MLink TickerBasket

SpiderRock provides a TickerBasket feature via MLink REST (WebSockets coming) that allows clients to group multiple tickers into named baskets for efficient querying. This feature is available through the MLink/REST API.

Overview

MLink TickerBasket enables clients to:

• Group multiple tickers into named baskets
• Query data for all tickers in a basket using a single parameter
• Achieve faster query performance compared to WHERE clause filtering
• Scale efficiently from small (10 tickers) to large (200+ tickers) baskets

To use TickerBasket, clients must:

1. Secure an MLink API Key
2. Connect to an MLink/WebSocket or REST server
3. Define baskets using TickerItemDef messages
4. Query using the basket number parameter

TickerBasket Workflow

Key Messages

Message	Source	Description
TickerItemDef	Client	Define tickers in a basket

Workflow

1. Client Sends TickerItemDef Objects:

   • Send multiple TickerItemDef objects to the MLink server
   • Each object represents a ticker with key details (ticker symbol, asset type, ticker source)
   • Include a basketNumber field to group tickers into a single basket
   • Include a userName field to identify the basket owner

2. Post Basket Definitions:

   • Post using: POST /rest/proto?cmd=postmsgs&postaction=I
   • Each TickerItemDef adds one ticker to the specified basket
   • Baskets can contain varying numbers of tickers (10-200+), each being its own object.
   • Baskets are user-specific: the same basket number can exist for different users

3. Query Using TickerBasket Parameter:

   • Use the tickerbasket parameter with the basket number
   • Example: GET /rest/proto?cmd=getmsgs&msgtype=OptionNbboQuote&tickerbasket=0000-0000-0000-0001
   • Server processes the query for all tickers in the basket

API Reference

TickerItemDef Message

The TickerItemDef message is used to define individual tickers within a basket.

Primary Key Fields:

• ticker (TickerKey): The ticker symbol, asset type, and ticker source
• basketNumber (HexLong): The basket identifier (can be formatted with or without dashes, e.g., 1 or 0000-0000-0000-0001)
• userName: The username that owns this basket - your username

Body Fields:

• clientFirm (ClientFirm): The client firm associated withyour userName - not mandatory
• timestamp (Timestamp): Timestamp - not mandatory

Example TickerItemDef POST with Objects as Body:

POST /rest/json?cmd=postmsgs&postaction=I
{
  "header": {
    "mTyp": "TickerItemDef"
  },
  "message": {
    "pkey": {
      "ticker": {
        "at": "EQT",
        "ts": "NMS",
        "tk": "AAPL"
      },
      "basketNumber": "0000-1111-2222-3333",
      "userName": "YOUR_USERNAME"
    },
    "clientFirm": "YOUR_CLIENT_FIRM",
    "timestamp": "2025-01-01 12:00:00.000000"
  }
}

Query Parameter

Parameter Name: tickerbasket

Format: HexLong (supports both 1 and 0000-0000-0000-0001 formats)

Usage: Add to any getmsgs or getcount query

Examples:

GET /rest/json?cmd=getmsgs&msgtype=StockBookQuote&tickerbasket=1

GET /rest/json?cmd=getmsgs&msgtype=OptionNbboQuote&tickerbasket=1&l=5000

GET /rest/json?cmd=getcount&msgtype=LiveImpliedQuote&tickerbasket=0000-0000-0000-0001

Supported Message Types

TickerBasket filtering works with message types that have one of the following key types in their schema (primary key OR body fields):

• TickerKey in Primary Key: Messages like StockBookQuote, StockPrint
• OptionKey in Primary Key: Messages like OptionNbboQuote, LiveImpliedQuote
• ExpiryKey in Primary Key: Messages like LiveSurfaceCurve

Features

• Performance Optimization: Faster query performance compared to WHERE clause filtering, especially for queries involving multiple tickers
• Scalability: Support for baskets ranging from 10 to 200+ tickers
• Flexible Querying: Use basket number as a single parameter instead of complex WHERE clauses
• Named Baskets: Organize tickers into logical groups with unique basket numbers
• Combined Filtering: Can be combined with other query parameters like where, limit, etc.

Error Handling

The server returns specific error messages for common issues:

• Basket Not Found: TickerBasket: basket {basketNumber} not found for user {userName}
• Empty Basket: TickerBasket: basket {basketNumber} is empty
• Unsupported Message Type: TickerBasket: message type {messageType} does not support ticker basket filtering
• Invalid Format: invld param: tickerbasket ({value})

Best Practices

1. Basket Size: Keep baskets to a reasonable size (10-200 tickers) for optimal performance
2. Combining Filters: TickerBasket works well with other filters, but complex WHERE clauses may negate performance benefits

Example Use Cases

Example 1: Equity Quote Basket

# Define basket with 3 equity tickers
POST /rest/json?cmd=postmsgs&postaction=I
[Multiple TickerItemDef messages with basketNumber=1]

# Query all quotes for basket
GET /rest/json?cmd=getmsgs&msgtype=StockBookQuote&tickerbasket=1

Example 2: Option Quote Basket

# Define basket with option underliers (Ticker)
POST /rest/json?cmd=postmsgs&postaction=I
[Multiple TickerItemDef messages with basketNumber=2]

# Query all option quotes for basket
GET /rest/json?cmd=getmsgs&msgtype=OptionNbboQuote&tickerbasket=2&l=5000

Example 3: Combined with WHERE Clause

# Query options in basket with additional filtering
GET /rest/json?cmd=getmsgs&msgtype=OptionNbboQuote&tickerbasket=1&where=okey.tk:eq:2025-01-17