EECS767_Presentation2_Example1.py

'''
@author Michael J Bommarito II
@date Mar 26, 2010

This is just a cute little example of an asset graph with the max and min spanning trees highlighted.
'''

import dateutil.parser
import csv
import igraph
import numpy
import urllib2

def downloadReturn(symbol):
	'''
	Download the data for the given symbol and return the log-return from adjusted close.
	'''
	url = 'http://ichart.finance.yahoo.com/table.csv?s={0}&a=02&b=1&c=2010&d=02&e=26&f=2010&g=d&ignore=.csv'.format(symbol)
	buffer = urllib2.urlopen(url).read()
	
	A = [float(row.split(',')[6]) for row in buffer.splitlines()[1:]]
	return numpy.diff(numpy.log(A))
	
	
if __name__ == "__main__":
	# Set the list of symbols
	symbols = ['MSFT','IBM','YHOO','GOOG','AKAM','ORCL','HPQ','DELL','INTC','AMD', 'C', 'BAC', 'JPM', 'GS']
	# Get the return for each symbol
	returns = map(downloadReturn, symbols)

	# Graph data
	edgelist = []
	weights = []
	
	# Correlation threshold
	threshold = 0.2
	
	'''
	Construct the graph by seeing which pairs meet our threshold.
	'''
	for i in range(len(symbols)):
		for j in range(i):
			C = numpy.corrcoef(returns[i], returns[j])
			if C[0,1] > threshold:
				edgelist.append((i,j))
				weights.append(C[0,1])
	
	'''
	Create the graph object and label the vertices.
	'''
	g = igraph.Graph(edgelist)
	for i,v in enumerate(g.vs):
		v['label'] = symbols[i]
		
	# Calculate the layout
	layout = g.layout_fruchterman_reingold(weights = [int(100 * w) for w in weights])
	
	# Calculate the max and min spanning trees
	g.es["width"] = [10.0 * w for w in weights]
	maxst = g.spanning_tree([numpy.exp(-w) for w in weights])
	minst = g.spanning_tree([w for w in weights])
	
	'''
	Now plot the original graph and overlay the two spanning trees.
	'''
	fig = igraph.Plot(bbox = (800,800))
	fig.add(g, layout=layout, opacity=0.25, vertex_label=symbols, margin = 50)
	fig.add(maxst, layout=layout, opacity=0.5, edge_color="green", vertex_label=symbols, margin = 50)
	fig.add(minst, layout=layout, opacity=0.5, edge_color="red", vertex_label=symbols, margin = 50)
	fig.show()