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Driving and defining change with expertise, compassion and persistence.

Case Study

Driving and defining change with expertise, compassion and persistence.

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Cryptocurrency Price Regression Model for Hedge Fund Trading

Cryptocurrency Price Regression Model for Hedge Fund Trading

Background

A hedge fund seeks to uncover trading signals in the cryptocurrency space.

Gaia Labs Consulting was tasked to conduct regression analysis to discover price-affecting factors for strategic trading.

Design

Tackle the challenge of fundamentally evaluating cryptocurrencies in a rapidly growing digital currency landscape.

Tackle the challenge of fundamentally evaluating cryptocurrencies in a rapidly growing digital currency landscape.

Tackle the challenge of fundamentally evaluating cryptocurrencies in a rapidly growing digital currency landscape.

Identify factors with strong correlation to cryptocurrency prices as a basis for trading insights.

Identify factors with strong correlation to cryptocurrency prices as a basis for trading insights.

Identify factors with strong correlation to cryptocurrency prices as a basis for trading insights.

Objective

Use linear regression to unveil relationships between cryptocurrency prices and fundamental factors.

Use linear regression to unveil relationships between cryptocurrency prices and fundamental factors.

Use linear regression to unveil relationships between cryptocurrency prices and fundamental factors.

Provide a foundation for cryptocurrency fundamental analysis to inform hedge fund trading strategies.

Provide a foundation for cryptocurrency fundamental analysis to inform hedge fund trading strategies.

Provide a foundation for cryptocurrency fundamental analysis to inform hedge fund trading strategies.

Methodological Approach

Initial Steps: Scrape data, clean, and establish baseline regression model.

Initial Steps: Scrape data, clean, and establish baseline regression model.

Initial Steps: Scrape data, clean, and establish baseline regression model.

Validation: Conduct cross-validation, regularization, and feature engineering.

Validation: Conduct cross-validation, regularization, and feature engineering.

Validation: Conduct cross-validation, regularization, and feature engineering.

Model Evaluation: Utilize statistical methods to verify model assumptions and optimize performance.

Model Evaluation: Utilize statistical methods to verify model assumptions and optimize performance.

Model Evaluation: Utilize statistical methods to verify model assumptions and optimize performance.

Result & Impact

Strong Signals

Discovered strong correlation between Circulating Supply and Crypto Price (R² = 0.868), pivotal for price signal analysis.

On-Chain Transactions

Identified Reddit discussions and On-Chain Transaction² as significant factors influencing price.

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© 2024 Gaialabs. All rights reserved.

Design AI solutions that create more efficiency and impact in the world

About

Services

Case Studies

© 2024 Gaialabs. All rights reserved.