International Journal of Finance & Economics最新文献

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.

This was a typo

Page 667 – Figure 1 Notes.

The correct years are 1990–2019 not 1990–2017

This was a typo

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

This was a typo

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.

Understanding institutional investors' investment criteria in emerging markets is essential because they typically make large investments without control rights or protection of the rule of law. This study undertakes an investment criteria investigation of institutional investors in Turkiye. The sample covers real and financial sector companies to investigate sectoral differences in Borsa Istanbul-listed firms for 2010–2021. Using a panel data approach, we show that the presence of growth options, generous payout policy, attractive firm valuation, and quality of the external governance mechanisms are important factors in attracting institutional investors by real sector firms. Only a large firm size and the quality of the external governance mechanisms arise as important factors for financial sector firms. Moreover, institutional holdings positively impact the percentage shares of institutional investors during crisis periods among real sector firms, whereas they do not affect financial sector firms. Real-sector and financial-sector firms can use our findings to increase institutional ownership. Our results have important implications for institutional investors, individual investors, and market regulators to demand critical corporate governance practices.

This study employs the Bayesian Networks (BN) and the wavelet coherence approaches to invest the relationship between Bitcoin volatility and financial asset classes (MSCI world equity index, S&P Goldman Sachs Commodity Index [GSCI], US index and Investment Grade Corporate Bond Index ETF [PIMCO]) using daily data for the period from August 2011 to October 2021. The results show that the causal relationship between Bitcoin and other financial assets varies depending on the market states. During the low volatility periods, Bitcoin has a stronger impact on the GSCI, while during the stability periods, it has a direct effect on the US index and the MSCI world index. In contrast, during high volatility periods, Bitcoin has a direct impact on both the GSCI and PIMCO indices. The key findings enabled us to provide implications for US investors to promote asset allocation and risk management covering both Bitcoin and traditional financial markets. The results suggest that policymakers should watch Botcoin closely to preserve financial stability.

We develop a four-state regime-switching model for optimal foreign exchange (FX) hedging using forward contracts. The states correspond to four distinct market conditions, each defined by the direction and magnitude of deviation of the prevailing FX spot rate from its long-term trends. The model's performance is evaluated for five currencies against the pound sterling for various horizons. Our examination compares the hedging outcomes of the proposed model to those of other commonly employed hedging methods. The empirical results suggest that our model demonstrates the highest level of risk reduction for the US dollar, euro, Japanese yen and Turkish lira and the second-best performance for the Indian rupee. The risk reduction is significantly higher for lira compared with the other approaches, implying that the proposed model might be able to provide much more effective hedging for highly volatile currencies. The improved performance of the model can be attributed to the adjustability of the estimation horizon for the optimal hedge ratio based on the prevailing market conditions. This, in turn, allows it to better capture fat-tail properties that are frequently observed in FX returns. Our findings suggest that FX investors tend to use short-term memory during low market conditions (relative to trend) and long-term memory in high ones.   The results would be also useful to build a better understanding of how investor behaviour depends on market conditions and mitigate the adverse behavioural implications of short-term memory, such as panic.

We argue that the corporate board of an exchange-listed firm cannot make an independent business decision if it has an affiliation with a conglomerate group. This is because the corporate board of a conglomerate-affiliated firm (CAF) has high moral hazard exposure due to its accountability to the superior parent board at the apex of the conglomerate structure. Based on a sample of 304 listed firms from 18 countries, we find a CAF board is less independent than a standalone board with no superior reporting body. A firm's affiliation with the conglomerate per se affects its board independence, regardless of the parent shareholding level. The additional analysis finds that the lack of board independence significantly impacts a CAF's financial performance, although the market impact is insignificant.