fxmanager.strategies package

Package contents

This sub-package contains the mudules used for building and injecting trading strategies int FX-Manager’s trading simulations.

Public Modules:

naieve_momentum: This module contains simple implementation of momentum trading strategy, used as default for simulations.

This module contains simple implementation of momentum trading strategy.

Public Functions:

get_orders(): sample trading strategy for purposes of testing live and historic trading simulators.

fxmanager.strategies.naieve_momentum.get_orders(prices, **kwargs)

sample trading strategy for purposes of testing live and historic trading simulators.

Args:

prices: pandas DataFrame with range index and a the following columns:
- ask_open: open ask price of the candle stick.
- bid_open: open bid price of the candle stick.
- ask_close: close ask price of the candle stick.
- bid_close: close bid price of the candle stick.
kwargs: special dictionary to hold any number of required arguments for the function.

Returns:

orders: pandas DataFrame with ONE RAW and the following columns:
- order_type: can be one of 3 values (buy, sell, hold)
- SL : stop loss.
- TP : take profit.

This module contains a class that is used by user to create a strategy object which is passed to fxmanager’s built-in live and historical simulators.

Public Classes:

strategy_template: Class for injecting user defined trading strategies into fxmanager’s built-in live and historical simulators.

class fxmanager.strategies.template.strategy_template(strategy, take_all_prices=False)

Bases: object

Class for injecting user defined trading strategies into fxmanager’s built-in live and historical simulators.

Args:

strategyreference to a user defined function for some trading strategy. The function MUST be structured as follows in order for the simulation to work proberly:
- takes ONLY ONE positional argument called ‘prices’. This argument is a pandas DataFrame with range index and the following columns:
  
  ask_open: open ask price of the candle stick.
  
  bid_open: open bid price of the candle stick.
  
  ask_close: close ask price of the candle stick.
  
  bid_close: close bid price of the candle stick.
- takes **kwargs for any other keword arguments.
- returns a pandas DataFrame with ONE RAW and the following columns:
  
  order_type: can be one of 3 values (buy, sell, hold)
  
  SL : stop loss.
  
  TP : take profit.
take_all_prices: boolean that controls the frequency of the range index of ‘prices’ DataFrame.
If True: all the prices history since the begining of the day is passed to the strategy function, the index is a normal range index (0, 1, 2, …). the time difference between every reading is determined by the ‘sleep_time’ argument in the ‘fxmanager.simulation.live.run()’ or ‘fxmanager.simulation.historic.run()’ functions. If False: the frequncy of the prices becomes dependant on the time frame in which we want to generate an order, for examble, if we want to open a position in ‘EURUSD’ in the ‘5min’ time frame, the index will become (0, 5, 10, ..).

Methods:

get_orders: used in ‘fxmanager.simulation.live.run()’ and ‘fxmanager.simulation.historic.run()’ functions.

get_portfolios_template(): returns a list of dictionaries of length = num_days where each dictionary is a portfolio used for a given day.

kwargs_template(): returns a template dictionary for keyword args used in used defined strategies.

template(**kwargs)

function template for the user to build trading strategies.

Args:

prices: pandas DataFrame with range index and the following columns:
- ask_open: open ask price of the candle stick.
- bid_open: open bid price of the candle stick.
- ask_close: close ask price of the candle stick.
- bid_close: close bid price of the candle stick.
kwargs: special dictionary to hold any number of required arguments for the function.

Returns:

orders: pandas DataFrame with ONE RAW and the following columns:
- order_type: can be one of 3 values (buy, sell, hold)
- SL : stop loss.
- TP : take profit.