Let assume invoice amount 1000$ 15 Dec 2015 Invoice @10MXN/$ =10000MXN ON YEAR END 31 DEC 2015 REVALUE AT 12MXN/$ = 12000 MXN On payment date 20th DEC 2015 VALUED AT 11.5MXN/$ = 11500 MXN NET AMOUJT WILL BE GAIN OF 2000-500 =1500MXN
Let assume invoice amount 1000$
15 Dec 2015Invoice @10MXN/$ =10000MXN
ON YEAR END 31 DEC 2015 REVALUE AT 12MXN/$ = 12000 MXN
On payment date 20th DEC 2015 VALUED AT 11.5MXN/$ = 11500 MXN
1. “Whenever we estimate a regression, we must assume that the regression has the correct functional form. This assumption can fail in several ways: Omitted variable(s). One or more important variables could be omitted from regression. Inappropriate variable scaling. One or more of the regression vaRead more
1. “Whenever we estimate a regression, we must assume that the regression has the correct functional form. This assumption can fail in several ways:
Omitted variable(s). One or more important variables could be omitted from regression.
Inappropriate variable scaling. One or more of the regression variables may need to be transformed (for example, by taking the natural logarithm of the variable) before estimating the regression.
Inappropriate data pooling. The regression model pools data from different samples that should not be pooled.”
2. “In models that use time-series data to explain the relations among different variables, it is particularly easy to violate Regression Assumption 3: that the error term has mean 0, conditioned on the independent variables. If this assumption is violated, the estimated regression coefficients will be biased and inconsistent.
Three common problems that create this type of time-series misspecification are:
including lagged dependent variables as independent variables in regressions with serially correlated errors;
including a function of a dependent variable as an independent variable, sometimes as a result of the incorrect dating of variables; and
independent variables that are measured with error.”
3. “the most frequent source of misspecification in linear regressions that use time series from two or more different variables is nonstationarity. Very roughly, nonstationarity means that a variable’s properties, such as mean and variance, are not constant through time. We will postpone our discussion about stationarity to the later coverage on time-series analysis, but we can list some examples in which we need to use stationarity tests before we use regression statistical inference.
Relations among time series with trends (for example, the relation between consumption and GDP).
Relations among time series that may be random walks (time series for which the best predictor of next period’s value is this period’s value). Exchange rates are often random walks.”
Excerpt From
2022 CFA Program Level II Volume 1 Quantitative Methods and Economics
CFA Institute
This material may be protected by copyright.
If right now boom is going on expected inflation will be higher for short term but in the long tern we expect that the economy will fall from boom to recession (business cycle) so expected inflation will fall for long term.
If right now boom is going on expected inflation will be higher for short term but in the long tern we expect that the economy will fall from boom to recession (business cycle) so expected inflation will fall for long term.
“There may be instances in which a member or candidate is hired by an employer on a “part-time” basis. “Part-time” status applies to employees who do not commit the full number of hours required for a normal work week. Members and candidates should discuss possible limitations to their abilities toRead more
“There may be instances in which a member or candidate is hired by an employer on a “part-time” basis. “Part-time” status applies to employees who do not commit the full number of hours required for a normal work week. Members and candidates should discuss possible limitations to their abilities to provide services that may be competitive with their employer during the negotiation and hiring process. The requirements of Standard IV(B) would be applicable to limitations identified at that time.”
Excerpt From
2022 CFA Program Level II Volume 6 Portfolio Management and Ethical and Professional Standards
CFA Institute
This material may be protected by copyright.
n the chapter, they’ve considered model misspecification in silos, as in they didn’t consider the effects of multicollinearity when discussing the OVB. In practicality, there is something called Bias Variance Tradeoff. Adding a correlated independent variable increases the risk of multicollinearity,Read more
n the chapter, they’ve considered model misspecification in silos, as in they didn’t consider the effects of multicollinearity when discussing the OVB.
In practicality, there is something called Bias Variance Tradeoff. Adding a correlated independent variable increases the risk of multicollinearity, but omitting the same leads to OBV……a tradeoff is required.
so I think you should remember this statement instead.
Capital Budgeting- Corporate Finance- CFA Leve 2
The project specific Kc.
The project specific Kc.
See lessValuing Currency Swap
FRA CFA L2 Multinational Operations
Let assume invoice amount 1000$ 15 Dec 2015 Invoice @10MXN/$ =10000MXN ON YEAR END 31 DEC 2015 REVALUE AT 12MXN/$ = 12000 MXN On payment date 20th DEC 2015 VALUED AT 11.5MXN/$ = 11500 MXN NET AMOUJT WILL BE GAIN OF 2000-500 =1500MXN
Let assume invoice amount 1000$
15 Dec 2015 Invoice @10MXN/$ =10000MXN
ON YEAR END 31 DEC 2015 REVALUE AT 12MXN/$ = 12000 MXN
On payment date 20th DEC 2015 VALUED AT 11.5MXN/$ = 11500 MXN
NET AMOUJT WILL BE GAIN OF 2000-500 =1500MXN
See lessValue of Swap
Model misspecification
1. “Whenever we estimate a regression, we must assume that the regression has the correct functional form. This assumption can fail in several ways: Omitted variable(s). One or more important variables could be omitted from regression. Inappropriate variable scaling. One or more of the regression vaRead more
1. “Whenever we estimate a regression, we must assume that the regression has the correct functional form. This assumption can fail in several ways:
2. “In models that use time-series data to explain the relations among different variables, it is particularly easy to violate Regression Assumption 3: that the error term has mean 0, conditioned on the independent variables. If this assumption is violated, the estimated regression coefficients will be biased and inconsistent.
Three common problems that create this type of time-series misspecification are:
3. “the most frequent source of misspecification in linear regressions that use time series from two or more different variables is nonstationarity. Very roughly, nonstationarity means that a variable’s properties, such as mean and variance, are not constant through time. We will postpone our discussion about stationarity to the later coverage on time-series analysis, but we can list some examples in which we need to use stationarity tests before we use regression statistical inference.
Excerpt From
See less2022 CFA Program Level II Volume 1 Quantitative Methods and Economics
CFA Institute
This material may be protected by copyright.
Economics and Investment Markets- PM- Cfa level 2
If right now boom is going on expected inflation will be higher for short term but in the long tern we expect that the economy will fall from boom to recession (business cycle) so expected inflation will fall for long term.
If right now boom is going on expected inflation will be higher for short term but in the long tern we expect that the economy will fall from boom to recession (business cycle) so expected inflation will fall for long term.
See lessETF- Portfolio- Level 2
yes you are right.
yes you are right.
See lessEthics- Standards for part-time workers/contractors
“There may be instances in which a member or candidate is hired by an employer on a “part-time” basis. “Part-time” status applies to employees who do not commit the full number of hours required for a normal work week. Members and candidates should discuss possible limitations to their abilities toRead more
“There may be instances in which a member or candidate is hired by an employer on a “part-time” basis. “Part-time” status applies to employees who do not commit the full number of hours required for a normal work week. Members and candidates should discuss possible limitations to their abilities to provide services that may be competitive with their employer during the negotiation and hiring process. The requirements of Standard IV(B) would be applicable to limitations identified at that time.”
Excerpt From
See less2022 CFA Program Level II Volume 6 Portfolio Management and Ethical and Professional Standards
CFA Institute
This material may be protected by copyright.
Valuation of bond with embedded options
.
.
See lessMultiple Regression
n the chapter, they’ve considered model misspecification in silos, as in they didn’t consider the effects of multicollinearity when discussing the OVB. In practicality, there is something called Bias Variance Tradeoff. Adding a correlated independent variable increases the risk of multicollinearity,Read more
n the chapter, they’ve considered model misspecification in silos, as in they didn’t consider the effects of multicollinearity when discussing the OVB.
In practicality, there is something called Bias Variance Tradeoff. Adding a correlated independent variable increases the risk of multicollinearity, but omitting the same leads to OBV……a tradeoff is required.
so I think you should remember this statement instead.
See less