Transparent econometric models, verified data, confidence index visible on each advanced analysis.
The Brazilian real estate market decides based on averages, comparables and intuition. These three pillars share the same limit: they don't isolate causes. Lycaon Data built its platform from econometrics, a discipline whose function is precisely this: to extract, from a mass of data, the measured impact of each variable on an outcome.
Any statistical estimate comes with a margin of uncertainty. Most tools hide it. We make it public: each advanced analysis displays a confidence index from 0 to 100, based on the model's goodness of fit (R²) and the sample size. You know, before making a decision, how much you can rely on it.
An econometric model does not replace the developer's professional judgment. It informs it. Lycaon Data acknowledges and documents the limits of its models: areas with insufficient samples are flagged, periods of volatility are identified, and unobserved factors are recognized. This transparency about what we know, and what we don't know, is the condition for your informed decision.
This methodological rigor rests on a team rooted in economics research: Dr Vincent Leroy (PhD in economics), Stéphane Daumillare (research Master's in macroeconomics) and Saleem Djima (research Master's in empirical and theoretical economics with a specialization in housing economics). It is this academic expertise that guarantees the robustness of the models behind every analysis.
Our data goes through a rigorous process of verification, deduplication and outlier handling before entering the econometric models.
Result: with each analysis, you know exactly where the figure comes from, how it was calculated, and the level of confidence you can attribute to it.
Principle: A property's price is broken down according to its characteristics (surface area, typology, equipment, location). The model isolates the pure impact of each characteristic, controlling for all the others.
Principle: A property's price partly depends on its neighbors' prices. The model quantifies this dependence by a coefficient between 0 (zero neighborhood effect) and 0.25 (maximum neighborhood effect).
Principle: From dozens of raw indicators, the model extracts 6 synthetic dimensions (health, safety, wealth, education, job diversity, housing) that summarize an area's quality of life.
Each advanced analysis (Real estate project optimization module) comes with a confidence index from 0 to 100.
Robust results, applicable with full confidence in your acquisition or product-definition decisions.
Reliable trend, but to be cross-checked with additional sources before locking a critical decision.
A score below 60 calls for considering the results with great caution.
The confidence index value of an area will tend to vary as new data is added within it.
Each advanced analysis displays the confidence index and the sample size. Without exception.
The limits of our models are published in the methodology: areas with low samples, periods of volatility, unobserved factors.
Properties are updated monthly. Models are re-estimated each quarter to capture market evolution.
Our team answers any methodological question sent by email. Without delay, without filter.
Our data science team answers any detailed request.
