Pricing efficiency and asymmetric multifractality of major asset classes before and during COVID-19 crisis

We examine the impact of COVID-19 pandemic crisis on the pricing efficiency and asymmetric multifractality of major asset classes (S&P500, US Treasury bond, US dollar index, Bitcoin, Brent oil, and gold) within a dynamic framework. Applying permutation entropy on intraday data that covers between April 30, 2019 and May 13, 2020, we show that efficiency of all sample asset classes is deteriorated with the outbreak, and in most cases this deterioration is significant. Results are found to be robust under different analysis schemes. Brent oil is the highest efficient market before and during crisis. The degree of efficiency is heterogeneous among all markets. The analysis by an asymmetric multifractal detrended fluctuation analysis (A-MF-DFA) approach shows evidence of asymmetric multifractality in all markets which rise with the scales. The inefficiency is higher during downward trends before the pandemic crisis as well as during COVID-19 except for gold and Bitcoin. Moreover, the pandemic intensifies the inefficiency of all markets except Bitcoin. Findings reveal increased opportunities for price predictions and abnormal returns gains during the COVID-19 outbreak.     

校园踩踏草坪现象监管措施的假设检验及博弈分析

就如何制定踩踏草坪现象的监管措施提出假设，参考“囚徒困境博弈模型”，构建博弈支付矩阵，对假设措施进行检验。依据期望效用公式对假设进行优劣对比，最终否定假设，并得出相对的最优策略，以期对进一步减少校园踩踏草坪现象的发生提出建议。     

校园踩踏草坪现象监管措施的假设检验及博弈分析

就如何制定踩黯草坪现象的监管措施提出假设,参考“囚徒困境博弈模型”,构建博弈支付矩阵,对假设措施进行检验.依据期望效用公式对假设进行优劣对比,最终否定假设,并得出相对的最优策略,以期对进一步减少校园踩踏草坪现象的发生提出建议.     

Forecasting high-frequency excess stock returns via data analytics and machine learning

Borsa Istanbul introduced data analytics to present additional information about its market conditions. We examine whether this product can be utilized via various machine learning methods to predict intraday excess returns. Accordingly, these analytics provide significant prediction ratios above 50% with ideal profit ratios that can reach up to 33%. Among all the methods considered, XGBoost (logistic regression) performs better in predicting excess returns in the long-term analysis (short-term analysis). Results provide evidence for the benefits of both the analytics and the machine learning methods and raise further discussion on the semistrong market efficiency.     

Regulating rating agencies: A conservative behavioural change

We investigate whether the European regulatory reforms of the credit rating industry have been successful in improving the quality of financial institutions’ credit ratings. A shift to more conservative rating behaviour rather than rating quality improvement is identified, which is attributable to increased regulatory scrutiny. This change leads to a reduction in rating inflation and an increase in the number of unwarranted downgrades and false rating warnings in the post-regulatory period. A significant decrease (increase) in the informativeness of rating downgrades (upgrades) is evident. Our findings contrast with prior evidence for US corporates where reputational effects dominated.     

Shocks derived from mining windfalls and horizontal transfers: Exploring the permanent income hypothesis in Chilean municipalities from a spatial competition approach

We explore how spatial interaction affects the strategic use of municipal income when deciding between 1) an optimal long-run expenditure strategy versus 2) using the current income to finance current activities, a phenomenon known as the permanent income hypothesis. Even when this hypothesis is grounded in temporal logic, insufficient attention has been given to the impact of spatial dependence on this type of budget decision. Therefore, we present two reasons why spatial interaction adds new insight to this discussion. First, subnational governments located inside larger functional areas have lower average costs due to the population concentration, allowing for coordination between jurisdictions to achieve more power of negotiation and to potentially exploit economies of scale. Second, local government decision-making is not independent of other jurisdictions as municipalities would constantly evaluate the others’ actions regarding local tax effort, spending, and debt. While this spatial consideration remains a challenge for theoretical modeling, we offer empirical evidence to evaluate how robust the permanent income hypothesis is when geography is incorporated. Our empirical approach uses dynamic panel data with spatial dependence on debt, expenditure, and the error term. To evaluate our hypothesis, we exploit panel data from 320 Chilean municipalities between 2008 and 2020 and use two sources of income: non-matched grants via mining windfalls and horizontal fiscal transfers among cities. The evidence indicates that jurisdictions make backward-looking decisions regarding spending; that is, there are no significant differences between the short and long run. The results for debt, however, are not robust. Policy pertaining to the use of public resources should consider the spatial dependence between municipalities which should be a crucial factor in budgetary decision-making.     

不同管理处服务质量均值比较研究——以保利广州物业管理有限公司为例

在对保利广州物业管理有限公司六个管理处进行服务质量测评的过程中,我们采用多种统计方法,对不同管理处服务质量样本均值差异比较进行了假设检验,纠正了简单采用样本均值比较的错误,为物业管理服务质量测评工作提供了科学的方法。     

Diagnostic Tests for the Necessity of Weight in Regression With Survey Data

To weight or not to weight in regression analyses with survey data has been debated in the literature. The problem is essentially a tradeoff between the bias and the variance of the regression coefficient estimator. An array of diagnostic tests for informative weights have been developed. Nonetheless, studies comparing the performance of the tests, especially for finite samples, are scarce, and the theoretical equivalence of some tests has not been investigated. Focusing on the linear regression setting, we review a collection of such tests and propose enhanced versions of some of them that require an auxiliary regression model for the weight. Further, the equivalence of two popular tests is established which has not been reported before. In contrast to existing reviews with no empirical comparison, we compare the sizes and powers of the tests in simulation studies. The reviewed tests are applied to a regression analysis of the family expenditure using the data from the China Family Panel Study.     

碳交易试点政策对中国区域经济绿色增长的影响机制研究

碳排放权交易既是实现“双碳”目标的必然选择，也是推动中国区域经济绿色增长的重要途径。本文基于“波特假说”和新发展理念，探讨碳交易试点政策对中国区域经济绿色增长的影响机制。将试点政策作为一项准自然实验，基于2005—2018年中国内地30个省份面板数据（因数据缺失，不包括西藏和港澳台地区），采用双重差分模型进行实证检验。结果表明：(1)碳交易试点政策对中国区域经济绿色增长起显著促进作用，且存在正向累积动态效应，经过安慰剂检验和PSM-DID检验，发现结论依然成立。(2)碳交易试点政策对中国区域经济绿色增长的影响具有区域异质性，东部地区政策促进效应显著，而中部地区不显著，西部地区则呈现不明显的抑制效应。(3)机制研究表明，碳交易试点政策通过推动绿色技术创新、调整产业结构、优化能源结构、吸引外商直接投资以及促进共享发展以实现中国区域经济绿色增长。其中，共享发展的中介效应最大，其次为绿色技术创新和产业结构，而能源结构和外商直接投资的中介效应较小。(4)分区域机制检验发现，东部地区共享发展的中介效应最大，绿色技术创新和产业结构次之，能源结构的中介效应最小；中部地区中介效应最大为能源结构，其次为绿...