systemtrading's Introduction

Python_project_SystemTrading with Bank API

About

1. Strategy

Counter-trend Strategy Based On RSI

RSI = 100 * AU / (AU+AD)
RS = AU / AD
RSI Signal = moving average line of RSI

# Assuming mean reversion effect
# Used RSI(2), judged based on the closing prices of the last two days for short term
# USed RSI Signal (20 or 60) for mid-term trend

Conditions

if RSI_Signal(20) > RSI_Signal(60) and
   RSI(2) < 5 and
   Current stock price change rate compared to two days ago < -2%:
   
   Result = Buy at the current highest bid price

if RSI(2) > 80 and
   Current price > Buying Price:

   Result = Sell at the current best ask price

Universe Composition

1. Excluding ETF, preferred stock 
2. Excluding holding companies
3. Selecting companies with a sales growth rate greater than 0
4. Selecting companies with an ROE greater than 0
5. Sorting ROE and 1/PER in descending order, 
    extracting 200 companies by calculating the average of the two ranks

Backtesting

How To Run

Development Tools:    # PyCharm 2023.2.3  # Anaconda3
Programming Language: # Python
API:                  # Kiwoom Open API+
Database:             # Mysql
Crawling:             # bs4, lxml, openpyxl, numpy

Logical Structure (initialization phase)

Logical Structure (post)

Continous Development

This project continues to progress and further implements the strategy.

Commit Rule

Do not commit from/to the main branch
After committing the new branch, make a pull request to the main branch
Branch name rule:
- Development Dir/content (e.g. api/Kiwoom, Util/const)
Pull request writing rules
- Title: What was developed
- Content: Brief description of the developed content

Used MySQL with Python

1. 'Connecter' = pymysql.connect('connect options')
2. 'Cursor name' = 'Connecter'.cursor()
3. 'Cursor name'.execute("CREATE TABLE 'sentence'")
4. 'Cursor name'.execute("INSERT 'sentence'")
5. 'Connecter'.commit()
6. 'Connecter'.close()

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