Assessing international financial integration: do industry and firm-specific characteristics matter? Evidence from the Japanese market

Abstract

International financial integration has received much attention among professional investors. The purpose of this study is to investigate the relationship between financial integration and industry and firmspecific characteristics through analysing cross-listing premiums (determined by the price difference between American Depositary Receipts (A.D.R.s) and their underlining stocks) in Japan. Employing autoregressive models to examine convergence speeds of a shock to the price difference and non-linear Band-threshold autoregressive models to identify non-arbitrage bands, we find that firms integrate well when they are larger in size, sales growth, turnover, performance, institutional holdings, or marked by merger activity, overseas subsidiaries, industrial or consumer goods industries, and a longer history of A.D.R. listing. That is, the A.D.R. with the abovementioned characteristics tends to have less scope for arbitrage. However, crossmarket premiums for firms which have large shareholders and a larger extent of earnings management converge more slowly and have longer half-lives, implying more arbitrage opportunities exist. The explanatory variables applied explain over 35% of variance of premium, and most of the variables remain significant determinants of half-lives whether autoregressive or threshold autoregressive modules are used, but firm leverage is not. The results show that the metals and mining industry converges notably slower than other industries, indicating arbitrage is possible.

Behavior of Global Investors in Five ASEAN Stock Markets in the Industry Level

“…These results support the findings of Roll [1], Hwang and Sitorus [4], Do et al [5], Setyawan [14], and Setyawan and Wibowo [15]. If considered in panel A, all industries have the potential benefits of diversification, referring to Chen et al [6], namely, the value of standard deviation is smaller than that of the mean.…”

“…If you see Table 1, the ASEAN countries are Singapore (LOC and USD), Indonesia (USD), and Thailand (LOC). The comparison between standard deviations and the mean of each pair of correlations is actually identical to the Sharpe ratio formula used to measure portfolio performance [see Chen et al [6]]. One form of practical implication is the comparison between mean and standard deviation which refers to Sharpe ratio as the benchmark for benefits of international diversification [see Piumsombun [21], Hwang and Sitorus [4], and Do et al [5]].…”

“…But what's interesting in Table 2 is the higher unconditional correlation of some sectors such as basic materials, financial institution, and property and real estate. According to Kim [11] referred to by Piumsombun [21], Hwang and Sitorus [4], and Chen et al [6], the cause of the high correlation of the three sectors is the specification of the EW-LOC, VW-LOC, EW-USD, and VW-USD, as follows: According to Menchero and Morozov [7], market capitalization of the three sectors also contributed to the high correlation in addition to the number of industry members in GICS. Referring to Table 2, the practical implication is that global investors can choose the basic material industry (code 15) and industrial goods (code 20) because both have very low standard deviation values among other industries.…”

“…Several other researchers stated that industrial factors are more non-systematic than state factors. Since the classic study of Roll [1] states that industrial factors have an important role in the effectiveness of international diversification, many researchers such as Ratner and Leal [2], Richard [3], Hwang and Sitorus [4], Do et al [5], and Chen et al [6] began to use industry data such as Global Industry Classification Standard (GICS). According to Menchero and Morozov [7] GICS has been more globalized than other industry standards since it was handled by Morgan Stanley Capital International (MSCI).…”

The evolution of the financial technology ecosystem: An introduction and agenda for future research on disruptive innovations in ecosystems

“…Simultaneously, the innovation outperforms the existing offering on some other dimension(s), which makes it attractive to the 'low-end' customers of the established product and/or new markets. As ongoing technological progress continuously improves the innovation's performance on the former dimension, more and more customers of the original product switch to the innovation so that the market share of the old solution progressively erodes (Chen et al, 2018;Kumaraswamy et al, 2018;Schmidt and Druehl, 2008).…”