toonchien/Options
0
1# -*- coding: utf-8 -*-2"""Untitled8.ipynb3 4Automatically generated by Colab.5 6Original file is located at7 https://colab.research.google.com/drive/1-trZwwGMPWA_C9u7gec4eHux9sPbaADQ8"""9 10#!pip install pandas gradio yfinance11 12import gradio as gr13import pandas as pd14import yfinance as yf15from datetime import datetime16from dateutil.relativedelta import relativedelta17import tempfile18import os19 20 21def scan_options(ticker, strike_price, months):22 23 try:24 ticker = ticker.upper().strip()25 26 stock = yf.Ticker(ticker)27 28 hist = stock.history(period="1d")29 30 if hist.empty:31 return "Invalid Ticker", pd.DataFrame(), None32 33 current_price = float(hist["Close"].iloc[-1])34 35 today = datetime.today()36 max_expiry = today + relativedelta(months=int(months))37 38 results = []39 40 for expiry in stock.options:41 42 expiry_date = datetime.strptime(43 expiry,44 "%Y-%m-%d"45 )46 47 # Filter by selected months48 if expiry_date > max_expiry:49 continue50 51 try:52 53 chain = stock.option_chain(expiry)54 55 days_to_expiry = max(56 (expiry_date - today).days,57 158 )59 60 # CALL OPTIONS61 calls = chain.calls62 63 matching_calls = calls[64 calls["strike"] == strike_price65 ]66 67 for _, row in matching_calls.iterrows():68 69 premium = float(row["lastPrice"])70 71 roi = (72 premium /73 strike_price74 ) * 10075 76 annualized_roi = (77 roi *78 365 /79 days_to_expiry80 )81 82 results.append({83 "Type": "CALL",84 "Expiration": expiry,85 "Days": days_to_expiry,86 "Stock Price":87 round(current_price, 2),88 "Strike":89 row["strike"],90 "Premium":91 premium,92 "Bid":93 row["bid"],94 "Ask":95 row["ask"],96 "Volume":97 row["volume"],98 "Open Interest":99 row["openInterest"],100 "IV (%)":101 round(102 row["impliedVolatility"] * 100,103 2104 ),105 "Breakeven":106 round(107 row["strike"] + premium,108 2109 ),110 "ROI (%)":111 round(roi, 2),112 "Annualized ROI (%)":113 round(114 annualized_roi,115 2116 )117 })118 119 # PUT OPTIONS120 puts = chain.puts121 122 matching_puts = puts[123 puts["strike"] == strike_price124 ]125 126 for _, row in matching_puts.iterrows():127 128 premium = float(row["lastPrice"])129 130 roi = (131 premium /132 strike_price133 ) * 100134 135 annualized_roi = (136 roi *137 365 /138 days_to_expiry139 )140 141 results.append({142 "Type": "PUT",143 "Expiration": expiry,144 "Days": days_to_expiry,145 "Stock Price":146 round(current_price, 2),147 "Strike":148 row["strike"],149 "Premium":150 premium,151 "Bid":152 row["bid"],153 "Ask":154 row["ask"],155 "Volume":156 row["volume"],157 "Open Interest":158 row["openInterest"],159 "IV (%)":160 round(161 row["impliedVolatility"] * 100,162 2163 ),164 "Breakeven":165 round(166 row["strike"] - premium,167 2168 ),169 "ROI (%)":170 round(roi, 2),171 "Annualized ROI (%)":172 round(173 annualized_roi,174 2175 )176 })177 178 except Exception:179 continue180 181 if len(results) == 0:182 183 empty_df = pd.DataFrame({184 "Message": [185 "No matching options found."186 ]187 })188 189 return (190 f"Current Stock Price: ${current_price:.2f}",191 empty_df,192 None193 )194 195 df = pd.DataFrame(results)196 197 df = df.sort_values(198 by="Annualized ROI (%)",199 ascending=False200 )201 202 csv_file = os.path.join(203 tempfile.gettempdir(),204 f"{ticker}_{strike_price}_{months}M_ROI.csv"205 )206 207 df.to_csv(csv_file, index=False)208 209 return (210 f"Current Stock Price: ${current_price:.2f}",211 df,212 csv_file213 )214 215 except Exception as e:216 217 return (218 "Error",219 pd.DataFrame({"Error": [str(e)]}),220 None221 )222 223 224with gr.Blocks(225 title="US Option ROI Scanner"226) as demo:227 228 gr.Markdown(229 """230 # 📈 US Option ROI Scanner231 232 Enter:233 234 1. US Stock Ticker235 2. Strike Price236 3. Date Range (Months)237 238 Results include:239 240 - Calls & Puts241 - Premium242 - ROI %243 - Annualized ROI %244 - Breakeven245 - CSV Download246 """247 )248 249 with gr.Row():250 251 ticker = gr.Textbox(252 label="Ticker",253 placeholder="AAPL"254 )255 256 strike = gr.Number(257 label="Strike Price",258 value=200259 )260 261 months = gr.Number(262 label="Date Range (Months)",263 value=6,264 precision=0265 )266 267 scan_btn = gr.Button(268 "Scan Options"269 )270 271 stock_price = gr.Textbox(272 label="Current Stock Price"273 )274 275 results = gr.Dataframe(276 label="ROI Results",277 interactive=False278 )279 280 csv_download = gr.File(281 label="Download CSV"282 )283 284 scan_btn.click(285 fn=scan_options,286 inputs=[287 ticker,288 strike,289 months290 ],291 outputs=[292 stock_price,293 results,294 csv_download295 ]296 )297 298if __name__ == "__main__":299 demo.launch(share=True)