In a causal relationship involving independent and dependent variables, a mediator is a variable that influences both, sitting between them in the causal chain. Conversely, a moderator is a variable that affects the dependent variable but is not part of the direct causal relationship. This study analyzes variables affecting real estate using fuzzy moderation and fuzzy moderatedmediation analyses, which apply fuzzy theory to data observed with ambiguous information. Among the various variables that affect real estate, this study analyzes the relationship between variables that affect real estate prices, particularly house prices, by analyzing stock price, foreign exchange reserve, and so on, which are various variables that can affect real estate sales by loans. Given that these data are collected over a month or more, using observations at a single price point for analysis inevitably leads to a significant amount of information being condensed or summarized. Therefore, this study applies fuzzy moderation and fuzzy moderated-mediation analyses using fuzzy data. In addition to the existing fuzzy moderatedmediation analysis, a model for additional possible moderation was proposed. For the data analysis, six real estate-related variables from the Bank of Korea and KB Data Bank are analyzed. Two fuzzy moderation models and three fuzzy moderated-mediation models are proposed for the given dataset.