A B C D F G I J K L M N O P R S T U V X Y
A0N_MLEdensity_WOE__jointQ_Bootstrap | Compute the maximum likelihood function (joint Q models) - Bootstrap version |
A0N_MLEdensity_WOE__jointQ_sepSigma_Bootstrap | Compute the maximum likelihood function ("joint Q" models for separate Sigma estimation) - Bootstrap version |
A0N_MLEdensity_WOE__sepQ_Bootstrap | Compute the maximum likelihood function ("sep Q" models) - Bootstrap version |
A0N__computeBnAn_jointQ | Compute the cross-section loadings of yields of a canonical A0_N model ("joint Q" models) |
A0N__computeBnAn_sepQ | Compute the cross-section loadings of yields of a canonical A0_N model ("sep Q" models) |
aux2true | Map auxiliary (unconstrained) parameters a to constrained parameters b |
Bootstrap | Generates the bootstrap-related outputs |
BootstrapBoundsSet | Builds the confidence bounds and graphs (Bootstrap set) |
bound2x | Transform a number bounded between a lower bound and upper bound to x by: |
BR_jps_out | Replications of the JPS (2014) outputs by Bauer and Rudebusch (2017) |
BUnspannedAdapJoint | Transform B_spanned into B_unspanned for jointQ models |
BUnspannedAdapSep | Transform B_spanned into B_unspanned for sepQ models |
BUnspannedAdapSep_BS | Obtain the full form of B unspanned for "sep Q" models within the bootstrap setting |
contain | Check whether one element is a subset of another element |
DatabasePrep | Prepare the GVARFactors database |
DataForEstimation | Retrieve data from Excel and build the database used in the model estimation |
DataSet_BS | Prepare the factor set for GVAR models (Bootstrap version) |
df__dx | Computes numerical first order derivative of f(x) |
FactorsGVAR | Data: Risk Factors for the GVAR - Candelon and Moura (2021) |
FEVDandGFEVDbs_jointQ | Creates the confidence bounds and the graphs of FEVDs and GFEVDs after bootstrap ("joint Q" models) |
FEVDandGFEVDbs_jointQ_Ortho | Creates the confidence bounds and the graphs of FEVDs and GFEVDs after bootstrap (JLL-based models) |
FEVDandGFEVDbs_sepQ | Creates the confidence bounds and the graphs of FEVDs and GFEVDs after bootstrap ("sep Q" models) |
FEVDgraphsJLLOrtho | FEVDs graphs for orthogonalized risk factors of JLL-based models |
FEVDgraphsJoint | FEVDs graphs for ("joint Q" models) |
FEVDgraphsSep | FEVDs graphs for ("sep Q" models) |
FEVDjoint | FEVDs for "joint Q" models |
FEVDjointOrthogoJLL | Orthogonalized FEVDs for JLL models |
FEVDjointOrthogoJLL_BS | FEVDs after bootstrap for JLL-based models |
FEVDjoint_BS | FEVDs after bootstrap for "joint Q" models |
FEVDsep | FEVDs for "sep Q" models |
FEVDsep_BS | FEVDs after bootstrap for "sep Q" models |
FitgraphsJoint | Model fit graphs for ("joint Q" models) |
FitgraphsSep | Model fit graphs for ("sep Q" models) |
FMN__Rotate | Performs state rotations |
ForecastYields | Gather bond yields forecasts for all the model types |
ForecastYieldsJointQ | Bond yields forecasts ("joint Q" models) |
ForecastYieldsSepQ | Bond yields forecasts ("sep Q" models) |
Functionf | Set up the vector-valued objective function (Point estimate) |
Functionf_Boot | Set up the vector-valued objective function (Bootstrap) |
f_with_vectorized_parameters | Use function f to generate the outputs from a ATSM |
GaussianDensity | computes the density function of a gaussian process |
getpara | Extract the parameter values from varargin |
getx | Obtain the auxiliary values corresponding to each parameter, its size and its name |
GFEVDgraphsJLLOrtho | GFEVDs graphs for orthogonalized risk factors of JLL-based models |
GFEVDgraphsJoint | GFEVDs graphs for ("joint Q" models) |
GFEVDgraphsSep | GFEVDs graphs for ("sep Q" models) |
GFEVDjoint | GFEVDs for "joint Q" models |
GFEVDjointOrthoJLL | Orthogonalized GFEVDs for JLL models |
GFEVDjointOrthoJLL_BS | GFEVDs after bootstrap for JLL-based models |
GFEVDjoint_BS | GFEVDs after bootstrap for "joint Q" models |
GFEVDsep | GFEVDs for "sep Q" models |
GFEVDsep_BS | GFEVDs after bootstrap for "sep Q" models |
GIRFgraphsJLLOrtho | GIRFs graphs for orthogonalized risk factors of JLL-based models |
GIRFgraphsJoint | GIRFs graphs for ("joint Q" models) |
GIRFgraphsSep | GIRFs graphs for ("sep Q" models) |
GIRFjoint | GIRFs for "joint Q" models |
GIRFjointOrthoJLL | Orthogonalized GIRFs for JLL models |
GIRFjointOrthoJLL_BS | GIRFs after bootstrap for JLL-based models |
GIRFjoint_BS | GIRFs after bootstrap for "joint Q" models |
GIRFSep | GIRFs for "sep Q" models |
GIRFSep_BS | GIRFs after bootstrap for "sep Q" models |
GraphicalOutputs | Generate the graphical outputs for the selected models (Point estimate) |
GVAR | Estimate a GVAR(1) and a VARX(1,1,1) |
IdxAllSpanned | Find the indexes of the spanned factors |
IdxSpanned | Extract the indexes related to the spanned factors in the variance-covariance matrix |
InputsForMLEdensity | Generates several inputs that are necessary to build the likelihood function |
InputsForMLEdensity_BS | Generates several inputs that are necessary to build the likelihood function - Bootstrap version |
InputsForOutputs | Collect the inputs that are used to construct the numerical and the graphical outputs |
IRFandGIRFbs_jointQ | Creates the confidence bounds and the graphs of IRFs and GIRFs after bootstrap ("joint Q" models) |
IRFandGIRFbs_jointQ_Ortho | Creates the confidence bounds and the graphs of IRFs and GIRFs after bootstrap (JLL-based models) |
IRFandGIRFbs_sepQ | Creates the confidence bounds and the graphs of IRFs and GIRFs after bootstrap ("sep Q" models) |
IRFgraphsJLLOrtho | IRFs graphs for orthogonalized risk factors of JLL-based models |
IRFgraphsJoint | IRFs graphs for ("joint Q" models) |
IRFgraphsSep | IRFs graphs for ("sep Q" models) |
IRFjoint | IRFs for "joint Q" models |
IRFjointOrthoJLL | Orthogonalized IRFs for JLL models |
IRFjointOrthoJLL_BS | IRFs after bootstrap for JLL-based models |
IRFjoint_BS | IRFs after bootstrap for "joint Q" models |
IRFsep | IRFs for "sep Q" models |
IRFsep_BS | IRFs after bootstrap for "sep Q" models |
JLL | Set of inputs present at JLL's P-dynamics |
K1XQStationary | Impose stationarity under the Q-measure |
killa | Eliminates the @ |
LabelsSpanned | Generate the labels of the spanned factors |
LabelsStar | Generate the labels of the star variables |
LabFac | Generates the labels factors |
Maturities | Create a vector of numerical maturities in years |
MLEdensity_jointQ | Compute the maximum likelihood function ("joint Q" models) |
MLEdensity_jointQ_sepSigma | Compute the maximum likelihood function ("joint Q" models for separate Sigma estimation) |
MLEdensity_sepQ | Compute the maximum likelihood function ("sep Q" models) |
ModelPara | Replications of the JPS (2014) outputs by the MultiATSM package |
MultiATSM | ATSM Package |
NumOutputs | Construct the model numerical outputs (model fit, IRFs, GIRFs, FEVDs, and GFEVDs) |
NumOutputs_Bootstrap | Numerical outputs (IRFs, GIRFs, FEVD, and GFEVD) for bootstrap |
Optimization | Peform the minimization of mean(f) |
Optimization_Boot | Peform the minimization of mean(f) (adapted for the bootstrap setting) |
OutputConstructionJoint | Numerical outputs (variance explained, model fit, IRFs, GIRFs, FEVDs, and GFEVDs) for "joint Q" models |
OutputConstructionJoint_BS | Gathers all the model numerical ouputs after bootstrap for "joint Q" models |
OutputConstructionSep | Numerical outputs (variance explained, model fit, IRFs, GIRFs, FEVDs, and GFEVDs) for "sep Q" models |
OutputConstructionSep_BS | Gathers all the model numerical ouputs after bootstrap for "sep Q" models |
ParaLabels | Create the variable labels used in the estimation |
pca_weights_one_country | Weigth matrix from principal components (matrix of eigenvectors) |
PdynamicsSet_BS | Compute some key parameters from the P-dynamics (Bootstrap set) |
pos2x | Transform a positive number y to back to x by: |
Reg_K1Q | Estimate the risk-neutral feedbak matrix K1Q using linear regressions |
Reg__OLSconstrained | Restricted OLS regression |
RemoveNA | Exclude series that contain NAs |
RiskFactors | Data: Risk Factors - Candelon and Moura (2021) |
RiskFactorsGraphs | Spanned and unspanned factors plot |
RiskFactorsPrep | Builds the complete set of time series of the risk factors (spanned and unspanned) |
RMSEjoint | Compute the root mean square error ("joint Q" models) |
RMSEsep | Compute the root mean square error ("sep Q" models) |
SpannedFactorsjointQ | Gather all spanned factors ("joint Q" models) |
SpannedFactorsSepQ | Gather all spanned factors ("sep Q" models) |
Spanned_Factors | Compute the country-specific spanned factors |
sqrtm_robust | Compute the square root of a matrix |
StarFactors | Generates the star variables necessary for the GVAR estimation |
TradeFlows | Data: Trade Flows - Candelon and Moura (2021) |
Transition_Matrix | Compute the transition matrix required in the estimation of the GVAR model |
true2aux | Map constrained parameters b to unconstrained auxiliary parameters a. |
update_para | converts the vectorized auxiliary parameter vector x to the parameters that go directly into the likelihood function. |
VAR | Estimates a VAR(1) |
VarianceExplainedJoint | Percentage explained by the spanned factors of the variations in the set of observed yields for "joint Q" models |
VarianceExplainedSep | Percentage explained by the spanned factors of the variations in the set of observed yields for "sep Q" models |
x2bound | Transform x to a number bounded btw lb and ub by: |
x2pos | Transform x to a positive number by: y = log(e^x + 1) |
Yields | Data: Yields - Candelon and Moura (2021) |
YieldsFitJoint | Computes two measures of model fit for bond yields |
YieldsFitsep | Computes two measures of model fit for bond yields |