution
Correlated Variables'
Simulations Continuous Does not matter Yes Scenario
analysis Discrete No Yes Decision trees Discrete Yes No
ECONOMICS bid-ask spread = ask quote - bid quote Cross rates with bid-ask spreads:
'A '
vC,
'A '
vC,
bid
' A '
B ,
n >
X
bid
.B
C
offer
/A X
\ B ,
V ^ /
/ T-x \
X
offer
bid B C
\ ^ /offer Currency arbitrage: “Up the bid and down the ask.” Forward premium = (forward price) - (spot price) Value of fwd currency contract prior to expiration:
(FPt — FP)(contract size)
Vt =
1 + RA days
360
\
Covered interest rate parity:
1 + Ra
F = ^
-days
360 / •0
1 + RB days
360 Uncovered interest rate parity:
e(%a s w , = R , - K
Fisher relation:
R nominal real= R + E(inflation) International Fisher Relation:
R — R nominal A nominal B = E(inflation.)v A' E(inflationB) Relative Purchasing Power Parity: High inflation rates leads to currency depreciation
%AS(A/B) = inflation Xj - inflation,B)
Profit on FX Carry Trade = interest differential - change in the spot rate of investment currency Mundell-Fleming model: Impact of monetary and fiscal policies on interest rates & exchange rates Under high capital mobility, expansionary monetary policy/restrictive fiscal policy —> low
interest rates —> currency depreciation Under low
capital mobility, expansionary monetary policy/ expansionary fiscal policy —> current account deficits —» currency depreciation
Dornbusch overshooting model: Restrictive monetary policy —» short-term appreciation of currency, then slow depreciation to PPP value Labor Productivity:
output per worker Y/L = T(K/L)‘' Growth Accounting:
growth rate in potential GDP
= long-term growth rate of technology + a (long-term growth rate of capital) + (1 - a) (long-term growth rate of labor) growth rate in potential GDP
= long-term growth rate of labor force + long-term growth rate in labor productivity Classical Growth T heory
• Real GDP/person reverts to subsistence level Neoclassical Growth T heory
• Sustainable growth rate is a function of population growth, labor’s share of income, and the rate of technological advancement
• Growth rate in labor productivity driven only by improvement in technology