Neuro Evolution Market Trader

Neuro evolution agent to trade

If you like this project you can support me.

It took me several experiments to get to this agent. I tried several deep learning architectures and technical analysis parameters.

Agent v 3.0141

The agent has the following characteristics:

Using neuro evolution
Receives OHLC as parameters
Generates RSI and MACD technical indicators to be used as parameters
Also run through a pretrained CNN buy and sell classifier to get the last set of parameters

Running

# Building notebook
docker build -t my-notebook -f docker/Dockerfile .

# Running notebook
docker run --rm -p 8888:8888 -p 6006:6006 -e JUPYTER_ENABLE_LAB=yes -v "$PWD":/home/jovyan/work my-notebook

# Optional: Tensorboard
docker exec -it <container_id> /bin/bash
tensorboard --logdir work/GA/tensorboard_Market_v3.0141/

Results

Right now the best agent v3.0141, the agent uses OHLC, RSI and MACD inputs, as well as the output of a pretrained CNN buy and sell classifier. The agent has these results applied to EURUSD with 30M candles:

Mean over backtest returns: 14.17%
Points above buy and hold mean: 12.26%
Winning Percent mean: 80%

Training

Max fitness for each generation

Mean fitness for each generation

Backtesting

2016 15M candles

2017 30M candles

2018 30M candles

RUNINFO: v3.0141 - OHLC + CNN Classifier B/S w10 15x15 + RSI&MACD

Params

layers: 16, 32, 64, 32, 16
population_size: 256
generations: 100
episodes: 10
mutation_variance: 0.005
survival_ratio: 0.3
both_parent_percentage: 0.8
one_parent_percentage: 0.1
reward_function: SimpleProfit
initial_cash: 5.0
profit_window_size: 10
close_col: 0
large_holdings_penalty: 0
lost_all_cash_penalty: -1e2
inaction_penalty: 0

Results

After 100 generations
- Max rewards: 2.508929
- Mean rewards: 0.963821
- Std rewrads: 1.400484
- Best Profit (Env 10k - 50k): 37.23
- Mean profit over all best genome (Env 10k - 50k): 14.35
Backtesting:
- Mean of 2016 + 2017 + 2018 returns: 14.17
- Points above BH mean: 12.26
- Winning Percent mean: 80%
- 2016 15M
  - Return [%] 24.8711
  - Buy & Hold Return [%] -3.144688847131627
  - Max. Drawdown [%] 2.58
  - Avg. Drawdown [%] 0.64
  - n Trades 7860
  - Win Rate [%] 81.40
  - Best Trade [%] 0.12363999999999997
  - Worst Trade [%] -0.08284999999999965
  - SQN 4.67
  - Sharpe Ratio 0.0
  - Sortino Ratio -2.1676
- 2017 30M
  - Return [%] 8.5952
  - Buy & Hold Return [%] 13.862653618570775
  - Max. Drawdown [%] 3.55
  - Avg. Drawdown [%] 0.75
  - n Trades 3160
  - Win Rate [%] 80.54
  - Best Trade [%] 0.02414999999999967
  - Worst Trade [%] -0.04445000000000032
  - SQN 2.20
  - Sharpe Ratio 0.0
  - Sortino Ratio -2.3002
- 2018 30M
  - Return [%] 9.0453
  - Buy & Hold Return [%] -5.008444957273516
  - Max. Drawdown [%] 2.72
  - Avg. Drawdown [%] 0.12
  - n Trades 3318
  - Win Rate [%] 78.99
  - Best Trade [%] 0.024970000000000603
  - Worst Trade [%] -0.038909999999999556
  - SQN 2.31
  - Sharpe Ratio 0.0
  - Sortino Ratio -2.8040

Next Steps

Develop an API
Develop a training API
Use socket inside API
Develop a front end to visualize the training

daniloaleixo / neuroevolutionmarkettrader Goto Github PK