REIT Price Prediction Model Using Population Distribution Data

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Solution Overview

Problem

Existing real-time evaluation systems for REIT securities prices do not effectively predict future REIT investment trust values, limiting investors' ability to make informed decisions.

Innovation Solution

A prediction device and model that utilizes machine learning to forecast future REIT investment trust values by analyzing population distribution data, REIT prices, and other relevant data, generating a prediction model that outputs future values.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Speed

If REIT securities prices are used in real-time evaluation systems, then real-time evaluation capability is improved, but prediction accuracy of future REIT values deteriorates

Engineering Contradiction:

Improvereal-time evaluation capabilityVSAvoidprediction accuracy of future REIT values

Core Design Contradiction:

SpeedVSMeasurement precision

Solution Approach 1:

The system segments the evaluation process into two distinct modes: real-time evaluation using current REIT securities prices, and prediction evaluation using machine learning models that incorporate population distribution data. This segmentation allows each mode to optimize for its specific purpose without compromising the other.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces population distribution data as an intermediary element that bridges the gap between current REIT prices and future value prediction. This intermediary data source enables the prediction model to look beyond current market prices and capture underlying demographic trends that drive future REIT performance.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Device complexity

If only REIT securities prices are used for evaluation, then system simplicity is improved, but predictive capability for future values deteriorates

Engineering Contradiction:

Improvesystem simplicityVSAvoidpredictive capability

Core Design Contradiction:

Device complexityVSReliability

Solution Approach 1:

The system merges multiple data sources including REIT securities prices, population distribution data, and machine learning prediction models into a unified evaluation framework. This combination allows the system to maintain simplicity in implementation while significantly enhancing predictive capability through diverse data inputs.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The evaluation system is designed with multi-functionality, capable of performing both real-time evaluation based on current prices and future value prediction based on demographic trends. This universal design allows a single system to serve multiple purposes without requiring separate specialized systems.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20240386499A1Investment trust price prediction device and prediction model

Publication Date: 2024.11.21 NTT DOCOMO INC

AI summary

The value of the real estate investment trust is predicted. A REIT price prediction device 1 includes: a storage unit 10 that stores a prediction model for predicting a future REIT price, the prediction model being generated by learning based on training data comprising sets of input data, which comprises population distribution data regarding the population distribution around each of a plurality of real estate properties in which a REIT (Real Estate Investment Trust) invests, and a REIT price indicating the value of the REIT; an acquisition unit 11 that acquires the input data; and an output unit 13 that outputs the future REIT price obtained by applying the input data acquired by the acquisition unit 11 to the prediction model stored in the storage unit 10.