Update app.py

app.py

@@ -55,40 +55,108 @@ def calculate_basic_indicators(data: pd.DataFrame) -> pd.DataFrame:
     return df.ffill().bfill()
 
 @pxt.udf
-def generate_analysis_prompt(data: str, analysis_type: str) -> list[dict]:
+def generate_analysis_prompt(data: str, analysis_type: str, time_horizon: str, 
+                           risk_tolerance: str, investment_style: str, 
+                           technical_depth: str) -> list[dict]:
     """Generate a structured prompt for AI analysis"""
-    system_prompt = '''You are a financial analyst providing market analysis. Structure your response using EXACTLY the following format and sections:
+    
+    # Create specific guidance based on parameters
+    time_horizon_guidance = {
+        'short': 'Focus on short-term trading opportunities within 1-3 months. Emphasize technical signals and immediate catalysts.',
+        'medium': 'Balance short-term opportunities with medium-term trends over 3-12 months. Consider both technical and fundamental factors.',
+        'long': 'Prioritize long-term growth potential over 1+ years. Emphasize fundamental analysis and strategic positioning.'
+    }
+    
+    risk_tolerance_guidance = {
+        'conservative': 'Prioritize capital preservation. Focus on stable, large-cap stocks with strong fundamentals. Suggest conservative options strategies like covered calls.',
+        'moderate': 'Balance growth opportunities with risk management. Consider mid-cap stocks and moderate options strategies.',
+        'aggressive': 'Seek high-growth opportunities. Include small-cap stocks and more aggressive options strategies in the analysis.'
+    }
+    
+    investment_style_guidance = {
+        'value': 'Focus on valuation metrics, margin of safety, and undervalued opportunities.',
+        'growth': 'Emphasize revenue growth, market expansion, and future potential.',
+        'momentum': 'Focus on price trends, relative strength, and technical indicators.',
+        'balanced': 'Consider both value and growth factors, maintaining a balanced perspective.',
+        'income': 'Prioritize dividend yield, payout ratio, and income-generating options strategies.'
+    }
+    
+    analysis_depth = {
+        'comprehensive': 'Provide detailed analysis across all categories.',
+        'quantitative': 'Focus on numerical metrics and statistical analysis.',
+        'technical': 'Emphasize technical analysis and chart patterns.'
+    }
+    
+    technical_guidance = {
+        'basic': 'Focus on essential technical indicators (MA, RSI, MACD).',
+        'advanced': 'Include advanced technical analysis including Fibonacci levels, Elliott Wave patterns, and advanced options analysis.'
+    }
+
+    system_prompt = f'''You are a senior investment advisor and market analyst with decades of experience, holding CFA and CMT certifications. Provide analysis tailored to the following parameters:
+
+TIME HORIZON: {time_horizon.upper()}
+{time_horizon_guidance[time_horizon]}
+
+RISK PROFILE: {risk_tolerance.upper()}
+{risk_tolerance_guidance[risk_tolerance]}
+
+INVESTMENT STYLE: {investment_style.upper()}
+{investment_style_guidance[investment_style]}
+
+ANALYSIS FOCUS: {analysis_type.upper()}
+{analysis_depth[analysis_type]}
+
+TECHNICAL DEPTH: {technical_depth.upper()}
+{technical_guidance[technical_depth]}
+
+Structure your response using EXACTLY the following format and sections:
 
 SUMMARY
-Provide a clear 2-3 sentence executive summary of your analysis.
+Provide a clear 2-3 sentence executive summary aligned with the specified time horizon ({time_horizon}) and risk tolerance ({risk_tolerance}).
 
 TECHNICAL ANALYSIS
-• Moving Averages: Analyze trends using MA20, MA50, and MA200
+{technical_guidance[technical_depth]}
+• Moving Averages: Analyze trends with emphasis on {time_horizon} timeframe
 • RSI Analysis: Current RSI level and implications
-• MACD Analysis: MACD trends and signals
+• MACD Analysis: Signal trends relevant to {time_horizon} horizon
 • Volume Analysis: Notable volume patterns and implications
+{"• Advanced Patterns: Fibonacci levels, Elliott Wave analysis" if technical_depth == "advanced" else ""}
 
 MARKET CONTEXT
-• List 2-3 key market factors affecting the stock
-• Include relevant sector/industry context
-• Note any significant recent developments
+• Sector Analysis: {"Long-term industry trends and positioning" if time_horizon == "long" else "Short-term sector momentum" if time_horizon == "short" else "Medium-term sector outlook"}
+• {"Fundamental Drivers: Key growth catalysts" if investment_style == "growth" else "Value Metrics: Key valuation catalysts" if investment_style == "value" else "Market Dynamics: Key price catalysts"}
+• Economic Impact: Factors relevant to {time_horizon} horizon
 
 RISKS
-• Risk 1: [Specific risk and brief explanation]
-• Risk 2: [Specific risk and brief explanation]
-• Risk 3: [Specific risk and brief explanation]
+• Identify and quantify risks specific to {risk_tolerance} risk tolerance
+• Focus on {time_horizon} horizon risks
+• {"Include volatility analysis" if technical_depth == "advanced" else ""}
 
 OPPORTUNITIES
-• Opportunity 1: [Specific opportunity and brief explanation]
-• Opportunity 2: [Specific opportunity and brief explanation]
-• Opportunity 3: [Specific opportunity and brief explanation]
+• Align opportunities with {investment_style} style
+• Focus on {time_horizon} timeline
+• Match risk/reward to {risk_tolerance} profile
+
+OPTIONS STRATEGY
+{"• Advanced Options Analysis: Complex strategies and volatility analysis" if technical_depth == "advanced" else "• Basic Options Strategies: Simple hedging and income generation"}
+• Tailor strategies to {risk_tolerance} risk tolerance
+• Focus on {time_horizon} expiration cycles
+• Match strategies to {investment_style} style objectives
 
 RECOMMENDATION
-Provide a clear, actionable investment recommendation based on the analysis above.'''
+• Provide specific recommendations aligned with:
+  - {time_horizon.capitalize()} time horizon
+  - {risk_tolerance.capitalize()} risk tolerance
+  - {investment_style.capitalize()} investment style
+• Include position sizing appropriate for risk level
+• Specify entry, exit, and stop-loss levels
+• {"Include advanced technical levels" if technical_depth == "advanced" else "Focus on key support/resistance levels"}
+
+IMPORTANT: This analysis is for informational purposes only. All investments carry risk. Please consult with a licensed financial advisor before making investment decisions.'''
 
     return [
         {'role': 'system', 'content': system_prompt},
-        {'role': 'user', 'content': f'Analyze this market data for {analysis_type} analysis:\n{data}'}
+        {'role': 'user', 'content': f'Analyze this market data considering the specified parameters:\n{data}'}
     ]
 
 def parse_analysis_response(response: str) -> Dict[str, str]:
@@ -99,6 +167,7 @@ def parse_analysis_response(response: str) -> Dict[str, str]:
         'MARKET CONTEXT': None,
         'RISKS': None,
         'OPPORTUNITIES': None,
+        'OPTIONS STRATEGY': None,
         'RECOMMENDATION': None
     }
     
@@ -140,6 +209,7 @@ def parse_analysis_response(response: str) -> Dict[str, str]:
         'MARKET CONTEXT': 'Market context information not available',
         'RISKS': 'Risk assessment not available',
         'OPPORTUNITIES': 'Opportunity analysis not available',
+        'OPTIONS STRATEGY': 'Options trading analysis not available',
         'RECOMMENDATION': 'Investment recommendation not available'
     }
     
@@ -252,6 +322,26 @@ def process_outputs(ticker_symbol, analysis_type, time_horizon, risk_tolerance,
         market_data = stock.history(period='1y')
         if market_data.empty:
             raise ValueError("No data found for the specified ticker symbol.")
+        options_data = stock.options  # Get available expiration dates
+
+        if len(options_data) > 0:
+            nearest_expiry = options_data[0]
+            opt_chain = stock.option_chain(nearest_expiry)
+            options_info = {
+                'Nearest Expiry': nearest_expiry,
+                'Call Volume': int(opt_chain.calls['volume'].sum()),
+                'Put Volume': int(opt_chain.puts['volume'].sum()),
+                'Put/Call Ratio': float(opt_chain.puts['volume'].sum() / opt_chain.calls['volume'].sum()),
+                'Implied Volatility': float(opt_chain.calls['impliedVolatility'].mean())
+            }
+        else:
+            options_info = {
+                'Nearest Expiry': 'N/A',
+                'Call Volume': 0,
+                'Put Volume': 0,
+                'Put/Call Ratio': 0,
+                'Implied Volatility': 0
+            }
 
         technical_data = calculate_basic_indicators(market_data)
         market_data_json = technical_data.to_json(date_format='iso')
@@ -263,7 +353,14 @@ def process_outputs(ticker_symbol, analysis_type, time_horizon, risk_tolerance,
             'timestamp': datetime.now()
         }])
 
-        data_table['prompt'] = generate_analysis_prompt(data_table.data, analysis_type)
+        data_table['prompt'] = generate_analysis_prompt(
+            data_table.data,
+            analysis_type,
+            time_horizon,
+            risk_tolerance,
+            investment_style,
+            technical_depth
+        )
         data_table['analysis'] = openai.chat_completions(
             messages=data_table.prompt,
             model='gpt-4o-mini-2024-07-18',
@@ -324,15 +421,17 @@ def process_outputs(ticker_symbol, analysis_type, time_horizon, risk_tolerance,
         return (
             json.dumps(company_info_data),
             json.dumps(market_stats_data),
+            json.dumps(options_info),  # Add options info to return values
             plot,
             parsed_analysis['SUMMARY'],
             parsed_analysis['TECHNICAL ANALYSIS'],
             parsed_analysis['MARKET CONTEXT'],
             parsed_analysis['RISKS'],
             parsed_analysis['OPPORTUNITIES'],
+            parsed_analysis['OPTIONS STRATEGY'],  # Add options strategy
             parsed_analysis['RECOMMENDATION'],
             technical_data_with_time,
-            raw_llm_output  # Add raw output to return values
+            raw_llm_output
         )
 
     except Exception as e:
@@ -342,6 +441,7 @@ def process_outputs(ticker_symbol, analysis_type, time_horizon, risk_tolerance,
         empty_df = pd.DataFrame()
         
         return (
+            empty_json,
             empty_json,
             empty_json,
             None,
@@ -351,8 +451,9 @@ def process_outputs(ticker_symbol, analysis_type, time_horizon, risk_tolerance,
             no_data_msg,
             no_data_msg,
             no_data_msg,
+            no_data_msg,
             empty_df,
-            f"Error occurred: {str(e)}"  # Add error message to raw output
+            f"Error occurred: {str(e)}"
         )
 
 def create_interface() -> gr.Blocks:
@@ -472,6 +573,11 @@ def create_interface() -> gr.Blocks:
                                     label="Market Statistics",
                                     height=150
                                 )
+                            with gr.Column(scale=1):
+                                options_info = gr.JSON(
+                                    label="Options Market Data",
+                                    height=150
+                                )
                         
                     with gr.TabItem("📑 Historical Data"):
                         technical_data = gr.DataFrame(
@@ -544,6 +650,14 @@ def create_interface() -> gr.Blocks:
                             max_lines=7,
                             show_label=True
                         )
+
+                with gr.Row():
+                    options_strategy = gr.Textbox(
+                        label="Options Trading Strategy",
+                        lines=8,
+                        max_lines=10,
+                        show_label=True
+                    )
                 
                 with gr.Row():
                     recommendation = gr.Textbox(
@@ -606,10 +720,10 @@ def create_interface() -> gr.Blocks:
                 investment_style, technical_depth
             ],
             outputs=[
-                company_info, market_stats, plot_output,
+                company_info, market_stats, options_info, plot_output,
                 summary, tech_analysis, market_context,
-                risks, opportunities, recommendation,
-                technical_data, raw_output  # Add raw_output to outputs
+                risks, opportunities, options_strategy, recommendation,
+                technical_data, raw_output
             ]
         )