in this article, we are going to describe some important criteria of a Market Maker.
Key Qualities of a Market Maker:
- Price improvement
- Depth of liquidity
- Service offering whatever the financial climate
- Broad coverage
- Immediacy of dealing
- Bespoke technology solutions
According to Corvil: Today’s market-making business leaves little room for second best in technology and infrastructure. Successful market makers must operate a predictable, reliable low-latency trading environment. Market makers must be as fast as the fastest traders on the venue they are providing liquidity on.
The reason why every investor must use a professional market maker to manage assets:
- Detect gaps in market data
- Optimize quote latency response
- Reduce Mean Time to Resolve
- Track order life cycle precisely
- Reduce order gateway latency
- Validate performance of gateways
- Benchmark performance of software updates
- Quickly troubleshoot problems
- Police and hold accountable service providers
- Offload logging to speed up performance
- Analyze exchange latency
- Balance flows across gateways
- Monitor connectivity health
- Analyze throttling on order flow
- Measure order to tick for the venue
As a market maker;
- Managing market data quality and performance
- Making Sure You Never Miss an Order
- Right-Sizing your Systems so you are “Fast Enough”
Trade performance analytics are:
Fill rate: Order tracking state is used to monitor the success or failure of orders through the fill-rate calculation – the percentage of the request volume that was filled.
Tick to order: Calculates the algorithm response latency – the time from receipt of the triggering tick to the transmission of the order.
Order to tick: Calculates the venue response latency – the time from transmission of an order to receipt of tick update on the venue feed reflecting the trade.
Order response: Calculates the venue order response latency – the time from transmission of an order to receipt of acknowledgment of the order from the venue.
Gap detection: Track the sequence numbers of all multicast market data feeds, and use this tracking to report and alert on any gaps.
Relative latency: Calculates the relative latency between two measured events with time-stamps from a common time reference.
Brandwidth protection: Calculates an estimate of the amount of bandwidth needed to meet a quality of service objective for a given traffic load e.g. a market data feed.
You can also read, how AI helps market makers.