{"title":"Characterizing India’s Financial Cycle","authors":"Harendra Behera, Saurabh Sharma","doi":"10.1177/09726527221077727","DOIUrl":"https://doi.org/10.1177/09726527221077727","url":null,"abstract":"The severity of the effects of global financial crisis resuscitates the need for assessing the macro-financial linkages and measuring financial cycle to prevent the economy from major financial shocks. Our article measures financial cycle by using turning point analysis, spectral analysis and band-pass filter and provides the evidence on the existence of financial cycle in India. We find the length and duration of cycles in financial variables are much greater as compared to the business cycle. While both credit and equity prices drive financial cycles over time, the contribution of house prices has increased since mid-2000s. We find that the expansionary phase of the financial cycle provides an early warning signal about stress build-up in the banking sector and impending depress in the economy. JEL Codes: C22, E30, E44, E58, G18","PeriodicalId":44100,"journal":{"name":"Journal of Emerging Market Finance","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49585761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Corruption, Chinese Investment, and Trade: Evidence from Africa","authors":"V. Tawiah, J. Kebede, Anthony K. Kyiu","doi":"10.1177/09726527221073981","DOIUrl":"https://doi.org/10.1177/09726527221073981","url":null,"abstract":"We investigate whether corruption in host countries drives the different routes of Chinese economic engagement with Africa. Using data from 49 African countries for 2000–2018, we find that corruption affects each route of China’s engagement with Africa differently. Corruption in Africa is significantly negatively associated with FDI from China, but significantly positive with both trade and construction. These relationships are moderated by the availability of natural resources but do not change after the implementation of the Xi Jinping anti-corruption campaign. By disaggregating China–Africa financial engagement into its different routes, we demonstrate that the relationship between corruption and China’s presence in Africa varies with the nature of the engagement. JEL Codes: F21, F23","PeriodicalId":44100,"journal":{"name":"Journal of Emerging Market Finance","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49381344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Viswanathan, Sandeep Srivathsan, Wayne L. Winston
{"title":"Multiclass Discriminant Analysis using Ensemble Technique: Case Illustration from the Banking Industry","authors":"P. Viswanathan, Sandeep Srivathsan, Wayne L. Winston","doi":"10.1177/09726527211070947","DOIUrl":"https://doi.org/10.1177/09726527211070947","url":null,"abstract":"Linear discriminant analysis (LDA) has found extensive application in predicting bankruptcy. In this article, we elucidate a novel modelling approach for LDA that can also aid in gaining useful insights regarding the relative importance and ranking of factors in the banking industry. The model steers away from the traditional computation of the variance/covariance matrix and employs an ensemble technique to assign records to classes. The efficacy of our model is tested using two datasets. Specifically, a large dataset from the banking industry was partitioned into the testing and training datasets, and an accuracy of 87.9% was achieved JEL Codes: C38, G33","PeriodicalId":44100,"journal":{"name":"Journal of Emerging Market Finance","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45933128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Can Equity be Safe-haven for Investment?","authors":"Janani Sri, P. Kayal, G. Balasubramanian","doi":"10.1177/09726527211068411","DOIUrl":"https://doi.org/10.1177/09726527211068411","url":null,"abstract":"Popular investment choices such as fixed income, gold, and real estate have generated low returns over long horizons. Equity seems to have performed much better despite its inherent risk. Although, investors prefer safe-haven assets, they are increasingly moving to equities in search for better returns. We consider whether equity could be a safe-haven investment if chosen from quality stocks’ basket. We examine the safe-haven and hedging properties of the Nifty-50 constituent stocks over the period 2008–2020. To address this, we employ copula-based framework to model the dependence structure between stocks and five indices. We distinguish between safe-haven attributes and hedging features of the individual stocks. We show that the safe-haven properties of the Nifty-50 listed stocks are not as concentrated as gold but they show much low co-movement with the market. We call them pseudo–safe-haven as they are the safe-bets for investors seeking relatively safe-haven assets with impressive returns. JEL Codes: G11, G12, G15","PeriodicalId":44100,"journal":{"name":"Journal of Emerging Market Finance","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47111519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Dynamic Impacts of Economic Policy Uncertainty on Australian Stock Market: An Intercontinental Evidence","authors":"R. K. Bairagi","doi":"10.1177/09726527211069610","DOIUrl":"https://doi.org/10.1177/09726527211069610","url":null,"abstract":"This study empirically investigates the impacts of economic policy uncertainty (EPU) of five countries from four continents on the Australian stock market with monthly observations from January 1998 to January 2021. The dynamic linkage model reports that EPUs are negatively influenced by their own lagged effect along with bidirectional volatility spillover and the returns of stock markets unidirectionally spillover to the EPU of the corresponding economy. The study documents that shocks originated in the Australian stock market spillover negatively onto its own EPU and that of China and positively onto EPUs of Europe and Japan. The shocks originated in EPUs of Australia, Europe, China, and Japan significantly negatively impact the Australian stock market. The bidirectional volatilities of EPUs can offer insight for portfolio investors in searching the possible hedging opportunities in Australia. The reported drivers of Australian EPU can be incorporated in formulating and implementing the EPU-sensitive Australian trade policies. JEL: G15, G17, G18","PeriodicalId":44100,"journal":{"name":"Journal of Emerging Market Finance","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47571919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Central Bank Communications and Professional Forecasts: Evidence From India","authors":"A. Goyal, Prashant Parab","doi":"10.1177/09726527211044056","DOIUrl":"https://doi.org/10.1177/09726527211044056","url":null,"abstract":"We analyze the influence of qualitative and quantitative communications of the Reserve Bank of India (RBI) on inflation expectations of professional forecasters and draw out implications for policy. Estimating Carroll-type epidemiological models of expectation formation under information rigidities, we get a large speed of adjustment of professional forecasters’ expectations. Analysis of the determinants of inflation forecasts, inflation surprises, and forecaster disagreement reveals significant influence of quantitative RBI communications in the form of inflation projections. This effect is prominent for shorter-horizon forecasts and after adoption of flexible inflation targeting. Macroeconomic fundamentals like lagged inflation and repo rate also significantly influence inflation forecasts. Choice of words in the RBI monetary policy statements has more impact after October 2016, when the monetary policy committee became the decision-making body. JEL Classification: E31, E52, E58","PeriodicalId":44100,"journal":{"name":"Journal of Emerging Market Finance","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2021-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47171095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Competition and Banking Industry Stability: How Do BRICS and G7 Compare?","authors":"Abayomi Oredegbe","doi":"10.1177/09726527211045759","DOIUrl":"https://doi.org/10.1177/09726527211045759","url":null,"abstract":"This study examines banking industry stability in BRICS and G7 from the period 2005 to 2014. The results show that stability level in a prior period affects stability in the subsequent period. Also, the study reveals that competition improves stability, which validates the competition-stability proposition. Economic growth enhances stability in BRICS but not in G7. Inefficiency weakens stability in BRICS; however, its impact in G7 is insignificant. Profitability, capitalization, and inflation enhance stability in G7; however, they show no meaningful impacts in BRICS. These findings contribute to literature and policy discussion on banking industry stability JEL Codes: G21, G28, G32, L11","PeriodicalId":44100,"journal":{"name":"Journal of Emerging Market Finance","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47478963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Nonlinearity in Global Crude Oil Benchmarks: Disentangling the Effect of Time Aggregation","authors":"George Varghese, V. Madhavan","doi":"10.1177/09726527211043013","DOIUrl":"https://doi.org/10.1177/09726527211043013","url":null,"abstract":"We model the first and second moments of global crude oil benchmarks, using iterative pre-whitened generalized autoregressive conditional heteroskedasticity (GARCH) models and, in doing so, validate the efficacy of such models in assimilating the neglected nonlinearities in the underlying data-generating processes. The benchmarks considered for this study are Brent, Dubai/Oman, and West Texas Intermediate (WTI) crude oil. While nonlinear serial dependence happens to be a stylized fact across different asset classes, it is our view that prior scholarly contributions have not adequately untangled the effect of data aggregation (in time) in the examination of nonlinear dependencies. In this context, the present study strives to untangle the critical role that time aggregation plays in the examination of nonlinearity in global crude oil benchmarks using data at daily, weekly as well as monthly time frequencies. Our findings are as follows: the optimum GARCH models perform well in capturing all of the neglected nonlinearity in monthly returns of the crude benchmarks. When it comes to daily and weekly returns, our study reveals traces of neglected nonlinearities that are not completely captured by GARCH models. Moreover, such residual traces of neglected nonlinear dependencies are relatively more pronounced at the granular levels and become more and more elusory as the data get aggregated in time. JEL Codes: C22, C53, C58, G1, Q47","PeriodicalId":44100,"journal":{"name":"Journal of Emerging Market Finance","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2021-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46212879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Antecedents of Stage-wise Investment Preferences of Venture Capital and Private Equity Firms in India: An Empirical Exploration","authors":"Poonam Dugar, R. Basant","doi":"10.1177/09726527211022900","DOIUrl":"https://doi.org/10.1177/09726527211022900","url":null,"abstract":"This article is a maiden attempt at exploring determinants of stage-specific investment choices of Indian venture capital and private equity (VCPE) firms. Analysis of 5,782 VCPE investment deals during 1998–2016 shows that firms’ preferences to invest in various stages (early vs. late) are significantly affected by the characteristics of the VCPE firms, features of the deal, and characteristics of the investee firms. More specifically, experience and ownership (foreign vs. domestic) of VCPE firm, type of deal (syndicated or otherwise), investment size of the deal, and location and industry of the investee firm influence the stage of investment. Detailed empirical analysis shows that younger VCPE firms and those with domestic investors prefer to invest in early stages, presumably because they wish to build a reputation and also leverage their proximity with investee firms to manage high market and technological risks associated with early-stage investments. Syndication is another mechanism used to manage the risks associated with early-stage deals. Investee firms in industries that have lower investment requirements or shorter gestation periods and those located in regions with a mature entrepreneurial ecosystems are more likely to attract early-stage investments. JEL Classification: G24, L26, D81","PeriodicalId":44100,"journal":{"name":"Journal of Emerging Market Finance","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/09726527211022900","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44082672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Financial Access of Latin America and Caribbean Firms: What Are the Roles of Institutional, Financial, and Economic Development?","authors":"L. Chu","doi":"10.1177/09726527211015317","DOIUrl":"https://doi.org/10.1177/09726527211015317","url":null,"abstract":"This article examines the impact of institutional, financial, and economic development on firms’ access to finance in Latin America and Caribbean region. Based on firm- and country-level data from the World Bank databases, we employ an ordered logit model to understand the direct and moderating role of institutional, financial, and economic development in determining firms’ financial obstacles. The results show that older, larger, facing less competition and regulation burden, foreign owned, and affiliated firms report lower obstacles to finance. Second, better macro-fundamentals help to lessen the level of obstacles substantially. Third, the role of institutions in promoting firms’ inclusive finance is quite different to the role of financial development and economic growth. JEL Classification: E02; G10; O16; P48","PeriodicalId":44100,"journal":{"name":"Journal of Emerging Market Finance","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/09726527211015317","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45375698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}