论刑法因果关系之原因力

过于迷恋自洽体系的理论建构模式大大拉开了刑法因果关系研究与司法实践的距离,当务之急是把刑法因果关系理论从哲学的附庸中解救出来,重新定位。刑法因果关系是一个由诸多因素构建的体系,原因力、因果场、因果链、着力点是其核心要素。而原因力在诸多因素中的穿针引线使其成为理解刑法因果关系理论的主轴。通过对原因力的形成、内涵、归类、功能、具体适用的分析,让人们在清晰地把握原因力理论的同时,也给予了刑法因果关系理论准确的定位。

因果性究竟是什么?

本文依据现代逻辑学和现代科学的研究成果,指出穆勒的因果性概念是含混不清的。当代西方一些大哲学家,如波普、亨普耳,纳格尔等人对因果性概念的理解也是不够全面的。于是作者对因果性作了条件逻辑的分析,研究了因果场,因果箭头和相互作用的本质等问题,指出因果性就是由于物质的、能量的或信息的作用的传递使得对于一定的因果场来说,一事件是另一事件的INUS条件,从而加深了对“因果性是普遍联系的一个环节”这个辩证唯物主义原理的理解。

Trading volume and returns relationship in SET50 index futures market

This study investigates the relationship between trading volume and returns in SET50 index Futures market in the period from April 2006 to December 2008 using 653 observations. From previous studies, we include three methodologies namely the GARCH model, the Generalized Method of Moments （GMM） to estimate systems of equations and the Granger causality test to investigate the relationship more thoroughly. In addition, we introduce the lagged volume as a new explanatory variable in the GARCH model. Overall, the results show the significant contemporaneous and dynamic relationships between trading volume and returns volatility which support the sequential information arrival hypothesis and imply some degree of market inefficiency. The results from this study also show that past information of trading volume can be used to improve the prediction of price volatility. Therefore, regulators and traders could include past information of trading volume of SET50 index futures in tracking and monitoring the market volatility level and the investment risk in order to make a timely decision.

To What Extent Does the Market Price of Imported Fishmeal Affect the Market Price of Pisciculture Products in Japan？ The Case of Yellowtail and Sea Bream

This study investigates the extent of the influence of imported fishmeal price changes on the market price of pisciculture products. To date, there have been only a few insufficient researches on this topic in Japan. This paper aims to reveal the causality relationship between the market price of imported fishmeal and the market price of pisciculture products using the granger causality test, and to simulate the market price of pisciculture products using impulse response functions as the price of imported fishmeal increases. The results of the granger causality test and impulse response function analyses were as follows： （1） there is a market linkage from the price of imported fishmeal to the market price of sea bream, but no causality with the market price yellowtail; and （2） this has a positive impact on the market price of sea bream when the price of imported fishmeal changes. Moreover, spillover effects were noticed in this simple scenario （at a market price of 800 yen/kg and one unit shock of 1 yen） of about 3 yen/kg.

Study on the Intraday Pattern and the Dynamic Correlation Among Return,Volume and Open Interest——Evidence from Chinese Commodity Futures Markets

This paper uses minute by minute data series from Chinese commodity futures markets to study patterns of intraday effect and discovers the L pattern of absolute return and volume.It is different from stock market,which has a distinctive pattern of U-shaped.The financial market microstructure theory,traders' psychology and trading mechanism are applied to explain it.Then this paper studies the factors that influence volatility of return and the lagged orders.The results show that there is a bilateral Granger causality among any two of the absolute return,volume and open interest,and it is different from the empirical results of the stock market,in the sense that there is only a unilateral Granger causal relationship from volume to absolute return.The authors also analyze the dynamic relationship among these three factors.The empirical results tell that the influence of open interest on volatility of absolute return and volume is weak,and there is a strong correlation between absolute return and volume.Some investment suggestions are offered from the analysis mentioned above.

A NEW APPROACH TO MODEL FINANCIAL MARKETS

This paper deals with the problem of how to take full use of prices information to model financial markets.A range decomposition technique is proposed to decompose the returns into two components.It is proved theoretically that these two components are bi-directional Granger causality,which makes it convenient to establish a vector autoregressive model(VAR).Both simulations and empirical studies are performed,and the results are consistent with the theoretical ones.The range decomposition approach presented in this paper is more efficient in information employment and suggests a new framework to model financial markets.

TESTING LINEAR AND NONLINEAR GRANGER CAUSALITY IN CSI300 FUTURES AND SPOT MARKETS BASED ON NEW CONCEPTS OF NONLINEAR POSITIVE/NEGATIVE SPILLOVER

supported by the National Natural Science Foundation of China under Grant Nos.71125005 70871108 and 70810107020;; Outstanding Talents Funds of Organization Department Beijing Committee of CPC

Hybrid-augmented intelligence： collaboration and cognition

The long-term goal of artificial intelligence （AI） is to make machines learn and think like human beings. Due to the high levels of uncertainty and vulnerability in human life and the open-ended nature of problems that humans are facing, no matter how intelligent machines are, they are unable to completely replace humans. Therefore, it is necessary to introduce human cognitive capabilities or human-like cognitive models into AI systems to develop a new form of AI, that is, hybrid-augmented intelligence. This form of AI or machine intelligence is a feasible and important developing model. Hybrid-augmented intelligence can be divided into two basic models： one is human-in-the-loop augmented intelligence with human-computer collaboration, and the other is cognitive computing based augmented intelligence, in which a cognitive model is embedded in the machine learning system. This survey describes a basic framework for human-computer collaborative hybrid-augmented intelligence, and the basic elements of hybrid-augmented intelligence based on cognitive computing. These elements include intuitive reasoning, causal models, evolution of memory and knowledge, especially the role and basic principles of intuitive reasoning for complex problem solving, and the cognitive learning framework for visual scene understanding based on memory and reasoning. Several typical applications of hybrid-augmented intelligence in related fields are given.

Structure and Connectivity Analysis of Financial Complex System Based on G-Causality Network

The recent financial crisis highlights the inherent weaknesses of the financial market. To explore the mechanism that maintains the financial market as a system, we study the interactions of U.S. financial market from the network perspective. Applied with conditional Granger causality network analysis, network density, in-degree and out-degree rankings are important indicators to analyze the conditional causal relationships among financial agents, and further to assess the stability of U.S. financial systems. It is found that the topological structure of G-causality network in U.S. financial market changed in different stages over the last decade, especially during the recent global financial crisis. Network density of the G-causality model is much higher during the period of 2007-2009 crisis stage, and it reaches the peak value in 2008, the most turbulent time in the crisis. Ranked by in-degrees and out-degrees, insurance companies are listed in the top of 68 financial institutions during the crisis. They act as the hubs which are more easily influenced by other financial institutions and simultaneously influence others during the global financial disturbance.