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Learn to Program Pyramiding Algorithm

Would you like to learn how to do this?  Check back over the next few days and I will show you to do it.  Warning:  its not straightforward as it seems – some tricks are involved.  Remember to sign up for email notifications of new posts.

UPDATE[1]:  I have recorded an introductory webcast on how to program this pyramiding scheme.  This webcast is Part 1 and illustrates how to brainstorm and start thinking/programming about a problem.  Part 1 introduces some concepts that show how you can use and adapt some of EasyLanguage built-in reserved words and functions.  I start from the perspective of a somewhat beginning EasyLanguage programmer  – one that knows enough to maybe not get the problem solved, but at least get the ball rolling.  The final code may not look anything like the code I present in Part 1.  However it is sometimes important to go down the wrong trail so that you can learn the limitations of a programming language.  Once you know the limitations, you can go about programming workarounds and fixes.  I hope you enjoy Part 1  I should have Part 2 up soon.  Don’t be too critical, this is really the first webcast I have recorded.  You’ll notice I repeat myself and I refer  to one function input as a subscript.  Check it out:  https://youtu.be/ip-DyyKpOTo

Adding positions at fixed intervals.

Using Jupyter Notebook and Plot.ly To Create Candle Stick Chart

In today’s post I show how you can plot a very nice looking Candlestick chart inside a Jupyter (IPython) notebook. This chore is
made much easier by using  Plotly. So first thing you sholud do is sign up for a free account at Plotly and then download Jupyter Interactive Python notebooks.  I did this in an interactive notebook for demonstration purposes only.  After installing Plotly I was able to import the libraries into my notebook and then call the various functions to graph the data.  I imported numpy, but it wasn’t necessary.  I simply copied some data (CL.CSV) to the subdirectory that held my notebooks and then used the CSV Reader to pull the data into the various lists that the Plotly functions required.  All of the plotting is done in a browser and its interactive.  After creating the PSB I wanted to provide a tool for plotting the data that was being tested.  Jupyter and Plotly are free for non-commercial users.

import numpy as np
import datetime
import csv
import plotly.plotly as py
from plotly.tools import FigureFactory as FF
from plotly.graph_objs import *

d = list()
dt = list()
o = list()
h = list()
l = list()
c = list()
v = list()
oi = list()
cnt = 0

with open("CL.CSV") as f:
    f_csv = csv.reader(f)
    for row in f_csv:
        numCols = len(row)
        cnt += 1
        d.append(int(row[0]))
        dt.append(datetime.datetime.strptime(row[0],'%Y%m%d'))
        o.append(float(row[1]))
        h.append(float(row[2]))
        l.append(float(row[3]))
        c.append(float(row[4]))
        v.append(float(row[5]))
        oi.append(float(row[6]))
        
xDate = list()
yVal = list()
indicCnt = 0
for i in range(len(c)-40,len(c)):
    xDate.append(dt[i])
    sum = 0.0
    for j in range(i-9,i):
        sum += c[j]
    yVal.append(sum/10)
                      
fig = FF.create_candlestick(o, h,l, c, dt)

add_line = Scatter(
    x=xDate, 
    y=yVal, 
    name= 'movingAverage', 
    line=Line(color='blue')
    )

fig['data'].extend([add_line])

py.iplot(fig, filename='simple-candlestick', validate=False)
Candlesticks with Plot.ly
CandleStick of Crude Oil with Moving Average Overlay
CandleStick of Crude Oil with Moving Average Overlay