https://github.com/dopevog/stox
A Python Module That Uses ANN To Predict A Stocks Price And Also Provides Accurate Technical Analysis With Many High Potential Implementations!
https://github.com/dopevog/stox
python python-module stock-market stock-price-prediction stockmarket-ai technical-analysis
Last synced: about 2 months ago
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A Python Module That Uses ANN To Predict A Stocks Price And Also Provides Accurate Technical Analysis With Many High Potential Implementations!
- Host: GitHub
- URL: https://github.com/dopevog/stox
- Owner: dopevog
- License: mit
- Created: 2021-05-22T14:40:32.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2021-06-21T12:05:20.000Z (about 4 years ago)
- Last Synced: 2025-04-13T05:19:27.591Z (2 months ago)
- Topics: python, python-module, stock-market, stock-price-prediction, stockmarket-ai, technical-analysis
- Language: Python
- Homepage:
- Size: 396 KB
- Stars: 34
- Watchers: 1
- Forks: 3
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: License.txt
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README
Stox
⚡ A Python Module For The Stock Market ⚡
A Module to predict the "close price" for the next day and give "technical analysis". It
uses a Neural Network and the LSTM algorithm to predict the price. It uses a technical
indicator algorithm developed by the Stox team for technical analysis.
## Installation
Get it from [PyPi](https://pypi.org/project/stox/):
```
pip3 install stox
```
Clone it from github:
```
git clone https://github.com/dopevog/stox.git
cd stox
python3 setup.py install
```
## Usage
### Arguments:
```
stock (str): stock ticker symbol
output (str): 'list' or 'message' (Format Of Output)
years (int or float): years of data to be considered
chart (bool): generate performance plot
```
### Returns:
List:
```
[company name, current price, predicted price, technical analysis, date (For)]
```
Message:
```
company name
current price
predicted price
technical analysis
data (for)
```
### Examples:
#### Basic
```
import stox
script = input("Stock Ticker Symbol: ")
data = stox.stox.exec(script,'list')
print(data)
```
```
$ stox> python3 main.py
$ Stock Ticker Symbol: AAPL
$ ['Apple Inc.', 125.43000030517578, 124.91, 'Bearish (Already)', '2021-05-24']
```
#### Intermediate
```
import stox
import pandas as pd
stock_list = pd.read_csv("SPX500.csv")
df = stock_list
number_of_stocks = 505
x = 0
while x < number_of_stocks:
ticker = stock_list.iloc[x]["Symbols"]
data = stox.stox.exec(ticker,'list')
df['Price'] = data[1]
df['Prediction'] = data[2]
df['Analysis'] = data[3]
df['DateFor'] = data[4]
if data[2] - data[1] >= data[1] * 0.02:
if data[3] == "Bullish (Starting)":
df['Signal'] = "Buy"
elif data[3] == "Bullish (Already)":
df['Signal'] = "Up"
elif data[2] - data[1] <= data[1] * -0.02:
if data[3] == "Bearish (Starting)":
df['Signal'] = "Sell"
elif data[3] == "Bearish (Already)":
df['Signal'] = "Down"
else:
df['Signal'] = "None"
x = x+1
df.to_csv("output.csv")
print("Done")
```
```
$ stox> python3 main.py
$ Done
```
#### More Examples Including These Ones Can Be Found [Here](https://github.com/cstox/stox/tree/main/Examples)
### Possible Implentations
* Algorithmic Trading
* Single Stock Analysis
* Multistock Analysis
* And Much More!
## Credits
* [Dopevog](https://github.com/dopevog)
* [Gerard López](https://macosicons.com/u/Gerard%20L%C3%B3pez) - Logo
## License
This Project Has Been [MIT Licensed](https://github.com/cstox/stox/blob/main/License.txt)