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CloudQuant Coral Ostrich

CloudQuant Coral Ostrich by CloudQuant

CloudQuant Coral Ostrich

In the dynamic landscape of financial markets, comprehending trading activities is the cornerstone of informed decision-making. "CQ Coral Ostrich" serves as a comprehensive resource, meticulously dissecting the daily buy activity into two pivotal components: "buy cover" and "buy long." By delving into these dimensions, this dataset unveils the intricate structure of market flow, providing invaluable insights to traders and analysts.

Dataset Overview:

"CQ Coral Ostrich" is engineered to meticulously deconstruct daily trading activities across a spectrum of US traded equities. It parses the trading volumes into two fundamental constituents:

  • Buy Cover: This metric quantifies the volume of shares or contracts that traders acquire to cover their short positions. "Buy cover volume" is a fundamental gauge of market sentiment and can serve as an indicator of potential short squeezes. This parameter is pivotal for grasping shifts in investor sentiment and potential price fluctuations.
  • Buy Long: This parameter encapsulates the volume of shares or contracts associated with the establishment of new long positions. The influx of "buy long" reflects investor optimism and confidence in the asset's upward trajectory.

Key Features:

The dataset boasts a range of key features designed to facilitate insightful analysis:

  • ISIN and Ticker: Provides the unique International Securities Identification Number (ISIN) and ticker symbols associated with the respective financial instruments.
  • Trade Date and Timestamp: Two pivotal date columns are included. The "Trade Date" denotes the date corresponding to the trading flow being analyzed. The "Timestamp" signifies the date of dataset generation.

The dataset is generated daily at 8:00 AM CST, one day after each trading session. This ensures the availability of comprehensive and up-to-date data for analysis.

The "CQ Coral Ostrich" empowers market participants to navigate the intricacies of market flow, providing a nuanced perspective of buying activities. As a vital tool for interpreting trading dynamics, this dataset equips traders and analysts with the insights needed to make informed trading decisions

Column Type Description
_seq uint Internal sequence number used to keep data rows in order
timestamp string Timestamp of the Data (underlying field is nc_publish_date_actual)
muts uint64 Microseconds Unix Timestamp. An integer representation of a timestamp with microsecond precision that can be compared directly to other timestamps. (underlying field is nc_publish_date_actual)
symbol string Trading Symbol
ISIN string International Securities Identification Number. An international code which identifies a securities issue
Buy_Cover double Volume of shares of buy orders for closing out an existing short positions.
Buy_Long double Volume of shares of buy orders for opening new long positions
Trade_Date string Trade Date refers to what trade date´s flow is the signal trying to break down