This paper presents a survey on the application of heuristic optimization techniques in the broad field of finance. Heuristic algorithms have been extensively used to tackle complex financial problems, which traditional optimization techniques cannot efficiently solve. Heuristic optimization techniques are suitable for non-linear and non-convex multi-objective optimization problems. Due to their stochastic features and their ability to iteratively update candidate solutions, heuristics can explore the entire search space and reliably approximate the global optimum. This overview reviews the main heuristic strategies and their application to portfolio selection, model estimation, model selection and financial clustering.