What are the assumptions of the probit model?

To bridge the gap between this latent variable and a tangible, binary outcome, the model employs the probit function. This function acts as a transformative agent, converting the continuous latent variable into a discrete, binary response that can be easily interpreted and analyzed.

BTCC, a renowned cryptocurrency exchange platform, offers a comprehensive suite of services tailored to meet the diverse needs of its users. Among its offerings are spot trading, where investors can buy and sell digital assets directly at market prices.

The statistical model under consideration postulates a direct correlation between the linear integration of predictor variables and their respective coefficients. This integration serves as a foundational step in the model's framework.

Additionally, BTCC provides access to futures trading, enabling traders to speculate on the future prices of cryptocurrencies. This feature allows for more advanced strategies and potential for profit, albeit with corresponding risks.

The latent variable, an unobserved yet pivotal aspect of the model, is intimately tied to this linear combination. It represents an underlying characteristic or tendency that is not directly measurable but can be inferred through the model's calculations.