Social media bots and stock markets

This study examines the link between information spread by social media bots and stock trading. Based on a large sample of tweets mentioning 55 companies in the FTSE 100 composites, we find significant relations between bot tweets and stock returns, volatility, and trading volume at both daily and intraday levels. These results are also confirmed by an event study of stock response following abnormal increases in the volume of tweets. The findings are robust to various specifications, including controlling for traditional news channel, alternative measures of volatility, information flows in pretrading hours, and different measures of sentiment.     

Inference for large financial systems

We treat the parameter estimation problem for mean‐field models of large interacting financial systems such as the banking system and a pool of assets held by an institution or backing a security. We develop an asymptotic inference approach that addresses the scale and complexity of such systems. Harnessing the weak convergence results developed for mean‐field financial systems in the literature, we construct an approximate likelihood for large systems. The approximate likelihood has a conditionally Gaussian structure, enabling us to design an efficient numerical method for its evaluation. We provide a representation of the corresponding approximate estimator in terms of a weighted least‐squares estimator, and use it to analyze the large‐system and large‐sample behavior of the estimator. Numerical results for a mean‐field model of systemic financial risk highlight the efficiency and accuracy of our estimator.     

浅析大学物理微积分思想与矢量思想

本文探讨了微积分思想和矢量思想在大学物理教学中的应用,致力于总结出一个可靠的应用模式用于提高大学物理教学的质量。     

Learning to bid in sequential Dutch auctions

We propose an agent-based computational model to investigate sequential Dutch auctions with particular emphasis on markets for perishable goods and we take as an example wholesale fish markets. Buyers in these markets sell the fish they purchase on a retail market. The paper provides an original model of boundedly rational behavior for wholesale buyers׳ behavior incorporating learning to improve profits, conjectures as to the bids that will be made and fictitious learning. We analyze the dynamics of the aggregate price under different market conditions in order to explain the emergence of market price patterns such as the well-known declining price paradox and the empirically observed fact that the very last transactions in the day may be at a higher price. The proposed behavioral model provides alternative explanations for market price dynamics to those which depend on standard hypotheses such as diminishing marginal profits. Furthermore, agents learn the option value of having the possibility of bidding in later rounds. When confronted with random buyers, such as occasional participants or new entrants, they learn to bid in the optimal way without being conscious of the strategies of the other buyers. When faced with other buyers who are also learning their behavior still displays some of the characteristics learned in the simpler case even though the problem is not analytically tractable.     

The Complementary Relationship Between Institutional and Complexity Economics: The Example of Deep Mechanismic Explanations

Analyzing economic systems from an evolutionary-institutional or a complexity perspective are two complementary approaches to economic inquiry. I discuss three arguments in favor of this hypothesis: (i) eminent institutional economists have examined the economy as what today could be considered a complex system; (ii) complexity economists lack meta-theoretical foundations which could be provided by institutionalist theory; and (iii) institutional economists could benefit from using methods of complexity economics. In this context, I argue that scholars considering the economy to be complex should seek to explain it by discovering social mechanisms instead of focusing on prediction. In order to distinguish between alternative explanations, scholars should refer to the deepness of an explanation, rather than to Occam’s razor.     

独立学院大学物理教学方法研究与探索

大学物理是理论和实践结合极为紧密的一门基础课程,本文针对独立学院大学物理教学现状,从加强微元法、理论联系实际和分层次教学等5方面来研究提高独立学院大学物理教学质量的方法和途径。     

普通物理教学之我见

加强普通物理学的教学研究 ,不断提升教师的认识和学识是至关重要的。在教学中应注意基本概念和规律 ,研究数学与物理的关联 ,重视实验教学 ,培养学生观察能力、思维能力和动手能力。     

应用信息技术创新高校物理教学

有选择、有目的地把CAI、虚拟实验室和网络教学等信息技术融合到大学物理教学中 ,建构信息化的教学和学习环境是大学物理教学创新的重要内容 ,是提高教学水平和效率的有效途径。     

基于计算实验的工程承发包模式选择机理分析

工程承发包模式是工程建设管理的重要组织方式，工程能否进行有效的目标控制及组织协调主要取决于承发包模式的选择。论文运用Multi-Agent方法建立了承发包模式选择的计算实验模型，通过具体数值算例分别分析了工程复杂度、业主能力及承包商水平对工程承发包模式选择路径的影响。研究结果表明：在工程复杂度越高、业主能力越弱情景下，业主选择DB模式的偏好就越大；提升承包商水平和培育有序的DB建设市场环境是提高业主选择DB模式偏好的重要途径。研究结论为业主的承发包模式选择、行业政策制订提供了参考依据。     

浅谈《高等数学》知识在物理学中的应用

本文主要通过运用高等数学的思想来解决物理问题,阐明了高等数学与物理学之间联系,以提高学生分析问题和解决问题的综合能力。