Graphic analysis of the existence of disposition effect is the basis of breakpoint regression analysis. Graphic analysis plays an important role in the realization of breakpoint regression. By describing the sample points and the key variables in the coordinate system, we can clearly see whether the sample points near the critical value have jumps. If the sample point jumps, it means that disposition effect does exist. On the other hand, if there is no corresponding jump at the sample point, it shows that there may be problems in the model identification of breakpoint regression. When we find that disposition effect exists at the critical value from the graphic analysis, we should make further and more detailed empirical analysis. In order to make the graph more intuitive, it is necessary to divide the positions and positions according to the key variables that determine the disposal [reprint]. Breakpoint regression and its application in economics, and calculate the average value of variables in this range. Generally speaking, the scope of the box needs to be large enough to accommodate enough samples to make its sample points smooth on both sides of the critical value, but small enough to make the sample points jump obviously at the critical value.