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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)) | |