FAQ

Precision Alpha OnDemand and General

Is your data time-stamped?
Yes.

What are some of the key data fields you provide?
Next day probabilities (both mechanical and thermal), market emotion/energy, market power, market resistance, market noise, market temperature, and market free energy.  In short, the thermodynamics of a time-series.

What is the granularity of the data? How often is the data delivered?
Exchange uses six months of closing prices to return exact machine-learned results.  Exchange is processed and delivered after each trading day.  For OnDemand, the data is collected and (re-) sampled by the customer to produce a time-series.  The returned output from OnDemand can take up to five minutes, by, for example, bundling 25 time-series together.

Does Precision Alpha only process closing prices?
Exchange is based on closing prices, the OnDemand product can process any time-series, subject to data quality.  OnDemand permits up to 25 concurrent time-series to be processed together in the same file.

How does Market Power compare with Relative Strength Index?
Precision Alpha relies on the same measurement data as the Relative Strength Index. Precision Alpha uses the measurements to calculate exact values for market probabilities, market energy, market power, market resistance, market noise, market temperature and market free energy. The Relative Strength Index is the closest dimensionally to market energy.

Precision Alpha Exchange

What files do you provide to Exchange subscribers?
Exchange subscribers receive a daily text file for each global exchange subscription with a filename format (e.g., NASD_07_01_2021.txt).  Processing begins 4 hours after market-close each day, and delivery targeted for 5 hours after market close.  Contains all historical data (six months of closing prices) for each security and ScienceML’s scientific measurements.  File size can vary across exchanges. For NASD the size of a daily file is between 50MB-75MB.  All data used for processing (six months of closing prices) and the key data fields are returned for a whole exchange (~ 3000 equities) and are supplied in the data file.

How is the Exchange data normalized?
Exchange data is available as processed location-level (exchange) data. Data is presented as a flat, comma-delimited file with each row representing a closing price date.

Which exchanges do you currently offer?
Precision Alpha offers access to over 85 global exchanges. All tickers are covered for each of the exchanges. However, thinly traded instruments must have enough data for the analysis to be meaningful. Data quality processes filter out instruments that have fewer than 100 price changes in a six month period.

Do you provide back testing, and for how long time back in history?
We have 5+ years of historical data for NASD and NYSE.  Customers can also generate their own back test data, if  they own the necessary historical data.

How do Exchange subscribers receive the data?
Data is delivered as a text file to AWS S3, or directly to a customer endpoint (SFTP, S3, etc.).

What is the granularity of the Exchange data? How often is the data delivered?
Every security on the exchange, using six months of closing prices, subject to minimum data quality requirements. Delivered daily, approximately 5 hours after market close.

How is closing price data procured? How often is the data delivered?
Closing prices are procured from market data supplier, Xignite. Closing prices do not originate from an intraday feed or a real-time feed. Our feed from Xignite has no ability to access fee-liable data, in fact, we cannot access any data for the trading day during market hours.

Source of data?
Licensed from Xignite.

When did you start selling this data?
2018-05-01

In which time zone is each time series measured?
Data observations are provided In UTC time and converted to local time.

Does your company store or test data using a cloud infrastructure?
Yes, store data in Amazon AWS S3, and process data using AWS Lambda.

Sharpe ratio?
The Sharpe ratio is defined using statistical expressions, namely, the average return and the standard deviation. It is clear, however, that financial markets are not in statistical equilibrium, and this measure is misleading in most financial markets. The non-equilibrium generalization of the Sharpe ratio can be shown to be always greater than the equilibrium case. Therefore we call the non-equilibrium expression a “Sharper ratio”, and is defined as the ratio of the expected PL minus the risk-free return, divided by the expected PL minus the average return.

Do you map your equities in your data to industry standards like CUSIP, SEDOL or ISIN?
Yes, market data provider maps SEDOL (Stock Exchange Daily Official List)

Does your data contain PII (Personally identifiable information) or MNPI (Material Nonpublic Information)?
No.