International Journal of Finance & Economics最新文献

While the oil market-investors sentiment (IS) has been considerably investigated, almost all studies have focused on the assumption of a constant relationship, and no attention has been given to the causality analysis in a time-varying approach. To fill this gap, this study investigates the predictive power between IS and oil price based on a time-varying Granger causality test. Using data over the period 1987–2020, we find evidence of significant bidirectional asymmetric time-varying causal influences between investor sentiment and oil prices, suggesting that oil prices may predict investor sentiment and vice versa. Besides, the results suggest that bearish (bullish) investor sentiment has positive (negative) influences on oil prices during major economic and political events. In contrast, oil price exerts an influence on the sentiment which switches between positive and negative from one period to another. Further analysis shows that uncertainty related to the oil and equity markets can be a driver of the predictive power of oil prices on the bearish IS.

Amin, A., Anwar, S., & Liu, X. H. (2022). Outward foreign direct investment and economic growth in Romania: Evidence from non-linear ARDL approach. International Journal of Finance & Economics, 27(1), 665–677.

Page 665 – In abstract section, 1990–2019 was incorrect. The correct years are 1990–2017.

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Page 667 – Figure 1 Notes.

The correct years are 1990–2019 not 1990–2017

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Page 669 line 7, The correct years are 1990–2017 not 1990–2019

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Page 670 – Table 1 Source should read Authors calculations 1990–2017

The date was omitted by the authors and this is a clarification

Page 671 – Table 2 Source should read Authors calculations 1990–2017

The date was omitted by the authors and this is a clarification

Page 671 – Table 3 Source should read Authors calculations 1990–2017

The date was omitted by the authors and this is a clarification

Page 672 – Table 4 Source should read Authors calculations 1990–2017

The date was omitted by the authors and this is a clarification

Page 672 – Table 5 Source should read Authors calculations 1990–2017

The date was omitted by the authors and this is a clarification

Page 673 – Figure 2 should read Asymmetric cumulative dynamic adjustment of GDP per capita to OFDI 1990–2017

The date was omitted by the authors and this is a clarification

Page 676 Figure A1 should read A plot of CUSUM & CUSUM of square of the recursive residuals from model 1, 1990–2017

The date was omitted by the authors and this is a clarification

Page 677 Figure A2 should read A plot of CUSUM & CUSUM of square of the recursive residuals from model 2, 1990–2017

The date was omitted by the authors and this is a clarification

Page 677 Figure A3 should read A plot of CUSUM & CUSUM of square of the recursive residuals from model 3, 1990–2017

The date was omitted by the authors and this is a clarification

We apologize for these errors.

We use the two-way fixed-effect panel logit model to examine the impact of U.S. economic uncertainty shocks on the probability of extreme capital flow episodes based on quarterly data from 71 emerging and developing economies from 1998Q1 to 2022Q4. According to the findings, U.S. economic uncertainty shocks has a negative effect on the probability of gross capital surges, gross capital flight, and net capital surges, and has a positive effect on the probability of gross capital sudden stops, gross capital retrenchment, and net capital sudden stops. Moreover, we find differences in the factors affecting net and gross capital flows, which are usually more closely related to earnings factors dominated by real economic growth rates. Additionally, the sample's heterogeneity is analysed in accordance with the exchange rate regimes. Our results differ from traditional views, as floating exchange rates do not act as a buffer against extreme capital flows. Finally, capital flows are classified into direct investment, other investment, and portfolio investment, and it is found that U.S. economic uncertainty shocks have a significant impact on the extreme flow episodes of other and portfolio investment.

This study examines the impact of credit ratings on the efficiency of firms' investments. Using a large sample of US firms, we find a positive relationship between the existence of credit ratings and investment efficiency. The cross-sectional analyses show the positive relationship is more pronounced for firms with greater information asymmetry and weaker corporate governance. Our results are robust to different methods to address potential endogeneity concerns, alternative measures of key variables, and the inclusion of additional control variables. Overall, the findings support the notion that credit rating agencies enhance information transparency and external monitoring, thereby allowing rated firms to promote investment efficiency. The findings contribute to our understanding of the significant role played by credit rating agencies in shaping firms' investment behaviour and efficiency.

We are the first to determine the effect of intangible intensity (INTANG) on cross-sectional stock returns after controlling financial constraints in the Vietnam stock market. Our sample includes 37,938 firm-month observations from 488 non-financial firms from October 2008 to February 2021. We employ Fama and MacBeth regressions and portfolio analysis methodologies to estimate the impact of intangible assets and financial constraints on stock returns. Our findings show that a percentage increase in INTANG empowers stock returns by 0.922%. Meanwhile, the cross-sectional stock returns decrease by 0.506% when the financial constraints index increases by a percentage point. Moreover, the results suggest that intangible assets in the entire sample and before COVID-19 empower the stock return cross-sectionally. Our findings are robust after employing alternative INTANG proxies. Our findings support the risk-based explanation, the pecking order theory, and prior literature. Our findings suggest governments should promote intellectual property and copyright regulations to encourage Small and Medium Enterprises (SMEs) to expand intangible assets. Furthermore, investors can utilize our suggested models to construct their portfolios efficiently.

In the setting of a dynamic panel data framework, we investigate the international five-factor Fama–French (2017) model augmented with traditional illiquidity factors (Amihud, Journal of Financial Markets, 2002, 5, 31–56; Amihud, Critical Finance Review, 2019, 8, 203–221; Pástor and Stambaugh, Journal of Political Economy, 2003, 111, 642–685; Pástor and Stambaugh, Critical Finance Review, 2019, 8, 277–299) to determine if any of these factors are priced. Since illiquidity measures are endogenous, we propose an algorithm that generates robust instruments which are combined with a GMM estimator to cope with both the endogeneity issues surrounding illiquidity and other eventual specification errors. In this dynamic framework, we generally find that the most significant factors correspond to market and size but illiquidity may matter depending on the level of the beta. We find that illiquidity has more impact on returns in expansion than in recession. However, the bid-ask spread seems to behave differently from the other illiquidity measures.

This paper aims to investigate the relationship between brand value and firm value by using a two-step approach. In the first step, we use the financial-based brand valuation model (FBVEM) to obtain the brand value of firms that operated in the Turkish manufacturing industry during the period between 2014 and 2018. In the second step, we examine the effect of brand value on Tobin's Q. In doing so, we use a novel GMM, with a measurement errors model, which takes into account mismeasurements of the financial variables. We try to get an accurate estimation of the link between brand value and Tobin's Q in our analysis. The obtained findings show that the effect of brand value on firm value is positive in the Turkish manufacturing sector. Our results remain stable after robustness checks. This is the first well-controlled study that considers the endogeneity problem and consequent measurement errors in the relationship between brand value and firm value.

This study investigates the effect of both conventional and unconventional monetary policies on loan default of UK personal and business peer-to-peer (P2P) loans. I employ loan book data of Zopa, Lending Works, and MarketFinance, which are three of the most popular UK P2P lending platforms. Survival analysis reveals consistent evidence for the existence of the risk-taking channel of monetary policy. Monetary easing, be it conventional or unconventional, reduces loan survival in the P2P lending market. This finding delivers useful information for policymakers to rebalance the countervailing effects of expansionary monetary policies on financial stability during the era of alternative financing.

The rapid development of digital finance is reshaping the business model of the traditional bank industry and bringing challenges to it as well. Based on an unbalanced panel of data constructed by 36 banks in Malaysia from 2006 to 2020, this study examines the impact of financial technology on banks' stability and efficiency. We find that, compared with Islamic banks, FinTech innovation significantly improves the stability of commercial banks. Additionally, it improves the entire sample banks' efficiency calculated by the data envelopment analysis-Malmquist method, which can capture the efficiency changes from a dynamic perspective. These baseline results are affirmed by the generalized method of moment approach to mitigate potential endogeneity issues. Furthermore, the impacts of FinTech innovation on banks are heterogeneous. The high-profit banks enjoy the benefits of improving their stability level from FinTech development. However, for the small-sized and low-profit banks, FinTech innovation contributes more to improving their efficiency. Our analysis provides empirical evidence for Malaysia and similar developing countries that are receptive to FinTech development but have relatively less advanced technology infrastructure. It can also shed light on the FinTech investment decisions of bank management.

Using a dataset of bank- and regional-level data, we study the effectiveness and heterogeneity of the transmission mechanism of the ECB's large scale asset purchases (LSAPs) to the real economy. Our results indicate that banks more exposed to government debt securities had higher growth of loans and loans relative to total assets than less exposed banks after the asset purchase programme (APP), but not after the pandemic emergency purchase programme (PEPP). Furthermore, our results demonstrate that regions where banks are more exposed to government securities exhibit more favorable outcomes after the APP in GDP, fixed capital formation, unemployment, and compensation of employees than regions with less exposed banks, via the bank lending channel. We argue that banks' exposure to LSAPs targeted assets and their geographical location is an important factor determining the magnitude and heterogeneity of the portfolio rebalancing transmission mechanism to the real economy.