How to interpret ordered logistic regression coefficients?

One application of the ordered logit model can be found in the cryptocurrency industry, particularly in the context of exchanges like BTCC. BTCC, a leading cryptocurrency exchange, offers a range of services to its users, including spot trading, futures trading, and cryptocurrency wallets.

The ordered logit model provides a framework for analyzing categorical response variables with an inherent ordering. In this context, the coefficient associated with each predictor variable carries a specific interpretation.

Specifically, when interpreting the ordered logit coefficient, we focus on the effect of a one-unit increase in the predictor on the response variable. This change is expected to shift the level of the response variable in a predictable manner, as determined by the model's regression coefficients.

BTCC's spot trading service allows users to buy and sell cryptocurrencies at current market prices, while its futures trading service enables users to speculate on the future prices of cryptocurrencies. Additionally, BTCC provides a secure wallet service for storing and managing cryptocurrencies.

The change in the response variable's level is measured on an ordered log-odds scale. This scale accounts for the inherent ordering of the categorical response variable, allowing for a more nuanced understanding of how predictor variables influence the outcome.