企业“脱实向虚”与金融市场稳定——基于股价崩盘风险的视角

近年来,经济中出现的\"脱实向虚\"问题引起了政府和学术界的广泛关注。本文从企业金融投资如何影响股价崩盘风险的视角,研究了企业\"脱实向虚\"对金融市场稳定的影响。通过构建一个包含市场、公司和经理人的三期博弈模型,本文发现,上市公司为了隐藏负面信息而持有金融资产会提升企业股价崩盘的概率。基于沪深两市A股上市公司样本的实证分析验证了理论模型的结论。平均而言,企业金融投资每增加1个标准差,未来一期的股价崩盘风险约增加5.5%个标准差。进一步的研究表明,金融投资水平越高的企业与外界的信息不对称程度也越高。金融投资与股价崩盘风险之间的正相关关系在经营风险更高、内部人受监督程度更低的企业中更为显著。本文的发现揭示出了经济\"脱实向虚\"引起系统性金融风险的一条路径。国家自然科学基金青年项目(71802170、71603302、71603304)的资助;;“计量经济学教育部重点实验室(厦门大学)”;;“数量经济与数理金融教育部重点实验室(北京大学)”的支

Introduction to Fast Frequency-Response Measurements in Micro and Nano Technology

频率响应测试技术作为一种有效的系统辨识技术,可用于开发新型全自动系统,如微注射等.由于缺乏快速、高效的测量方法,频率响应测试技术仍未得到广泛应用.典型的频率响应测试是采用传统的正弦扫描法,一次测量往往需要几分钟.本文提出一种快速测量方法,以最大长度的伪随机二进制序列作为激励信号,利用互相关技术处理输出信号,得到系统的特征频率响应.采用这种方法只需几秒钟就能获得频率响应的测试结果.对三种不同系统的实际测试结果证实了该方法的有效性.Increasing automation is of great interest in various fields of micro and nano technology.Past studies have shown that frequency responses can provide efficient system-identification techniques which can be used in developing novel automated systems e.g.in microinjection.Despite this fact, the frequency responses have not gained so much popularity so far.The reason is that efficient and fast measurement techniques are not so well known in these fields.Typically the frequency responses have been measured by using traditional sine-sweep technique.The traditional technique requires several minutes for one measurement and hence, the development of most practical applications is effectively prevented.This paper presents a fast measurement technique where maximum-length binary sequence (MLBS) is applied as an excitation and the system-characterizing frequency responses are possible to obtain within few seconds.The proposed techniques are verified by experimental data from three different applications.The aim of the paper is to give a short introduction of the methods, thus becoming a starting point for engineers who are trying to find new ideas to implement fast system analysis.江苏省自然科学基金资助项目“高灰阶低干扰LED显示驱动芯片关键技术研究”(BK2011366

JUNO sensitivity on proton decay p → ν K + searches*

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the $p\to \bar{\nu} K^+$ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar{\nu} K^+$ is 36.9% ± 4.9% with a background level of $0.2\pm 0.05({\rm syst})\pm$$0.2({\rm stat})$ events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is $9.6 \times 10^{33}$ years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies

JUNO Sensitivity on Proton Decay p→νˉK+p\to \bar\nu K^+ Searches

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \bar\nu K^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar\nu K^+$ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is $9.6 \times 10^{33}$ years, competitive with the current best limits on the proton lifetime in this channel