The Microsoft Finance Time Series Forecasting Framework, aka finnts or Finn, is an automated forecasting framework for producing financial forecasts. While it was built for corporate finance activities, it can easily expand to any time series forecasting problem!

• Automated feature engineering, feature selection, back testing, and model selection.
• Access to 25+ models. Both univariate and multivariate models.
• Azure integration to run thousands of time series in parallel within the cloud.
• Supports daily, weekly, monthly, quarterly, and yearly forecasts.
• Handles external regressors, either purely historical or historical+future values.

install.packages("finnts")

To get a bug fix or to use a feature from the development version, you can install the development version of finnts from GitHub.

# install.packages("devtools")
devtools::install_github("microsoft/finnts")

library(finnts)

# prepare historical data
hist_data <- timetk::m4_monthly %>%
  dplyr::rename(Date = date) %>%
  dplyr::mutate(id = as.character(id))

# call main finnts modeling function
finn_output <- forecast_time_series(
  input_data = hist_data,
  combo_variables = c("id"),
  target_variable = "value",
  date_type = "month",
  forecast_horizon = 3,
  back_test_scenarios = 6, 
  models_to_run = c("arima", "ets"), 
  run_global_models = FALSE, 
  run_model_parallel = FALSE
)

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