sapphire921 / midas_pro

Python version of Mixed Data Sampling (MIDAS) regression (allow for multivariate MIDAS) :golf:

midas_pro

Python version of Mixed Data Sampling (MIDAS) regression (allow for multivariate MIDAS)

This package is developed based on midaspy. This version can be used for MIDAS regression and multivariate MIDAS regression.

A brief introduction to MIDAS model:

Mixed-data sampling (MIDAS) model is a direct forecasting tool which can relate future low-frequency data with current and lagged high-frequency indicators, and yield different forecasting models for each forecast horizon. It can flexibly deal with data sampled at different frequencies and provide a direct forecast of the low-frequency variable. It incorporates each individual high-frequency data in the regression, which solves the problems of losing potentially useful information and including mis-specification.

MIDAS model can have more than one high-frequency indicator at the same time which lead to the Multivariate-MIDAS (Multi-MIDAS) model. The high-frequency indicators considered can have different theta parameters, different sampling frequencies and different lag length.

midas_pro's Issues

error

---

TypeError Traceback (most recent call last)
Cell In[14], line 1
----> 1 y, yl, x1, x2, yf, ylf, x1f, x2f =mix_freq2(gdp.GDP_CYOY, ip.IP_YOY,lei.LEI_YOY, "3m","3m", 1, 2,
2 start_date=datetime.datetime(2011,3,31),
3 end_date=datetime.datetime(2013,3,31))

File D:\MIDAS\midas_pro-master\example\midas\mix.py:119, in mix_freq2(lf_data, hf_data1, hf_data2, x1lag, x2lag, ylag, horizon, start_date, end_date)
116 x2_rows = []
118 for lfdate in lf_data.loc[start_date:max_date].index:
--> 119 start_hf1 = hf_data1.index.get_loc(lfdate, method='bfill') # @todo Find a more efficient way
120 start_hf2 = hf_data2.index.get_loc(lfdate, method='bfill')
121 x1_rows.append(hf_data1.iloc[start_hf1 - horizon: start_hf1 - x1lag - horizon: -1].values)

TypeError: DatetimeIndex.get_loc() got an unexpected keyword argument 'method'

farmpay

may i have farmpay.csv?
because your code uses this data

DCC-MIDAS

how to caculate DCC-MIDAS model

How to use daily data to predict monthly data?

Hello! Can I use daily data to predict monthly data with this code? and how to change code? Thanks.

Mix and Ald packages

Hello,

what kind of Python library are Mix and Adl ?
Can be they used in Jupyter environment?

Thank you for paying attention to this issue,

kind regards