Wavelet Coherence using R

Here you can view instructions for Wavelet Coherence (CWT-based) using R:

http://rpubs.com/ibn_abdullah/rwcoher

Here is the zip file with the manual, dataset and RMarkdown document:

Download

You can refer to this article for the details on the dataset and methodology:

Nagayev, R., Disli, M., Inghelbrecht, K., & Ng, A. (2016). 
On the dynamic links between commodities and Islamic equity. 
Energy Economics, 58, 125-140.

All the best!

Best regards,

Ibn Abdullah

Wavelet Variances, Covariances, Correlations, and Cross-Correlations

Here are the instructions for Wavelet (MODWT-based) variances, 

covariances, correlations, and cross-correlations using R: LINK

To download the manual, dataset and RMarkdown file with the codes, click HERE.


For the details on the dataset, please refer to this article:

Nagayev, R., Disli, M., Inghelbrecht, K., & Ng, A. (2016). 
On the dynamic links between commodities and Islamic equity. 
Energy Economics, 58, 125-140.

All the best!

Regards,

Ibn Abdullah

Structural VAR using Eviews

TIME SERIES ECONOMETRICS WORKSHOP:

"Asymmetric Co-integration, NARDL and Structural VAR"

by Professor Mansor Ibrahim

Session 3: Structural VAR using Eviews

Types of VAR: Reduced Form (approximate) and Structural Form (based on theory)

This technique is strongly based on theoretical relationship between the variables.

Nonlinear ARDL using Eviews

TIME SERIES ECONOMETRICS WORKSHOP:

"Asymmetric Co-integration, NARDL and Structural VAR"

by Professor Mansor Ibrahim

Session 2: Nonlinear ARDL using Eviews

Asymmetric Co-integration using Eviews

TIME SERIES ECONOMETRICS WORKSHOP:

"Asymmetric Co-integration, NARDL and Structural VAR"

by Professor Mansor Ibrahim

Session 1: Asymmetric Co-integration using Eviews

List of Islamic Banks

List of Islamic banks with asset size by country (as of Year 2015):

ARDL using Microfit 5

Manuals for download:

1. Extract from Pesaran's Book "Time Series Econometrics using Microfit 5",
2. Instructions.


Bonus: VAR/VECM using Microfit 5
(The manual includes unit root tests, VAR lag order selection, cointegration tests, LRSM, VECM, VDC, Impulse-response, Persistence profile)

Other Tips and Hints

• To get the full path to a file on your computer:

1. on Windows: Locate the file --> Hold SHIFT key and RIGHT click on file --> Copy as Path

Source: HERE

2. on MacOS: Open Automator application --> Select the Service template --> Set options at the top to “Service receives selected files or folders in Finder.” --> Drag over “Copy to Clipboard.” --> Save the service with a name like “Copy Path.”

That’s it! Now you can right-click on any selection in the Finder (even multiple selections) and select Services > Copy Path and then paste the text anywhere you like.

Source: HERE

Artificial Neural Network using Matlab

Getting Data from DataStream

Markov-Switching using R

Here are the instructions for Markov Switching:

http://rpubs.com/ibn_abdullah/markovs

Here is the zip file with the manual, dataset and RMarkdown document with codes: LINK

All the best!

Best regards,

Ibn Abdullah

MGARCH-DCC using Microfit 5

1. Open Microfit,

2. Import your data: File --> Open File

Wavelet Coherence using Matlab

1. Import your data: as column vectors --> OK,

2. Download WTC (wavelet coherence) package and unzip:
http://noc.ac.uk/using-science/crosswavelet-wavelet-coherence

Quantile Regression using STATA

Why Quantile Regression?

1. Provides more complete picture on relationship between Y and X: it allows us to study the impact of independent variables on different quantiles of the dependent variable. Normal regression is based on mean of Y.
2. Robust to outliers in Y observations.
3. Estimation and inferences are distribution-free.

Application of Quantile Regression using Stata:

Panel Technique using STATA

*0. Data preparation stage:

set more off

* Download and open the dataset using Stata: LINK

* To start recording the commands and outputs:

log using Panel_log.log, replace

Tips for Stata

                                                               

Tip 1: Steps for preparing data for Stata (panel format):

If you have data in this format:

Company______Accounts______2013______2014____2015
Petronas         Total Assets         1500           1700         2000
Petronas            EBIT                  750             850          1000

An, you need to transpose the data to make it look like this:

Publication-Quality Tables in Stata

Creating Publication-Quality Tables in Stata

Stata's tables are, in general, clear and informative. However, they are not in the format or of the aesthetic quality normally used in publications. Several Stata users have written programs that create publication-quality tables. This article will discuss esttab (think "estimates table") by Ben Jann. The esttab command takes the results of previous estimation or other commands, puts them in a publication-quality table, and then saves that table in a format you cause use directly in your paper such as RTF or LaTeX. Major topics for this article include creating tables of regression results, tables of summary statistics, and frequency tables.

The estout Package

The esttab command is just one member of a family of commands, or package, called estout. In fact, esttab is just a "wrapper" for a command called estout. The estout command gives you full control over the table to be created, but flexibility requires complexity and estout is fairly difficult to use. The esttab command runs estout for you and handles many of the details estout requires, allowing you to create the most common tables relatively easily. We will also discuss estpost, which puts results like summary statistics in a form esttab can work with. The ability to handle summary statistics and frequencies in addition to regression results is one of the reasons we elected to focus this article on esttab.

Quantile regression using R

Here you can get detailed instructions for Quantile Regression using R:

http://rpubs.com/ibn_abdullah/rquantile

Here you can download a zip file with the manual,
dataset and RMarkdown document with codes: Download

All the best!

Best regards,

Ibn Abdullah

Tips for R

Here are some useful tips for R:

• To import/export data into/from R:

1. Install xlsx package: install.packages("xlsx")
2. Turn on the library: library(xlsx)
3. For example, there is excel workbook called 'mydata' and you want to upload a data from its worksheet called 'Data' : myfile = read.xlsx("mydata.xlsx", sheetName = "Data")
4. To export data from R into excel, run: write.xlsx(mydata, "myfile.xlsx")

Reference