Understanding the Chinese stock market: international comparison and policy implications

The definitions of the bear, sidewalk and bull markets are ambiguous in the existing literature. This makes it difficult for practitioners to distinguish between different market conditions. In this paper, we propose statistical definitions of the bear, sidewalk and bull markets, which correspond to the three states in our hidden semi-Markov model. We apply this analysis to the daily returns of the Chinese stock market and seven developed markets. Using the Viterbi algorithm to globally decode the most likely sequence of the market conditions, we systematically find the precise timing of the bear, sidewalk and bull markets for all the eight markets. Through the comparison of the estimation and decoding results, many unique characteristics of the Chinese stock market are revealed, such as ‘crazy bull’, ‘frequent and quick bear’ and ‘no buffer zone’. In China, the bull market is more volatile than in developed markets, the bear market occurs more frequently than in developed markets, and the sidewalk market has not functioned as a buffer zone since 2005. Possible causes of these unique characteristics are also discussed and implications for policy-making are suggested

Decoding Chinese stock market returns: three-state hidden semi-Markov model

In this paper, we employ a three-state hidden semi-Markov model (HSMM) to explain the time-varying distribution of the Chinese stock market returns since 2005. Our results indicate that the time-varying distribution depends on the hidden states, which are represented by three market conditions, namely the bear, sidewalk, and bull markets. We find that the inflation, the PMI, and the exchange rate are significantly related to the market conditions in China. A simple trading strategy based on expanding window decoding shows profitability with a Sharpe ratio of 1.14

Multipole seismoelectric logging while drilling (LWD) for acoustic velocity measurements

In seismoelectric well logging, an acoustic wave propagates along a borehole and induces electrical signals along the borehole wall. The apparent velocities of these seismoelectric signals are equal to the formation velocities. Laboratory scale-model multipole acoustic and seismoelectric LWD tools are built to conduct measurements in a borehole drilled into a sandstone formation. The tools include either an acoustic receiver array of an electrode receiver array along with four acoustic sources to allow the generation of monopole, dipole, and quadrupole modes. Results show that the standard acoustic measurement of formation velocities are impacted by strong tool wave contamination in most situations. However, because the propagating tool waves do not induce any electrical signals, the seismoelectric measurements can provide a more robust velocity measurement. The multipole seismoelectric logging-while-drilling (LWD) could be used as a new logging method to measure the acoustic velocities of the borehole formations.Massachusetts Institute of Technology. Earth Resources Laboratory (Founding Member Consortium

R2DE: a NLP approach to estimating IRT parameters of newly generated questions

The main objective of exams consists in performing an assessment of students' expertise on a specific subject. Such expertise, also referred to as skill or knowledge level, can then be leveraged in different ways (e.g., to assign a grade to the students, to understand whether a student might need some support, etc.). Similarly, the questions appearing in the exams have to be assessed in some way before being used to evaluate students. Standard approaches to questions' assessment are either subjective (e.g., assessment by human experts) or introduce a long delay in the process of question generation (e.g., pretesting with real students). In this work we introduce R2DE (which is a Regressor for Difficulty and Discrimination Estimation), a model capable of assessing newly generated multiple-choice questions by looking at the text of the question and the text of the possible choices. In particular, it can estimate the difficulty and the discrimination of each question, as they are defined in Item Response Theory. We also present the results of extensive experiments we carried out on a real world large scale dataset coming from an e-learning platform, showing that our model can be used to perform an initial assessment of newly created questions and ease some of the problems that arise in question generation

A Professional Mode of the Transformation of Sci-tech Achievements in Scientific Research Institutions of Tianjin City

There are too many scientific research institutions in Tianjin, and the scientific research activities are very active. The transformation of Sci-tech achievements is badly in need of a set of suitable and standardized mode, and how to establish this kind of mode is an important problem faced by researchers of Tianjin Sci-tech development. Based on analyzing the situation in Tianjin research activities, the paper proposes a way to solving this problem--the professional mode of the transformation of Sci-tech achievements, illustrates the connotation of the professional mode, and describes the implement environment and the specific operation progress. According to the characteristics of factors in Tianjin, such as society, government, market, industrial technology and so on, the paper designs the professional mode of the transformation of Sci-tech achievements, which is suitable for the characteristics of Tianjin, and which plays an important role in promoting the development of the productive force in science and technology of Tianjin

Analysis of weak faults of planetary gears based on frequency domain information exchange method

This paper focuses on solving a series of problems, in particular, the extraction of planetary gear fault characteristics for cracked and broken teeth, using the frequency domain information exchange method. First, we discuss deficiencies in classical stochastic resonance fault feature extraction method. A number of issues are associated with adaptive stochastic resonance based on the re-scaling frequency method used during the small parameter issues, such as sampling frequency ratio constraints and easily induced aliasing of the target frequency band. Second, to overcome the above-mentioned problems, this paper proposes a frequency domain information exchange optimization method. Simulations were carried out used the proposed method and results were compared to those obtained using previously presented adaptive stochastic resonance based on the re-scaling frequency method. Finally, tests were performed on an experimental planetary gearbox failure platform to further verify the frequency domain information exchange method for effectively extracting planetary gear crack and missing tooth fault features