Wavelets and quantile methods

Wavelets & Quantile on Quantile

Wavelet Analysis is a powerful tool for compressing, processing, and analyzing data. It can be applied to extract useful information from numerous types of data, including images and audio signals in Physics, Chemistry, and Biology, and high-frequency time series in Economics and Finance.

Unlike ordinary least squares that estimate the conditional mean of the dependent variable given a set of predictor variables, quantile regression, yields valuable insights in applications such as risk management, where answers to important questions lie in modeling the tails of the conditional distribution. 

This structured training provides an excellent opportunity for scholars, bankers, and industrial data practitioners to learn and enhance their knowledge about Wavelet and quantile methods using R programming language and Matlab. 

Learning by "Researching" TM

Training Calendar

February  / - Normal Group (7-10 participants)                                    

May / - Normal Group (7-10 participants)                                           

July  / - Normal Group (7-10 participants)                                      

November  / - Normal Group (7-10 participants)       5 seats left                        




It was excellent training for me. I think Dr. Arhsian is the best in his field. He is a well-qualified person. I will recommend this institute for all my colleagues if they need it


Ass. Prof. Hitit University, Turkey

Excellent Training

Excellent training, professional moderators, highly recommended


Student Leipzig University, Leipzig


I have published 3 papers in SSCI journals based on what I have learned


Cyprus International University, Turkey

Live Training


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Video 1: Installing Wavelets package on R Studio

  (20 Minutes)

Video 2: Difference between simple and quantile regression

  (2 Minutes)

Wavelets & Quantile on Quantile

Intensive structured training to master wavelets and quantile methods for econometric modeling and data analysis using R and Matlab

Duration: Approx. 7 Hours

Training Mode: Normal group (7-10 trainees), small group (2-5 trainees), and one-to-one

Platform: online (Zoom)

Extra benefits:

  • Certified certificate after completing the training
  • 10% trainee discount on future bookings
  • Trainees become eligible to submit their papers at the MSR working paper series (SSRN and RePEc indexed).

Training content is systematic and structured as follows:

1. Introduction to R-Programming Language and R-studio Interface

2. The basic concept of Wavelet and its applications

3. Decomposition and plotting of the series using the MODWT method.

4. Wavelet correlation, wavelet covariance, and cross-wavelet correlation

5. Continuous wavelet transform and cross wavelet transform

6. Wavelet coherence  and partial wavelet coherence 

7. Introduction to quantile on quantile and quantile autoregressive distributed lags error correction model to times series

8- Granger causality in Quantile on Quantile regression

9- Non-parametric quantile methods  New