This post explains a Markov regime switching state space model. The bottom line is two-fold: 1) expanding states by each regime transitions and 2) collapsing each updated estimates for the next state prediction. The step 2) is necessary to fix t...

This post explains smoothing algorithm of a regime switching model, which is known as Kim (1994) smoother. It is known that smoothing algorithm is more difficult to understand than filtering algorithm. For this perspective, I give detailed deriv...

This post estimates parameters of a regime switching model directly by using R code. The same model was already implemented by using MSwM R package in the previous post. Through this hand-on example I hope we can learn the process of Hamilton fi...

This post explains how to model a regime switching (Markov switching) model which is based on Hamilton (1989). the estimation is done by 1) predicting states by each regimes, 2) constructing a likelihood from data and state predictions, and 3) u...

This post implements a R code for Carter-Kohn algorithm in a simple univariate state space model. For clear understanding of this backward sampling algorithm, only Gibbs sampling for state estimates is considered with other parameters being fixed or known. Gibbs Sampling for State Space Models in R In the previous ...

This post explains how to perform the F-test of joint parameter restrictions on a linear regression model. As an example, we use the data in Chen and Tsang (2013), who introduce so called relative Nelson-Siegel factor model to predict exchange r...

This post deals with some interesting issues regarding the VECM model. Among them are the VAR representation of VECM, the weak exogeniety restrictions and user-defined cointegrating vectors and so on. With the help of useful R packages, these is...

This post explains how to estimate and forecast a Vector Error Correction Model (VECM) model using R. The VECM model consists of VAR model (short-term dynamics) and cointegration (long-term comovement). We use the Johansen cointegration test. The co...

This post shows how to calculate the liquidity measure (gamma) of Pastor and Stambaugh (2003) using R code. For exposition purposes we use only two individual series : small firm index and ESG firm index. As expected, a PS liquidity measure for smal...

This post shows how to interpret the results of the augmented Dickey-Fuller (ADF) test easily with the help of Hank Roark's R function. His R function provides kind descriptions of the results of a unit root ADF test. I explains why this description...

This post explains how to use the augmented Dickey-Fuller (ADF) test in R. The ADF Test is a common statistical test to determine whether a given time series is stationary or not. We explain the interpretation of ADF test results from R package by m...

This post gives a brief introduction to the estimation and forecasting of a Vector Autoregressive Model (VAR) model using R . We use vars and tsDyn R package and compare these two estimated coefficients. We also consider VAR in level and VAR in diff...

This post presents a R code for pricing a bond forward. It is well known that insurance companies use it as the instrument of a duration management with lower cost. Here, a pricing formula and its implementation are provided with delta sensitivity u...

This post presents a R code for a k-fold cross validation of Lasso in the case of a gaussian regression (continuous Y). This work easily can be done by using a mean squared error. Cross Validation in Lasso : Gaussian Regression We have implem...

This post explains more details regarding cross validation of Lasso in the case of a binomial response. We implement a R code for a lasso model's cross validation. In addition, We calculate lambda.min and lambda.1se manually. Finally we compare thes...

This post shows how to use the R packages for estimating an exclusive lasso and a group lasso. These lasso variants have a given grouping order in common but differ in how this grouping constraint is functioning when a variable selection is performe...

This post shows a R counterpart of Excel VBA's MSXML2.ServerXMLHTTP related commands with which server APIs are called easily. In case of R, it is done by using httr R package. As an illustration, SQL query for retrieving swap date schedule is execu...

This post makes a user-defined R function for Adams and Deventer (1994, revised 2010) maximum smoothness forward curve for the purpose of reusing and performs robustness checks for various initial term structures. We find that every time an initial ...

This post solves Adams and Deventer (1994) maximum smoothness forward rate curve as the matrix inversion of equality constrained quadratic programming problems. We implement R code for this model and elaborate on how to get monthly forward and spot ...

This post implements Adams and Deventer (1994) approach which generates the best fitting yield curve smoothing with the principle of maximum smoothness forward rate curve. This provides a powerful closed-form solution by which we can sidestep a kink...