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from stocks import * | |
from functions import * | |
from datetime import datetime | |
import streamlit as st | |
st.set_page_config(layout="wide") | |
st.title("Tech Stocks Trading Assistant") | |
left_column, right_column = st.columns(2) | |
with left_column: | |
all_tickers = { | |
"Apple":"AAPL", | |
"Microsoft":"MSFT", | |
"Nvidia":"NVDA", | |
"Paypal":"PYPL", | |
"Amazon":"AMZN", | |
"Spotify":"SPOT", | |
#"Twitter":"TWTR", | |
"adanipower":"adanipower.ns", | |
"Uber":"UBER", | |
"Google":"GOOG" | |
} | |
st.subheader("Technical Analysis Methods") | |
option_name = st.selectbox('Choose a stock:', all_tickers.keys()) | |
option_ticker = all_tickers[option_name] | |
execution_timestamp = datetime.now() | |
'You selected: ', option_name, "(",option_ticker,")" | |
'Last execution:', execution_timestamp | |
s = Stock_Data() | |
t = s.Ticker(tick=option_ticker) | |
m = Models() | |
with st.spinner('Loading stock data...'): | |
technical_analysis_methods_outputs = { | |
'Technical Analysis Method': [ | |
'Bollinger Bands (20 days & 2 stand. deviations)', | |
'Bollinger Bands (10 days & 1.5 stand. deviations)', | |
'Bollinger Bands (50 days & 3 stand. deviations)', | |
'Moving Average Convergence Divergence (MACD)' | |
], | |
'Outlook': [ | |
m.bollinger_bands_20d_2std(t), | |
m.bollinger_bands_10d_1point5std(t), | |
m.bollinger_bands_50d_3std(t), | |
m.MACD(t) | |
], | |
'Timeframe of Method': [ | |
"Medium-term", | |
"Short-term", | |
"Long-term", | |
"Short-term" | |
] | |
} | |
df = pd.DataFrame(technical_analysis_methods_outputs) | |
def color_survived(val): | |
color = "" | |
if (val=="Sell" or val=="Downtrend and sell signal" or val=="Downtrend and no signal"): | |
color="#EE3B3B" | |
elif (val=="Buy" or val=="Uptrend and buy signal" or val=="Uptrend and no signal"): | |
color="#3D9140" | |
else: | |
color="#CD950C" | |
return f'background-color: {color}' | |
st.table(df.sort_values(['Timeframe of Method'], ascending=False). | |
reset_index(drop=True).style.applymap(color_survived, subset=['Outlook'])) | |
with right_column: | |
st.subheader("FinBERT-based Sentiment Analysis") | |
with st.spinner("Connecting with www.marketwatch.com..."): | |
st.plotly_chart(m.finbert_headlines_sentiment(t)["fig"]) | |
"Current sentiment:", m.finbert_headlines_sentiment(t)["current_sentiment"], "%" | |
st.subheader("LSTM-based 7-day stock price prediction model") | |
with st.spinner("Compiling LSTM model.."): | |
st.plotly_chart(m.LSTM_7_days_price_predictor(t)) | |