【CFRI 第十三卷 第1期】

CFRI · 2023年第一期

CFRI期刊2023年第1期共8篇文章，本期文章汇聚了来自中国、奥地利、巴基斯坦等国家的多位优秀学者的高质量论文，围绕“不可交易资产”、“全球股票市场”、“公共养老金”、“投资者情绪”以及“治理质量”等话题进行了深入的研究与探讨。扫描文中二维码可快速下载文章PDF全文，点击文末阅读原文，可以在线查看本期所有文章，感谢您对CFRI的关注与支持！

1

存在不可交易资产条件下的均衡投资组合

Equilibrium policy portfolios when some investors are restricted from holding certain assets

Otto Randl Vienna University of Economics and Business, AustriaArne Westerkamp IQAM Research Center, AustriaJosef Zechner Vienna University of Economics and Business, Austria

Abstract

The authors analyze the equilibrium effects of non-tradable assets on optimal policy portfolios. They study how the existence of non-tradable assets impacts optimal asset allocation decisions of investors who own such assets and of investors who do not have access to non-tradable assets. The study finds that the existence of non-tradable assets has a large impact on optimal asset allocation. Investors with (without) access to non-tradable assets tilt their portfolios of tradable assets away from (toward) assets to which non-tradable assets exhibit positive betas. The model provides important insights not only for investors holding non-tradable assets such as private equity but also for investors who do not have access to non-tradable assets. Investors who ignore the effect of non-tradable assets when reverse-engineering risk premia from asset covariances and market capitalizations might severely underestimate the equity risk premium. The authors provide the first comprehensive analysis of the equilibrium effects of non-tradability of some assets on optimal policy portfolios.

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2

COVID-19 期间全球股市的时间变化：动态网络分析

Temporal changes in global stock markets during COVID-19: an analysis of dynamic networksKashif ZaheerCOMSATS University Islamabad, PakistanFaheem AslamCOMSATS University Islamabad, PakistanYasir Tariq MohmandCOMSATS University Islamabad, PakistanPaulo FerreiraPolytechnic Institute of Portalegre, Portugal

Abstract

This study applies a dynamic network analysis approaches to evaluate the evolution over time of the impact of COVID-19 on the stock markets' network. Daily closing prices of 55 global stock markets from August 1, 2019 to September 10, 2020 were retrieved. This sample period was further divided into nine subsample periods for dynamic analysis purpose. Distance matrix based on long-range correlations was calculated, using rolling window's length of 100 trading days, rolled forward at an interval of one month's working days. The findings are, with the evolution of COVID-19, a change in co-movements amongst stock markets' indices occurred. On the 100th day from the date of reporting of the first cluster of cases, the co-movement amongst the stock markets become 100% positively correlated. However, the international investor can still get better portfolio performance with such temporal correlation structure either avoiding risk or pursuing profits.

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3

彩票偏好与股票市场参与: 来自中国的证据

Lottery preference and stock market participation: evidence from China
Tingting Zhang Hainan University, ChinaDesheng Wei Southwestern University of Finance and Economics, ChinaZhifeng Liu Hainan University, ChinaXihao Wu Hainan University, ChinaAbstractThis paper studies the effects of lottery preference on stock market participation at the macro level. The authors use the abnormal search volume intensity for lottery-related keywords from the Baidu search engine to capture retail investors' lottery preference. To measure stock market participation, they use five different macro-level measures from various angles. They perform the time series regression analysis in their empirical study. First, the validation tests show that the lottery preference index in this study is reasonable. Further, the authors find that lottery preference increases people's propensity to enter and trade in the stock market. Besides, they find that the effect on trading behavior is asymmetric, that is, high lottery preference has a more significant impact on trading behavior than low lottery preference. However, lottery preference has no significant effect on the stockholding. This paper contributes to the growing literature that examines the determinants of stock market participation and the role of lottery/gambling preference in the financial market.

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4

公共养老金与借贷行为: 来自中国农村的证据

Public pension and borrowing behavior: evidence from rural China

Conglong Fang Shanghai Jiao Tong University, ChinaQinghua Shi Shanghai Jiao Tong University, China
AbstractThe purpose of this paper is to investigate how China's rural public pension affects farmers' formal borrowing, which has always been rationed. This paper uses a difference-in-difference (DID) estimation to evaluate the effect of the implementation of the New Rural Pension Scheme (NRPS) at the end of 2009 on farmers' formal borrowing. The results show that the NRPS significantly reduces farmers' formal borrowing from rural credit cooperatives (RCCs). The effect is significant among the elderly, eastern China and high-income groups. This study contributes to the literature by identifying another potential reason for rural formal credit shortage. Policymakers and rural formal financial institutions should consider the demand side problem of lending.
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5

投资者关注度与绿色证券市场的动态互动：基于百度指数的实证研究

The dynamic interaction between investor attention and green security market: an empirical study based on Baidu index
Yang Gao Beijing University of Technology, ChinaYangyang Li Beijing University of Technology, ChinaYaojun Wang China Agricultural University, ChinaAbstractThis paper aims to explore the interaction between investor attention and green security markets, including green bonds and stocks. This study takes the Baidu index of “green finance” as the proxy for investor attention and constructs several generalized prediction error variance decomposition models to investigate the interdependence. It further analyzes the dynamic interaction between investor attention and the return and volatility of green security markets using the rolling time window. The empirical analysis and robustness test results reveal that the spillovers between investor attention and the return and volatility of the green bond market are relatively stable. In contrast, the spillover level between investor attention and the green stock market displays significant time-varying and asymmetric effects. Moreover, the volatility spillover between investor attention and green securities is vulnerable to major financial events, while the return spillover is extremely sensitive to market performance. The conclusion further expands the practical application and theoretical framework of behavioral finance in green finance and provides a new reference for investors and regulators.

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6

投资者情绪如何影响股票波动? 来自上海A股市场的新证据

How does investor sentiment impact stock volatility? New evidence from Shanghai A-shares marketDejun Xie Xi'an Jiaotong-Liverpool University, ChinaYu Cui Xi'an Jiaotong-Liverpool University, ChinaYujian Liu Xi'an Jiaotong-Liverpool University, ChinaAbstractThe focus of the current research is to examine whether mixed-frequency investor sentiment affects stock volatility in the China A-shares stock market. Mixed-frequency sampling models are employed to find the relationship between stock market volatility and mixed-frequency investor sentiment. Principal analysis and MIDAS-GARCH model are used to calibrate the impact of investor sentiment on the large-horizon components of volatility of Shanghai composite stocks. The results show that the volatility in Chinese stock market is positively influenced by B-W investor sentiment index, when the sentiment index encompasses weighted mixed frequencies with different horizons. Moreover, it is demonstrated that mixed-frequency sampling model has better explanatory powers than exogenous regression models when accounting for the relationship between investor sentiment and stock volatility. The findings of the current paper are of particularly scholarly and practical significance by shedding lights to the applicableness GARCH-MIDAS in the focused frontiers.
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7

在普惠金融和稳定的关系中，治理质量是否重要？

Does governance quality matter in the nexus of inclusive finance and stability?
Mallika Saha University of Barishal, Bangladesh; Zhongnan University of Economics and Law, ChinaKumar Debasis Dutta Patuakhali Science and Technology University, Bangladesh; Zhongnan University of Economics and Law, China
AbstractDespite numerous evidence of policy trade-off in financial inclusion-stability nexus, little is known about the role of governance quality to align policy goals and maximizing the social benefits. Therefore, to fill the gap, this study focuses to investigate the moderating effect of country governance (CG) in the interplay between financial-inclusion (FI) and financial-stability (FS), using a large panel of 84 economies covering the years 2004-2017. For attaining this objective, the study constructs several indexes for FI, FS and CG using principal component analysis (PCA) and examines how FI influences FS at different CG levels applying advanced econometrics. The results show that CG plays a very crucial role in eradicating the trade-off and strengthens the synergy between FI and FS.  The findings are insensitive to several robustness validations and could be constructive for policymakers to devise policies and to ensure financial stability.
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8

模型偏差在预测波动率中的作用: 来自美国股市的证据

The role of model bias in predicting volatility: evidence from the US equity marketsYan Li Southwest Jiaotong University, ChinaLian Luo Southwest Jiaotong University, ChinaChao Liang Southwest Jiaotong University, ChinaFeng Ma Southwest Jiaotong University, ChinaAbstractThe purpose of this paper is to explore whether the out-of-sample model bias plays an important role in predicting volatility. Under the heterogeneous autoregressive realized volatility (HAR-RV) framework, we analyze the predictive power of out-of-sample model bias for the realized volatility (RV) of the Dow Jones Industrial Average (DJI) and the S&P 500 (SPX) indices from in-sample and out-of-sample perspectives respectively. The in-sample results reveal that the prediction model including the model bias can obtain bigger R2, and the out-of-sample empirical results based on several evaluation methods suggest that the prediction model incorporating model bias can improve forecast accuracy for the RV of the DJI and the SPX indices. That is, model bias can enhance the predictability of original HAR family models. The author introduce out-of-sample model bias into HAR family models to enhance model capability in predicting realized volatility.
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关于 CFRI

China Finance Review International (CFRI) 作为上海交通大学安泰经济与管理学院创办的一本反映经济金融最前沿研究成果的全英文学术期刊，从创刊至今稳步发展。目前CFRI期刊已被二十多个权威数据库收录：Scopus、Web of Science 、ABI、CNKI、Google Scholar、Cabell's Dictionary、ProQuest、EBSCO、Summon、RePEc、Econlit，进入ABDC和Association of Business Schools' (ABS) Academic Journal Guide等一系列评级列表。目前期刊在Web of Science中的模拟影响因子为6.97；期刊在Scopus数据库中的实时CiteScore为6.8；2020年和2022年期刊均入选FMS管理科学高质量期刊列表，欢迎广大作者投稿，感谢大家对CFRI一路以来的关注和支持！

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