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)