Data Showcasing Service

Data Showcasing Alternative Data

We demonstrate the value of Alternative Data to traders, investment managers, and senior management. Vendors who collect data don’t have access to experienced backtesting engines, historical news, and fundamental data that allows the quantitative analyst to verify that value in the data set is worth the investment. CloudQuant has been able to incorporate time-series data into our Backtesting, and Research tools since our inception. Showcasing or exploring data in CloudQuant is the best way to see the value (alpha) in the data. Showcase provides Protfolio Managers and Quantitative Traders:
  • White Paper(s) that validate the alpha in the data set and independently prove vendor research whitepapers.
  • Functioning Backtest Algorithms that allow quants to see the backtesting logic.
  • Quantitative Experts who can discuss the use of the data set.
  • Access to the institutional grade Mariner(tm) Backtesting and Visualization tools used by other professional quantitative portfolio managers.
  • Time synched historical tick market data.
  • Dataset Catalog – Entries for each dataset with Showcase Partners data being featured above other data sets.
Feature Description
  • Fully enabled backtesting
  • Sample algorithmic trading strategies
  • Trading Scorecards
  • Online detailed demonstration results
  • Trade History Files
  • Working Algos that Showcase your Data Set
  • Full source code to all algos
  • Industry Standard Ticker Symbology
  • Point-in-Time Historical Symbols
  • AI Driven Symbology Maps
  • Point-in-Time API access to Data
  • Specify the symbol and time range to query data.
  • Results in JSON or DataFrame
Data Security
  • No one can download or copy your dataset.
  • Only authorized users have access to the data through our Liberator API.
CloudQuant’s standard whitepapers allow you to see the Alpha in the dataset.
CloudQuant Explorer allows researchers to overlay alternative data, news, and other trading signals with historical market data

The Difficulties Of Dataset Onboarding

The industry knows that the onboarding a new data set is a difficult process. There are numerous problems that include*:

  • Data not compatible with current data analysis systems
  • Can’t find the correct resource
  • Lack of time
  • Difficulty understanding the data’s value
  • Human Capital not available
  • Management not convinced of the value
  • Prohibitively High Fees

For those in the trading industry, we have additional problems that include:

  • Difficulty symbology mapping.
  • Dealing with point-in-time changes to symbol changes.
  • Correlating time series data correctly.

*Source: Greenwich Associates, Alternative Data Usage Study, 2017