Lucena KPI Forecasting - HD
Analysis Period5/29/15 - 8/7/20
Report Generated8/9/20
company

Analysis Overview
Lucena conducted multi-phase research to validate Equifax’s data and illustrate its predictive power in forecasting KPIs for certain publicly traded constituents. This report provides graphical and statistical representations of the effectiveness of Equifax’s consumer credit data in forecasting future quarter over quarter growth in revenue.
Targeted KPIs
Quarterly gross revenue
Constituents
HD - Home Depot Inc
Lucena's Forecast
HD - Revenue Projections to Actuals
Accuracy Statistics
Lucena Consensus
R² N/A 0.05
SMAPE N/A -18.78
RMSE N/A 0.01
Directional N/A N/A
Outperformance 42.11% 21.05%

KPI Attribution

SeasonalityN/A

TrendN/A

ResidualN/A

*KPI Attribution is a combination of ‘Seasonality’, ‘Trend’, & ‘Residual’, which sum to 100%.

Y over Y Quarterly Change % (Forecast vs Actuals)
Quarter Lucena Consensus Actual Difference
Q3-2019 0.05 -0.03 0.05 -0.00
Q4-2019 -0.03 -0.03 -0.03 -0.00
Q1-2021 0.05 0.05 N/A N/A
Q1-2020 N/A 0.11 N/A N/A
Q2-2021 N/A N/A N/A N/A
*Values are in billions
Performance Analysis
Using Regression Analysis, Lucena constructed multiple models composed of Equifax, Macro, Fundamental, and Alternative Data factors. As can be seen, Equifax data is well suited for KPI forecasting and can be further optimized by combining it with other data sets.
Data Sources & Features
Equifax - Consumer credit dataset for the United States population.
+ Delinquency Rate
+ Utilization Rate
+ Debt to Income
+ Inquiries TTM
+ Payment to Balance Ratio
+ Available Credit+ Payment Due
+ Credit Score
+ Number of Accounts
+ Number of New Accounts
+ Total Balance
+ Number of Consumers
 
Machine Learning
Lucena Machine Learning models are built using SVM, Random Forest, Knn, Logistic Regression, and other traditional Machine Learning techniques. An ensemble of uncorrelated multi-factor models are created and weighted based on their recent accuracy. Final forecast values are based on calculating the mean from the weighted sum of all models.

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Disclaimer Pertaining to Content Delivered & Investment Advice
This information has been prepared by Lucena Research Inc. and is intended for informational purposes only. This information should not be construed as investment, legal and/or tax advice. Additionally, this content is not intended as an offer to sell or a solicitation of any investment product or service. Lucena is a technology company and not a certified investment advisor. Do not take the opinions expressed explicitly or implicitly in this communication as investment advice. The opinions expressed are of the author and are based on statistical forecasting based on historical data analysis. Past performance does not guarantee future success. In addition, the assumptions and the historical data based on which an opinion is made could be faulty. All results and analyses expressed are hypothetical and are NOT guaranteed. All Trading involves substantial risk. Leverage Trading has large potential reward but also large potential risk. Never trade with money you cannot afford to lose. If you are neither a registered nor a certified investment professional this information is not intended for you. Please consult a registered or a certified investment advisor before risking any capital.
Copyright
Copyright © 2019, Equifax Inc., Atlanta, Georgia. All rights reserved. Equifax is a registered trademark of Equifax Inc.