Merger and Acquisition (M&A) has been a critical practice about corporate restructuring. Previous studies are mostly devoted to evaluating the suitability of M&A between a pair of investor and target company, or a target company for its propensity of being acquired. This paper focuses on the dual problem of predicting an investor's prospective M&A based on its activities and firmographics. We propose to use a mutually-exciting point process with a regression prior to quantify the investor's M&A behavior. Our model is motivated by the so-called contagious 'wave-like' M&A phenomenon, which has been well-recognized by the economics and management communities. A tailored model learning algorithm is devised that incorporates both static profile covariates and past M&A activities. Results on CrunchBase suggest the superiority of our model. The collected dataset and code will be released together with the paper.