Banking and Finance Issues in Emerging Markets: Volume 25

For the past decades, issues concerning the impact of economic integration on financial integration, especially exchange rate integration, has been criticized among several regions such as ASEAN. This chapter intends to: (i) test for the exchange rate integration among the ASEAN-5, including Indonesia, Philippines, Malaysia, Singapore, and Thailand, using panel data techniques; and (ii) determine the impact of economic integration on the level of exchange rate integration among the ASEAN-5 countries. The purchasing power parity (PPP) is tested using panel unit root tests on monthly data. The results confirm the PPP among the ASEAN-5 countries due to lower transaction costs from ASEAN agreements. The chapter applies Multivariate GARCH (M-GARCH) models using daily data to determine the level of exchange rate integration among the ASEAN-3, including Malaysia, Singapore, and Thailand. The results of panel cointegration tests using quarterly data of economic integration and exchange rate integration confirm the impact of international trade openness on exchange rate integration. With free trade agreements leading to lower trade barriers, lower transaction costs, and low transportation costs, the economic integration among ASEAN countries practically leads to a higher degree of exchange rate integration. The findings imply that trade liberalization has the strongest effect on the real exchange rate. As such, regulators of ASEAN countries should pay more attention to the exchange rate policies of each other because of the interdependence of their exchange rates.

The RMB Internationalization has a great impact on China’s domestic economy. This chapter applies the Gap Estimation approach to estimate the RMB overseas circulation amount from 1997 to 2015, as the indicator of RMB internationalization. Using the recently developed Directed Acyclic Graph (DAG) method for the model identification and contemporaneous causality analysis. The structural vector auto regression (SVAR) model is constructed between the economic indicators (the interest rate, the CPI, and the exchange rate) and the RMB overseas circulation. The dynamic relationship and degree of mutual influence are further studied between the economic indicators and overseas circulation. The results show that there exist contemporaneous causalities of “from RMB overseas circulation to inflation rate,” “from exchange rate to overseas circulation,” and “from exchange rate to the inflation rate.” The influence of interest rate adjustment on macro economy presents the time lag effect. The internationalization of the RMB encourages the currency appreciation. The China’s Central Bank passively looses monetary policy to meet the needs of internationalization and reduce the shock of the international hot money, thereby further deepening the domestic inflation.

This chapter examines dynamic connectedness among emerging Asian equity markets as well as explores their linkages vis-à-vis other major global markets. We find that international equity markets are tightly integrated. Measuring connectedness based on a generalized Vector Autoregressive (VAR) model, more than half of all total forecast error variance in equity return and volatility shocks come from other markets as opposed to country own shocks. When examining the degree of connectedness over time, we find that international stock markets have become increasingly connected, with a gentle upward trend since the Asian financial crisis (AFC) but with a rapid burst during the global financial crisis (GFC). Despite the growing importance of Asian emerging markets in the world economy, we find that their influence on advanced economies are still relatively small, with no significant increase over time. During the past decade, advanced markets have been consistently net transmitters of shocks while emerging Asian markets act as net receivers. Based on the nature of equity shock spillovers, we also find that advanced countries are still tightly connected among themselves while intraregional connectedness within Asia remains strong. By investigating whether uncertainty plays an important role in explaining the degree of stock market connectedness, we find that economic policy uncertainty (EPU) from the US is an important source of financial shock spillover for the majority of international equity markets. In contrast, US financial market uncertainty as proxied by the VIX index drives equity market spillovers only among advanced economies.

This chapter proposes augmenting a simple income stock price model with spatial structures to evaluate the significance of real and financial linkages in instigating stock market contagion. The treatment is premised upon the clustering of excessive returns and volatilities during the Subprime crisis envisaged from our regime switching analysis over a long time span, and the presence of spatial autocorrelation in the baseline income stock model. With the channel factors manifested as spatial weights, this chapter explores specifications of explicit interrelated stock price returns and implicit spatial autocorrelation in the error term for the 3-year period from 2007 to 2009. Model validity is authenticated by way of model choice and spatial weight selection. The finding shows that spatial dependence in either specification is not too sizable indicating that contagion is not spreading fast in the sample period. Of the various factors considered, non-performing loans, market liquidity, and credit to deposit ratio turn out to be the most important transmission factors. Current account balance, net FDI flows, and size of GDP are among the least significant media. In sum, these suggest that financial linkages could play a more important role in facilitating shock transmission when compared to real linkages such as trade.

A full Edgeworth cycle of deposit rate is divided into two phases: an “overcutting cycle” in which the banks battle for deposits, and a “relenting cycle” in which the banks cease battling and instead choose to restore a temporarily low deposit rate. Such strategies have two testable implications on overall market movements. First, deposit rate decreases are more likely to be initiated when the deposit rate is near the upper bound of a cycle. Second, deposit rate decreases are more sensitive than increases to market interest rate changes. This chapter empirically confirms this pattern and shows strong evidence for the presence of Edgeworth cycles in deposit rates after Hong Kong’s interest rate deregulation.

In the economic literature, a crisis has been thematically defined around bank runs, failure of large financial corporations, and financial distress. Section 1 summarizes our learnings about international banking crisis, in terms of the origin and impact of such crises. This provides us an international benchmark before we delve deeper into India's banking distress, its size and trends. Section 2 focuses on the twin-balance-sheet crisis in India. On one side, corporate firms recklessly overleveraged, resulting in excess capacities and business diversification. On the other side, banks, both private and public, fell prey to excessive and procyclical credit lending and improper monitoring. Overall, too many projects were left too weakly monitored. Separately, we have focused on two subsections, first, how the financial institutions in India have overstretched their credit-disposal limit during market upturns. Second, we found absence of any theoretically grounded approaches to determine the capital-adequacy ratios (CARs) for the banks. In Section 3, we have identified the steps taken so far by the Banking regulator and the Government to resolve the crisis. Further, we critically examine the role of Korea Asset Management Corporation (KAMCO) towards a successful non-performing assets (NPAs) resolution in South Korea. Few key takeaways include, (1) establishing a public asset-management company (AMC) focused on maximization of recoveries and resolution of stressed assets, (2) well-defined governance structure for the AMC ensuring it works on market principles, shielded from political interferences, and (3) realistic asset valuation and transfer price that ensures limited downside risks for the public AMC.

In seminal work, Den Haan et al. (2007, 2010, 2011) show business loans respond in the opposite direction of what may be intended by monetary policy action in the United States and Canada. Based on various approaches, identification schemes, and samples, we document evidence this loan puzzle is not exclusive to developed economies but is also pervasive in emerging markets. We find business loans generally decline following expansionary monetary policy shocks. A preponderance of statistical and structural evidence indicates important transmissions of this puzzle from the United States to emerging markets.

Japanese regional banks have actively expanded their overseas business in emerging markets, and this topic is quite important for regional banks that have confronted severe business environments over the decades. An aging population suppresses long-term increases in loan demands, and stagnant economic conditions lead to lowered interest rates in the medium-term. Overseas business is a promising business field for regional banks, but recent developments have not been investigated in detail.

This chapter examines overseas investments using data from regional banks’ financial reports. Our sample comprises 44 regional banks without overseas branches, and a research period from FY2011 to FY2015. We demonstrate different overseas business patterns among regional banks. This investigation uses X-means clustering, which is nonhierarchical, as this method automatically presents an optimal number of clusters, and sorts regional banks into their appropriate clusters.

The X-means clustering method indicates five business patterns among regional banks. This also characterizes respective clusters and demonstrates that medium-sized banks actively develop security investments, which increases overseas business’s contributions to profits. Meanwhile, small banks cannot expand overseas investments, which differ from other banks. These banks must seek other business models to compensate for this decline in their earning power.

The chapter studies the role of Financial Technology (FinTech) in disrupting the existing traditional banking system. It identifies FinTech’s evolution in Asia across Deposits & lending, Capital Raising, Investment Management, Market provisioning, Payments, and Insurance. This technology revolution allows us to have a banking system based on values that serve customers better, reduce risk to the society and improve returns for the shareholders. Data on unbanked population, smartphone penetration, and Internet penetration has led to retail side innovations such as Mobile Wallets, P2P Payments, and Real-time Payments in the most of Asia (except China). A total of 49% of Global Investments in FinTech are in Asia and the Chinese dragon alone accounts for 46%. India is witnessing a strong amount of FinTech deals in 2017 and it is being driven by payment and lending solutions. ASEAN FinTech industry is dominated by m-wallets and online payments; this is followed by retail investment and financial comparison. The chapter dives into the challenges Asian banks are facing because of this disruption. Now more than ever, is the important role governments and central banks of each nation play to assess the path these start-ups are headed on and this will unfold the landscape of banking in Asia a few years down the lane.

The rapid change of technology has significantly affected the financial markets in Thailand. In order to enhance the market efficiency and liquidity, the Stock Exchange of Thailand (SET) has granted Thai stock brokers permission to develop and offer their customers algorithm and automatic stock trading. However, algorithm trading on SET was not widely adopted. This chapter intends to design and empirically estimate a model in explaining Thai investors’ acceptance of algorithm trading. The theoretical framework is based on the theory of reasoned action and technology acceptance model (TAM). A sample of 400 investors who have used online stock trading and 300 investors who have used algorithm stock trading were observed and analyzed using structural equations model (SEM) and generalized linear regression model (GLM) with a Logit specification. The results confirm that attitudes, subjective norm, perceived risks, and trust toward algorithm stock trading are factors determining investors’ behavior and acceptance of using algorithm stock trading. Investor’s perception and trust on algorithm stock trading as a trading strategy is a major factor in determining their perceived behavior and control, which affect their decision on whether to invest using algorithm trading. Accordingly, it can be concluded that Thai investors is willing to accept algorithm trading as a new financial technology, but still has concern about the reliability and profitable of this new stock trading strategy. Therefore, algorithm trading can be promoted by building investors’ trust on algorithm trading as a reliable and profitable trading strategy.

There has been a financial revolution lead by technology firms over the past decade. Many large established technology giants, from Google, Apple to Amazon in the US are entering the financial service industry. Smaller start-ups, in particular robotic advisors, a.k.a. Robo-Advisors, have been taking market shares from traditional asset management firms. In China, firms like Tencent and Alibaba have created a whole new field of online finance. At the center of our study is a critical examination of the key components of the financial innovation over the past 10 years. Mobile banking was the beginning, followed by trading, investment, and insurance business. We study innovation through several cases. Due to the size and number o firms in Financial technology (FinTech) space, the US and China are the focus of the chapter. Artificial intelligence (AI) and machine learning are included for discussion in this chapter. We emphasize a market approach in our study, albeit, incorporating the historical and cultural perspectives in our analysis. Our goal is to develop a thorough understanding of the art and science of financial innovation, from both bottom-up market indicators and a top-down holistic view. We want to demonstrate that the technological changes are just the beginning of a new world of financial services. Unprecedented changes are still yet to come and it is crucially important to be prepared and even embrace the changes. A special discussion was devoted to the phenomenon of FinTech boom in Asia. Lastly, many new technologies are being developed to combat fraudulent activities in the FinTech space.