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.
Highlights
Stock markets provide an opportunity for people to increase their wealth
Agent-based modeling is an important way to analyze the behavior of agents in complex systems [10,11], which has been widely used in analyzing stock markets [12,13]
We have studied the profit landscape defined by some straightforward investment strategies in this work
Summary
Stock markets provide an opportunity for people to increase their wealth. Most of people who invest in stock markets want to earn excess profits [1]. Various technical trading strategies based on moving averages, Bollinger lines and so on have been set up [2,3,4]. Biondo (2013) compared four mainstream technical strategies including the random one, and obtained the following results: the average percentages of wins for these strategies are similar, but the risk of the random one is surprisingly the lowest [7]. We all know that the stock markets belong to the family of complex systems. Agent-based modeling is an important way to analyze the behavior of agents in complex systems [10,11], which has been widely used in analyzing stock markets [12,13]
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