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options-trading

Options trading with OpenAlgo - single leg orders, multi-leg strategies (Iron Condor, Straddle, Strangle, Spreads), options chain analysis, and Greeks calculation

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SKILL.md

OpenAlgo Options Trading

Execute options trading strategies using OpenAlgo's unified Python SDK. Supports index options (NIFTY, BANKNIFTY, FINNIFTY), stock options, and complex multi-leg strategies.

Environment Setup

python
from openalgo import api

client = api(
    api_key='your_api_key_here',
    host='http://127.0.0.1:5000'
)

Quick Start Scripts

Single Leg Options Order

bash
python scripts/options_order.py --underlying NIFTY --expiry 30JAN25 --offset ATM --option-type CE --action BUY --quantity 75

Iron Condor Strategy

bash
python scripts/iron_condor.py --underlying NIFTY --expiry 30JAN25 --quantity 75

Straddle Strategy

bash
python scripts/straddle.py --underlying BANKNIFTY --expiry 30JAN25 --action BUY --quantity 30

Options Symbol Format

OpenAlgo uses standardized symbol formats:

Type Format Example
Index Options [INDEX][DDMMMYY][STRIKE][CE/PE] NIFTY30JAN2526000CE
Stock Options [SYMBOL][DDMMMYY][STRIKE][CE/PE] RELIANCE30JAN251400CE
Index Futures [INDEX][DDMMMYY]FUT NIFTY30JAN25FUT

Offset System

OpenAlgo uses an intuitive offset system to select strikes relative to ATM:

Offset Meaning Example (NIFTY ATM=26000)
ATM At The Money 26000
ITM1 1 strike In The Money CE: 25950, PE: 26050
ITM2 2 strikes In The Money CE: 25900, PE: 26100
OTM1 1 strike Out of The Money CE: 26050, PE: 25950
OTM2 2 strikes Out of The Money CE: 26100, PE: 25900
OTM5 5 strikes Out of The Money CE: 26250, PE: 25750

Core API Methods

1. Single Leg Options Order

Place ATM, ITM, or OTM options orders:

python
# ATM Call Option
response = client.optionsorder(
    strategy="OptionsBot",
    underlying="NIFTY",
    exchange="NSE_INDEX",
    expiry_date="30JAN25",
    offset="ATM",
    option_type="CE",
    action="BUY",
    quantity=75,
    pricetype="MARKET",
    product="NRML",
    splitsize=0  # 0 = no splitting
)

Response:

json
{
  "exchange": "NFO",
  "offset": "ATM",
  "option_type": "CE",
  "orderid": "25013000000001",
  "status": "success",
  "symbol": "NIFTY30JAN2526000CE",
  "underlying": "NIFTY30JAN25FUT",
  "underlying_ltp": 26015.50
}

ITM Put Option:

python
response = client.optionsorder(
    strategy="OptionsBot",
    underlying="NIFTY",
    exchange="NSE_INDEX",
    expiry_date="30JAN25",
    offset="ITM3",  # 3 strikes ITM
    option_type="PE",
    action="BUY",
    quantity=75,
    pricetype="MARKET",
    product="NRML"
)

OTM Call Option:

python
response = client.optionsorder(
    strategy="OptionsBot",
    underlying="NIFTY",
    exchange="NSE_INDEX",
    expiry_date="30JAN25",
    offset="OTM5",  # 5 strikes OTM
    option_type="CE",
    action="SELL",
    quantity=75,
    pricetype="MARKET",
    product="NRML"
)

2. Multi-Leg Options Order

Execute complex strategies with multiple legs in a single call:

Iron Condor (4 legs)

python
response = client.optionsmultiorder(
    strategy="Iron Condor",
    underlying="NIFTY",
    exchange="NSE_INDEX",
    expiry_date="30JAN25",
    legs=[
        {"offset": "OTM6", "option_type": "CE", "action": "BUY", "quantity": 75},
        {"offset": "OTM6", "option_type": "PE", "action": "BUY", "quantity": 75},
        {"offset": "OTM4", "option_type": "CE", "action": "SELL", "quantity": 75},
        {"offset": "OTM4", "option_type": "PE", "action": "SELL", "quantity": 75}
    ]
)

Response:

json
{
  "status": "success",
  "underlying": "NIFTY",
  "underlying_ltp": 26050.45,
  "results": [
    {"leg": 1, "action": "BUY", "offset": "OTM6", "option_type": "CE", "symbol": "NIFTY30JAN2526350CE", "orderid": "123", "status": "success"},
    {"leg": 2, "action": "BUY", "offset": "OTM6", "option_type": "PE", "symbol": "NIFTY30JAN2525750PE", "orderid": "124", "status": "success"},
    {"leg": 3, "action": "SELL", "offset": "OTM4", "option_type": "CE", "symbol": "NIFTY30JAN2526250CE", "orderid": "125", "status": "success"},
    {"leg": 4, "action": "SELL", "offset": "OTM4", "option_type": "PE", "symbol": "NIFTY30JAN2525850PE", "orderid": "126", "status": "success"}
  ]
}

Bull Call Spread (2 legs)

python
response = client.optionsmultiorder(
    strategy="Bull Call Spread",
    underlying="NIFTY",
    exchange="NSE_INDEX",
    expiry_date="30JAN25",
    legs=[
        {"offset": "ATM", "option_type": "CE", "action": "BUY", "quantity": 75},
        {"offset": "OTM2", "option_type": "CE", "action": "SELL", "quantity": 75}
    ]
)

Bear Put Spread (2 legs)

python
response = client.optionsmultiorder(
    strategy="Bear Put Spread",
    underlying="NIFTY",
    exchange="NSE_INDEX",
    expiry_date="30JAN25",
    legs=[
        {"offset": "ATM", "option_type": "PE", "action": "BUY", "quantity": 75},
        {"offset": "OTM2", "option_type": "PE", "action": "SELL", "quantity": 75}
    ]
)

Straddle (2 legs)

python
response = client.optionsmultiorder(
    strategy="Long Straddle",
    underlying="BANKNIFTY",
    exchange="NSE_INDEX",
    expiry_date="30JAN25",
    legs=[
        {"offset": "ATM", "option_type": "CE", "action": "BUY", "quantity": 30},
        {"offset": "ATM", "option_type": "PE", "action": "BUY", "quantity": 30}
    ]
)

Strangle (2 legs)

python
response = client.optionsmultiorder(
    strategy="Short Strangle",
    underlying="NIFTY",
    exchange="NSE_INDEX",
    expiry_date="30JAN25",
    legs=[
        {"offset": "OTM3", "option_type": "CE", "action": "SELL", "quantity": 75},
        {"offset": "OTM3", "option_type": "PE", "action": "SELL", "quantity": 75}
    ]
)

Diagonal Spread (Different Expiries)

python
response = client.optionsmultiorder(
    strategy="Diagonal Spread",
    underlying="NIFTY",
    exchange="NSE_INDEX",
    legs=[
        {"offset": "ITM2", "option_type": "CE", "action": "BUY", "quantity": 75, "expiry_date": "27FEB25"},
        {"offset": "OTM2", "option_type": "CE", "action": "SELL", "quantity": 75, "expiry_date": "30JAN25"}
    ]
)

Calendar Spread (Same Strike, Different Expiries)

python
response = client.optionsmultiorder(
    strategy="Calendar Spread",
    underlying="NIFTY",
    exchange="NSE_INDEX",
    legs=[
        {"offset": "ATM", "option_type": "CE", "action": "BUY", "quantity": 75, "expiry_date": "27FEB25"},
        {"offset": "ATM", "option_type": "CE", "action": "SELL", "quantity": 75, "expiry_date": "30JAN25"}
    ]
)

Options Analysis

Get Option Symbol

Find the exact symbol for a given strike:

python
response = client.optionsymbol(
    underlying="NIFTY",
    exchange="NSE_INDEX",
    expiry_date="30JAN25",
    offset="ATM",
    option_type="CE"
)
# Response: {'symbol': 'NIFTY30JAN2526000CE', 'exchange': 'NFO', 'lotsize': 75, ...}

Get Option Chain

Retrieve the full option chain for analysis:

python
chain = client.optionchain(
    underlying="NIFTY",
    exchange="NSE_INDEX",
    expiry_date="30JAN25",
    strike_count=10  # ±10 strikes from ATM
)

Response includes for each strike:

json
{
  "strike": 26000.0,
  "ce": {
    "symbol": "NIFTY30JAN2526000CE",
    "label": "ATM",
    "ltp": 250.50,
    "bid": 250.00,
    "ask": 251.00,
    "volume": 1500000,
    "oi": 5000000,
    "lotsize": 75
  },
  "pe": {
    "symbol": "NIFTY30JAN2526000PE",
    "label": "ATM",
    "ltp": 245.00,
    "bid": 244.50,
    "ask": 245.50,
    "volume": 1200000,
    "oi": 4500000,
    "lotsize": 75
  }
}

Calculate Option Greeks

Get Delta, Gamma, Theta, Vega, Rho for any option:

python
greeks = client.optiongreeks(
    symbol="NIFTY30JAN2526000CE",
    exchange="NFO",
    interest_rate=0.00,
    underlying_symbol="NIFTY",
    underlying_exchange="NSE_INDEX"
)

Response:

json
{
  "status": "success",
  "symbol": "NIFTY30JAN2526000CE",
  "option_type": "CE",
  "strike": 26000.0,
  "spot_price": 25966.05,
  "option_price": 250,
  "days_to_expiry": 28.5,
  "implied_volatility": 15.6,
  "greeks": {
    "delta": 0.4967,
    "gamma": 0.000352,
    "theta": -7.919,
    "vega": 28.9489,
    "rho": 9.733994
  }
}

Calculate Synthetic Future Price

python
synthetic = client.syntheticfuture(
    underlying="NIFTY",
    exchange="NSE_INDEX",
    expiry_date="30JAN25"
)
# Response: {'synthetic_future_price': 26050.05, 'atm_strike': 26000.0, ...}

Get Expiry Dates

python
expiries = client.expiry(
    symbol="NIFTY",
    exchange="NFO",
    instrumenttype="options"
)
# Returns list of expiry dates: ['30-JAN-25', '06-FEB-25', '13-FEB-25', ...]

Common Index Details

Index Exchange Lot Size Strike Gap
NIFTY NSE_INDEX 75 50
BANKNIFTY NSE_INDEX 30 100
FINNIFTY NSE_INDEX 65 50
MIDCPNIFTY NSE_INDEX 50 25
SENSEX BSE_INDEX 20 100
BANKEX BSE_INDEX 30 100

Strategy Patterns

Weekly Options Selling (Theta Decay)

python
# Short Strangle - Sell OTM options to collect premium
response = client.optionsmultiorder(
    strategy="Weekly Strangle",
    underlying="NIFTY",
    exchange="NSE_INDEX",
    expiry_date="30JAN25",  # Weekly expiry
    legs=[
        {"offset": "OTM5", "option_type": "CE", "action": "SELL", "quantity": 75},
        {"offset": "OTM5", "option_type": "PE", "action": "SELL", "quantity": 75}
    ]
)

Directional Play with Protection

python
# Bull Call Spread - Limited risk bullish bet
response = client.optionsmultiorder(
    strategy="Bullish Spread",
    underlying="BANKNIFTY",
    exchange="NSE_INDEX",
    expiry_date="30JAN25",
    legs=[
        {"offset": "ATM", "option_type": "CE", "action": "BUY", "quantity": 30},
        {"offset": "OTM3", "option_type": "CE", "action": "SELL", "quantity": 30}
    ]
)

Event Day Volatility Play

python
# Long Straddle before results/events
response = client.optionsmultiorder(
    strategy="Event Straddle",
    underlying="RELIANCE",
    exchange="NSE",
    expiry_date="30JAN25",
    legs=[
        {"offset": "ATM", "option_type": "CE", "action": "BUY", "quantity": 250},
        {"offset": "ATM", "option_type": "PE", "action": "BUY", "quantity": 250}
    ]
)

Butterfly Spread (Low Capital)

python
response = client.optionsmultiorder(
    strategy="Long Butterfly",
    underlying="NIFTY",
    exchange="NSE_INDEX",
    expiry_date="30JAN25",
    legs=[
        {"offset": "ITM2", "option_type": "CE", "action": "BUY", "quantity": 75},
        {"offset": "ATM", "option_type": "CE", "action": "SELL", "quantity": 150},
        {"offset": "OTM2", "option_type": "CE", "action": "BUY", "quantity": 75}
    ]
)

Margin Calculation

Calculate required margin before placing orders:

python
margin = client.margin(positions=[
    {
        "symbol": "NIFTY30JAN2526000CE",
        "exchange": "NFO",
        "action": "SELL",
        "product": "NRML",
        "pricetype": "MARKET",
        "quantity": "75"
    },
    {
        "symbol": "NIFTY30JAN2525000CE",
        "exchange": "NFO",
        "action": "BUY",
        "product": "NRML",
        "pricetype": "MARKET",
        "quantity": "75"
    }
])

print(f"Total Margin Required: {margin['data']['total_margin_required']}")
print(f"SPAN Margin: {margin['data']['span_margin']}")
print(f"Exposure Margin: {margin['data']['exposure_margin']}")

Notes

  • Always check available margin before placing option sell orders
  • Use splitsize parameter for large orders to avoid freeze quantity limits
  • Weekly options expire on Thursday, monthly on last Thursday
  • NIFTY lot size is 75, BANKNIFTY is 30
  • Use Analyzer mode for paper trading: client.analyzertoggle(mode=True)

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