title: Scaling and predictability in stock markets: a comparative study.
abstract: Most people who invest in stock markets want to be rich, thus, many technical methods have been created to beat the market. If one knows the predictability of the price series in different markets, it would be easier for him/her to make the technical analysis, at least to some extent. Here we use one of the most basic sold-and-bought trading strategies to establish the profit landscape, and then calculate the parameters to characterize the strength of predictability. According to the analysis of scaling of the profit landscape, we find that the Chinese individual stocks are harder to predict than US ones, and the individual stocks are harder to predict than indexes in both Chinese stock market and US stock market. Since the Chinese (US) stock market is a representative of emerging (developed) markets, our comparative study on the markets of these two countries is of potential value not only for conducting technical analysis, but also for understanding physical mechanisms of different kinds of markets in terms of scaling.
authors.affiliation: Department of Physics and State Key Laboratory of Surface Physics, Fudan University, Shanghai, China.
authors.forename: Huishu
authors.initials: H
authors.lastname: Zhang
authors.affiliation: Department of Physics and State Key Laboratory of Surface Physics, Fudan University, Shanghai, China.
authors.forename: Jianrong
authors.initials: J
authors.lastname: Wei
authors.affiliation: Department of Physics and State Key Laboratory of Surface Physics, Fudan University, Shanghai, China.
authors.forename: Jiping
authors.initials: J
authors.lastname: Huang
mesh_terms: D000465:Algorithms; D007449:Investments; D018803:Models, Economic