philippe554 / mrp_10_forex Goto Github PK

This repository contains an algorithm which is able to predict the Forex market perfectly.

Python 99.13% Shell 0.87%

mrp_10_forex's Introduction

MRP_10_Forex

Trading in Forex can lead to profit if you react well (by buying and selling money) to dynamic changes in the exchange rates. However, forecasting of the Forex market is very difficult, due to its size, dispersion, and continuous operation. Therefore, the goal of this project is to investigate whether neural networks and deep learning can be used to achieve an accurate data-driven forecast of the Forex market.

Dependencies

Tested on Python 3.6.4. Install the dependencies by running this command in your terminal (python should be added to your PATH):

python -m pip install -r requirements.txt

FXCM

We connect to a Forex demo account using fxcm fxcmpy docs: https://www.fxcm.com/uk/algorithmic-trading/forex-python/

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Accumulation/Distribution Index (ADI)
On-Balance Volume (OBV)
On-Balance Volume mean (OBV mean)
Chaikin Money Flow (CMF)
Force Index (FI)
Ease of Movement (EoM, EMV)
Volume-price Trend (VPT)
Negative Volume Index (NVI)

Go through the API connections

Live Forex Data
Love Trading
transaction fees.

Moving Average Convergence Divergence (MACD)

Average Directional Movement Index (ADX)

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Vortex Indicator (VI)
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Trix (TRIX)
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Mass Index (MI)
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Commodity Channel Index (CCI)
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Detrended Price Oscillator (DPO)
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KST Oscillator (KST)
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Ichimoku Kinkō Hyō (Ichimoku)
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Money Flow Index (MFI)
Relative Strength Index (RSI)
True strength index (TSI)
Ultimate Oscillator (UO)
Stochastic Oscillator (SR)
Williams %R (WR)
Awesome Oscillator (AO)

Technical Analysis: Volatility

Average True Range (ATR)
Bollinger Bands (BB)
Keltner Channel (KC)
Donchian Channel (DC)

All Technical Indicators with live data

Currently the classes are using the database, which is good for training but still there's an extension needed for the live data from API responses or the streams.