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Python Trader code and skills sharing

  • #21
  • Jan 7, 2015 7:25pm Jan 7, 2015 7:25pm
Quoting john3344
ForexSamsam, Here's a trading method that is very interesting. I would like to back-test it by coding in Python, but I am very early in my learning curve. I've attached the details for FirstStrike_Plus created by Joel Rensink. All credit for his work is included in the pdf. He included 6 years of GBPUSD results which are outstanding. If I knew Python, I would test all (at least major) currencies for Win%, Reward to Risk Ratio, and Draw-down. Perhaps this is something you could code in Python. This would determine if the program was profitable over...

Is not too heavy to backtest this i guess .. give me a couple of week.. i will try it in my free time

Do you want to use GBPUSD ?

we can use any other ... i get the data here : http://www.histdata.com/download-free-forex-data/
  • #22
  • Jan 7, 2015 7:47pm Jan 7, 2015 7:47pm
Quote
want to use GBPUSD ?

Yes, GBPUSD would be a good pair to use. It will be exciting to learn if this would be a sustainable profitable method. I hope you can share the coding with us. I learn much faster with I have good code examples to learn from.

Thanks for doing this!

John
  • #23
  • Jan 8, 2015 1:35am Jan 8, 2015 1:35am
Do you have any example code you can share? While I'm familiar with developing MQL EAs writing my own backtesting platform is something that's new to me
  • #24
  • Jan 8, 2015 11:32am Jan 8, 2015 11:32am
Quote
Do you have any example code you can share?

No, unfortunately I do not have MQL EA code.
  • #25
  • Jan 8, 2015 3:56pm Jan 8, 2015 3:56pm
Quoting john3344
{quote} No, unfortunately I do not have MQL EA code.
I'm not looking for MQL EA code, I'm looking for example code of how to use Python to build a backtesting platform.
  • #26
  • Jan 8, 2015 4:02pm Jan 8, 2015 4:02pm
Quoting john3344
{quote} No, unfortunately I do not have MQL EA code.
See here.
Since there seems to be a ready-made mql code, it might be easier to backtest it in Metatrader, and then if the strategy is good, to spend some time and port it to Python?

k
  • #27
  • Jan 8, 2015 5:27pm Jan 8, 2015 5:27pm
Quote
i get the data here : http://www.histdata.com/download-free-forex-data/
You may also want to check http://www.strategyquant.com/tickdatadownloader/ for forex tick data free.
  • #28
  • Jan 8, 2015 5:34pm Jan 8, 2015 5:34pm
Quote
Since there seems to be a ready-made mql code, it might be easier to backtest it in Metatrader,

Thanks Kprsa,
Yes, I download the EA from this site. I have had it running for a short while. Results so far are promising. I'm not a coder so I don't know how much time and effort is involved with back-testing this method in Python. But, if it is reasonable it might be well worth the effort. The EA could run for several weeks with great results, but longer term testing on several pairs across varies market conditions might be better evaluated using a back-test in Python.
  • #29
  • Jan 8, 2015 6:32pm Jan 8, 2015 6:32pm
Here very simple base of implement Backtesting in Pyhon, i use Mysql Database, i load Ticks into its

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sqlalchemy import create_engine
from datetime import *
from Fonctions import *
from talib.abstract import *
import pdb
pd.options.display.mpl_style = 'default'
ticker = "EUR_JPY"
diviseur = 100
hauteurmin = 10.0#25.0
vola = 0.40#0.25
resu = pd.DataFrame()
effacelog()
engine = create_engine('mysql://root:ForexSamsam@localhost/Forex')
df=pd.DataFrame(columns=['date_time','last'])
df = pd.read_sql_query("SELECT date_time, last FROM " + ticker + " where date_time between '2013-01-01' and '2014-12-31'",engine)

print 'End Extraction'
#CALCUL DES VARIABLES
i_df = df.set_index('date_time')
last = i_df['last'].resample('4H', how='ohlc',base=1).dropna()
last.index = last.index+pd.offsets.Hour(4)
#MACD
MACD535=MACD(last,5,35,5)
#TDI
MBL = pd.DataFrame(RSI(last,13),columns=['close'])
RSI_PL = SMA(MBL,2)
TSL = SMA(MBL,7)
CROSSING = RSI_PL-TSL
#SLOPE
moyenne = EMA(last,10)
pente_moy = pd.Series(np.gradient(moyenne),index=moyenne.index)
#ATR
ATR = ATR(last,3)
volatility = ATR/EMA(last,3)[-1]*100
print volatility.describe()
  • #30
  • Mar 9, 2015 7:31pm Mar 9, 2015 7:31pm
If interest, i can share talib version on Raspbian wheezy for pi.

I just finish compile new code for pi 2.0
  • #31
  • Mar 11, 2015 3:39am Mar 11, 2015 3:39am
Hi ForexSamsam.
I also have installed a Python algorithmic trading environment on the Raspberry Pi 2 running Raspbian Wheezy.
All running fine except for Talib. Could you please send me your version?
Thanks, ForexF.
  • #32
  • Jul 23, 2015 10:24am Jul 23, 2015 10:24am
Hi all,

I'm trying to setup a system for FX algo trading in python. may you help me what is the best source to get FX data for backtest and live trading in python?
it's also valuable for me to have your recommendations about python sources for learning.
hope to hear from you.
best,
  • #33
  • Sep 3, 2015 6:22am Sep 3, 2015 6:22am
hello,
is it possible to do analysis with python based on the live quote of currency? i just want do some simple calculation based on live chart (want to work with donchian channel). another question: how to become the data into python, for example 1 minute candlestick? is there any good ressource where i can learn this specific stuff?

thank you very much
tickoedo
  • #34
  • Sep 24, 2015 8:44pm Sep 24, 2015 8:44pm
Have you guys found any resources that help to use the API? MT4's MQL had lots of documentation.
  • #35
  • Oct 6, 2015 3:54am Oct 6, 2015 3:54am
Quoting ForexSamsam
Here very simple base of implement Backtesting in Pyhon, i use Mysql Database, i load Ticks into its import pandas as pd import numpy as np import matplotlib.pyplot as plt from sqlalchemy import create_engine from datetime import * from Fonctions import * from talib.abstract import * import pdb pd.options.display.mpl_style = 'default' ticker = "EUR_JPY" diviseur = 100 hauteurmin = 10.0#25.0 vola = 0.40#0.25 resu = pd.DataFrame() effacelog() engine = create_engine('mysql://root:ForexSamsam@localhost/Forex') df=pd.DataFrame(columns=['date_time','last'])...
Hi SamSam,
Do you use any library to assist you with backtesting and reporting?
  • #36
  • Oct 6, 2015 6:37am Oct 6, 2015 6:37am
I use Pandas for backtesting, very powefull lib with everything you need.

Last 6 month, i work on backtesting system on a virtual machine with VMBOX on Lubuntu.
work very well with python, pandas, scikitlearn, talib.
  • #37
  • Oct 6, 2015 6:49am Oct 6, 2015 6:49am
Quoting ForexSamsam
I use Pandas for backtesting, very powefull lib with everything you need. Last 6 month, i work on backtesting system on a virtual machine with VMBOX on Lubuntu. work very well with python, pandas, scikitlearn, talib.
Cool, thanks for replying.

Can you also advice on how you calculate p&l for backtests?
i.e. if we take simple MA cross.
would you create simple list with entries, direction and exits; and than calculate p&l or you have do something else?
  • #38
  • Oct 6, 2015 8:44am Oct 6, 2015 8:44am
I always use stoploss or takeprofit so you need to find which is come firs after the opening of the position.

For that i verify every tick after the trade open.

If stoploss is hit before i loss the stoploss pip value
If takeprofit is hit first i take a profit of my takeprofit value
  • #39
  • Oct 6, 2015 10:33am Oct 6, 2015 10:33am
Quoting ForexSamsam
I always use stoploss or takeprofit so you need to find which is come firs after the opening of the position. For that i verify every tick after the trade open. If stoploss is hit before i loss the stoploss pip value If takeprofit is hit first i take a profit of my takeprofit value
cool, thanks.

have you looked in to Zipline and quantopian?

Not sure if accepting limitations any library will give will overcome benefits..
  • #40
  • Oct 6, 2015 11:05am Oct 6, 2015 11:05am
I dont try those package.

Do your own is not more effort than learn new package but its more adaptative in the long term
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