投资者结构与股价波动关系——基于理论的思考

长期以来，人们认为机构投资者可以稳定股市。本文从更广的视角研究了投资者结构与股价波动的关系。本文结论如下：（1）在市场产品机构、交易制度和规则体系等要素给定的情况下，股价波动是投资者结构参数的函数。（2）机构投资者与稳定股市没有必然的联系。即使在市场的产品结构和交易制度等要素给定的情况下．不同的投资者结构中机构投资者比例的增加既可以增加股价波动，也可以减少股价波动。（3）在一些投资者结构中，股价波动反而随着理性机构投资者比例的增加而增加。即使在投资者结构中其他参数相同的情况下，理，比机构投资者的比例过多或过少均有可能增加波动。（4）即使在上市公司不分红且没有重大利好消息支持股价的情况下，在一定的投资者结构中，机构投资者仍能通过买入来制造股价波动。并从中获利。但这种策略能够成功依赖于市场中其他类型投资者的结构。（5）适度的羊群行为会使股价波动最小，而过强或者过弱的羊群行为都使股价波动增加。     

How do economic policy uncertainty and geopolitical risk drive Bitcoin volatility?

We investigate how economic policy uncertainty (EPU) and geopolitical risks (GPR) impact Bitcoin volatility with respect to factors related to type and nationality of uncertainty, investigated period, relationship horizon and extreme conditions. Applying ARDL model and quantile regression for monthly data from August 2010 to September 2021, we reveal that June 2014 corresponds to a key date that marks a reversal in the investigated relationship. Furthermore, we show that the relationship between uncertainty and bitcoin volatility changes according to different factors. US uncertainty has short run effects on Bitcoin volatility, while China’s uncertainty has rather long run effects. Moreover, Bitcoin volatility responds in the same manner to US EPU and GPR, while, it responds differently to China's EPU and GPR. In extreme quantiles, we find that Bitcoin hedges against US EPU and GPR. Further, Bitcoin hedges against either individual or joint effects of US uncertainty, but not both.     

旅游危机管理系统机制分析与战略对策研究--以长江三峡旅游发展为例

借助长江三峡旅游发展中的大量事实．按照时间序列依次对旅游危机的生成机制、旅游危机的影响机制以及旅游危机管理的作用机制进行了系统分析．并在此基础上提出了不同阶段旅游危机管理的战略对策。     

制度环境的改善与我国房贷证券化的推进

实行房贷证券化,能够积极有效地推动银行和金融市场的发展,增强国家宏观政策施行的效果,从而促进经济社会的发展。借鉴美国等模式的经验,推进我国房贷证券化,需要构建适合我国MBS发展模式及其体制建设,为住房抵押贷款证券化提供发展空间,创造发展环境。     

我国股权分置改革下权证定价的实证研究

权证在性质上也是一种期权，但并不是一种单纯的期权，定价要比普通期权复杂。我国在近十年后，重新推出了权证。在一系列假设条件下，利用Black—Scholes和二叉树模型，推导出权证定价公式。最后采用我国发行的权证及标的股票的收盘价格资料，计算了公司权益的波动率，从而利用已推导的公式对权证理论价值进行了实证分析。并同其实际市场价进行了比较，为权证的投资决策提供了参考依据。     

基于外汇期权方法的汇率预测研究

文章利用2004年芝加哥商品交易所的美元-欧元期货期权的信息,分析了其隐含偏度和隐含波动率在预测短期汇率中的效力。结果发现,隐含偏度、隐含波动率的偏度与每日汇率变化率有紧密的联系。     

上海股市收益与波动的周内效应研究

股市周内效应一直是金融投资者关注的焦点问题，许多学者已做了大量研究，但多数文献将收益与波动的周内效应分开来进行研究和检验，忽视了波动与收益的共生性，其结果缺乏严密性和说服力。针对这种情况，提出平行数据GARCH模型并给出了参数的极大似然估计方法，进而对上海股市收益和波动的周内效应进行检验，既反映收益与风险存在共生关系，又避免了分别判断收益和波动的周内效应所致的缺点。     

资本市场开放与公司内部控制质量——基于“沪港通”的证据

以中国“沪港通”交易制度的实施为政策背景,采用多时点双重差分模型,考察资本市场开放对标的公司内部控制质量的影响,研究发现,“沪港通”交易制度的实施显著提升了公司的内部控制质量,在控制其他因素并经过安慰剂检验、去除A+H股影响、改变周期范围等稳健性检验后,结论依然成立。机制检验表明,“沪港通”主要通过内部和外部两种机制对公司内部控制质量产生影响,其中,内部机制是对股价波动性风险控制,外部机制是审计师声誉风险与政府部门监管。     

Minnesota-type adaptive hierarchical priors for large Bayesian VARs

Large Bayesian VARs with stochastic volatility are increasingly used in empirical macroeconomics. The key to making these highly parameterized VARs useful is the use of shrinkage priors. We develop a family of priors that captures the best features of two prominent classes of shrinkage priors: adaptive hierarchical priors and Minnesota priors. Like adaptive hierarchical priors, these new priors ensure that only ‘small’ coefficients are strongly shrunk to zero, while ‘large’ coefficients remain intact. At the same time, these new priors can also incorporate many useful features of the Minnesota priors such as cross-variable shrinkage and shrinking coefficients on higher lags more aggressively. We introduce a fast posterior sampler to estimate BVARs with this family of priors—for a BVAR with 25 variables and 4 lags, obtaining 10,000 posterior draws takes about 3 min on a standard desktop computer. In a forecasting exercise, we show that these new priors outperform both adaptive hierarchical priors and Minnesota priors.     

How does news sentiment affect the states of Japanese stock return volatility?

This paper examines the impact of public news sentiment on the volatility states of firm-level returns on the Japanese Stock market. We firstly adopt a novel Markov Regime Switching Long Memory GARCH (MRS-LMGARCH), which is employed to estimate the latent volatility states of intraday stock return. By using the RavenPack Dow Jones News Analytics database, we fit discrete choice models to investigate the impact of news sentiment on changes of volatility states of the constituent stocks in the TOPIX Core 30 Index. Our findings suggest that news occurrence and sentiment, especially those of macro-economic news, are a key factor that significantly drives the volatility state of Japanese stock returns. This provides essential information for traders of the Japanese stock market to optimize their trading strategies and risk management plans to combat volatility.