Why Does A Hedge Fund Want Level 3?
Trading and Investing
A hedge fund may use Level 3 historical data in order to gain a more detailed understanding of market activity and price movements. Level 3 data refers to the most detailed level of market data available, including individual order books and the specific prices at which buyers and sellers are willing to transact.
As a result of accessing Level 3 historical data, a hedge fund can gain a more granular view of market dynamics!
Including the size and frequency of buy and sell orders, the liquidity of particular assets or markets, and the behavior of individual market participants. Furthermore, this information can be used to inform trading strategies and help the fund make better investment decisions.
For example, a hedge fund may use Level 3 historical data to identify trends in market activity!
Moreover, as changes in supply and demand occur, they can adjust their trading strategies accordingly.
The data may also be used to identify potential arbitrage opportunities. Where the fund can profit from price discrepancies between different markets or assets.
In addition, Level 3 data can be a very useful tool for risk management! And help your risk management team identify potential market vulnerabilities.
As a result of analyzing the behavior of individual market participants and identifying changes in trading patterns, hedge funds and other traders may be able to better manage risk and avoid pitfalls.
Access to Level 3 historical data has typically been only available to professional traders and institutions. However, Level 3 historical data is now becoming more accessible and business critical for hedge funds that specialize in high-frequency trading or other quantitative strategies.
The BMLL Data Feed is an API feed containing over 400 market metrics derived from the full Level 3 order book, including every single insert, modify, execute or delete order message across every venue, available at daily and intraday resolution.
Below is a selection of aggregated metrics used by BMLL clients to better understand the market. Contact us to find out more about how the BMLL Data Feed can supplement your market insight.
BMLL uses Cboe Indices for European Indices and the Nasdaq 100 for the US index. Across an index, the values become aggregated by using a weighted mean of the considered metric. With the lit trade notional of that listing. The Notional Liquidity and Trade Notional has become converted to Euros from all other currencies. In addition, the conversion rate uses the daily rate published by the ECB. On each bar chart, the white whiskers span the 25th to the 75th percentile, additionally weighted by the lit trade notional, to show the distribution width.
The standard deviation of the log returns of the mid-price of the lit order book on a venue during continuous trading, Using a sampling frequency of 1 minute. The volatility is annualised assuming a standard 8.5 hours in a trading day and 252 trading days in a year.
The time weighted mean bid-ask spread of the day, given in basis points relation to the time-weighted mean mid-point price.
Quote to Trade
The ratio of quotes to trades. The number of quotes is calculated as the number of messages which did not signify an order execution. The number of trades becomes calculated as the number of aggressive executions. Where simultaneous partial executions of a single order become counted as a single trade.
Mean Resting Time
The mean time, in seconds, when an order placed at the 1st level of the book will sit on the book before being totally or partially filled.
The time weighted average notional amount up to 30 basis points around the BBO.
The probability that an order placed at the 1st level of the book will become filled within 60 seconds.
The change (in basis points) between the mid-point price 1 minute prior to the end of continuous trading. In addition, the closing price of the auction on the Regulated Market.
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Why Does A Hedge Fund Want Level 3?