FemtoTrader femtotrader

## gist:c76004a8597f72d8d9a2c63b5c26816b
Verifying my Blockstack ID is secured with the address 14BzAGWqh8hx72DZ7J5Df71fAeWMzKrckH https://explorer.blockstack.org/address/14BzAGWqh8hx72DZ7J5Df71fAeWMzKrckH

## first_profitable_exit.jl
###############################################################
# 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

## alpha_vantage.jl
# 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"]

## alphavantage.py
import requests
from pandas.io.common import urlencode
from pandas.tseries.frequencies import to_offset


ALPHAVANTAGE_API_URL = "http://www.alphavantage.co/query"
ALPHAVANTAGE_API_KEY_DEFAULT = "demo"


def _init_session(session):

## lobster_reader.py
#!/usr/bin/env python

"""
Read Lobster orderbook files to Python Pandas DataFrame
"""

import click
import os
import pandas as pd
from pandas.io.common import ZipFile

## gist:9ab7d2c6f6dacd794ba16a3c06b3a74b
Verifying that +femtotrader is my blockchain ID. https://onename.com/femtotrader

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

@author: root
"""

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

## digit_version_charles_dadi.py
#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

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

## ipython_btc_part1
{
 "metadata": {
  "name": ""
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
	###############################################################
	# 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
	# 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"]
	import requests
	from pandas.io.common import urlencode
	from pandas.tseries.frequencies import to_offset


	ALPHAVANTAGE_API_URL = "http://www.alphavantage.co/query"
	ALPHAVANTAGE_API_KEY_DEFAULT = "demo"


	def _init_session(session):
	#!/usr/bin/env python

	"""
	Read Lobster orderbook files to Python Pandas DataFrame
	"""

	import click
	import os
	import pandas as pd
	from pandas.io.common import ZipFile
	# -- coding: utf-8 --
	"""
	Created on Mon Feb 17 13:56:10 2014

	@author: root
	"""

	import urllib2
	opener = urllib2.build_opener()
	from bs4 import BeautifulSoup
	#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
	##############################################################
	## ##
	## VaR and C-VaR computation with ETV on EURUSD ##
	## ##
	## by Charles-Abner Dadi ##
	## ##
	## <charles-abner.dadi@graduates.centraliens.net> ##
	## ##
	##############################################################
	{
	"metadata": {
	"name": ""
	},
	"nbformat": 3,
	"nbformat_minor": 0,
	"worksheets": [
	{
	"cells": [
	{