Skip to content

dkassin/nascent_quant_dev

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

18 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Trading Strategy From Signals

We are taking a csv, with two columns signal and equity. Constructing a trading strategy that beats a baseline strategy that selects every signal

Overview

There are 5 jupyter notebook

  1. My Methodology and Thoughts
    • This is exactly what it sounds like, I feel like its easier to follow and trace my thought process in one (kinda) long document basically walks through my decision making, the choices i've made and why.
    • It doesn't really go into much detail on the statistics because then there wouldn't be a point of looking at the other notebooks but does highlight some stand out statistics.
    • It may be a little redudant when you're in the notebooks because it could say something similar or near similar (sorry)
  2. Data Preprocessing
  3. Understanding the signal column
    • This is crucial in how we determine our trading strategy
  4. Implementing our trading strategy and looking at the comparison to our baseline strategy
  5. Optimization
    • I kind of nerded out on this, it wasn't necessarilly asked for but I like this stuff
    • Due to time constraints i wasn't able to incorporate this into the trading strategy but was able to get some interesting results.

Getting this going

  • There are some instructions, in the data preprocessing to set up some folders that are in the gitignore
  • You will need the dataset to put in a ../data/raw/ folder to get it to read
  • You will also need to create a ../data/processed/ folder that should receive processed csvs.

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published