Project Meeting (17/11/2017)

Topics Discussed

Report Structure

1. Intro
2. Lit Review
   • Financial time series - description/properties
   • preprocessing
   • modelling - arima models
   • AI models
     • Lagramge
     • Mathew Butler’s paper
   • Neural Networks for modelling time series (this should be half of the lit review)
     • general NN
     • …
3. Problem Analysis
   • Research Hypothesis - mention using arima as baseline
   • Software Engineering
     • Requirements
     • Gantt chart
     • Ethics Statement?
4. Design and implementation - ARIMA experiments
5. Results and Evaluation
   • Put results from ARIMA experiments here
6. Appendix - all results go here

Writing workflow

Writing things up should ideally happen after immediately after performing experiment. Experiments generally should not be repeated until project is pretty much done.

Tasks Competed

• Create benchmark ARIMA models in R (python arima library proved to be harder to use).
• Created python data and experiments utils for easier importing/exporting of data and results.
• Created custom preprocessing helper function.

Tasks for Next Week

• Write results from arima forecasts in Results and Evaluation part of report
• Write Problem Analysis part for arima
• Write Design and Implementation part for arima
• Write Literature Review for arima
• Write up literature review outline in Latex and further break it down into smaller topics.
• Figure out correct formatting for project report (fonts, margins etc.) and modify document accordingly.
• Experiment with first difference univariate models .
• Experiment with decomposition univariate models.
• Create plots from hyper-parameter grid search
• Read deep learning book on RNNs.
• Read more papers.