Further modifying the Bollinger Bands features

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In this chapter, we will further modify the previous plot_stock_technical method which uses to plot the Bollinger Bands graph. We will create a few combo boxes that offer various extra parameters that will be used to plot the Bollinger Band for any selected stock. The result is amazing after this edit.

Below are some facts about the Bollinger Bands.


Developed by John Bollinger, Bollinger Bands® are volatility bands placed above and below a moving average. Volatility is based on the standard deviation, which changes as volatility increases and decreases. The bands automatically widen when volatility increases and contract when volatility decreases. Their dynamic nature allows them to be used on different securities with the standard settings. For signals, Bollinger Bands can be used to identify M-Tops and W-Bottoms or to determine the strength of the trend. Signals derived from narrowing BandWidth are discussed in the ChartSchool article on BandWidth.

Here is the modify version of the current ongoing Stock and Forex project.

import json
from tkinter import *
import tkinter.ttk as tk
from alpha_vantage.foreignexchange import ForeignExchange
from alpha_vantage.techindicators import TechIndicators
from alpha_vantage.timeseries import TimeSeries
import matplotlib.pyplot as plt
from alpha_vantage.sectorperformance import SectorPerformances

win = Tk() # Create tk instance
win.title("Real Forex n Stock") # Add a title
win.resizable(0, 0) # Disable resizing the GUI
win.configure(background='white') # change window background color

selectorFrame = Frame(win, background="white") # create the top frame to hold base and quote currency combobox
selectorFrame.pack(anchor = "nw", pady = 2, padx=10)
currency_label = Label(selectorFrame, text = "Select base currency / quote currency :", background="white")
currency_label.pack(anchor="w") # the currency pair label

selector1Frame = Frame(win, background="white") # create the middle frame to hold base and quote currency combobox
selector1Frame.pack(anchor = "nw", pady = 2, padx=10)
stock_label = Label(selector1Frame, text = "Select Stock :", background="white")
stock_label.pack(anchor="w") # the stock label

curr1 = tuple() # the tuple which will be populated by base and quote currency
currency_list = ['AUD', 'BCH', 'BNB', 'BND', 'BTC', 'CAD', 'CHF', 'CNY', 'EOS', 'EUR', 'ETH', 'GBP', 'HKD', 'JPY', 'LTC', 'NZD', 'MYR', 'TRX', 'USD', 'USDT', 'XLM', 'XRP'] # major world currency pairs

# populate the combo box for both the base and quote currency
for key in currency_list:
    curr1 += (key, )

# populate the stock symbol tuple
f = open("stock.txt", "r")
curr2 = tuple()
for line in f.readlines():
    curr2 += (line.replace('\n', ''),)
f.close()

# Create a combo box for base currency
base_currency = StringVar() # create a string variable
based = tk.Combobox(selectorFrame, textvariable=base_currency)
based['values'] = curr1
based.pack(side = LEFT, padx=3)

# Create a combo box for quote currency
quote_currency = StringVar() # create a string variable
quote = tk.Combobox(selectorFrame, textvariable=quote_currency)
quote['values'] = curr1
quote.pack(side = LEFT, padx=3)

# Create a combo box for stock items
stock_symbol = StringVar() # create a string variable
stock = tk.Combobox(selector1Frame, textvariable=stock_symbol)
stock['values'] = curr2
stock.current(0)
stock.pack(side = LEFT, padx=3)

interval = tk.Combobox(selector1Frame)
interval['values'] = ('1min', '5min', '15min', '30min', '60min', 'daily', 'weekly', 'monthly')
interval.current(0)
interval.pack(side = LEFT, padx=3)

price_type = tk.Combobox(selector1Frame)
price_type['values'] = ('close', 'open', 'high', 'low')
price_type.current(0)
price_type.pack(side =LEFT, padx=3)

matype_type = tk.Combobox(selector1Frame, width=37)
matype_type['values'] = ('Simple Moving Average (SMA)', 'Exponential Moving Average (EMA)', 'Weighted Moving Average (WMA)', 'Double Exponential Moving Average (DEMA', 'Triple Exponential Moving Average (TEMA)', 'Triangular Moving Average (TRIMA', 'T3 Moving Average', 'Kaufman Adaptive Moving Average (KAMA)', ' MESA Adaptive Moving Average (MAMA)')
matype_type.current(0)
matype_type.pack(side =LEFT, padx=3)
mattype_list = ['Simple Moving Average (SMA)', 'Exponential Moving Average (EMA)', 'Weighted Moving Average (WMA)', 'Double Exponential Moving Average (DEMA', 'Triple Exponential Moving Average (TEMA)', 'Triangular Moving Average (TRIMA', 'T3 Moving Average', 'Kaufman Adaptive Moving Average (KAMA)', ' MESA Adaptive Moving Average (MAMA)']

s = StringVar() # create string variable which will be used to fill up the Forex data
# create currency frame and text widget to display the incoming forex data
currencyFrame = Frame(win)
currencyFrame.pack(side=TOP)
currency = Label(currencyFrame)
currency.pack(fill=X)
text_widget = Text(currency, fg='white', background='black')
text_widget.pack(fill=X)
s.set("Click the find button to find out the currency exchange rate")
text_widget.insert(END, s.get())

buttonFrame = Frame(win) # create a bottom frame to hold the find button
buttonFrame.pack(side = BOTTOM, fill=X, pady = 6, padx=10)

# first get the api key and secret from the file
f = open("alpha.txt", "r")
api_key = f.readline()
f.close()
api_key = api_key.replace('\n', '')

def get_exchange_rate(): # this method will display the incoming forex data after the api called

    try:
        cc = ForeignExchange(key= api_key)
        from_ = based.get()
        to_ = quote.get()

        countVar = StringVar()  # use to hold the character count
        text_widget.tag_remove("search", "1.0", "end")  # cleared the hightlighted currency pair

        if(from_ != '' and to_ != '' and from_ != to_):
            data, _ = cc.get_currency_exchange_rate(from_currency=from_, to_currency=to_)
            exchange_rate = dict(json.loads(json.dumps(data)))
            count = 1
            sell_buy = str(count) + ".) Pair : " + exchange_rate['1. From_Currency Code'] + "(" + exchange_rate['2. From_Currency Name'] + ")" + " / " + exchange_rate['3. To_Currency Code']+"(" + exchange_rate['4. To_Currency Name'] + ") : "  + str(exchange_rate['5. Exchange Rate']) + '\n'
            text_widget.delete('1.0', END)  # clear all those previous text first
            s.set(sell_buy)
            text_widget.insert(INSERT, s.get())  # display forex rate in text widget
            pos = text_widget.search(from_, "1.0", stopindex="end", count=countVar)
            text_widget.tag_configure("search", background="green")
            end_pos = float(pos) + float(0.7)
            text_widget.tag_add("search", pos, str(end_pos))  # highlight the background of the searched currency pair
            pos = float(pos) + 2.0
            text_widget.see(str(pos))

    except:
        print("An exception occurred")

def plot_stock_echange():

    try:
        stock_symbol_text = stock.get() # get the selected symbol
        if(stock_symbol_text!= ''):
            ts = TimeSeries(key=api_key, output_format='pandas')
            data, meta_data = ts.get_intraday(symbol=stock_symbol_text, interval='1min', outputsize='full')
            data['4. close'].plot()
            stock_title = 'Intraday Times Series for the ' + stock_symbol_text + ' stock (1 min)'
            plt.title(stock_title)
            plt.show()
    except:
        print("An exception occurred")

def plot_stock_technical():

    try:
        stock_symbol_text = stock.get() # get the selected stock symbol
        if(stock_symbol_text!= ''):

            ti = TechIndicators(key=api_key, output_format='pandas')
            data, meta_data = ti.get_bbands(symbol=stock_symbol_text, interval=interval.get(), series_type=price_type.get(), matype=mattype_list.index(matype_type.get()), time_period=int(interval.get().replace('min', '')))
            data.plot()
            stock_title = 'BBbands indicator for ' + stock_symbol_text + ' ' + interval.get()
            plt.title(stock_title)
            plt.show()
    except:
        print("An exception occurred")

def plot_sector_performance():

    sp = SectorPerformances(key=api_key, output_format='pandas')
    data, meta_data = sp.get_sector()
    data['Rank A: Real-Time Performance'].plot(kind='bar')
    plt.title('Real Time Performance (%) per Sector')
    plt.tight_layout()
    plt.grid()
    plt.show()

action_vid = tk.Button(buttonFrame, text="Calculate Exchange Rate", command=get_exchange_rate) # button used to find out the exchange rate of currency pair
action_vid.pack(side=LEFT, padx=2)
action_stock_plot = tk.Button(buttonFrame, text="Plot Stock", command=plot_stock_echange) # button used to plot the intra-minute stock value
action_stock_plot.pack(side=LEFT, padx=2)
action_technical_plot = tk.Button(buttonFrame, text="Plot Technical", command=plot_stock_technical) # button used to plot the 60 minutes stock technical value
action_technical_plot.pack(side=LEFT, padx=2)
action_sector_plot = tk.Button(buttonFrame, text="Plot Sector Performance", command=plot_sector_performance) # button used to plot the sector performance graph
action_sector_plot.pack(side=LEFT, padx=2)

win.iconbitmap(r'ico.ico')
win.mainloop()

We will continue develop this python application in the next chapter.

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