| Compute the cross-section loadings of yields of a canonical A0_N model ("joint Q" models) | A0N__computeBnAn_jointQ |
| Compute the cross-section loadings of yields of a canonical A0_N model ("sep Q" models) | A0N__computeBnAn_sepQ |
| Compute the maximum likelihood function (joint Q models) - Bootstrap version | A0N_MLEdensity_WOE__jointQ_Bootstrap |
| Compute the maximum likelihood function ("joint Q" models for separate Sigma estimation) - Bootstrap version | A0N_MLEdensity_WOE__jointQ_sepSigma_Bootstrap |
| Compute the maximum likelihood function ("sep Q" models) - Bootstrap version | A0N_MLEdensity_WOE__sepQ_Bootstrap |
| Map auxiliary (unconstrained) parameters a to constrained parameters b | aux2true |
| Estimate an unbiased VAR(1) using stochastic approximation (Bauer, Rudebusch and Wu, 2012) | Bias_Correc_VAR |
| Generates the bootstrap-related outputs | Bootstrap |
| Builds the confidence bounds and graphs (Bootstrap set) | BootstrapBoundsSet |
| Transform a number bounded between a lower bound and upper bound to x by: | bound2x |
| Replications of the JPS (2014) outputs by Bauer and Rudebusch (2017) | BR_jps_out |
| Transform B_spanned into B_unspanned for jointQ models | BUnspannedAdapJoint |
| Transform B_spanned into B_unspanned for sepQ models | BUnspannedAdapSep |
| Obtain the full form of B unspanned for "sep Q" models within the bootstrap setting | BUnspannedAdapSep_BS |
| Check whether one element is a subset of another element | contain |
| Prepare the GVARFactors database | DatabasePrep |
| Retrieve data from Excel and build the database used in the model estimation | DataForEstimation |
| Prepare the factor set for GVAR models (Bootstrap version) | DataSet_BS |
| Computes numerical first order derivative of f(x) | df__dx |
| Estimate a VAR(1) - suited to Bauer, Rudebusch and Wu (2012) methodology | estVARbrw |
| Use function f to generate the outputs from a ATSM | f_with_vectorized_parameters |
| Data: Risk Factors for the GVAR - Candelon and Moura (2021) | FactorsGVAR |
| Creates the confidence bounds and the graphs of FEVDs and GFEVDs after bootstrap ("joint Q" models) | FEVDandGFEVDbs_jointQ |
| Creates the confidence bounds and the graphs of FEVDs and GFEVDs after bootstrap (JLL-based models) | FEVDandGFEVDbs_jointQ_Ortho |
| Creates the confidence bounds and the graphs of FEVDs and GFEVDs after bootstrap ("sep Q" models) | FEVDandGFEVDbs_sepQ |
| FEVDs graphs for orthogonalized risk factors of JLL-based models | FEVDgraphsJLLOrtho |
| FEVDs graphs for ("joint Q" models) | FEVDgraphsJoint |
| FEVDs graphs for ("sep Q" models) | FEVDgraphsSep |
| FEVDs for "joint Q" models | FEVDjoint |
| FEVDs after bootstrap for "joint Q" models | FEVDjoint_BS |
| Orthogonalized FEVDs for JLL models | FEVDjointOrthogoJLL |
| FEVDs after bootstrap for JLL-based models | FEVDjointOrthogoJLL_BS |
| FEVDs for "sep Q" models | FEVDsep |
| FEVDs after bootstrap for "sep Q" models | FEVDsep_BS |
| Model fit graphs for ("joint Q" models) | FitgraphsJoint |
| Model fit graphs for ("sep Q" models) | FitgraphsSep |
| Performs state rotations | FMN__Rotate |
| Gather bond yields forecasts for all the model types | ForecastYields |
| Bond yields forecasts ("joint Q" models) | ForecastYieldsJointQ |
| Bond yields forecasts ("sep Q" models) | ForecastYieldsSepQ |
| Set up the vector-valued objective function (Point estimate) | Functionf |
| Set up the vector-valued objective function (Bootstrap) | Functionf_Boot |
| computes the density function of a gaussian process | GaussianDensity |
| Generate M data sets from VAR(1) model | genVARbrw |
| Extract the parameter values from varargin | getpara |
| Obtain the auxiliary values corresponding to each parameter, its size and its name | getx |
| GFEVDs graphs for orthogonalized risk factors of JLL-based models | GFEVDgraphsJLLOrtho |
| GFEVDs graphs for "joint Q" models | GFEVDgraphsJoint |
| GFEVDs graphs for ("sep Q" models) | GFEVDgraphsSep |
| GFEVDs for "joint Q" models | GFEVDjoint |
| GFEVDs after bootstrap for "joint Q" models | GFEVDjoint_BS |
| Orthogonalized GFEVDs for JLL models | GFEVDjointOrthoJLL |
| GFEVDs after bootstrap for JLL-based models | GFEVDjointOrthoJLL_BS |
| GFEVDs for "sep Q" models | GFEVDsep |
| GFEVDs after bootstrap for "sep Q" models | GFEVDsep_BS |
| GIRFs graphs for orthogonalized risk factors of JLL-based models | GIRFgraphsJLLOrtho |
| GIRFs graphs for ("joint Q" models) | GIRFgraphsJoint |
| GIRFs graphs for ("sep Q" models) | GIRFgraphsSep |
| GIRFs for "joint Q" models | GIRFjoint |
| GIRFs after bootstrap for "joint Q" models | GIRFjoint_BS |
| Orthogonalized GIRFs for JLL models | GIRFjointOrthoJLL |
| GIRFs after bootstrap for JLL-based models | GIRFjointOrthoJLL_BS |
| GIRFs for "sep Q" models | GIRFSep |
| GIRFs after bootstrap for "sep Q" models | GIRFSep_BS |
| Generate the graphical outputs for the selected models (Point estimate) | GraphicalOutputs |
| Estimate a GVAR(1) and a VARX(1,1,1) | GVAR |
| Find the indexes of the spanned factors | IdxAllSpanned |
| Extract the indexes related to the spanned factors in the variance-covariance matrix | IdxSpanned |
| Generates several inputs that are necessary to build the likelihood function | InputsForMLEdensity |
| Generates several inputs that are necessary to build the likelihood function - Bootstrap version | InputsForMLEdensity_BS |
| Collect the inputs that are used to construct the numerical and the graphical outputs | InputsForOutputs |
| Creates the confidence bounds and the graphs of IRFs and GIRFs after bootstrap ("joint Q" models) | IRFandGIRFbs_jointQ |
| Creates the confidence bounds and the graphs of IRFs and GIRFs after bootstrap (JLL-based models) | IRFandGIRFbs_jointQ_Ortho |
| Creates the confidence bounds and the graphs of IRFs and GIRFs after bootstrap ("sep Q" models) | IRFandGIRFbs_sepQ |
| IRFs graphs for orthogonalized risk factors of JLL-based models | IRFgraphsJLLOrtho |
| IRFs graphs for ("joint Q" models) | IRFgraphsJoint |
| IRFs graphs for ("sep Q" models) | IRFgraphsSep |
| IRFs for "joint Q" models | IRFjoint |
| IRFs after bootstrap for "joint Q" models | IRFjoint_BS |
| Orthogonalized IRFs for JLL models | IRFjointOrthoJLL |
| IRFs after bootstrap for JLL-based models | IRFjointOrthoJLL_BS |
| IRFs for "sep Q" models | IRFsep |
| IRFs after bootstrap for "sep Q" models | IRFsep_BS |
| Set of inputs present at JLL's P-dynamics | JLL |
| Impose stationarity under the Q-measure | K1XQStationary |
| Eliminates the @ | killa |
| Generate the labels of the spanned factors | LabelsSpanned |
| Generate the labels of the star variables | LabelsStar |
| Generates the labels factors | LabFac |
| Concatenate the model-specific inputs in a list | ListModelInputs |
| Find mean or median of OLS when DGP is VAR(1) | m_var |
| Create a vector of numerical maturities in years | Maturities |
| Compute the maximum likelihood function ("joint Q" models) | MLEdensity_jointQ |
| Compute the maximum likelihood function ("joint Q" models for separate Sigma estimation) | MLEdensity_jointQ_sepSigma |
| Compute the maximum likelihood function ("sep Q" models) | MLEdensity_sepQ |
| Replications of the JPS (2014) outputs by the MultiATSM package | ModelPara |
| ATSM Package | MultiATSM |
| Construct the model numerical outputs (model fit, IRFs, GIRFs, FEVDs, GFEVDs, and risk premia decomposition) | NumOutputs |
| Numerical outputs (IRFs, GIRFs, FEVD, and GFEVD) for bootstrap | NumOutputs_Bootstrap |
| Peform the minimization of mean(f) | Optimization |
| Peform the minimization of mean(f) (adapted for the bootstrap setting) | Optimization_Boot |
| Numerical outputs (variance explained, model fit, IRFs, GIRFs, FEVDs, GFEVDs and risk premia decomposition) for "joint Q" models | OutputConstructionJoint |
| Gathers all the model numerical ouputs after bootstrap for "joint Q" models | OutputConstructionJoint_BS |
| Numerical outputs (variance explained, model fit, IRFs, GIRFs, FEVDs, GFEVDs, and risk premia decomposition) for "sep Q" models | OutputConstructionSep |
| Gathers all the model numerical ouputs after bootstrap for "sep Q" models | OutputConstructionSep_BS |
| Create the variable labels used in the estimation | ParaLabels |
| Weigth matrix from principal components (matrix of eigenvectors) | pca_weights_one_country |
| Compute some key parameters from the P-dynamics (Bootstrap set) | PdynamicsSet_BS |
| Transform a positive number y to back to x by: | pos2x |
| Restricted OLS regression | Reg__OLSconstrained |
| Estimate the risk-neutral feedbak matrix K1Q using linear regressions | Reg_K1Q |
| Exclude series that contain NAs | RemoveNA |
| Data: Risk Factors - Candelon and Moura (2021) | RiskFactors |
| Spanned and unspanned factors plot | RiskFactorsGraphs |
| Builds the complete set of time series of the risk factors (spanned and unspanned) | RiskFactorsPrep |
| Compute the root mean square error ("joint Q" models) | RMSEjoint |
| Compute the root mean square error ("sep Q" models) | RMSEsep |
| Killan's VAR stationarity adjustment | shrink_Phi |
| Compute the country-specific spanned factors | Spanned_Factors |
| Gather all spanned factors ("joint Q" models) | SpannedFactorsjointQ |
| Gather all spanned factors ("sep Q" models) | SpannedFactorsSepQ |
| Compute the square root of a matrix | sqrtm_robust |
| Generates the star variables necessary for the GVAR estimation | StarFactors |
| Decomposition of yields into the average of expected future short-term interest rate and risk premia for "joint Q" models | TermPremiaDecompJoint |
| Decomposition of yields into the average of expected future short-term interest rate and risk premia for "joint Q" models | TermPremiaDecompSep |
| Term Premia decomposition graphs for "joint Q" models | TPDecompGraphJoint |
| Term Premia decomposition graphs for "joint Q" models | TPDecompGraphSep |
| Data: Trade Flows - Candelon and Moura (2021) | TradeFlows |
| Compute the transition matrix required in the estimation of the GVAR model | Transition_Matrix |
| Map constrained parameters b to unconstrained auxiliary parameters a. | true2aux |
| converts the vectorized auxiliary parameter vector x to the parameters that go directly into the likelihood function. | update_para |
| Estimates a VAR(1) | VAR |
| Percentage explained by the spanned factors of the variations in the set of observed yields for "joint Q" models | VarianceExplainedJoint |
| Percentage explained by the spanned factors of the variations in the set of observed yields for "sep Q" models | VarianceExplainedSep |
| Transform x to a number bounded btw lb and ub by: | x2bound |
| Transform x to a positive number by: y = log(e^x + 1) | x2pos |
| Data: Yields - Candelon and Moura (2021) | Yields |
| Fit yields for all maturities of interest | YieldsFitAllJoint |
| Fit yields for all maturities of interest | YieldsFitAllSep |
| Computes two measures of model fit for bond yields | YieldsFitJoint |
| Computes two measures of model fit for bond yields | YieldsFitsep |
