On the predictive power of ARJI volatility forecasts for Bitcoin

Motivated by the recent literature on cryptocurrency volatility dynamics, this paper adopts the ARJI, GARCH, EGARCH, and CGARCH models to explore their capabilities to make out-of-sample volatility forecasts for Bitcoin returns over a daily horizon from 2013 to 2018. The empirical results indicate that the ARJI jump model can cope with the extreme price movements of Bitcoin, showing comparatively superior in-sample goodness-of-fit, as well as out-of-sample predictive performance. However, due to the excessive volatility swings on the cryptocurrency market, the realized volatility of Bitcoin prices is only marginally explained by the GARCH genre of employed models.     

What drives the Bitcoin price? A factor augmented error correction mechanism investigation

This article aims to determine what drives the price of Bitcoin. To achieve this aim, a large set of data is analysed using VEC models augmented by factors representing unobservable economic forces. They have been obtained by means of principal component analysis. This method enables us to contribute to the existing literature on Bitcoin in two ways. First, we employ the dimension reduction technique to combine variables from several papers. Second, we estimate several unobservable economic concepts instead of utilizing proxy variables as is usually done. We find that the main factor driving the Bitcoin price is its popularity. Hence, our result not only confirms some previous findings but reinforces them by providing a better definition of popularity. Finally, we conclude that the Bitcoin price is not affected by supply and demand factors in the way that is natural for conventional currencies.     

Some stylized facts of the cryptocurrency market

We examine the stylized facts of eight forms of cryptocurrencies representing almost 70% of cryptocurrency market capitalization. In particular, the empirical results show that (1) there exists heavy tails for all the returns of cryptocurrencies; (2) the autocorrelations for returns decay quickly, while the autocorrelations for absolute returns decay slowly; (3) returns of cryptocurrencies display strong volatility clustering and leverage effects; (4) Hurst exponent for volatility is more volatile than that of the returns, while they all suggest the long-range dependence phenomena; and (5) there exists power-law correlation between price and volume.     

我国实施中小企业集群战略的研究

企业集群现象与“中国制造”受到越来越多的关注,如何理解企业集群化成长对中国工业化的有效性,关键在于全面认识企业集群效应的现实经济意义。本文认为,企业集群对于提升我国制造业的国际竞争力、加快外向型经济的发展、推动企业组织网络化、促进中小企业的发展以及实现农村工业化等方面具有重要的作用。我国发挥企业集群效应需要应对经济全球化和自由贸易的挑战、加快集群化成长、提高集群技术创新能力和培育产业文化环境等战略性问题。     

Irving Fisher's debt deflation analysis: From the Purchasing Power of Money (1911) to the Debt-deflation Theory of the Great Depression (1933)

Abstract

In 1933, Irving Fisher proposed an explanation for the Great Depression based on the distinction between the price level and price change effect of deflation in a context of over-indebtedness. This paper compares the debt-deflation theory of Fisher (1933 Fisher, I., 1933. The debt-deflation theory of great depressions, Econometrica 1 (1933), pp. 337–57. DOI: 10.2307/1907327[Crossref], [Web of Science ®] , [Google Scholar]) with the dynamic depression process he had expounded almost 20 years earlier in the Purchasing Power of Money (1911). The role played by both price level and price change effects in the analyses of Fisher (1933, 1911) are clarified in the context of the disequilibrium model of Tobin (1975 Tobin, J., 1975. Keynesian models of recession and depression, American Economic Review 65 (1975), pp. 195–202.[Web of Science ®] , [Google Scholar]). More precisely, we show that the stationary equilibrium is assumed to be locally unstable according to Fisher's 1911 insights and globally unstable according to his 1933 analysis.     

我国股市涨跌幅限制日内效应的实证研究

本文利用我国沪市ST股和普通股的5分钟高频数据对我国股市涨跌幅限制的效应进行分析。结果表明,虽然普通股和ST股在接近涨跌幅限制时均存在趋势反转现象,但普通股10％的涨跌幅限制存在一定的磁吸效应,而ST股5％的涨跌幅限制不存在磁吸效应。这与国外其他研究以及国内基于其他方法得出的研究结论存在差异。本文的分析还说明,国内所谓涨跌幅限制的冷却效应只是股价正常的均值回复,与涨跌幅限制制度无关。     

我国畜产品价格波动分析——基于ARCH类模型

运用ARCH类模型对我国主要畜产品的价格波动率进行了分析。结果表明:牛肉、羊肉和鸡肉的价格波动具有显著的波动积聚性,鸡蛋价格波动没有显著的异方差效应;除牛肉市场外,羊肉和鸡肉市场不具有高风险、高回报的特征;猪肉、牛肉、羊肉和鸡肉的价格波动没有非对称性。认为应在畜产品市场出现大的价格波动时及时采取平抑措施,且政府需规范畜产品市场秩序、完善畜产品市场制度。     

Can Bitcoin become money? The monetary rule problem

The growing literature on Bitcoin can be divided into two groups. One performs an economic analysis of Bitcoin focusing on its monetary characteristics. The other one takes a financial look at the price of Bitcoin. Interestingly, both of these groups have not given much more than passing comments to the problem of whether or not Bitcoin has the right monetary rule in order to become a well‐established currency. This paper argues that Bitcoin in particular, and cryptocurrencies in general, do not have a good monetary rule and that this shortcoming seriously limits its prospect of becoming widely used money.     

高校扩招改善了收入不平等吗？

高校扩招对城镇居民收入产生的变化与影响,是个需要深入研究的问题。在2002年和2008年中国居民收入项目（ CHIP）数据的基础上,使用RIF分布分解法离析出高校扩招的禀赋效应与价格效应,基于RIF回归的实证研究结果表明：高校扩招的禀赋效应与价格效应都在一定程度上扩大了城镇居民收入不平等;城镇居民收入不平等扩大主要是由上侧分位数与下侧分位数之差拉大造成的;教育回报率与城镇居民收入在样本期内呈“马太效应”。     

贸易开放、不完全竞争与成本加成——基于中国制造业数据的实证分析

文章利用中国制造行业的面板数据,分析贸易开放对我国国内行业成本加成的影响。回归结果表明,市场竞争与国际贸易是影响我国制造行业成本加成的重要因素。进口贸易在高竞争性行业对成本加成具有正向的促进效应,而在低竞争性行业具有相反的效应;出口贸易对国内行业的成本加成具有显著的正向促进效应。