Create app.py

app.py

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+import streamlit as st
+import pandas as pd
+import numpy as np
+import yfinance as yf
+import plotly.graph_objects as go
+from plotly.subplots import make_subplots
+import warnings
+warnings.filterwarnings('ignore')
+from curl_cffi import requests
+session = requests.Session(impersonate="chrome")
+
+# Import all technical indicators from your file
+from technical_indicators import *
+
+# Page configuration
+st.set_page_config(
+    page_title="Technical Analysis Dashboard",
+    page_icon="📈",
+    layout="wide",
+    initial_sidebar_state="expanded"
+)
+
+# Custom CSS for better styling
+st.markdown("""
+<style>
+    .main-header {
+        font-size: 2.5rem;
+        font-weight: bold;
+        color: #1f77b4;
+        text-align: center;
+        margin-bottom: 2rem;
+    }
+    .sub-header {
+        font-size: 1.5rem;
+        font-weight: bold;
+        text-align: center;
+        margin-bottom: 1rem;
+    }
+    .metric-container {
+        background-color: #f0f2f6;
+        padding: 1rem;
+        border-radius: 0.5rem;
+        margin: 0.5rem 0;
+    }
+    .indicator-section {
+        background-color: #ffffff;
+        padding: 1.5rem;
+        border-radius: 0.5rem;
+        margin: 1rem 0;
+        border: 1px solid #e0e0e0;
+    }
+</style>
+""", unsafe_allow_html=True)
+
+# Title
+st.markdown('<h1 class="main-header">📈 Technical Analysis Dashboard</h1>', unsafe_allow_html=True)
+st.markdown('<h3 class="sub-header">Developed By Zane Vijay Falcao</h3>', unsafe_allow_html=True)
+st.divider()
+# Sidebar for inputs
+with st.sidebar:
+    st.header("📊 Configuration")
+    
+    # Stock symbol input
+    symbol = st.text_input("Stock Symbol", value="AAPL", help="Enter stock symbol (e.g., AAPL, GOOGL, MSFT)")
+    
+    # Time period selection
+    period = st.selectbox(
+        "Time Period",
+        ["1mo", "3mo", "6mo", "1y", "2y", "5y", "max"],
+        index=3
+    )
+    
+    # Interval selection
+    interval = st.selectbox(
+        "Data Interval",
+        ["1d", "5d", "1wk", "1mo"],
+        index=0
+    )
+    
+    st.divider()
+    
+    # Indicator Categories
+    st.header("📈 Select Indicators")
+    
+    # Trend Indicators
+    with st.expander("Trend Indicators", expanded=True):
+        show_sma = st.checkbox("Simple Moving Average (SMA)", value=True)
+        show_ema = st.checkbox("Exponential Moving Average (EMA)", value=True)
+        show_hma = st.checkbox("Hull Moving Average (HMA)")
+        show_wma = st.checkbox("Weighted Moving Average (WMA)")
+        show_kama = st.checkbox("Kaufman Adaptive Moving Average (KAMA)")
+        show_frama = st.checkbox("Fractal Adaptive Moving Average (FRAMA)")
+        show_evwma = st.checkbox("Ehlers Volatility Weighted MA (EVWMA)")
+        show_vwap = st.checkbox("Volume Weighted Average Price (VWAP)")
+    
+    # Momentum Indicators
+    with st.expander("Momentum Indicators", expanded=True):
+        show_rsi = st.checkbox("Relative Strength Index (RSI)", value=True)
+        show_macd = st.checkbox("MACD", value=True)
+        show_stochrsi = st.checkbox("Stochastic RSI")
+        show_cmo = st.checkbox("Chande Momentum Oscillator (CMO)")
+        show_roc = st.checkbox("Rate of Change (ROC)")
+        show_tsi = st.checkbox("True Strength Index (TSI)")
+        show_kst = st.checkbox("Know Sure Thing (KST)")
+        show_ppo = st.checkbox("Price Percentage Oscillator (PPO)")
+        show_uo = st.checkbox("Ultimate Oscillator (UO)")
+    
+    # Volume Indicators
+    with st.expander("Volume Indicators"):
+        show_obv = st.checkbox("On-Balance Volume (OBV)")
+        show_adl = st.checkbox("Accumulation/Distribution Line (ADL)")
+        show_chaikin = st.checkbox("Chaikin Oscillator")
+        show_efi = st.checkbox("Elder's Force Index (EFI)")
+        show_emv = st.checkbox("Ease of Movement (EMV)")
+        show_mfi = st.checkbox("Money Flow Index (MFI)")
+        show_vpt = st.checkbox("Volume Price Trend (VPT)")
+        show_fve = st.checkbox("Fractal Volume Efficiency (FVE)")
+        show_vzo = st.checkbox("Volume Zone Oscillator (VZO)")
+    
+    # Volatility Indicators
+    with st.expander("Volatility Indicators"):
+        show_bollinger = st.checkbox("Bollinger Bands", value=True)
+        show_kc = st.checkbox("Keltner Channels")
+        show_dc = st.checkbox("Donchian Channels")
+        show_atr = st.checkbox("Average True Range (ATR)")
+        show_chandelier = st.checkbox("Chandelier Exit")
+        show_psar = st.checkbox("Parabolic SAR")
+        show_apz = st.checkbox("Adaptive Price Zone (APZ)")
+    
+    # Oscillators
+    with st.expander("Oscillators"):
+        show_adx = st.checkbox("Average Directional Index (ADX)")
+        show_cci = st.checkbox("Commodity Channel Index (CCI)")
+        show_fish = st.checkbox("Fisher Transform")
+        show_ao = st.checkbox("Awesome Oscillator (AO)")
+        show_mi = st.checkbox("Mass Index (MI)")
+        show_wto = st.checkbox("Wave Trend Oscillator (WTO)")
+        show_copp = st.checkbox("Coppock Curve")
+        show_ift_rsi = st.checkbox("Inverse Fisher Transform RSI")
+    
+    # Complex Indicators
+    with st.expander("Complex Indicators"):
+        show_ichimoku = st.checkbox("Ichimoku Cloud")
+        show_pivot = st.checkbox("Pivot Points")
+        show_pivot_fib = st.checkbox("Fibonacci Pivot Points")
+        show_basp = st.checkbox("Buyer and Seller Pressure (BASP)")
+        show_baspn = st.checkbox("Normalized BASP")
+        show_dmi = st.checkbox("Directional Movement Index (DMI)")
+        show_ebbp = st.checkbox("Elder Bull/Bear Power")
+    
+    st.divider()
+    
+    # Parameter settings
+    st.header("⚙️ Parameters")
+    sma_period = st.slider("SMA Period", 5, 50, 20)
+    ema_period = st.slider("EMA Period", 5, 50, 20)
+    rsi_period = st.slider("RSI Period", 5, 30, 14)
+    bb_period = st.slider("Bollinger Bands Period", 10, 30, 20)
+    bb_std = st.slider("Bollinger Bands Std Dev", 1.0, 3.0, 2.0, 0.1)
+
+
+col1, col2, col3, col4, col5 = st.columns(5)
+st.divider()
+@st.cache_data
+def fetch_data(symbol, period, interval):
+    ticker = yf.Ticker(symbol.upper(), session=session)
+    return ticker.history(period=period, interval=interval)
+
+# Main content area
+if col3.button("🚀 Analyze Stock", type="secondary", use_container_width=True):
+    
+    try:
+        # Fetch data
+        with st.spinner(f"Fetching data for {symbol.upper()}..."):
+            
+            data = fetch_data(symbol, period, interval)
+            
+            if data.empty:
+                st.error("No data found for the given symbol. Please check the symbol and try again.")
+                st.stop()
+        
+        # Display basic info
+        col1, col2, col3, col4 = st.columns(4)
+        
+        with col1:
+            st.metric("Current Price", f"${data['Close'].iloc[-1]:.2f}")
+        
+        with col2:
+            price_change = data['Close'].iloc[-1] - data['Close'].iloc[-2]
+            st.metric("Price Change", f"${price_change:.2f}", f"{price_change:.2f}")
+        
+        with col3:
+            pct_change = (price_change / data['Close'].iloc[-2]) * 100
+            st.metric("% Change", f"{pct_change:.2f}%", f"{pct_change:.2f}%")
+        
+        with col4:
+            st.metric("Volume", f"{data['Volume'].iloc[-1]:,.0f}")
+        
+        # Calculate indicators
+        indicators = {}
+        
+        # Trend Indicators
+        if show_sma:
+            indicators['SMA'] = SMA(data, sma_period)
+        if show_ema:
+            indicators['EMA'] = EMA(data, ema_period)
+        if show_hma:
+            indicators['HMA'] = HMA(data, 20)
+        if show_wma:
+            indicators['WMA'] = WMA(data, 20)
+        if show_kama:
+            indicators['KAMA'] = KAMA(data)
+        if show_frama:
+            indicators['FRAMA'] = FRAMA(data)
+        if show_evwma:
+            indicators['EVWMA'] = EVWMA(data)
+        if show_vwap:
+            indicators['VWAP'] = VWAP(data)
+        
+        # Momentum Indicators
+        if show_rsi:
+            indicators['RSI'] = RSI(data, rsi_period)
+        if show_macd:
+            indicators['MACD'] = MACD(data)
+        if show_stochrsi:
+            indicators['StochRSI'] = STOCHRSI(data)
+        if show_cmo:
+            indicators['CMO'] = CMO(data)
+        if show_roc:
+            indicators['ROC'] = ROC(data)
+        if show_tsi:
+            indicators['TSI'] = TSI(data)
+        if show_kst:
+            indicators['KST'] = KST(data)
+        if show_ppo:
+            indicators['PPO'] = PPO(data)
+        if show_uo:
+            indicators['UO'] = UO(data)
+        
+        # Volume Indicators
+        if show_obv:
+            indicators['OBV'] = OBV(data)
+        if show_adl:
+            indicators['ADL'] = ADL(data)
+        if show_chaikin:
+            indicators['Chaikin'] = CHAIKIN(data)
+        if show_efi:
+            indicators['EFI'] = EFI(data)
+        if show_emv:
+            indicators['EMV'] = EMV(data)
+        if show_mfi:
+            indicators['MFI'] = MFI(data)
+        if show_vpt:
+            indicators['VPT'] = VPT(data)
+        if show_fve:
+            indicators['FVE'] = FVE(data)
+        if show_vzo:
+            indicators['VZO'] = VZO(data)
+        
+        # Volatility Indicators
+        if show_bollinger:
+            indicators['Bollinger'] = BOLLINGER(data, bb_period, bb_std)
+        if show_kc:
+            indicators['KC'] = KC(data)
+        if show_dc:
+            indicators['DC'] = DC(data)
+        if show_atr:
+            indicators['ATR'] = ATR(data)
+        if show_chandelier:
+            indicators['Chandelier'] = CHANDELIER(data)
+        if show_psar:
+            indicators['PSAR'] = PSAR(data)
+        if show_apz:
+            indicators['APZ'] = APZ(data)
+        
+        # Oscillators
+        if show_adx:
+            indicators['ADX'] = ADX(data)
+        if show_cci:
+            indicators['CCI'] = CCI(data)
+        if show_fish:
+            indicators['Fisher'] = FISH(data)
+        if show_ao:
+            indicators['AO'] = AO(data)
+        if show_mi:
+            indicators['MI'] = MI(data)
+        if show_wto:
+            indicators['WTO'] = WTO(data)
+        if show_copp:
+            indicators['Coppock'] = COPP(data)
+        if show_ift_rsi:
+            indicators['IFT_RSI'] = IFT_RSI(data)
+        
+        # Complex Indicators
+        if show_ichimoku:
+            indicators['Ichimoku'] = ICHIMOKU(data)
+        if show_pivot:
+            indicators['Pivot'] = PIVOT(data)
+        if show_pivot_fib:
+            indicators['Pivot_Fib'] = PIVOT_FIB(data)
+        if show_basp:
+            indicators['BASP'] = BASP(data)
+        if show_baspn:
+            indicators['BASPN'] = BASPN(data)
+        if show_dmi:
+            indicators['DMI'] = DMI(data)
+        if show_ebbp:
+            indicators['EBBP'] = EBBP(data)
+        
+        # Create main price chart
+        fig = make_subplots(
+            rows=4, cols=1,
+            shared_xaxes=True,
+            vertical_spacing=0.05,
+            subplot_titles=('Price Chart', 'Volume', 'Oscillators', 'Additional Indicators'),
+            row_heights=[0.5, 0.2, 0.15, 0.15]
+        )
+
+        # Add candlestick chart
+        fig.add_trace(
+            go.Candlestick(
+                x=data.index,
+                open=data['Open'],
+                high=data['High'],
+                low=data['Low'],
+                close=data['Close'],
+                name='Price'
+            ),
+            row=1, col=1
+        )
+
+        # Define colors for trend indicators to avoid repetition
+        colors = ["red", "yellow", "green", "purple", "orange", "brown", "pink", "gray", "cyan", "magenta"]
+        color_idx = 0
+
+        # Add trend indicators to price chart (row 1)
+        trend_indicators = ['SMA', 'EMA', 'HMA', 'WMA', 'KAMA', 'FRAMA', 'EVWMA', 'VWAP']
+        for name in trend_indicators:
+            if name in indicators:
+                fig.add_trace(
+                    go.Scatter(
+                        x=data.index,
+                        y=indicators[name].fillna(method='ffill'),  # Handle NaNs
+                        mode='lines',
+                        name=name,
+                        line=dict(color=colors[color_idx % len(colors)])
+                    ),
+                    row=1, col=1
+                )
+                color_idx += 1
+
+        # Add volatility indicators to price chart (row 1)
+        if 'Bollinger' in indicators:
+            bb = indicators['Bollinger']
+            fig.add_trace(
+                go.Scatter(
+                    x=data.index,
+                    y=bb['BB_UPPER'].fillna(method='ffill'),
+                    mode='lines',
+                    name='BB Upper',
+                    line=dict(color='lightblue', dash='dash')
+                ),
+                row=1, col=1
+            )
+            fig.add_trace(
+                go.Scatter(
+                    x=data.index,
+                    y=bb['BB_LOWER'].fillna(method='ffill'),
+                    mode='lines',
+                    name='BB Lower',
+                    line=dict(color='lightblue', dash='dash'),
+                    fill='tonexty',
+                    fillcolor='rgba(173, 216, 230, 0.2)'
+                ),
+                row=1, col=1
+            )
+
+        if 'KC' in indicators:
+            kc = indicators['KC']
+            fig.add_trace(
+                go.Scatter(x=data.index, y=kc['KC_UPPER'].fillna(method='ffill'), name='KC Upper', line=dict(color='orange')),
+                row=1, col=1
+            )
+            fig.add_trace(
+                go.Scatter(x=data.index, y=kc['KC_LOWER'].fillna(method='ffill'), name='KC Lower', line=dict(color='orange')),
+                row=1, col=1
+            )
+            fig.add_trace(
+                go.Scatter(x=data.index, y=kc['KC_MIDDLE'].fillna(method='ffill'), name='KC Middle', line=dict(color='gray', dash='dot')),
+                row=1, col=1
+            )
+
+        if 'DC' in indicators:
+            dc = indicators['DC']
+            fig.add_trace(
+                go.Scatter(x=data.index, y=dc['DC_U'].fillna(method='ffill'), name='DC Upper', line=dict(color='green')),
+                row=1, col=1
+            )
+            fig.add_trace(
+                go.Scatter(x=data.index, y=dc['DC_L'].fillna(method='ffill'), name='DC Lower', line=dict(color='green')),
+                row=1, col=1
+            )
+            fig.add_trace(
+                go.Scatter(x=data.index, y=dc['DC_M'].fillna(method='ffill'), name='DC Middle', line=dict(color='limegreen', dash='dot')),
+                row=1, col=1
+            )
+
+        if 'Chandelier' in indicators:
+            ce = indicators['Chandelier']
+            fig.add_trace(
+                go.Scatter(x=data.index, y=ce['CHANDELIER_Long'].fillna(method='ffill'), name='Chandelier Long', line=dict(color='darkred')),
+                row=1, col=1
+            )
+            fig.add_trace(
+                go.Scatter(x=data.index, y=ce['CHANDELIER_Short'].fillna(method='ffill'), name='Chandelier Short', line=dict(color='darkgreen')),
+                row=1, col=1
+            )
+
+        if 'APZ' in indicators:
+            apz = indicators['APZ']
+            fig.add_trace(
+                go.Scatter(x=data.index, y=apz['APZ_UPPER'].fillna(method='ffill'), name='APZ Upper', line=dict(color='orange', dash='dot')),
+                row=1, col=1
+            )
+            fig.add_trace(
+                go.Scatter(x=data.index, y=apz['APZ_LOWER'].fillna(method='ffill'), name='APZ Lower', line=dict(color='coral', dash='dot')),
+                row=1, col=1
+            )
+
+        if 'Ichimoku' in indicators:
+            ichimoku = indicators['Ichimoku']
+            fig.add_trace(
+                go.Scatter(x=data.index, y=ichimoku['TENKAN'].fillna(method='ffill'), name='Tenkan-sen', line=dict(color='blue')),
+                row=1, col=1
+            )
+            fig.add_trace(
+                go.Scatter(x=data.index, y=ichimoku['KIJUN'].fillna(method='ffill'), name='Kijun-sen', line=dict(color='red')),
+                row=1, col=1
+            )
+            fig.add_trace(
+                go.Scatter(x=data.index, y=ichimoku['SENKOU_A'].fillna(method='ffill'), name='Senkou A', line=dict(color='green')),
+                row=1, col=1
+            )
+            fig.add_trace(
+                go.Scatter(x=data.index, y=ichimoku['SENKOU_B'].fillna(method='ffill'), name='Senkou B', line=dict(color='red'), fill='tonexty', fillcolor='rgba(0, 255, 0, 0.2)'),
+                row=1, col=1
+            )
+            fig.add_trace(
+                go.Scatter(x=data.index, y=ichimoku['CHIKOU'].fillna(method='ffill'), name='Chikou Span', line=dict(color='purple')),
+                row=1, col=1
+            )
+
+        if 'Pivot' in indicators:
+            pivot = indicators['Pivot']
+            for col in ['pivot', 'r1', 'r2', 'r3', 's1', 's2', 's3']:
+                fig.add_trace(
+                    go.Scatter(x=data.index, y=pivot[col].fillna(method='ffill'), name=f'Pivot {col.upper()}', line=dict(dash='dash')),
+                    row=1, col=1
+                )
+
+        if 'Pivot_Fib' in indicators:
+            pivot_fib = indicators['Pivot_Fib']
+            for col in ['pivot', 'r1', 'r2', 'r3', 's1', 's2', 's3']:
+                fig.add_trace(
+                    go.Scatter(x=data.index, y=pivot_fib[col].fillna(method='ffill'), name=f'Fib Pivot {col.upper()}', line=dict(dash='dot')),
+                    row=1, col=1
+                )
+
+        if 'PSAR' in indicators:
+            psar = indicators['PSAR']
+            fig.add_trace(
+                go.Scatter(x=data.index, y=psar['psar'].fillna(method='ffill'), name='PSAR', mode='markers', marker=dict(size=5, color='blue')),
+                row=1, col=1
+            )
+            fig.add_trace(
+                go.Scatter(x=data.index, y=psar['psarbull'].fillna(method='ffill'), name='PSAR Bull', mode='markers', marker=dict(size=5, color='green')),
+                row=1, col=1
+            )
+            fig.add_trace(
+                go.Scatter(x=data.index, y=psar['psarbear'].fillna(method='ffill'), name='PSAR Bear', mode='markers', marker=dict(size=5, color='red')),
+                row=1, col=1
+            )
+
+        # Add volume (row 2)
+        fig.add_trace(
+            go.Bar(
+                x=data.index,
+                y=data['Volume'],
+                name='Volume',
+                marker_color='lightblue'
+            ),
+            row=2, col=1
+        )
+
+        # Add oscillators to row 3
+        if 'RSI' in indicators:
+            fig.add_trace(
+                go.Scatter(x=data.index, y=indicators['RSI'].fillna(method='ffill'), mode='lines', name='RSI', line=dict(color='purple')),
+                row=3, col=1
+            )
+            fig.add_hline(y=70, line_dash="dash", line_color="red", row=3, col=1)
+            fig.add_hline(y=30, line_dash="dash", line_color="green", row=3, col=1)
+
+        if 'StochRSI' in indicators:
+            fig.add_trace(
+                go.Scatter(x=data.index, y=indicators['StochRSI'].fillna(method='ffill'), mode='lines', name='StochRSI', line=dict(color='orange')),
+                row=3, col=1
+            )
+            fig.add_hline(y=80, line_dash="dash", line_color="red", row=3, col=1)
+            fig.add_hline(y=20, line_dash="dash", line_color="green", row=3, col=1)
+
+        if 'CCI' in indicators:
+            fig.add_trace(
+                go.Scatter(x=data.index, y=indicators['CCI'].fillna(method='ffill'), mode='lines', name='CCI', line=dict(color='blue')),
+                row=3, col=1
+            )
+            fig.add_hline(y=100, line_dash="dash", line_color="red", row=3, col=1)
+            fig.add_hline(y=-100, line_dash="dash", line_color="green", row=3, col=1)
+
+        if 'ADX' in indicators:
+            fig.add_trace(
+                go.Scatter(x=data.index, y=indicators['ADX'].fillna(method='ffill'), mode='lines', name='ADX', line=dict(color='cyan')),
+                row=3, col=1
+            )
+            fig.add_hline(y=25, line_dash="dash", line_color="gray", row=3, col=1)
+
+        if 'Fisher' in indicators:
+            fig.add_trace(
+                go.Scatter(x=data.index, y=indicators['Fisher'].fillna(method='ffill'), mode='lines', name='Fisher Transform', line=dict(color='magenta')),
+                row=3, col=1
+            )
+
+        if 'AO' in indicators:
+            fig.add_trace(
+                go.Scatter(x=data.index, y=indicators['AO'].fillna(method='ffill'), mode='lines', name='Awesome Oscillator', line=dict(color='green')),
+                row=3, col=1
+            )
+            fig.add_hline(y=0, line_dash="dash", line_color="gray", row=3, col=1)
+
+        if 'MI' in indicators:
+            fig.add_trace(
+                go.Scatter(x=data.index, y=indicators['MI'].fillna(method='ffill'), mode='lines', name='Mass Index', line=dict(color='purple')),
+                row=3, col=1
+            )
+            fig.add_hline(y=27, line_dash="dash", line_color="red", row=3, col=1)
+
+        if 'IFT_RSI' in indicators:
+            fig.add_trace(
+                go.Scatter(x=data.index, y=indicators['IFT_RSI'].fillna(method='ffill'), mode='lines', name='IFT RSI', line=dict(color='orange')),
+                row=3, col=1
+            )
+
+        # Add momentum and volume indicators to row 4
+        if 'MACD' in indicators:
+            macd = indicators['MACD']
+            macd_line = macd['MACD']
+            signal_line = macd['SIGNAL']
+            macd_histogram = macd_line - signal_line
+            fig.add_trace(
+                go.Scatter(x=data.index, y=macd_line.fillna(method='ffill'), mode='lines', name='MACD', line=dict(color='#04c6fc')),
+                row=4, col=1
+            )
+            fig.add_trace(
+                go.Scatter(x=data.index, y=signal_line.fillna(method='ffill'), mode='lines', name='MACD Signal', line=dict(color='blue', dash='dash')),
+                row=4, col=1
+            )
+            fig.add_trace(
+                go.Bar(x=data.index, y=macd_histogram.fillna(0), name='MACD Histogram', marker_color=['green' if val >= 0 else 'red' for val in macd_histogram]),
+                row=4, col=1
+            )
+
+        if 'TSI' in indicators:
+            tsi = indicators['TSI']
+            fig.add_trace(
+                go.Scatter(x=data.index, y=tsi['TSI'].fillna(method='ffill'), name='TSI', line=dict(color='blue')),
+                row=4, col=1
+            )
+            fig.add_trace(
+                go.Scatter(x=data.index, y=tsi['signal'].fillna(method='ffill'), name='TSI Signal', line=dict(color='blue', dash='dash')),
+                row=4, col=1
+            )
+
+        if 'KST' in indicators:
+            kst = indicators['KST']
+            fig.add_trace(
+                go.Scatter(x=data.index, y=kst['KST'].fillna(method='ffill'), name='KST', line=dict(color='purple')),
+                row=4, col=1
+            )
+            fig.add_trace(
+                go.Scatter(x=data.index, y=kst['signal'].fillna(method='ffill'), name='KST Signal', line=dict(color='purple', dash='dot')),
+                row=4, col=1
+            )
+
+        if 'PPO' in indicators:
+            ppo = indicators['PPO']
+            fig.add_trace(
+                go.Scatter(x=data.index, y=ppo['PPO'].fillna(method='ffill'), name='PPO', line=dict(color='cyan')),
+                row=4, col=1
+            )
+            fig.add_trace(
+                go.Scatter(x=data.index, y=ppo['PPO_signal'].fillna(method='ffill'), name='PPO Signal', line=dict(color='cyan', dash='dash')),
+                row=4, col=1
+            )
+            fig.add_trace(
+                go.Bar(x=data.index, y=ppo['PPO_histo'].fillna(0), name='PPO Histogram', marker_color=['green' if val >= 0 else 'red' for val in ppo['PPO_histo']]),
+                row=4, col=1
+            )
+
+        if 'CMO' in indicators:
+            fig.add_trace(
+                go.Scatter(x=data.index, y=indicators['CMO'].fillna(method='ffill'), name='CMO', line=dict(color='orange')),
+                row=4, col=1
+            )
+            fig.add_hline(y=50, line_dash="dash", line_color="red", row=4, col=1)
+            fig.add_hline(y=-50, line_dash="dash", line_color="green", row=4, col=1)
+
+        if 'ROC' in indicators:
+            fig.add_trace(
+                go.Scatter(x=data.index, y=indicators['ROC'].fillna(method='ffill'), name='ROC', line=dict(color='green')),
+                row=4, col=1
+            )
+            fig.add_hline(y=0, line_dash="dash", line_color="gray", row=4, col=1)
+
+        if 'UO' in indicators:
+            fig.add_trace(
+                go.Scatter(x=data.index, y=indicators['UO'].fillna(method='ffill'), name='Ultimate Oscillator', line=dict(color='purple')),
+                row=4, col=1
+            )
+            fig.add_hline(y=70, line_dash="dash", line_color="red", row=4, col=1)
+            fig.add_hline(y=30, line_dash="dash", line_color="green", row=4, col=1)
+
+        if 'OBV' in indicators:
+            fig.add_trace(
+                go.Scatter(x=data.index, y=indicators['OBV'].fillna(method='ffill'), name='OBV', line=dict(color='blue')),
+                row=4, col=1
+            )
+
+        if 'ADL' in indicators:
+            fig.add_trace(
+                go.Scatter(x=data.index, y=indicators['ADL'].fillna(method='ffill'), name='ADL', line=dict(color='cyan')),
+                row=4, col=1
+            )
+
+        if 'EFI' in indicators:
+            fig.add_trace(
+                go.Scatter(x=data.index, y=indicators['EFI'].fillna(method='ffill'), name='EFI', line=dict(color='magenta')),
+                row=4, col=1
+            )
+
+        if 'EMV' in indicators:
+            fig.add_trace(
+                go.Scatter(x=data.index, y=indicators['EMV'].fillna(method='ffill'), name='EMV', line=dict(color='orange')),
+                row=4, col=1
+            )
+
+        if 'MFI' in indicators:
+            fig.add_trace(
+                go.Scatter(x=data.index, y=indicators['MFI'].fillna(method='ffill'), name='MFI', line=dict(color='blue')),
+                row=4, col=1
+            )
+            fig.add_hline(y=80, line_dash="dash", line_color="red", row=4, col=1)
+            fig.add_hline(y=20, line_dash="dash", line_color="green", row=4, col=1)
+
+        if 'VPT' in indicators:
+            fig.add_trace(
+                go.Scatter(x=data.index, y=indicators['VPT'].fillna(method='ffill'), name='VPT', line=dict(color='blue', dash='dot')),
+                row=4, col=1
+            )
+
+        if 'FVE' in indicators:
+            fig.add_trace(
+                go.Scatter(x=data.index, y=indicators['FVE'].fillna(method='ffill'), name='FVE', line=dict(color='blue', dash='dot')),
+                row=4, col=1
+            )
+
+        if 'VZO' in indicators:
+            fig.add_trace(
+                go.Scatter(x=data.index, y=indicators['VZO'].fillna(method='ffill'), name='VZO', line=dict(color='blue', dash='dot')),
+                row=4, col=1
+            )
+            fig.add_hline(y=40, line_dash="dash", line_color="green", row=4, col=1)
+            fig.add_hline(y=5, line_dash="dash", line_color="red", row=4, col=1)
+            fig.add_hline(y=-5, line_dash="dash", line_color="red", row=4, col=1)
+            fig.add_hline(y=-40, line_dash="dash", line_color="green", row=4, col=1)
+
+        if 'WTO' in indicators:
+            wto = indicators['WTO']
+            fig.add_trace(
+                go.Scatter(x=data.index, y=wto['WT1'].fillna(method='ffill'), name='WTO WT1', line=dict(color='cyan')),
+                row=4, col=1
+            )
+            fig.add_trace(
+                go.Scatter(x=data.index, y=wto['WT2'].fillna(method='ffill'), name='WTO WT2', line=dict(color='cyan', dash='dash')),
+                row=4, col=1
+            )
+
+        if 'Coppock' in indicators:
+            fig.add_trace(
+                go.Scatter(x=data.index, y=indicators['Coppock'].fillna(method='ffill'), name='Coppock Curve', line=dict(color='purple')),
+                row=4, col=1
+            )
+            fig.add_hline(y=0, line_dash="dash", line_color="gray", row=4, col=1)
+
+        if 'BASP' in indicators:
+            basp = indicators['BASP']
+            fig.add_trace(
+                go.Scatter(x=data.index, y=basp['Buy'].fillna(method='ffill'), name='BASP Buy', line=dict(color='green')),
+                row=4, col=1
+            )
+            fig.add_trace(
+                go.Scatter(x=data.index, y=basp['Sell'].fillna(method='ffill'), name='BASP Sell', line=dict(color='red')),
+                row=4, col=1
+            )
+
+        if 'BASPN' in indicators:
+            baspn = indicators['BASPN']
+            fig.add_trace(
+                go.Scatter(x=data.index, y=baspn['BASPN_Buy'].fillna(method='ffill'), name='BASPN Buy', line=dict(color='limegreen')),
+                row=4, col=1
+            )
+            fig.add_trace(
+                go.Scatter(x=data.index, y=baspn['BASPN_Sell'].fillna(method='ffill'), name='BASPN Sell', line=dict(color='coral')),
+                row=4, col=1
+            )
+
+        if 'DMI' in indicators:
+            dmi = indicators['DMI']
+            fig.add_trace(
+                go.Scatter(x=data.index, y=dmi['+DI'].fillna(method='ffill'), name='+DI', line=dict(color='blue')),
+                row=4, col=1
+            )
+            fig.add_trace(
+                go.Scatter(x=data.index, y=dmi['-DI'].fillna(method='ffill'), name='-DI', line=dict(color='red')),
+                row=4, col=1
+            )
+
+        if 'EBBP' in indicators:
+            ebbp = indicators['EBBP']
+            fig.add_trace(
+                go.Scatter(x=data.index, y=ebbp['Bull'].fillna(method='ffill'), name='Bull Power', line=dict(color='green')),
+                row=4, col=1
+            )
+            fig.add_trace(
+                go.Scatter(x=data.index, y=ebbp['Bear'].fillna(method='ffill'), name='Bear Power', line=dict(color='red')),
+                row=4, col=1
+            )
+
+        if 'ATR' in indicators:
+            fig.add_trace(
+                go.Scatter(x=data.index, y=indicators['ATR'].fillna(method='ffill'), name='ATR', line=dict(color='blue')),
+                row=4, col=1
+            )
+            
+        # Update layout
+        fig.update_layout(
+            title=f'{symbol.upper()} - Technical Analysis',
+            xaxis_rangeslider_visible=False,
+            height=800,
+            showlegend=True
+        )
+        
+        st.plotly_chart(fig, use_container_width=True)
+        
+        # Display indicator values in tabs
+        st.subheader("📊 Indicator Values")
+        
+        # Create tabs for different categories
+        tab1, tab2, tab3, tab4, tab5 = st.tabs(["Trend", "Momentum", "Volume", "Volatility", "Oscillators"])
+        
+        with tab1:
+            st.markdown("### Trend Indicators")
+            trend_cols = st.columns(3)
+            col_idx = 0
+            
+            for name, indicator in indicators.items():
+                if name in ['SMA', 'EMA', 'HMA', 'WMA', 'KAMA', 'FRAMA', 'EVWMA', 'VWAP']:
+                    with trend_cols[col_idx % 3]:
+                        if isinstance(indicator, pd.Series):
+                            st.metric(name, f"{indicator.iloc[-1]:.2f}")
+                        col_idx += 1
+        
+        with tab2:
+            st.markdown("### Momentum Indicators")
+            momentum_cols = st.columns(3)
+            col_idx = 0
+            
+            for name, indicator in indicators.items():
+                if name in ['RSI', 'StochRSI', 'CMO', 'ROC', 'UO']:
+                    with momentum_cols[col_idx % 3]:
+                        if isinstance(indicator, pd.Series):
+                            st.metric(name, f"{indicator.iloc[-1]:.2f}")
+                        col_idx += 1
+        
+        with tab3:
+            st.markdown("### Volume Indicators")
+            volume_cols = st.columns(3)
+            col_idx = 0
+            
+            for name, indicator in indicators.items():
+                if name in ['OBV', 'ADL', 'EFI', 'EMV', 'MFI', 'VPT', 'FVE', 'VZO']:
+                    with volume_cols[col_idx % 3]:
+                        if isinstance(indicator, pd.Series):
+                            st.metric(name, f"{indicator.iloc[-1]:.2f}")
+                        col_idx += 1
+        
+        with tab4:
+            st.markdown("### Volatility Indicators")
+            volatility_cols = st.columns(3)
+            col_idx = 0
+            
+            for name, indicator in indicators.items():
+                if name in ['ATR', 'PSAR']:
+                    with volatility_cols[col_idx % 3]:
+                        if isinstance(indicator, pd.Series):
+                            st.metric(name, f"{indicator.iloc[-1]:.2f}")
+                        col_idx += 1
+        
+        with tab5:
+            st.markdown("### Oscillators")
+            osc_cols = st.columns(3)
+            col_idx = 0
+            
+            for name, indicator in indicators.items():
+                if name in ['ADX', 'CCI', 'Fisher', 'AO', 'MI']:
+                    with osc_cols[col_idx % 3]:
+                        if isinstance(indicator, pd.Series):
+                            st.metric(name, f"{indicator.iloc[-1]:.2f}")
+                        col_idx += 1
+        
+        # Raw data section
+        with st.expander("📋 Raw Data"):
+            st.dataframe(data.tail(50))
+        
+        # Download section
+        st.subheader("💾 Download Data")
+        
+        # Combine all indicators into one DataFrame
+        combined_df = data.copy()
+        for name, indicator in indicators.items():
+            if isinstance(indicator, pd.Series):
+                combined_df[name] = indicator
+            elif isinstance(indicator, pd.DataFrame):
+                for col in indicator.columns:
+                    combined_df[f"{name}_{col}"] = indicator[col]
+        
+        csv = combined_df.to_csv()
+        st.download_button(
+            label="Download CSV",
+            data=csv,
+            file_name=f'{symbol}_technical_analysis.csv',
+            mime='text/csv'
+        )
+        
+    except Exception as e:
+        st.error(f"An error occurred: {str(e)}")
+        st.error("Please check your internet connection and try again.")
+
+# Instructions
+else:
+    st.markdown("""
+    ## 🚀 How to Use This Dashboard
+    
+    1. **Enter a stock symbol** in the sidebar (e.g., AAPL, GOOGL, MSFT) for Indian Stocks, use NSE symbols like RELIANCE.NS
+    or BHEL.NS.
+    2. **Select time period and interval** for the data
+    3. **Choose technical indicators** you want to analyze
+    4. **Adjust parameters** for the indicators
+    5. **Click "Analyze Stock"** to generate the analysis
+    
+    ### 📈 Available Indicators
+    
+    This dashboard includes **40+ technical indicators** across multiple categories:
+    
+    - **Trend Indicators**: SMA, EMA, HMA, WMA, KAMA, FRAMA, EVWMA, VWAP
+    - **Momentum Indicators**: RSI, MACD, Stochastic RSI, CMO, ROC, TSI, KST, PPO, UO
+    - **Volume Indicators**: OBV, ADL, Chaikin Oscillator, EFI, EMV, MFI, VPT, FVE, VZO
+    - **Volatility Indicators**: Bollinger Bands, Keltner Channels, Donchian Channels, ATR, Chandelier Exit, Parabolic SAR
+    - **Oscillators**: ADX, CCI, Fisher Transform, Awesome Oscillator, Mass Index, Wave Trend Oscillator
+    - **Complex Indicators**: Ichimoku Cloud, Pivot Points, Fibonacci Pivots, BASP, DMI, Elder Bull/Bear Power
+    
+    ### 💡 Tips
+    
+    - Use multiple indicators together for better analysis
+    - Adjust parameters based on your trading timeframe
+    - Download the data for further analysis
+    - Check different time periods to understand trends
+    """)
+
+# Footer
+st.markdown("---")
+st.markdown("**Technical Analysis Dashboard** | Built with Streamlit & Python | Data from Yahoo Finance")
+st.markdown("---")
+st.markdown("**Made By Zane Vijay Falcao**")