452 lines
15 KiB
Python
452 lines
15 KiB
Python
# -*- coding: utf-8 -*-
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"""
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TODO: given a list of symbols, for each stock, plot
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Subplot1:
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1. price
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2. 50 and 200 day SMA lines
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3. bollinger band (200 day)
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Subplot2
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RSI
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Subplot3
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MACD
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TODO: validate the plots with online resource
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Updated on Mon Sep. 30, 2024
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Use one as buy/sell trigger and verify a bag of indicators to make final decision.
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Could also come up with a value that ties to the trading volume.
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@author: thomwang
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"""
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import pandas as pd
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import numpy as np
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import datetime as dt
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import plotly.express as px
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from plotly.subplots import make_subplots
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from dash import Dash, html, dcc, callback, Output, Input, State, no_update, ctx
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from waitress import serve
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from flask_caching import Cache
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from dash.exceptions import PreventUpdate
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from dash_auth import BasicAuth
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import yahoo_fin.stock_info as si
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from dotenv import load_dotenv
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import os
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from sec_cik_mapper import StockMapper, MutualFundMapper
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from subroutines import *
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pd.options.mode.chained_assignment = None # default='warn'
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load_dotenv()
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LB_YEAR = 3 # years of stock data to retrieve
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PLT_YEAR = 2.7 # number of years data to plot
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LB_TRIGGER = 5 # days to lookback for triggering events
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def intelligent_loop_plots(sym : str, stk_data):
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"""calculated indicators
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Args:
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sym (str): ticker
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stk_data (DataFrame): stock data
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Returns:
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DataFrame: price
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DataFrame: volume
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DataFrame: macd
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DataFrame: rsi
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str: detected indicators
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"""
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price = stk_data["adjclose"]
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vol = stk_data["volume"]
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stk = Security(sym, price, vol)
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rsi = stk.rsi()
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vorsi = stk.volume_rsi()
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macd, macd_sig, macd_hist, norm_hist = stk.macd()
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sma50 = stk.sma(50)
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vwma50 = stk.vwma(50)
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sma200 = stk.sma(200)
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bol_low, bol_up = stk.bollinger(200)
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# init
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plot_indicator = "["
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# print('{:5}: '.format(sym), end = '')
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# RSI outside window (over bought / over sold)
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rsi_tail = rsi.tail(LB_TRIGGER)
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if (rsi_tail >= 70).any() or (rsi_tail <= 30).any():
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# print('--RSI', end = '')
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plot_indicator += 'RSI, '
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# VoRSI outside window (over bought / over sold)
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vorsi_tail = vorsi.tail(LB_TRIGGER)
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if (vorsi_tail >= 70).any() or (vorsi_tail <= 30).any():
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# print('--VoRSI', end = '')
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plot_indicator += 'VoRSI, '
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# Normalized MACD histogram out of 3% range
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norm_hist_tail = abs(norm_hist.tail(LB_TRIGGER))
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if (abs(norm_hist_tail) >= 0.02).any():
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# print('--MACD/R', end = '') # outside normal range
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plot_indicator += 'MACD/R, '
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# MACD histogram zero crossing
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macd_hist_tail = macd_hist.tail(LB_TRIGGER)
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macd_hist_sign = np.sign(macd_hist_tail)
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macd_hist_diff = macd_hist_sign.diff()
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if (abs(macd_hist_diff) > 1).any():
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# print('--MACD', end = '') # zero crossing
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plot_indicator += 'MACD, '
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# Stock price crosses SMA50
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sma50_cross_tail = sma50.tail(LB_TRIGGER) - price.tail(LB_TRIGGER)
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sma50_cross_sign = np.sign(sma50_cross_tail)
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sma50_cross_diff = sma50_cross_sign.diff()
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if (abs(sma50_cross_diff) > 1).any():
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# print('--SMA50', end = '')
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plot_indicator += 'SMA50, '
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# Death cross or golden cross - SMA50 vs SMA200
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sma_cross_tail = sma50.tail(LB_TRIGGER) - sma200.tail(LB_TRIGGER).values
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sma_cross_sign = np.sign(sma_cross_tail)
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sma_cross_diff = sma_cross_sign.diff()
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if (abs(sma_cross_diff) > 1).any():
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# print('--Golden/Death', end = '')
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plot_indicator += 'Golden/Death, '
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# Price outside bollinger band or crossing
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price_tail = price.tail(LB_TRIGGER)
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bol_low_tail = bol_low.tail(LB_TRIGGER)
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bol_up_tail = bol_up.tail(LB_TRIGGER)
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price_high = price_tail - bol_up_tail.values
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price_low = price_tail - bol_low_tail.values
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if (price_high >= 0).any() or (price_low <= 0).any():
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# print('--Bollinger', end ='')
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plot_indicator += 'Bollinger, '
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# Price cross 200 day moving average
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sma200_tail = sma200.tail(LB_TRIGGER)
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sma200_cross = price_tail - sma200_tail.values
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sma200_cross_sign = np.sign(sma200_cross)
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sma200_cross_diff = sma200_cross_sign.diff()
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if (abs(sma200_cross_diff) > 1).any():
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# print('--SMA200', end = '')
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plot_indicator += 'SMA200, '
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# Large trading volume trigger
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volume_tail = vol.tail(LB_TRIGGER)
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vol_mean = vol.tail(50).mean()
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vol_std = vol.tail(50).std()
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if ((volume_tail - vol_mean - 2*vol_std) > 0).any():
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# print('--HiVol', end = '')
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plot_indicator += "HiVol, "
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# print(f"-- {watchlist.loc[sym, 'Notes']}") # carriage return
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plot_indicator += ']'
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# note_field = watchlist.loc[sym, 'Notes'].strip().lower()
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# if note_field != "watch" and ( note_field == "skip" or \
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# plot_indicator =="[]" ):
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# continue # skipping plotting to save memory and time
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# plot basic price info
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data = price.copy().to_frame(sym)
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# to limit low bound when plotting in log scale
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bol_low.loc[sma200.divide(bol_low) > bol_up.divide(sma200).mul(3)] = np.nan
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data = data.join(bol_low.rename('_BOL200L'))
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data = data.join(bol_up.rename('_BOL200U'))
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data = data.join(sma200.rename('_SMA200'))
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data = data.join(sma50.rename('_SMA50'))
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data = data.join(vwma50.rename('_WVMA50'))
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macd = macd.to_frame('_MACD').join(macd_sig.rename('_SIG'))
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macd = macd.join(macd_hist.rename('_HIST'))
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# macd.rename(columns={sym: sym+'_MACD'}, inplace=True)
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rsi = rsi.to_frame('_RSI').join(vorsi.rename('_VoRSI'))
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# rsi.rename(columns={sym: sym+'_RSI'}, inplace=True)
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return data, vol.to_frame('_VOL'), macd, rsi, plot_indicator
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VALID_USERNAME_PASSWORD_PAIRS = {
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os.environ['USER1']:os.environ['PASS1'],
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os.environ['USER2']:os.environ['PASS2'],
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}
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class Auth:
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def __init__(self) -> None:
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self.username = None
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def user_login(self, username, password):
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if VALID_USERNAME_PASSWORD_PAIRS.get(username) == hash_password(password):
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self.username = username
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return True
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return False
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auth = Auth()
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# Initialize the app
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app = Dash(__name__)
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BasicAuth(
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app,
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# VALID_USERNAME_PASSWORD_PAIRS,
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auth_func=auth.user_login,
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secret_key=os.environ['SECRET_KEY'],
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)
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CACHE_CONFIG = {'CACHE_TYPE': 'SimpleCache'}
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cache = Cache()
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cache.init_app(app.server, config=CACHE_CONFIG)
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@cache.memoize(timeout=14400) # cache timeout set to 4 hours
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def fetch_stk_data(sym, sd):
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return si.get_data(sym, start_date=sd)[["adjclose", "volume"]]
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# App layout
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app.layout = [
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html.Div([
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html.Button('Load', id="reload-button", n_clicks=0,
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style={'font-size': '12px', 'width': '80px', 'display': 'inline-block', 'margin-bottom': '10px', 'margin-right': '5px', 'height':'36px', 'verticalAlign': 'top'}),
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# html.Label('Add ticker:', style={'width': '80px', 'display': 'inline-block', 'height':'36px', 'textAlign': 'center', 'adjust': 'right', 'margin-bottom': '10px', 'margin-right': '5px', 'verticalAlign': 'top'}),
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html.Div([
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html.Label('Add ticker:'),
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dcc.Input(id='input-ticker', type='text', maxLength=5, debounce=True, style={'height':'31px', 'width':'50px'}),
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], style={'width': '150px', 'text-align': 'center'}),
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html.Button('Remove', id="remove-button", n_clicks=0,
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style={'font-size': '12px', 'width': '80px', 'display': 'inline-block', 'margin-bottom': '10px', 'margin-right': '5px', 'height':'36px', 'verticalAlign': 'top'}),
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html.Div([
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dcc.Dropdown(id='symbols_dropdown_list',),
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], style={'width': '330px', 'text-align': 'center'}),
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html.Button('Auto Play', id="start-button", n_clicks=0,
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style={'font-size': '12px', 'width': '80px', 'display': 'inline-block', 'margin-bottom': '10px', 'margin-right': '5px', 'height':'36px', 'verticalAlign': 'top'}),
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], style={'display':'flex', 'justify-content':'center'}),
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dcc.Graph(
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figure={},
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id='controls-and-graph',
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style={'height':'85vh'}
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),
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dcc.Interval(
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id='interval-component',
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interval=3*1000, # in milliseconds
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n_intervals=0,
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max_intervals=1,
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disabled=True,
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),
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dcc.Store(id="signaling"), # to pass the input ticker and signal reload
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dcc.Store(id="del_sig") # to signal reload only after delete a ticker
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]
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app.clientside_callback(
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"""
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function(id) {
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document.addEventListener("keyup", function(event) {
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if (event.key == ' ') {
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document.getElementById('start-button').click()
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event.stopPropogation()
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}
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});
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return window.dash_clientside.no_update
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}
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""",
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Output("start-button", "id"),
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Input("start-button", "id")
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)
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# delete ticker button callback
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@callback(Output('del_sig', 'data'),
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Input("remove-button", "n_clicks"),
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State("symbols_dropdown_list", "value")
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)
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def remove_ticker(n, sym_raw : str):
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if n and len(sym_raw) > 0:
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sym = sym_raw.split()[0]
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remove_from_db(auth.username, sym.upper())
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return n
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return no_update
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# ticker input callback
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@callback(Output('signaling', component_property='data'),
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Input('input-ticker', component_property='value'))
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def update_tickers(ticker : str):
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if ticker:
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ticker_upper = ticker.upper()
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long_name = StockMapper().ticker_to_company_name.get(ticker_upper)
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if long_name:
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insert_into_db(auth.username, ticker_upper, long_name)
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return ticker_upper
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else:
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long_name = MutualFundMapper().ticker_to_series_id.get(ticker_upper)
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if long_name:
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insert_into_db(auth.username, ticker_upper, 'Mutual Fund - ' + long_name)
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return ticker_upper
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return no_update
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# start / stop button callback
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@callback(Output('interval-component', 'disabled'),
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Output("start-button", "children"),
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Output('symbols_dropdown_list', 'disabled'),
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Input("start-button", "n_clicks"),
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State("start-button", "children"),
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)
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def start_cycle(n, value):
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if n:
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if value == "Pause":
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return True, "Auto Play", False
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else:
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return False, "Pause", True
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return no_update
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# clear input
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@callback(Output('input-ticker', component_property='value'),
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Input("signaling", "data"),
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)
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def clear_input(d):
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return ''
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# reload button callback
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@callback(Output('symbols_dropdown_list', 'options'),
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Output('interval-component', 'n_intervals'),
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Output('interval-component', 'max_intervals'),
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Input("reload-button", "n_clicks"),
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Input("signaling", "data"),
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Input("del_sig", "data"),
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)
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def reload_syms(n, s, d):
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# if n or s or d:
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watchlist = get_watchlist(auth.username)
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symbols = (watchlist.iloc[:, 0] + " - " + watchlist.iloc[:, 1]).tolist()
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return symbols, 0, 2*len(symbols)
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# return no_update
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# interval callback
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@callback(Output('symbols_dropdown_list', 'value'),
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Input("signaling", "data"),
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Input("interval-component", "n_intervals"),
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State('symbols_dropdown_list', 'options'),
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)
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def cycle_syms(tick_input, n, syms):
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if not syms:
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return no_update
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triggered_id = ctx.triggered_id
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if triggered_id == "interval-component":
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return syms[n % len(syms)]
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elif triggered_id == "signaling":
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row_num = None
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tick_len = len(tick_input) + 2
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tick_match = tick_input + ' -'
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for i in range(0, len(syms)):
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if syms[i][0:tick_len] == tick_match:
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row_num = i
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break
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if row_num is not None:
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return syms[row_num]
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return no_update
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# dropdown callback
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@callback(
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Output(component_id='controls-and-graph', component_property='figure'),
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Input(component_id='symbols_dropdown_list', component_property='value'),
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# State('symbols_dropdown_list', 'options')
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# Input(component_id='signal', component_property='data'),
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)
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def update_graph(col_chosen):
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if not col_chosen:
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raise PreventUpdate
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# return no_update
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sym = col_chosen.split()[0]
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end_date = dt.datetime.today()
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start_date = end_date - dt.timedelta(days = round(365 * LB_YEAR))
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days_to_drop = round(365 * (LB_YEAR-PLT_YEAR))
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days_to_drop = days_to_drop if days_to_drop > 0 else 0
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tmp = fetch_stk_data(sym, start_date) # cached function all
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data, vol, macd, rsi, plot_ind = intelligent_loop_plots(sym, tmp)
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data.drop(data.index[:days_to_drop], inplace=True)
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vol.drop(vol.index[:days_to_drop], inplace=True)
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macd.drop(macd.index[:days_to_drop], inplace=True)
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rsi.drop(rsi.index[:days_to_drop], inplace=True)
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fig = make_subplots(
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rows=3,
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cols=1,
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shared_xaxes=True,
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row_heights=[0.6, 0.2, 0.2],
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vertical_spacing=0.02,
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specs=[[{"secondary_y": True}],[{"secondary_y": False}],[{"secondary_y": False}]],
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)
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price_line = px.line(
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data,
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x=data.index,
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y=data.columns.to_list(),
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)
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volume_line = px.bar(
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vol,
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x=vol.index,
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y=vol.columns.to_list(),
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)
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macd_line = px.line(
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macd,
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x=macd.index,
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y=['_MACD', '_SIG'],
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)
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macd_neg = macd.copy()
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macd_pos = macd.copy()
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macd_neg[macd_neg>0] = 0
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macd_pos[macd_pos<0] = 0
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macd_hist_pos = px.line(
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macd_pos,
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x=macd_pos.index,
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y=['_HIST'],
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)
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macd_hist_pos.update_traces(fill='tozeroy', line_color='rgba(0,100,0,0.5)', showlegend=False)
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macd_hist_neg = px.line(
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macd_neg,
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x=macd_neg.index,
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y=['_HIST'],
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)
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macd_hist_neg.update_traces(fill='tozeroy', line_color='rgba(100,0,0,0.5)', showlegend=False)
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rsi_line = px.line(
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rsi,
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x=rsi.index,
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y=['_RSI', '_VoRSI'],
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)
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fig.add_traces(price_line.data + volume_line.data, rows=1, cols=1, secondary_ys=[True, True, True, True, True, True, False])
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fig.add_traces(macd_line.data + macd_hist_pos.data + macd_hist_neg.data, rows=2, cols=1)
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fig.add_traces(rsi_line.data, rows=3, cols=1)
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# fig.update_traces(marker_color = 'rgba(0,0,250,0.5)',
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# marker_line_width = 0,
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# selector=dict(type="bar"),
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fig.layout.yaxis.title="Volume"
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fig.layout.yaxis2.title="Price ($)"
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fig.layout.yaxis2.type="log"
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fig.layout.yaxis3.title="MACD"
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fig.layout.yaxis4.title="RSI/VoRSI"
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fig.layout.yaxis.griddash="dash"
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fig.update_layout(title_text=sym+' - '+plot_ind, title_x=0.5,
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margin=dict(l=30, r=20, t=50, b=20),
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)
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# fig.update_layout(showlegend=False)
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return fig
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if __name__ == "__main__":
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serve(app.server, host="0.0.0.0", port=8050, threads=7) # using production quality WSGI server Waitress
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# app.run(debug=True)
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