Advanced Indicators API

Overview

The Advanced Indicators API retrieves comprehensive technical analysis data including pivot points, exponential moving averages (EMA), simple moving averages (SMA), and technical indicator sentiment. This endpoint requires the Security ID (Sid) from the master ISIN map. Source File: fetch_advanced_indicators.py

Endpoint Details

URL

string

required

https://ow-static-scanx.dhan.co/staticscanx/indicator

Method

string

required

POST

Content-Type

string

required

application/json

Request Headers

{
  "Content-Type": "application/json",
  "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36",
  "Accept": "application/json, text/plain, */*"
}

Request Payload

exchange

string

required

Exchange code (typically “NSE”)

segment

string

required

Market segment (“E” for equities)

security_id

string

required

Security ID (Sid) from master_isin_map.json

isin

string

required

ISIN code of the security

symbol

string

required

Trading symbol

minute

string

required

Timeframe - “D” for daily, “W” for weekly, “M” for monthly

Example Payload

{
  "exchange": "NSE",
  "segment": "E",
  "security_id": "11536",
  "isin": "INE002A01018",
  "symbol": "RELIANCE",
  "minute": "D"
}

Example Request

curl -X POST https://ow-static-scanx.dhan.co/staticscanx/indicator \
  -H "Content-Type: application/json" \
  -H "User-Agent: Mozilla/5.0" \
  -d '{
    "exchange": "NSE",
    "segment": "E",
    "security_id": "11536",
    "isin": "INE002A01018",
    "symbol": "RELIANCE",
    "minute": "D"
  }'

Response Structure

data

array

Array containing single indicator object (always length 1)

Indicator Object Fields

EMA

array

Exponential Moving Average data points

SMA

array

Simple Moving Average data points

Indicator

array

Technical indicators including RSI, MACD, Stochastic, etc.

Pivot

array

Pivot point levels (support/resistance)

Example Response

{
  "data": [
    {
      "EMA": [
        {"period": 5, "value": 2598.5, "signal": "Buy"},
        {"period": 9, "value": 2595.2, "signal": "Buy"},
        {"period": 20, "value": 2580.1, "signal": "Buy"},
        {"period": 50, "value": 2550.3, "signal": "Buy"},
        {"period": 100, "value": 2500.5, "signal": "Buy"},
        {"period": 200, "value": 2450.8, "signal": "Buy"}
      ],
      "SMA": [
        {"period": 5, "value": 2600.0, "signal": "Buy"},
        {"period": 9, "value": 2597.5, "signal": "Buy"},
        {"period": 20, "value": 2582.3, "signal": "Buy"},
        {"period": 50, "value": 2552.1, "signal": "Buy"},
        {"period": 100, "value": 2502.6, "signal": "Buy"},
        {"period": 200, "value": 2453.2, "signal": "Buy"}
      ],
      "Indicator": [
        {"name": "RSI(14)", "value": 65.2, "signal": "Buy"},
        {"name": "MACD(12,26)", "value": 15.3, "signal": "Buy"},
        {"name": "Stochastic(14,3,3)", "value": 72.5, "signal": "Buy"},
        {"name": "ADX(14)", "value": 28.4, "signal": "Neutral"}
      ],
      "Pivot": [
        {"level": "R3", "value": 2750.5},
        {"level": "R2", "value": 2700.3},
        {"level": "R1", "value": 2650.2},
        {"level": "Pivot", "value": 2598.5},
        {"level": "S1", "value": 2550.1},
        {"level": "S2", "value": 2500.8},
        {"level": "S3", "value": 2450.6}
      ]
    }
  ]
}

Implementation Details

Configuration

Max Threads

integer

default:"50"

Concurrent threads for parallel processing (highest among all endpoints)

Timeout

integer

default:"10"

Request timeout in seconds

Input File

string

required

master_isin_map.json (must contain Sid field)

Output File

string

advanced_indicator_data.json (~8.3 MB for full market)

Processing Flow

Load Master Map: Read symbols with Sid from master_isin_map.json
Filter Valid Sids: Skip stocks without Sid (required field)
Parallel Fetch: Use ThreadPoolExecutor with 50 workers
Extract Data: Parse EMA, SMA, Indicators, and Pivots
Consolidate: Merge all results into single array
Save: Write to advanced_indicator_data.json

Code Implementation

import requests
import json
from concurrent.futures import ThreadPoolExecutor, as_completed

api_url = "https://ow-static-scanx.dhan.co/staticscanx/indicator"

def fetch_indicators(item):
    symbol = item.get("Symbol")
    isin = item.get("ISIN")
    sid = item.get("Sid")
    
    # Sid is required for this API
    if not sid:
        return None
    
    payload = {
        "exchange": "NSE",
        "segment": "E",
        "security_id": str(sid),
        "isin": isin,
        "symbol": symbol,
        "minute": "D"  # Daily timeframe
    }
    
    try:
        response = requests.post(api_url, json=payload, headers=headers, timeout=10)
        if response.status_code == 200:
            data = response.json().get("data", [])
            if data and isinstance(data, list) and len(data) > 0:
                result = data[0]
                
                return {
                    "Symbol": symbol,
                    "EMA": result.get("EMA", []),
                    "SMA": result.get("SMA", []),
                    "TechnicalIndicators": result.get("Indicator", []),
                    "Pivots": result.get("Pivot", [])
                }
        return None
    except:
        return None

# Load master list
with open("master_isin_map.json", "r") as f:
    master_list = json.load(f)

all_results = []

# Parallel processing
with ThreadPoolExecutor(max_workers=50) as executor:
    future_to_stock = {executor.submit(fetch_indicators, stock): stock 
                       for stock in master_list}
    
    for future in as_completed(future_to_stock):
        res = future.result()
        if res:
            all_results.append(res)

# Save results
with open("advanced_indicator_data.json", "w") as f:
    json.dump(all_results, f, indent=4)

Output Structure

[
  {
    "Symbol": "RELIANCE",
    "EMA": [...],
    "SMA": [...],
    "TechnicalIndicators": [...],
    "Pivots": [...]
  },
  {
    "Symbol": "TCS",
    "EMA": [...],
    "SMA": [...],
    "TechnicalIndicators": [...],
    "Pivots": [...]
  }
]

Technical Indicators Included

Moving Averages

EMA Periods: 5, 9, 20, 50, 100, 200 SMA Periods: 5, 9, 20, 50, 100, 200 Each includes:

Period length
Current value
Signal (Buy/Sell/Neutral)

Technical Indicators

RSI (14): Relative Strength Index
MACD (12,26): Moving Average Convergence Divergence
Stochastic (14,3,3): Stochastic Oscillator
ADX (14): Average Directional Index
CCI (20): Commodity Channel Index
Williams %R (14): Williams Percent Range
Bollinger Bands: Upper, Middle, Lower bands

Pivot Points

R3, R2, R1: Resistance levels
Pivot: Central pivot point
S1, S2, S3: Support levels

Signal Interpretation

Buy

string

Price is above the indicator (bullish)

Sell

string

Price is below the indicator (bearish)

Neutral

string

No clear directional bias

Performance Metrics

Total Stocks: ~2,775
Stocks with Sid: ~2,775 (nearly all)
Threads: 50 concurrent requests
Time per Stock: ~1-2 seconds
Total Time: ~2-3 minutes for full market
Output Size: ~8.3 MB
Success Rate: >99%

Progress Tracking

Progress: 100/2775 done.
Progress: 200/2775 done.
Progress: 500/2775 done.
...
Successfully saved indicators for 2750 stocks to advanced_indicator_data.json

Timeframe Options

minute

string

“D”: Daily (most common)
“W”: Weekly
“M”: Monthly
“1”: 1-minute (intraday)
“5”: 5-minute (intraday)
“15”: 15-minute (intraday)
“60”: 1-hour (intraday)

Note: The implementation defaults to “D” (daily) for end-of-day analysis.

Error Handling

Missing Sid

if not sid:
    return None  # Skip stocks without Sid

API Failure

try:
    response = requests.post(api_url, json=payload, headers=headers, timeout=10)
    if response.status_code == 200:
        data = response.json().get("data", [])
        if data:
            # Process data
            pass
    return None
except:
    return None  # Graceful failure

Use Cases

Technical Screening: Filter stocks by moving average crossovers
Momentum Trading: Identify overbought/oversold via RSI
Support/Resistance: Use pivot points for entry/exit levels
Trend Analysis: Analyze EMA/SMA alignment for trend strength
Signal Aggregation: Combine multiple indicator signals for conviction

Analysis Examples

Find Strong Uptrends

# Price above all major moving averages
strong_uptrends = [
    stock for stock in all_results
    if all(ma.get("signal") == "Buy" for ma in stock.get("SMA", []))
]

RSI Overbought/Oversold

# Find overbought stocks (RSI > 70)
overbought = [
    stock for stock in all_results
    if any(
        ind.get("name") == "RSI(14)" and ind.get("value", 0) > 70
        for ind in stock.get("TechnicalIndicators", [])
    )
]

Golden Cross Candidates

# SMA50 > SMA200 (golden cross)
golden_cross = [
    stock for stock in all_results
    if get_sma_value(stock, 50) > get_sma_value(stock, 200)
]

Notes

Sid (Security ID) is mandatory - stocks without Sid are skipped
Indicators are calculated based on historical price data
Signals are auto-generated based on price vs indicator value
Pivot points are calculated using standard formulas (Classic method)
Daily timeframe provides most reliable signals for swing trading
Intraday timeframes (1m, 5m, 15m) require different endpoint access
The API updates indicators at end-of-day after market close

Endpoints

Output Fields

Overview

Endpoint Details

Request Headers

Request Payload

Example Payload

Example Request

Response Structure

Indicator Object Fields

Example Response

Implementation Details

Configuration

Processing Flow

Code Implementation

Output Structure

Technical Indicators Included

Moving Averages

Technical Indicators

Pivot Points

Signal Interpretation

Performance Metrics

Progress Tracking

Timeframe Options

Error Handling

Missing Sid

API Failure

Use Cases

Analysis Examples

Find Strong Uptrends

RSI Overbought/Oversold

Golden Cross Candidates

Notes

Build docs developers (and LLMs) love

Endpoints

Output Fields

​Overview

​Endpoint Details

​Request Headers

​Request Payload

​Example Payload

​Example Request

​Response Structure

​Indicator Object Fields

​Example Response

​Implementation Details

​Configuration

​Processing Flow

​Code Implementation

​Output Structure

​Technical Indicators Included

​Moving Averages

​Technical Indicators

​Pivot Points

​Signal Interpretation

​Performance Metrics

​Progress Tracking

​Timeframe Options

​Error Handling

​Missing Sid

​API Failure

​Use Cases

​Analysis Examples

​Find Strong Uptrends

​RSI Overbought/Oversold

​Golden Cross Candidates

​Notes

Build docs developers (and LLMs) love

Overview

Endpoint Details

Request Headers

Request Payload

Example Payload

Example Request

Response Structure

Indicator Object Fields

Example Response

Implementation Details

Configuration

Processing Flow

Code Implementation

Output Structure

Technical Indicators Included

Moving Averages

Technical Indicators

Pivot Points

Signal Interpretation

Performance Metrics

Progress Tracking

Timeframe Options

Error Handling

Missing Sid

API Failure

Use Cases

Analysis Examples

Find Strong Uptrends

RSI Overbought/Oversold

Golden Cross Candidates

Notes