femtotrader

###############################################################
# exit first profitable price over entry
# exit after fixed bars (max_hold) if no profitable trade
###############################################################
signal = [0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
close = [10,10,8,3,14,5,6,2,4,22,2,1,1,1,10,3,3,3,3,3,3,30]

first_prof = zero(signal)
max_hold = 6
for i = 1:length(signal) # 1:length(signal)-1 if buying next bar at open

femtotrader

# Download Data Using Alphavantage
using HTTP
using StatPlots

res = HTTP.get("https://www.alphavantage.co/query?function=TIME_SERIES_INTRADAY&symbol=AAPL&interval=1min&apikey=your_api_key&datatype=csv")
mycsv = readcsv(res.body)
x = convert(DataFrame, mycsv)
x = x[2:nrow(x),:]  # subset remove header row
# Rename Columns
colnames = ["Date","Open","High","Low","Close","Volume"]

femtotrader

# -*- coding: utf-8 -*-
"""
Created on Mon Feb 17 13:56:10 2014

@author: root
"""

import urllib2
opener = urllib2.build_opener()
from bs4 import BeautifulSoup

femtotrader

#http://scikit-learn.org/stable/auto_examples/applications/face_recognition.html#example-applications-face-recognition-py
from sklearn.ensemble import RandomForestClassifier
from numpy import genfromtxt, savetxt
from sklearn import neighbors, datasets

from sklearn.cross_validation import train_test_split
from sklearn.datasets import fetch_lfw_people
from sklearn.grid_search import GridSearchCV
from sklearn.metrics import classification_report
from sklearn.metrics import confusion_matrix

femtotrader

	##############################################################
	##									                                      	##
	##	     VaR and C-VaR computation with ETV on EURUSD	      ##
	##										                                      ##
	##			by Charles-Abner Dadi 				                      ##
	##										                                      ##
	##  <charles-abner.dadi@graduates.centraliens.net>		      ##							
	##										                                      ##
	##############################################################

femtotrader

{
 "metadata": {
  "name": ""
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {

femtotrader

# -*- coding: utf-8 -*-

import time
t0 = time.clock()

import pandas as pd
from pandas.tseries.offsets import BDay
import numpy as np
import datetime as dt
from copy import copy

femtotrader

'''
Netfonds import 5 days of intraday data
'''

import numpy as np
import pandas as p
from pandas.tseries.offsets import *
import datetime as dt
import matplotlib.pyplot as plt
size = (14,10)