Various trading strategies are applied in intraday high-frequency market to provide investors with reference signals to be on the right side of market at the right time. In this paper, we apply a trading strategy based on the combination of ACD rules and pivot points system, which is first proposed by Mark B. Fisher, into Chinese market. This strategy has been used by millions of traders to achieve substantial profits in the last two decades, however, discussions concerning on the methods of calculating specific entry point in this trading strategy are rare, which is crucial to this strategy. We suggest an improvement to this popular strategy, providing the calculating and optimizing methods in detail to verify its effectiveness in recent Chinese futures market. Because of the high liquidity and low commissions in stock index futures market, this trading strategy achieves substantial profits .However, given the less liquidity in commodity futures market, profits decrease and even be neutralized by the relatively high commissions
Abstract.Transfer entropy provides a powerful information theoretic measurement of directed information flow between time series variables. Effective and convenient methods of estimation are desirable in practice. This article discusses the formulation of how to estimate transfer entropy via the statistical copula. Furthermore, this article provides theoretical justifications, and two estimation approaches via the Gaussian copula transformation and kernel methods. The experiment demonstrates that the proposed estimation approaches are competitive with the Linear estimator and the Nearest Neighbour estimator.
The year 2008 witnessed the greatest joint stock reform and financial crisis in Chinese history. After these two cases, significant changes have taken place in investors’ behaviors worldwide, along with which is the occurrence of structure change in stock market. In this paper, we employ copula model to simulate the joint distribution between Shanghai Stock Index (SSE) and Chinese Shanghai Index 300 (CSI 300), to find out structure change in Chinese stock market before and after 2008. From results of empirical studies, we get conclusions that the main nature of Chinese stocks market is symmetric, in both marginal and joint distributions. Via the changes of Copula types, upper and lower tail coefficients and Kendall coefficients, we can measure the structure change in Chinese stock market, and get further conclusion about investors’ behaviors change. Before 2008, there is an equal power in quitting market and longing, while diversified investors adjusted their expectation uniformly after this year. Testing results show that the general dependence structure of CSI 300 and SSE is highly dependent and symmetric in most cases. From the distribution of upper and lower tail coefficients, we can draw the conclusion that stratified investors are mainly focused on two tasks, after this year, to close the position on stocks with high correlated stocks market and to maintain market value of stocks
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