Why cryptocurrency markets are inefficient: The impact of liquidity and volatility

In this research, we study the multifractality, long-memory process, and efficiency hypothesis of six major cryptocurrencies (Bitcoin, Ethereum, Monero, Dash, Litecoin, and Ripple) using the time-rolling MF-DFA approach. For an in-depth analysis, this study uses the quantile regression approach to examine the determinants of efficient markets. The results show that all markets present evidence of long-memory property and multifractality. Furthermore, the inefficiency of cryptocurrency markets is time-varying, and Dash is the least inefficient market while Litecoin is the most inefficient. Finally, we find that higher liquidity improves but higher volatility weakens the efficiency of cryptocurrencies, depending on the quantiles. Therefore, we conclude that high liquidity with low volatility helps active traders to arbitrage away opportunities, resulting in market efficiency.     

新疆棉农残膜回收行为影响因素及实证研究*——基于棉农的调研数据

［目的］为响应农业农村部“农业绿色发展五大行动”，加强农业面源污染防治，缓解新疆棉田残膜危害，基于新疆棉农的问卷调查研究棉农的残膜回收行为。［方法］采用描述性统计和Logistic回归模型分析影响新疆棉农残膜回收行为的因素。［结果］（1）新疆农用地膜回收率低，地膜污染形势严峻。（2）棉农对残膜危害认知缺乏，对残膜回收的间接价值认识不足，影响新疆残膜回收效率。（3）残膜回收的成本收益是影响棉农残膜回收行为的关键因素，其他如棉农年龄、种棉年限、对残膜危害的认知等自身特征，以及农户劳动力数量、政府对残膜污染的关注程度等因素对棉农的残膜回收行为有重要影响。［结论］网络及电视广播等现代媒体对棉农的残膜危害认知水平有较大影响，棉农更愿意采用成本更节约的焚烧、堆地的残膜处理方式。因此提出引导棉农残膜回收、提高棉田残膜回收效率的对策建议。     

The time‐varying performance of UK analyst recommendation revisions: Do market conditions matter?

This study examines the time‐varying performance of investment strategies following analyst recommendation revisions in the UK stock market, with specific emphasis on the impact of changing market conditions. We find a negative relationship between the recommendation performance and market conditions as measured in terms of past market return and market volatility. In particular, the upgrade (downgrade) portfolio generates significantly positive (negative) net abnormal returns in bad market conditions (e.g., the dot‐com bubble burst in 2000 and the credit crisis in 2007), but not in other periods of time. Moreover, our non‐temporal threshold regression analysis shows that the reported negative relationship disappears when market conditions become better, i.e., when the past market return (market volatility) is higher (lower) than a certain level, indicating the importance of taking non‐linearity into account in the long sample period as examined in this study. Our time‐series bootstrap simulations further confirm that the superior recommendation performance in bad market conditions is not due to random chance; analysts have certain skills in making valuable up/downward revisions in bad markets.     

利用频移动态特征的辐射源目标盲分选

利用辐射源目标的频移动态特征进行盲分选时，针对已有的分选方法不能很好解决非合作接收数据非周期、间断、交叠的问题，提出了一种改进的逻辑回归分选算法,将信号分选转化为轨迹分类的问题来处理。首先，借鉴多目标航迹起始模型中的M/N逻辑法的框架，设计新的数据关联门限，以建立目标起始曲线；其次，采用最小二乘拟合方法替代卡尔曼滤波，设计新的外推规则，建立载频变化预测曲线；分析新的接收数据与预测曲线的关联性，不断迭代回归或形成新的分支，最后获得目标分选结果。仿真与实测试验表明，利用逻辑回归分选算法，对不同运动目标搭载的同频辐射源可进行自动分选，4个仿真目标与2个真实目标的分选正确率达到100%。同时，该方法拓展了辐射源目标盲分选中的动态频移特征应用，为辐射源个体识别提供了新的支持。     

Measuring extreme risk spillovers across international stock markets: A quantile variance decomposition analysis

This paper proposes a quantile variance decomposition framework for measuring extreme risk spillover effects across international stock markets. The framework extends the spillover index approach suggested by Diebold and Yilmaz (2009) using a quantile regression analysis instead of the ordinary least squares estimation. Thus, the framework provides a new tool for further study into the extreme risk spillover effects. The model is applied to G7 and BRICS stock markets, from which new insights emerged as to the extreme risk spillovers across G7 and BRICS stock markets, and revealed how extreme risk spillover across developed and emerging stock markets. These findings have important implications for market regulators.     

Factors Influencing Organic and Fair Trade Coffee Growers Level of Engagement with Cooperatives: The Case of Coffee Farmers in Mexico

We study the factors influencing the percentage of organic and fair trade certified coffee sold through a cooperative by growers of five cooperatives in Mexico. The percentage of coffee sold through the cooperative was used as a proxy of growers’ engagement with a cooperative. Using factor analysis and a fractional probit regression, we evaluated the proposition that the level of engagement can be explained by transaction cost economics, social norms and connections, and farmer and farm business characteristics. We found that farm size, uncertainty regarding cooperative time of payment to the members and cooperative commitment on price to be paid negatively influence the level of engagement. In contrast, asset specificity, relational commitment, and price have a positive impact on engagement. Our results may help cooperatives and policy makers to build strategies aiming to increase this level of engagement. This is relevant because lower grower engagement has been found to be positively correlated with weak performing cooperatives.     

Evaluating the efficiency of Korean festival tourism and its determinants on efficiency change: Parametric and non-parametric approaches

Local festivals may leverage local specialties and various historical, cultural, and artistic resources throughout their respective regions to attract tourists, inducing positive economic impacts. In this study, this paper is a first attempt to analyze the relative efficiency of local festival tourism by using parametric and non-parametric approaches with the data from local festivals held in Korea from 2015 to 2018. We also deal with the efficiency determinants of each typology of festivals by employing a truncated regression with double bootstrapping. Results showed that the leading sources of inefficiency were primarily embedded in pure technology inefficiency, while the principal operational drivers posed different effects depending on the typology of festivals. These insights have important practical implications for the local festival organizing committees and operators in Korea and are helpful in developing tailored operational strategies to maximize the efficiency among different typologies of festivals.     

Does the Reserve Bank of Australia follow a forward-looking nonlinear monetary policy rule?

ABSTRACT

The conventional monetary policy rule describes a simple linear relationship between the domestic interest rate, inflation rate and output gap. An important extension to this rule is to incorporate the forward-looking behaviour of central banks, where it is assumed that they target an expected level of inflation instead of its current realised value. Using quarterly observations for the period 1993:1-2018:2, this paper investigates whether the conduct of monetary policy in Australia can be described by a forward-looking linear monetary policy rule, or by a nonlinear forward-looking monetary policy rule. In particular, the nonlinear forward-looking monetary policy rule is analysed in a regime-switching framework using a smooth logistic transition regression model. While the results show that the conventional forward-looking linear monetary policy rule describes the application of monetary policy in Australia reasonably well, the interest rate setting behaviour of the RBA is best described by a nonlinear forward-looking monetary policy rule.     

数字普惠金融对地方税收影响的实证研究

采用北京大学测度的2011—2018年数字普惠金融指数与地方税收面板数据，研究了数字普惠金融发展与地方税收之间的关系。研究发现，数字普惠金融能够显著地促进地方税收增长，在考虑了内生性等因素后，这一结论仍然稳健地成立。分位数回归表明，数字普惠金融在低分位数上对地方税收影响小且统计显著性弱，在高分位数上数字普惠金融对地方税收的影响大且统计显著性强。数字普惠金融对地方税收的影响存在门槛效应，在不同发展阶段，其对地方税收影响有显著差异。数字普惠金融促进税收增长主要是通过数字普惠金融覆盖广度提高和移动化、便利化等程度加深实现的。     

丝绸之路河西走廊物流业效率演化分析

构建了分析河西走廊物流业效率演化的指标体系,基于2009-2017年河西走廊物流业统计数据,运用DEA-Malmquist指数法测算了各市物流业效率和技术进步率,采用Tobit回归模型分析了该地区物流业效率的影响因素,并从省内、省域间、各经济区域间三个方面进行了对比分析。实证分析表明,相较于全国各省市地区,河西走廊物流业整体水平较低,物流业效率和技术进步率的强正相关性普遍存在,其物流业发展对政策偏向具有较强的依赖性;同时,技术进步率低下和基础设施匮乏也是制约物流业发展的重要因素。基于此,从政策照顾与资金投入、科技进步与管理水平和市场运营与体系建设三个方面,为河西走廊物流业发展提出了建议与改善措施。