Finance Chart (2)

This example demonstrate creating a full-featured finance chart, with candlesticks, moving averages, Donchian channel, volume bars, MACD and Stochastic indicators.

This example employs the FinanceChart library add-on to allow complex financial charts to be composed easily. In this example, the key steps are:

Create a new FinanceChart object
Set data into the chart using FinanceChart.setData
Add a Slow Stochastic indicator chart as the top chart using FinanceChart.addSlowStochastic
Add the main chart using FinanceChart.addMainChart
Add simple moving average lines to the main chart using FinanceChart.addSimpleMovingAvg
Add candlestick symbols to the main chart using FinanceChart.addCandleStick
Add Donchian Channel to the main chart using FinanceChart.addDonchianChannel
Add volume bars to the main chart using FinanceChart.addVolBars
Add an additional MACD indicator chart using FinanceChart.addMACD

For simplicity and to allow this example to run without connecting to a real database, a RanTable object is used to simulate the data. RanTable is a ChartDirector utility class used for creating tables with random numbers.

pythondemo\finance2.py

#!/usr/bin/python

# The ChartDirector for Python module is assumed to be in "../lib"
import sys, os
sys.path.insert(0, os.path.join(os.path.abspath(sys.path[0]), "..", "lib"))

from FinanceChart import *

# Create a finance chart demo containing 100 days of data
noOfDays = 100

# To compute moving averages starting from the first day, we need to get extra data points before
# the first day
extraDays = 30

# In this exammple, we use a random number generator utility to simulate the data. We set up the
# random table to create 6 cols x (noOfDays + extraDays) rows, using 9 as the seed.
rantable = RanTable(9, 6, noOfDays + extraDays)

# Set the 1st col to be the timeStamp, starting from Sep 4, 2002, with each row representing one
# day, and counting week days only (jump over Sat and Sun)
rantable.setDateCol(0, chartTime(2002, 9, 4), 86400, 1)

# Set the 2nd, 3rd, 4th and 5th columns to be high, low, open and close data. The open value starts
# from 100, and the daily change is random from -5 to 5.
rantable.setHLOCCols(1, 100, -5, 5)

# Set the 6th column as the vol data from 5 to 25 million
rantable.setCol(5, 50000000, 250000000)

# Now we read the data from the table into arrays
timeStamps = rantable.getCol(0)
highData = rantable.getCol(1)
lowData = rantable.getCol(2)
openData = rantable.getCol(3)
closeData = rantable.getCol(4)
volData = rantable.getCol(5)

# Create a FinanceChart object of width 640 pixels
c = FinanceChart(640)

# Add a title to the chart
c.addTitle("Finance Chart Demonstration")

# Set the data into the finance chart object
c.setData(timeStamps, highData, lowData, openData, closeData, volData, extraDays)

# Add a slow stochastic chart (75 pixels high) with %K = 14 and %D = 3
c.addSlowStochastic(75, 14, 3, 0x006060, 0x606000)

# Add the main chart with 240 pixels in height
c.addMainChart(240)

# Add a 10 period simple moving average to the main chart, using brown color
c.addSimpleMovingAvg(10, 0x663300)

# Add a 20 period simple moving average to the main chart, using purple color
c.addSimpleMovingAvg(20, 0x9900ff)

# Add candlestick symbols to the main chart, using green/red for up/down days
c.addCandleStick(0x00ff00, 0xff0000)

# Add 20 days donchian channel to the main chart, using light blue (9999ff) as the border and
# semi-transparent blue (c06666ff) as the fill color
c.addDonchianChannel(20, 0x9999ff, 0xc06666ff)

# Add a 75 pixels volume bars sub-chart to the bottom of the main chart, using green/red/grey for
# up/down/flat days
c.addVolBars(75, 0x99ff99, 0xff9999, 0x808080)

# Append a MACD(26, 12) indicator chart (75 pixels high) after the main chart, using 9 days for
# computing divergence.
c.addMACD(75, 26, 12, 9, 0x0000ff, 0xff00ff, 0x008000)

# Output the chart
c.makeChart("finance2.png")