Technical Indicators

Calculate technical indicators (MACD, RSI, Bollinger Bands, EMA, etc.) with customizable parameters. Results are cached for 15 minutes.

Endpoints

Method	Endpoint	Auth	Description
GET	/indicators/{symbol}	No	Get indicators for a symbol
POST	/indicators/batch	No	Get indicators for multiple symbols

---

Get Indicators

Calculate technical indicators for a single symbol.

Request

GET /api/v1/indicators/AAPL?interval=1d&limit=500&rsi_period=14&macd_fast=12&macd_slow=26&ema_periods=20,50

Response

{
  "symbol": "AAPL",
  "interval": "1d",
  "count": 500,
  "data": [
    {
      "time": "2025-01-15T00:00:00Z",
      "open": 185.50,
      "high": 188.25,
      "low": 184.10,
      "close": 187.00,
      "volume": 52000000,
      "macd": 1.25,
      "macd_signal": 0.98,
      "macd_histogram": 0.27,
      "rsi": 62.5,
      "momentum": 3.2,
      "bb_upper": 192.50,
      "bb_middle": 185.00,
      "bb_lower": 177.50,
      "ema_20": 184.50,
      "ema_50": 182.00,
      "chandelier_long": 180.50,
      "chandelier_short": 190.25,
      "signal": "bullish"
    }
  ],
  "signal_summary": {
    "current_signal": "bullish",
    "signal_details": {
      "macd": "bullish",
      "rsi": "neutral",
      "bb": "neutral"
    }
  }
}

Path Parameters

Parameter	Type	Description
symbol	string	Stock ticker symbol

Query Parameters

Parameter	Type	Default	Range	Description
interval	string	1d	-	Data interval (1m, 5m, 15m, 30m, 1h, 1d)
limit	integer	500	1-10000	Max data points
start_date	date	-	-	Start date filter
end_date	date	-	-	End date filter
rsi_period	integer	14	5-50	RSI calculation period
macd_fast	integer	12	5-100	MACD fast EMA period
macd_slow	integer	26	5-100	MACD slow EMA period
macd_signal	integer	9	5-50	MACD signal line period
bb_period	integer	20	5-100	Bollinger Bands period
bb_std	float	2.0	1.0-3.0	Bollinger Bands std deviation
ema_periods	string	20,50	-	Comma-separated EMA periods
chandelier_period	integer	22	5-50	Chandelier Exit ATR period
chandelier_multiplier	float	3.0	1.0-5.0	Chandelier Exit multiplier

---

Available Indicators

MACD (Moving Average Convergence Divergence)

MACD

Momentum oscillator showing relationship between two EMAs.

Fields: macd, macd_signal, macd_histogram

Parameters: macd_fast (12), macd_slow (26), macd_signal (9)

Signals:

• Bullish: MACD crosses above signal line
• Bearish: MACD crosses below signal line

RSI (Relative Strength Index)

RSI

Momentum oscillator measuring speed and magnitude of price changes.

Field: rsi (0-100 scale)

Parameter: rsi_period (default: 14)

Signals:

• Oversold: RSI < 30 (potential buy)
• Overbought: RSI > 70 (potential sell)
• Neutral: 30 < RSI < 70

Bollinger Bands

Bollinger Bands

Volatility bands placed above and below a moving average.

Fields: bb_upper, bb_middle, bb_lower

Parameters: bb_period (20), bb_std (2.0)

Signals:

• Price near upper band: Potentially overbought
• Price near lower band: Potentially oversold
• Band squeeze: Low volatility, potential breakout

EMA (Exponential Moving Average)

EMA

Weighted moving average giving more weight to recent prices.

Fields: ema_{period} (e.g., ema_20, ema_50)

Parameter: ema_periods (comma-separated, e.g., “20,50,200”)

Signals:

• Golden Cross: Short EMA crosses above long EMA (bullish)
• Death Cross: Short EMA crosses below long EMA (bearish)

Momentum

Momentum

Rate of change indicator showing price velocity.

Field: momentum

Signals:

• Positive: Upward momentum
• Negative: Downward momentum
• Divergence: Price and momentum moving opposite directions

Chandelier Exit

Chandelier Exit

Volatility-based trailing stop indicator using ATR.

Fields: chandelier_long, chandelier_short

Parameters: chandelier_period (22), chandelier_multiplier (3.0)

Signals:

• Long exit: Price drops below chandelier_long
• Short exit: Price rises above chandelier_short

---

Signal Summary

The response includes a signal_summary object with aggregated signals:

{
  "signal_summary": {
    "current_signal": "bullish",
    "signal_details": {
      "macd": "bullish",
      "rsi": "neutral",
      "bb": "neutral"
    }
  }
}

Signal Values

Signal	Description
bullish	Buy signal - positive momentum indicators
bearish	Sell signal - negative momentum indicators
neutral	No clear signal - mixed or sideways indicators

---

Batch Indicators

Get indicators for multiple symbols in one request.

Request

POST /api/v1/indicators/batch
Content-Type: application/json

{
  "symbols": ["AAPL", "MSFT", "GOOGL"],
  "interval": "1d",
  "limit": 500,
  "rsi_period": 14,
  "macd_fast": 12,
  "macd_slow": 26,
  "macd_signal": 9,
  "bb_period": 20,
  "bb_std": 2.0,
  "ema_periods": "20,50"
}

Response

{
  "AAPL": {
    "symbol": "AAPL",
    "interval": "1d",
    "count": 500,
    "data": [...],
    "signal_summary": {...}
  },
  "MSFT": {
    "symbol": "MSFT",
    "interval": "1d",
    "count": 500,
    "data": [...],
    "signal_summary": {...}
  },
  "GOOGL": {
    "symbol": "GOOGL",
    "interval": "1d",
    "count": 500,
    "data": [...],
    "signal_summary": {...}
  }
}

---

Code Examples

JavaScript/TypeScript

import axios from 'axios';

const api = axios.create({
  baseURL: 'http://localhost:8501/api/v1'
});

// Get indicators with custom parameters
async function getIndicators(symbol, params = {}) {
  const { data } = await api.get(`/indicators/${symbol}`, {
    params: {
      interval: '1d',
      limit: 500,
      rsi_period: 14,
      macd_fast: 12,
      macd_slow: 26,
      ema_periods: '20,50,200',
      ...params
    }
  });

  return data;
}

// Analyze signals
async function analyzeSymbol(symbol) {
  const indicators = await getIndicators(symbol);
  const latest = indicators.data[indicators.data.length - 1];
  const summary = indicators.signal_summary;

  console.log(`\n${symbol} Analysis:`);
  console.log(`  Signal: ${summary.current_signal.toUpperCase()}`);
  console.log(`  RSI: ${latest.rsi.toFixed(1)}`);
  console.log(`  MACD: ${latest.macd.toFixed(2)} (Signal: ${latest.macd_signal.toFixed(2)})`);
  console.log(`  Price: $${latest.close.toFixed(2)}`);
  console.log(`  BB: $${latest.bb_lower.toFixed(2)} - $${latest.bb_upper.toFixed(2)}`);

  // Trading signals
  if (latest.rsi < 30) {
    console.log('  ⚠️ RSI Oversold - potential buy signal');
  } else if (latest.rsi > 70) {
    console.log('  ⚠️ RSI Overbought - potential sell signal');
  }

  if (latest.macd > latest.macd_signal && latest.macd_histogram > 0) {
    console.log('  📈 MACD bullish crossover');
  }

  return indicators;
}

// Screen multiple stocks
async function screenStocks(symbols) {
  const { data } = await api.post('/indicators/batch', {
    symbols,
    interval: '1d',
    limit: 100,
    rsi_period: 14
  });

  // Find oversold stocks
  const oversold = [];
  const overbought = [];

  for (const [symbol, result] of Object.entries(data)) {
    const latest = result.data[result.data.length - 1];
    if (latest.rsi < 30) {
      oversold.push({ symbol, rsi: latest.rsi });
    } else if (latest.rsi > 70) {
      overbought.push({ symbol, rsi: latest.rsi });
    }
  }

  console.log('Oversold stocks:', oversold);
  console.log('Overbought stocks:', overbought);

  return { oversold, overbought };
}

// Usage
await analyzeSymbol('AAPL');
await screenStocks(['AAPL', 'MSFT', 'GOOGL', 'AMZN', 'META']);

Python

import requests
import pandas as pd

BASE_URL = "http://localhost:8501/api/v1"

def get_indicators(
    symbol: str,
    interval: str = "1d",
    **kwargs
) -> dict:
    """Get technical indicators for a symbol."""
    params = {
        "interval": interval,
        "limit": kwargs.get("limit", 500),
        "rsi_period": kwargs.get("rsi_period", 14),
        "macd_fast": kwargs.get("macd_fast", 12),
        "macd_slow": kwargs.get("macd_slow", 26),
        "macd_signal": kwargs.get("macd_signal", 9),
        "bb_period": kwargs.get("bb_period", 20),
        "bb_std": kwargs.get("bb_std", 2.0),
        "ema_periods": kwargs.get("ema_periods", "20,50"),
    }

    response = requests.get(
        f"{BASE_URL}/indicators/{symbol}",
        params=params
    )
    response.raise_for_status()
    return response.json()

def indicators_to_dataframe(indicators: dict) -> pd.DataFrame:
    """Convert indicators response to DataFrame."""
    df = pd.DataFrame(indicators["data"])
    df["time"] = pd.to_datetime(df["time"])
    df.set_index("time", inplace=True)
    return df

def analyze_stock(symbol: str) -> dict:
    """Perform technical analysis on a stock."""
    indicators = get_indicators(symbol)
    df = indicators_to_dataframe(indicators)
    latest = df.iloc[-1]
    summary = indicators["signal_summary"]

    analysis = {
        "symbol": symbol,
        "signal": summary["current_signal"],
        "price": latest["close"],
        "rsi": latest["rsi"],
        "macd": latest["macd"],
        "macd_signal": latest["macd_signal"],
        "macd_histogram": latest["macd_histogram"],
        "bb_position": (latest["close"] - latest["bb_lower"]) /
                       (latest["bb_upper"] - latest["bb_lower"]) * 100,
        "alerts": []
    }

    # Generate alerts
    if latest["rsi"] < 30:
        analysis["alerts"].append("RSI oversold - potential buy")
    elif latest["rsi"] > 70:
        analysis["alerts"].append("RSI overbought - potential sell")

    if latest["macd"] > latest["macd_signal"]:
        analysis["alerts"].append("MACD bullish")
    else:
        analysis["alerts"].append("MACD bearish")

    if latest["close"] < latest["bb_lower"]:
        analysis["alerts"].append("Price below lower BB")
    elif latest["close"] > latest["bb_upper"]:
        analysis["alerts"].append("Price above upper BB")

    return analysis

def screen_stocks(symbols: list, rsi_threshold_low: float = 30, rsi_threshold_high: float = 70):
    """Screen multiple stocks for trading signals."""
    response = requests.post(
        f"{BASE_URL}/indicators/batch",
        json={
            "symbols": symbols,
            "interval": "1d",
            "limit": 100,
            "rsi_period": 14
        }
    )
    response.raise_for_status()
    results = response.json()

    signals = {"oversold": [], "overbought": [], "neutral": []}

    for symbol, data in results.items():
        latest = data["data"][-1]
        rsi = latest["rsi"]
        signal = data["signal_summary"]["current_signal"]

        stock_info = {
            "symbol": symbol,
            "rsi": rsi,
            "signal": signal,
            "price": latest["close"]
        }

        if rsi < rsi_threshold_low:
            signals["oversold"].append(stock_info)
        elif rsi > rsi_threshold_high:
            signals["overbought"].append(stock_info)
        else:
            signals["neutral"].append(stock_info)

    return signals

# Usage
if __name__ == "__main__":
    # Analyze single stock
    analysis = analyze_stock("AAPL")
    print(f"\n{analysis['symbol']} Analysis:")
    print(f"  Signal: {analysis['signal']}")
    print(f"  Price: ${analysis['price']:.2f}")
    print(f"  RSI: {analysis['rsi']:.1f}")
    print(f"  MACD: {analysis['macd']:.2f}")
    print(f"  BB Position: {analysis['bb_position']:.1f}%")
    for alert in analysis["alerts"]:
        print(f"  ⚠️ {alert}")

    # Screen multiple stocks
    symbols = ["AAPL", "MSFT", "GOOGL", "AMZN", "META", "NVDA", "TSLA"]
    signals = screen_stocks(symbols)

    print("\n📉 Oversold stocks:")
    for s in signals["oversold"]:
        print(f"  {s['symbol']}: RSI={s['rsi']:.1f}")

    print("\n📈 Overbought stocks:")
    for s in signals["overbought"]:
        print(f"  {s['symbol']}: RSI={s['rsi']:.1f}")

---

Best Practices

Parameter Tuning

Adjust indicator periods based on your trading timeframe. Shorter periods for day trading, longer for swing/position trading.

Multiple Confirmation

Don’t rely on a single indicator. Use multiple indicators that confirm each other.

Caching

Responses are cached for 15 minutes. Plan your refresh strategy accordingly.

Batch Requests

Use batch endpoint when analyzing multiple stocks to reduce API calls.

Tip

Timeframe Guidelines:

• Day trading: RSI 7-10, shorter EMAs (9, 21)
• Swing trading: RSI 14, EMAs (20, 50)
• Position trading: RSI 21, longer EMAs (50, 200)