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Python Trading Algorithm

I am looking for a coder or a professional trader that has hands on experience in the financial Market, that can help me take my trading strategy to the next level.

Problem Definition Use Case :

- My existing system relies heavily on Talib and Stockstats python modules. I am currently looking for someone that can help me create all the necessary modules so I can stop depending on them.

- With my current system, sometimes I enter a trade way too early , and the price keeps going down so my SL is activated. Eventually, it will turn around and go where we expected the price to go initially.

- On other occasions, I enter the trade in a timely fashion but leave way too early, leaving money on the table.

Requirements :

1. Download OHLC stock information from Yahoo Finance ( Done ).

2. For each Stock Ticker, create a data frame and populate an excel with all necessary calculations and technical indicators. ( SMA, EMA, MACD, RSI , Ichimoku, Keltner, OBV, CandleStick Pattern, etc.)

3. Use deep learning algorithms and pattern recognition to create Buy, Sell , Hold Signals with recommended entry and recommended exit signals, stop loss, and Confidence Interval to another excel sheet.

4. Keep a log and update it for each Signal triggered :

ex. For each Buy Signal, log the date when we first entered the position, and the Sell Signal, when we exit the position and P/L% made and how many days we were on the position.

Expected Result :

The Ideal Trading Strategy / Algorithm should make Decisions based on Technical analysis, or Pattern recognition, and for each Signal Risk-Reward ratio should be at minimum 1:2.

ex.

Strategy 1

Trendline breakout or Momentum Indicators with increasing volume, and take advantage of individual swings or longer positions until there is a change in trend.

Strategy 2

Channel trading system which can be trend line channels or some types of bands ( Keltner, BB etc )

Backtest

The back-test will be done against 5 random US Stocks 5 Mexican Stocks and 5 Indian Stocks.

For the system to be considered successful, it should give annual Return ~30%.

Important Notes:

- Most of the above pattern recognition , technical indicators are already available in Talib and Stockstats.

- Examples of some work you have done on Machine Learning Trading Strategy Systems.

- Proof of other algorithms similar to this project (own made)

- Weekly updates should be given on project status / progress.

- Please bid the actual cost estimate for this work. No price negotiating will be done nor accepted after assigning project.

Looking forward to your bidding

Habilidades: Algoritmo, Matemática, Python, Arquitetura de software, Estatísticas

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Acerca do Empregador:
( 0 comentários ) Guadalajara, United States

ID do Projeto: #19041735

18 freelancers estão ofertando em média $648 para esse trabalho

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