# Stock Market Prediction
Predicting the stock market using MATLAB and linear regression.
### Warning this algorithm does not make money, an error was found in our implementation
Using the opening price, high price, and low price of a stock over two weeks, as well as the current stock opening price, this model predicts the closing price of that stock with about 80% accuracy.
[Full Report Here](https://docs.google.com/document/d/1L3u5gKNvpuLp4S4-yjCEbRjHrwH91EEyRn_v-18-4_s/edit?usp=sharing)
## Repository Structure
The `data/` folder stores csv files in the form \<TICKER\>.csv which include historical data for each stock.\
This folder also has a shell script to import this from Yahoo Finance (Copyright (c) 2017 Brad Lucas, MIT License) \
The `minute/` subfolder also has a limited amount of minute data
The `backtesting-python/` folder uses backtesting libraries to test algorithms over time
The `output/` folder stores output data in text files
The `strategies/` directory stores worktrees (branches as folders) for each strategy implemented
The `live_trading/` directory live trades the algorithm using the Alpaca API
## Usage
To set up the repository, run `sh setup.sh` in the main folder of the repository. Then, if you want to trade on the market, add your API keys to the `live_trading/config/config.py` folder. \
To run the trading algorithm 24/7, run `nohup python3 live_trading/alpaca_sdk_trade.py auto`. You may want to run this on a virtual machine that stays online forever for optimal results.
matlab资源 利用线性代数和机器学习在MATLAB和Python中预测股市 仅供学习参考用代码.zip
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matlab资源 利用线性代数和机器学习在MATLAB和Python中预测股市 仅供学习参考用代码.zip （120个子文件） 
^IXIC.csv 922KB BA.csv 840KB PG.csv 828KB AAPL.csv 656KB AMD.csv 653KB GOOG.csv 286KB FTFT.csv 234KB FAZ.csv 205KB VXX.csv 204KB TVIX.csv 192KB FAS.csv 190KB SOXS.csv 186KB DRV.csv 185KB TMV.csv 185KB TMF.csv 180KB GASL.csv 178KB DRN.csv 174KB TSLA.csv 172KB SOXL.csv 168KB TQQQ.csv 168KB NUGT.csv 167KB UVXY.csv 166KB DUST.csv 166KB UGAZ.csv 157KB SVXY.csv 149KB DGAZ.csv 146KB CURE.csv 142KB JNUG.csv 122KB NUGT7d1m.csv 121KB JNUG7d1m.csv 120KB DUST7d1m.csv 119KB JDST.csv 117KB TVIX7d1m.csv 116KB GUSH.csv 95KB AMZN.csv 94KB AM.csv 88KB PCG.csv 85KB LABD.csv 82KB LABU.csv 81KB DRIP.csv 79KB SQ.csv 72KB GASX.csv 70KB DWT.csv 53KB JDST3d1m.csv 51KB DUSL.csv 46KB CWBHF.csv 24KB WEBL.csv 5KB WEBS.csv 5KB .gitmodules 158B trendfollowing.m 1KB meanreversion.m 951B README.md 2KB README.md 505B README.md 487B
Toolbox_Parameters_Quantiacs.pdf 194KB alpaca_sdk_trade.py 4KB meanReversion.py 3KB trendFollowing.py 3KB TradingSystemTemplate.py 2KB simpleTS.py 2KB rsiExample.py 2KB get-minute-data.py 1KB get-minute-data.py 1KB send_mail.py 1KB slackbot.py 48B get-yahoo-quotes.sh 2KB setup.sh 293B newworktree.sh 267B setupworktrees.sh 167B pullworktrees.sh 144B
F_ED.txt 614KB F_FV.txt 609KB F_TY.txt 608KB F_US.txt 603KB F_JY.txt 599KB F_TU.txt 592KB F_ES.txt 591KB F_BP.txt 583KB F_SF.txt 583KB F_CL.txt 582KB F_GC.txt 581KB F_C.txt 576KB F_HO.txt 575KB F_S.txt 574KB F_W.txt 571KB F_CD.txt 569KB F_SI.txt 569KB F_BO.txt 569KB F_SM.txt 569KB F_LC.txt 568KB F_NG.txt 568KB F_HG.txt 566KB F_AD.txt 565KB F_CT.txt 564KB F_KC.txt 563KB F_LN.txt 563KB F_SB.txt 562KB F_CC.txt 559KB F_FC.txt 558KB F_PL.txt 556KB共 120 条
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