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Add vwap to technical analysis

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This commit is contained in:
didier
2020-12-25 13:31:43 +00:00
parent 148a399bd8
commit f71259bcda
2 changed files with 51 additions and 6 deletions
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8
stock_market_cli.py
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@@ -55,6 +55,7 @@ def print_help(s_ticker, s_start, b_is_market_open):
print(" sma simple moving average")
print(" ema exponential moving average")
print(" macd moving average convergence/divergence")
print(" vwap volume weighted average price")
print("\nPrediction:")
print(" ma")
@@ -95,7 +96,7 @@ def main():
main_parser = argparse.ArgumentParser(prog='stock_market_bot', add_help=False)
# Add list of arguments that the main parser accepts
main_parser.add_argument('cmd', choices=['quit', 'help', 'gainers' ,'view', 'load', 'clear', 'sma', 'ema', 'macd', 'ratings'])
main_parser.add_argument('cmd', choices=['quit', 'help', 'gainers' ,'view', 'load', 'clear', 'sma', 'ema', 'macd', 'vwap', 'ratings'])
# Print first welcome message and help
print("\nWelcome to Didier's Stock Market Bot\n")
@@ -175,6 +176,11 @@ def main():
elif ns_known_args.cmd == 'macd':
smta.macd(l_args, s_ticker, df_stock)
continue
# ---------------------------------------------------- VWAP ----------------------------------------------------
elif ns_known_args.cmd == 'vwap':
smta.vwap(l_args, s_ticker, s_start)
continue
# --------------------------------------------------------------------------------------------------------------
# ------------------------------------------------ PREDICTION --------------------------------------------------

49
stock_market_technical_analysis.py
View File

@@ -1,5 +1,6 @@
import argparse
from alpha_vantage.timeseries import TimeSeries
from alpha_vantage.techindicators import TechIndicators
import pandas_ta as ta
import config_bot as cfg
from stock_market_helper_funcs import *
@@ -27,8 +28,8 @@ def sma(l_args, s_ticker, df_stock):
print(f"The following args couldn't be interpreted: {l_unknown_args}")
try:
df_ta = ta.sma(df_stock['4. close'], timeperiod=ns_parser.n_time_period).dropna()
plot_stock_ta(df_stock['4. close'], s_ticker, df_ta, f"{ns_parser.n_time_period} SMA")
df_ta = ta.sma(df_stock['5. adjusted close'], timeperiod=ns_parser.n_time_period).dropna()
plot_stock_ta(df_stock['5. adjusted close'], s_ticker, df_ta, f"{ns_parser.n_time_period} SMA")
except:
print("")
return
@@ -58,8 +59,8 @@ def ema(l_args, s_ticker, df_stock):
print(f"The following args couldn't be interpreted: {l_unknown_args}")
try:
df_ta = ta.ema(df_stock['4. close'], timeperiod=ns_parser.n_time_period).dropna()
plot_stock_ta(df_stock['4. close'], s_ticker, df_ta, f"{ns_parser.n_time_period} EMA")
df_ta = ta.ema(df_stock['5. adjusted close'], timeperiod=ns_parser.n_time_period).dropna()
plot_stock_ta(df_stock['5. adjusted close'], s_ticker, df_ta, f"{ns_parser.n_time_period} EMA")
except:
print("")
return
@@ -97,7 +98,7 @@ def macd(l_args, s_ticker, df_stock):
print(f"The following args couldn't be interpreted: {l_unknown_args}")
try:
df_ta = ta.macd(df_stock['4. close'],
df_ta = ta.macd(df_stock['5. adjusted close'],
fast=ns_parser.n_fast,
slow=ns_parser.n_slow,
signal=ns_parser.n_signal,
@@ -107,3 +108,41 @@ def macd(l_args, s_ticker, df_stock):
except:
print("")
return
# ----------------------------------------------------- VWAP -----------------------------------------------------
def vwap(l_args, s_ticker, s_start):
parser = argparse.ArgumentParser(prog='vwap',
description=""" The Volume Weighted Average Price that measures the average typical price
by volume. It is typically used with intraday charts to identify general
direction. """)
parser.add_argument('-i', "--interval", action="store", dest="n_interval", type=int, default=15, choices=[1,5,15,30,60], help='Stock ticker')
try:
(ns_parser, l_unknown_args) = parser.parse_known_args(l_args)
except SystemExit:
print("")
return
if l_unknown_args:
print(f"The following args couldn't be interpreted: {l_unknown_args}")
try:
ts = TimeSeries(key=cfg.API_KEY_ALPHAVANTAGE, output_format='pandas')
s_interval = str(ns_parser.n_interval)+'min'
df_stock, d_stock_metadata = ts.get_intraday(symbol=s_ticker, outputsize='full', interval=s_interval)
if s_start:
df_stock = df_stock[s_start:]
df_ta = ta.vwap(high=df_stock['2. high'], low=df_stock['3. low'], close=df_stock['4. close'], volume=df_stock['5. volume'], interval=s_interval)
plot_stock_ta(df_stock['4. close'], s_ticker, df_ta, f"{s_interval} VWAP")
# ti = TechIndicators(cfg.API_KEY_FINANCIALMODELINGPREP, output_format='pandas')
# df_ta, d_ta_metadata = ti.get_vwap(symbol=s_ticker, interval=s_interval)
# plot_ta(s_ticker, df_ta, f"{s_interval} VWAP")
except:
print("")
return