Reinforcement Learning for Algorithmic Trading

Testing applications of RL to algo trading. Thus far, work includes:

Simulating stock prices as sinusoids with added noise having a specified distribution
Fetching historical stock data using the yfinance API
Implementing Q-learning algorithms using TD(0) update rules
- Single stock: Q-table
- Multiple stocks: Approximate Q-function with artificial neural network containing single hidden layer
Applying Supervised Learning to enrich/augment/improve the agent's environment for decision making
- Pull data from FRED API to construct macroeconomic environment
- Applying SVMs with various kernels to predict improvement in economic conditions for trading

Name		Name	Last commit message	Last commit date
Latest commit History 45 Commits
FRED		FRED
RL_SVM		RL_SVM
WEB_SCRAPERS		WEB_SCRAPERS
market_streams		market_streams
.gitignore		.gitignore
LICENSE		LICENSE
Qlearn_2stock_trading.py		Qlearn_2stock_trading.py
Qlearn_2stockdistrib_trading.py		Qlearn_2stockdistrib_trading.py
Qlearn_stock_test.txt		Qlearn_stock_test.txt
Qlearn_stock_trading.py		Qlearn_stock_trading.py
README.md		README.md
ag_trader.py		ag_trader.py
agco_trader.py		agco_trader.py
av_examples.py		av_examples.py
bea_examples.py		bea_examples.py
consumer_staples.py		consumer_staples.py
dow30.py		dow30.py
dqn_2stock_trading.py		dqn_2stock_trading.py
hamming74.py		hamming74.py
limit_order_book.py		limit_order_book.py
lz_comp.py		lz_comp.py
market_txt_to_json.sh		market_txt_to_json.sh
pv_fv.py		pv_fv.py
ridge_regression_example.py		ridge_regression_example.py
stock_symbols.py		stock_symbols.py
stock_trader.py		stock_trader.py
tradier_mrkt_stream.py		tradier_mrkt_stream.py
tradier_stream_connect.cpp		tradier_stream_connect.cpp
tradier_stream_connect.py		tradier_stream_connect.py
wss_market_data.py		wss_market_data.py

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