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Stock market and inequality distributions - Evidence from the BRICS and G7 countries

INTERNATIONAL REVIEW OF ECONOMICS & FINANCE 2024年 92卷 1172-1190页

作者： Dang, Dong Quang Wu, Weiou Korkos, Ioannis London South Bank Univ Business Sch Div Finance Econ Accounting & Analyt 103 Borough Rd London SE1 0AA England

By examining the effects of three stock market indicators (market accessibility, efficiency, and stability) on income and wealth inequality in the BRICS and G7 countries, this study enriches lacking literature on income and wealth inequality, particularly for the BRICS countries. We apply the Autoregressive Distributed Lag-mixed data sampling (ADL-MIDAS) model. We find that only enhancements in market stability reduce income inequality in the BRICS and G7 countries. Additionally, we find that while expansions of market accessibility contribute to narrowing wealth inequality, improvements in market stability widen the wealth disparity in the BRICS countries. Limited effects of the stock market indicators on wealth distribution are observed in the G7 countries.

关键词： mixed data sampling Income inequality Wealth inequality Stock market Autoregressive distributed lag BRICS G7

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Predicting Financial Distress Using a MIDAS Hazard Model: Evidence from Listed Companies in China

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EMERGING MARKETS FINANCE AND TRADE 2023年第4期60卷 678-687页

作者： Li, Xiangrong Zhang, Maojun Nan, Jiangxia Yang, Qingyuan Guangxi Univ Sch Econ Nanning Peoples R China Suzhou Univ Sci & Technol Sch Business Suzhou Peoples R China Nanning Coll Vocat Technol Sch Finance & Econ Nanning Peoples R China Suzhou Univ Sci & Technol Sch Business Xuefu Rd 99 Suzhou 215009 Peoples R China

This study aims to predict financial distress in an emerging country using data on ST listed companies in China from 2001 to 2021. A new Aalen hazard model with mixed data sampling (MIDAS) is adopted to investigate the impact of monthly macroeconomic variables and quarterly financial variables on financial distress. The empirical results show that the current ratio, operating profit ratio, current capital ratio, retention ratio, profit ratio and income ratio of listed companies have a significant impact on the time-varying intensity of financial distress. The consumer price index has a negative relation with the intensity of financial distress, while the production price index and credit spreads have a positive influence. Finally, the results of the robustness tests are consistent with those with different lag orders.

关键词： Financial distress Aalen model mixed data sampling special treatment C52 G32 G33

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mixed frequency composite indicators for measuring public sentiment in the EU

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Quality and Quantity 2023年第3期57卷 2357-2382页

作者： Mattera, Raffaele Misuraca, Michelangelo Spano, Maria Scepi, Germana Department of Social and Economic Sciences Sapienza University of Rome Rome Italy Department of Economics and Statistics University of Naples “Federico II” Naples Italy Department of Business Administration and Law University of Calabria Rende Italy

Monitoring the state of the economy in a short time is a crucial aspect for designing appropriate and timely policy responses in the presence of shocks and crises. Short-term confidence indicators can help policymakers in evaluating both the effect of policies and the economic activity condition. The indicator commonly used in the EU to evaluate the public opinion orientation is the Economic Sentiment Indicator (ESI). Nevertheless, the ESI shows some drawbacks, particularly in the adopted weighting scheme that is static and not country-specific. This paper proposes an approach to construct novel composite confidence indicators, focusing on both the weights and the information set to use. We evaluate these indicators by studying their response to the policies introduced to contain the COVID-19 pandemic in some selected EU countries. Furthermore, we carry out an experimental study where the proposed indicators are used to forecast economic activity. © 2022, The Author(s).

关键词： Composite indicator Confidence indicator Media sentiment mixed data sampling Public opinion

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Forecasting VIX with time-varying risk aversion

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INTERNATIONAL REVIEW OF ECONOMICS & FINANCE 2023年 88卷 458-475页

作者： Wu, Xinyu He, Qizhi Xie, Haibin Anhui Univ Finance & Econ Sch Finance Bengbu 233030 Peoples R China Zhejiang Gongshang Univ Sch Stat & Math Hangzhou 310018 Peoples R China Univ Int Business & Econ Sch Banking & Finance Beijing 100029 Peoples R China

In this paper, we investigate the predictive value of time-varying risk aversion (RA) for VIX via the realized EGARCH-mixed-data sampling model incorporating RA (henceforth REGARCHMIDAS-RA). The REGARCH-MIDAS-RA model builds on the REGARCH model, which takes into account the high-frequency information by including the realized measure of volatility. Moreover, the model provides a convenient framework to model the long-run variance, which responds to changes in RA. We obtain the risk-neutralization of the REGARCH-MIDAS-RA model and derive the model-implied VIX formula. Our empirical results show that realized measure and RA possess predictive value for VIX. The REGARCH-MIDAS-RA model yields more accurate VIX forecasts compared to a range of competing models, including the GARCH, GJR-GARCH, nonlinear GARCH, EGARCH, REGARCH and REGARCH-MIDAS. In summary, our findings highlight the importance of incorporating the realized measure as well as RA in forecasting VIX.

关键词： VIX forecasting Time-varying risk aversion Realized EGARCH mixed data sampling Realized measure

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Deep factor asset pricing with policy guidance based on multi-source heterogeneous information

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APPLIED SOFT COMPUTING 2024年 159卷

作者： Wang, Zezhou Xu, Qifa Jiang, Cuixia Hefei Univ Technol Sch Management Hefei 230009 Anhui Peoples R China Minist Educ Key Lab Proc Optimizat & Intelligent Decis Making Hefei 230009 Anhui Peoples R China Minist Educ Engn Res Ctr Intelligent Decis Making Hefei 230009 Peoples R China

We propose a novel latent factor pricing model to extract latent pricing factors and corresponding factor loadings from multi -source heterogeneous information through a deep learning architecture. Notably, we pioneer the extraction of policy pricing factors from China's national strategies ("Five -Year Plans", "Government Work Reports", and "Monetary Policy Reports") using natural language processing and a dynamic topic model. The proposed mixed -frequency deep factor asset pricing (MIDAS-DF) model learns from mixed -frequency heterogeneous data and captures nonlinear joint patterns between inputs and outputs, providing more nuanced insights into asset pricing. The empirical analyses of the Chinese A -share market from January 1, 2003 to July 31, 2022 show that the MIDAS-DF model outperforms competing models in pricing individual stocks, various test portfolios, and investment portfolios. The results also demonstrate that low -frequency policy information anchors long-term pricing trends, while high -frequency market and sentiment information refine short-term pricing accuracy. They work together to enhance the pricing performance.

关键词： Asset pricing Multi-source heterogeneous information Policy guidance mixed data sampling Deep learning Latent factor model

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Dynamic panels with MIDAS covariates: Nonlinearity, estimation and fit

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JOURNAL OF ECONOMETRICS 2021年第2期220卷 589-605页

作者： Khalaf, Lynda Kichian, Maral Saunders, Charles J. Voia, Marcel Carleton Univ Econ Dept Ottawa ON Canada Carleton Univ Ctr Monetary & Financial Econ CMFE Ottawa ON Canada Ctr Interuniv Rech Econ Quantitat CIREQ Montreal PQ Canada Univ Ottawa Econ Dept Ottawa ON Canada Univ Ottawa Grad Sch Publ & Int Affairs Ottawa ON Canada Univ Western Univ Dept Econ London ON Canada Univ Orleans Orleans France

This paper introduces mixed data sampling (MIDAS) into the panel data context. To address the unidentified nuisance parameter problem, we propose to invert model specification tests for inference on the MIDAS parameter along with bounds tests for model coefficients. Illustrative identification, simulation and empirical analyses are conducted in the dynamic GMM framework. Our framework allows for departures from i.i.d errors such as clustering and dynamic specifications. A simulation study and an application to a model of reserve holdings illustrate the usefulness of the proposed methods, and more broadly set a promising template for shrinkage approaches. (c) 2020 Elsevier B.V. All rights reserved.

关键词： Dynamic panel model mixed data sampling Unidentified nuisance parameter Reserve holdings model

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Economic policy uncertainty, jump dynamics, and oil price volatility

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ENERGY ECONOMICS 2023年第1期120卷

作者： Liu, Feng Shao, Shuai Li, Xin Pan, Na Qi, Yu Hubei Univ Econ Inst Adv Studies Finance & Econ Wuhan 430205 Peoples R China East China Univ Sci & Technol Sch Business Shanghai 200237 Peoples R China Zhejiang Gongshang Univ Sch Econ Hangzhou 310018 Peoples R China Zhongnan Univ Econ & Law Sch publ Finance & Taxat Wuhan 430073 Hubei Peoples R China

Although the underlying forces behind oil price volatility have attracted the attention of scholars, a clear consensus is yet to be achieved on how to quantify the contributions of economic policy uncertainty (EPU) and jump dynamics simultaneously. This paper develops a joint EGARCH-MIDAS-ARJI model to address this issue and break the obstacle of mixed data sampling. To avoid the effect of political and business cycles, all EPU indices are detrended using the Hodrick Prescott (HP) filter. The results show that oil price volatility is adversely associated with EPU. As large EPU values imply that policymakers are trying to make some beneficial efforts, this finding challenges the neoclassical opinion that policy intervention is a source of market fluctuation. We also find that the US policy intervention can reduce only less than 6% of oil price volatility, while the effects of China's economic policy are even weaker. More importantly, jump dynamics still account for a remarkable percentage in oil price volatility, especially during lower volatility periods. Possible explanations are that policy makers only respond to large persistent oil price volatility, while the targets and actions of oil-importing countries and oil-exporting countries are also converse in most cases.

关键词： Oil price volatility Economic policy uncertainty Jump dynamics mixed data sampling China US

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Technology shocks-Gold market connection: Is the effect episodic to business cycle behaviour?

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RESOURCES POLICY 2023年第1期84卷

作者： Ayinde, Taofeek O. Olaniran, Abeeb O. Abolade, Onomeabure C. Ogbonna, Ahamuefula Ephraim Fountain Univ Dept Econ Osogbo Osun Nigeria Ctr Econometr & Appl Res Ibadan Nigeria Cent Bank Nigeria Dept Stat Abuja Nigeria Univ Ibadan Dept Stat Ibadan Nigeria Ctr Econometr & Appl Res Ibadan Nigeria

We explore the connection between technology shocks (TS) and gold return volatility using the various variants of the newly developed TS data and covering several decades from 1950. The consideration for a long range of data affords us to test whether or not the nexus is sensitive to business cycle dynamics. We employ the GARCHMIDAS framework to establish the connection owing to the mixed data frequencies of the variables of interest. Overall, we find that technological innovations drive higher volatilities in the gold market from a long term perspective. Examining the role of business cycles in the nexus, we partition the analyses into expansion and recession periods. Consequently, we show that the role of business cycles is indeed crucial as the TS increase the level of gold volatility during the period of expansion relative to the period of recession. This justifies that improvements in the economy may further stimulate technological innovations, and by extension, enhance the trading activity in the gold market. Finally, we also demonstrate the forecast gains of including the TS in the predictive model of gold volatility rather than subsuming it in the (aggregate) market risk. Our results are robust to multiple out-of-sample forecast horizons and alternative measures of gold returns, and technology shocks.

关键词： Technology shock Business cycle Gold market Volatility mixed data sampling GARCH-MIDAS Forecasting analysis

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mixed frequency evidence of the tourism growth relationship in small Island developing states: a case study of Tonga

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ASIA PACIFIC JOURNAL OF TOURISM RESEARCH 2021年第3期26卷 294-307页

作者： Kumar, Nikeel Nishkar Chandra, Ravinay Amit Patel, Arvind Univ South Pacific Fac Business & Econ Sch Accounting & Finance Suva Fiji Univ Fiji Sch Business & Econ Dept Management Saweni Fiji

In this study, we examine the effect of tourism on economic growth in Tonga. We apply Ghysels Beta-MIDAS approach to estimate the elasticity of tourism, identify breaks with the multiple break test, and test for causality using the mixed frequency VAR approach. We utilize a sample from 1995 quarter 1 to 2018 quarter 4. The results indicate that the long-run effect of tourism is 0.06. Two structural breaks are identified, and both have negative growth effects. Unidirectional causality from tourism to real per-capita GDP is noted. The findings indicate that Tonga's economic growth can be improved by promoting tourism.

关键词： Tourism led growth hypothesis tourism development seasonality and quarterly data mixed data sampling mixed frequency cointegration and causality airline and cruise-ship arrivals structural breaks small island developing states Asia Pacific region Tonga

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Daily currency interventions in an emerging market: Incorporating reserve accumulation to the reaction function

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ECONOMIC MODELLING 2021年 97卷 461-476页

作者： Frommel, Michael Midilic, Murat Univ Ghent Dept Econ Sint Pieterspl 5 B-9000 Ghent Belgium

Understanding the intervention policy of central banks on currency markets is important for both practitioners and researchers. Existing models for central bank interventions exclusively focus on exchange rate targeting in level or volatility. However, central banks in emerging economies use international reserves as an insurance against sudden capital outflows and use interventions to manage them. Omitting the reserve component in the reaction function may therefore lead to a bias and wrong conclusions. We therefore extend the reaction function by incorporating a reserve component and illustrate its benefit by applying it to the case of Turkey. We find that the intervention policy of the Turkish Central Bank indeed incorporated interventions to manage their reserves and is therefore better described by our extended model. Furthermore it provides a more accurate description of changes in the central bank?s policy. Our results strongly suggest to incorporate reserve variables in intervention functions for emerging countries.

关键词： Currency intervention International reserves Emerging markets Turkey mixed data sampling

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