New Constructs' specialized datasets provide adjusted financial metrics that reveal companies' true economic performance.
These proprietary metrics help investors see beyond standard financial statements by systematically adjusting for accounting anomalies, enabling more accurate valuations and performance comparisons across companies.
New Constructs Core Earnings reports - new_constructs_core_earnings
Core Earnings measure the normalized operating profitability of a business.
The Core Earnings dataset removes accounting distortions and non-operating items from profit calculations,
Fact: Only New Constructs research captures material unusual gains/losses in footnotes that legacy research providers miss.
Proof: Core Earnings: New Data & Evidence, featured in The Journal of Financial Economics.
Fact: New Constructs Core Earnings & Earnings Distortion data delivers a novel source of alpha for quants and PMs.
Proof: Earnings Distortion: The New Value Factor.
Core Earnings + Earnings Distortion = Reported Earnings
The Problem
Identifying unusual items that distort reported and consensus earnings is increasingly difficult.
So difficult that most analysts and data providers don´t do it – as proven in The Journal of Financial Economics (JFE).
The Answer
New Constructs technology enables them to provide the best database of unusual items in the world and, as a result, provide the best measure of Core Earnings & Earnings Distortion in the world.
Detailed Core Earnings & Earnings Distortion Reconciliation data - new_constructs_core_earnings_reconciliation
The Earnings Distortion Reconciliation dataset identifies and quantifies specific differences between reported and economic earnings.
Proprietary footnotes data on unusual gain/losses that distort consensus earnings and all reported measures of profits.