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The authors test the weak-form efficiency in cryptocurrency markets using the most recent and comprehensive data as of 2021. The authors apply various technical indicators to take a long or short position on 99 cryptocurrencies and compare the 10-day returns based on the technical trading strategies to the simple buy-and-hold returns. The authors find that the trading strategies based on single indicators or the combination of two indicators do not generate higher returns than buy-and-hold returns among cryptos. These findings suggest that cryptocurrency markets are weak-form efficient in general.

This chapter identifies three crisis warning indicators driven from trading in emerging markets’ carry trades, and empirically examines whether these indicators could predict two major financial crises that hit the global financial markets in the last decades — The 1997–1998 Asian crisis and the 2007–2008 global crisis. The probit regression is used to examine the power of the three indicators in forecasting financial crises, using data from eight Asian emerging countries which serve as proxies for emerging markets, independent of the origination of the crisis. I use both fixed effect and random effect estimation to measure crisis impacts. The empirical results show that financial crises could have been predicted. Probit estimation show that carry trade returns can predict a financial crisis, and the estimation results are robust to both panel level and country-level analysis. These three indicators are by no means an exhaustive list of all possible predictors of financial crisis. The literature suggests other fundamental indicators of financial crises such as the current account deficit and foreign debt. However, this chapter cannot fully consider these indicators for lack of data at this point in time. Although financial crisis may be better predicted by the well-known fundamental indicators, the contribution of this chapter is simply that carry trade-related indicators can help in predicting crises.

The purpose of this study is to empirically analyze the impact of logistics efficiency on trade volume growth, and to examine the effects of lower tariffs resulting from free trade agreements. In order to measure the impact of logistics efficiency on trade volume growth, the export and import trade volume among 53 countries was introduced as the dependent variable. Macroeconomic indicators including annual average tariff rate, logistics efficiency indicators for port, air, railroad, road and container vessel connectivity, as well as dummy variables such as whether a free trade agreement was signed, were introduced as the explanatory variables. Bilateral panel data between trading nations was used to estimate the gravity panel model, and analysis followed the categorization: 1) separate inputs of the five logistics efficiency variables and 2) one aggregated input of the five variables as a single indicator. The analysis found that logistics efficiency had a statistically significant impact on bilateral trade volume growth, while the impact of lowering tariff rates on increasing trade was insignificant. In addition, logistics efficiency was found to have a greater impact on increasing trade volume than free trade agreements. These results imply that trade can be promoted more effectively by establishing and efficiently operating logistics-related infrastructure rather than traditional methods of reducing trade barriers such as lowering tariffs and signing free trade agreements.

The purpose of this paper is to study the competitiveness of the stock markets in ASEAN 5, which are the Stock Exchange of Thailand (SET), the Singapore Exchange (SGX), Bursa Malaysia (BM), the Indonesia Stock Exchange (IDX), and the Philippine Stock Exchange (PSE).

This research applies Porter’s (1990) diamond model to analyze the competitiveness and the data were collected from World Economic Forum, International Institute for Management Development, the World Federation of Exchanges database, and DataStream.

The results show that SGX is the most competitive exchange in ASEAN 5 region. It dominates other exchanges in every dimension. It gains its reputation for being the region’s most prominent exchange, followed by BM, SET, IDX, and the PSE, respectively.

The results of this investigation provide rank for competitiveness of stock exchanges among ASEAN 5 and identify the way to improve its competitive position.

It is useful for public and private sectors involved in the development and policy making to promote funding and investment efficiency of the exchanges. It will be benefit to establish the well-planned development strategy and policy to build up the competitive advantage of the nations.

Identifying and benchmarking the competitiveness of the stock markets in ASEAN economies. By using Diamond Model, the authors propose indicators to assess the competitiveness of the stock markets in ASEAN 5 countries. Assessing the competitiveness of the ASEAN stock markets in this paper will lead us to better understand about each country’s strengths and weaknesses and to promote a mutual collaboration among the region toward ASEAN Economic Community.

The purpose of this paper is to study price discovery and price convergence in securities trading within a fragmented market environment where stocks are traded on multiple venues. The results provide novel empirical insights questioning the generalizability of the current literature and aim to expand the understanding of price determination in a fragmented market microstructure.

This paper provides an empirical data analysis based on an event study methodology. The authors applied Thomson Reuters Tick History data covering German blue chip stocks listed on multiple venues in 2009 and 2013. Different time aggregations up to one second are applied to provide an in-depth analysis.

The paper empirically discovers a persistent price leader-follower relationship not only during intraday auctions but also in subsequent continuous trading. The authors found that trading on alternative venues instantly dries out in case the dominant market switches to a call auction. In these situations, alternative markets await and adopt the official price signal of the dominant market although prices on alternative venues still indicate a certain extent of price discovery. This phenomenon remains persistent at different levels of market fragmentation, indicating that alternative trading venues fully accept the price leadership role of the dominant market, no matter their own market share.

This paper provides an innovative empirical setup to analyze price co-movement and convergence based on high-frequent data. Further, the results provide novel and robust insights into the price determination process in fragmented markets that clarify the role of price follower and price leader.

This paper aims to investigate the quickness, and test the accuracy, of liquidity taking high-frequency traders (HFT). This gives us important insights into a class of market participant who has come to be very influential in present markets.

The authors use the weekly natural gas (NG) storage report for the test because the information contained in the release often has a large effect on prices. Moreover, the NG market is heavily traded and liquid, and prone to high volatility. These factors make trading in this market attractive to HFT. The authors test for the profitability of those who trade in the first milliseconds after the report’s release; and for information leakage prior to the report.

The authors find those who trade within the first 50 ms accurately incorporate the information contained in the storage report into prices, and earn the majority of profits. In fact, HFT profits are decreasing in the time it takes them to trade after the announcement (measured to 200 ms). Further tests find no evidence of informed trading prior to the release of the report, and so the HFT reaction to the report incorporates the information contained therein into prices.

This is one of the few analyzes of the profitability of liquidity-taking HFT, and the only analysis that uses millisecond NG data. The data used is the exchanges original FIX/FAST messages.

The purpose of this paper is to contribute to the empirical literature of the macroeconomic effect of trade facilitation reforms by examining the impact of the latter on tax revenue in both developed and developing countries. The relevance of the topic lies on the fact that at the Bali Ministerial Conference of the World Trade Organization (WTO) in 2013, Trade Ministers agreed for the first time since the creation of the WTO (in 1995) on an Agreement to facilitate trade around the world, dubbed Trade Facilitation Agreement (TFA). The study considers both at-the-border and behind-the border measures of Trade Facilitation.

To conduct this study, the authors rely on the literature related to the structural factors that explain tax revenue mobilization. The authors mainly use within fixed effects estimator. The analysis relies on 102 countries (of which 23 industrial countries) over the period 2004-2007 (based on data availability). A focus has also been made on African countries, within the sample of developing countries.

The empirical analysis suggests evidence of a positive and significant effect of trade facilitation reforms on non-resources tax revenue, irrespective of the sample of countries considered in the analysis.

This finding should contribute to dampening the fear of policymakers in developing countries, including Africa that the implementation of the TFA would entail higher costs, without necessarily being associated with higher benefits. An avenue for future research would be to extend the period of the study when data would be available.

To the best of the authors knowledge, this study had not been performed in the literature of the determinants of tax revenue mobilization, although fact-based analysis was performed.

The article studies the problem of the impact of non-tariff barriers on mutual trade in goods between the EAEU member states. This problem is considered using the example of assessing the impact of non-tariff regulation measures of Russia, Kazakhstan and Kyrgyzstan on imports of goods from other EAEU member states. The conducted research is based on domestic and foreign scientific works that use barrier components to build a gravitational model of foreign trade. To study the impact of non-tariff regulatory measures of Russia, Kazakhstan and Kyrgyzstan on import commodity flow from other EAEU member states, two time periods are considered – the period of 2010–2014 and the period 2017–2019. In the context of the periods under consideration, a gravitational model of foreign trade is constructed. As a result of building a model within the framework of the study, it was revealed that during the period of the EAEU existence (2017–2019), non-tariff measures of foreign trade regulation had a more significant and negative impact on imports of the studied countries than before the formation of the EAEU (2010–2014). The latter indicates the relevance and necessity of further research of this problem.

The purpose of this paper is to examine the export, import, and total trade determinants using reduced form equations for six Pacific Island countries (PICs) with an institutional focus.

A fixed effects model, controlling for AR(1) errors, using panel data for selected PICs is utilized. Controlling for common determinants of trade, four indicators of institutional quality: government effectiveness; rule of law; regulatory quality; and control of corruption are tested.

The empirical results indicate that improvements in institutional quality variables matter for improved levels of trade. The results also provide confirmation that the appreciation of currency does not significantly harm trade; higher levels of technological diffusion are vital for improved trade; and that gradual liberalization of trade through tariff reduction strongly facilitates more trade.

This study clearly points out that the institutional quality in the selected countries is a significant factor in determining the level of trade.

This paper expresses the view that institutions matter for enhanced trade.

This study aims to explore information asymmetry (IA) (as measured by the adverse selection component of the bid-ask spread) around S&P 500 revisions.

The authors use adverse selection cost of trading measures to examine the effects of S&P 500 index composition changes on the trading environment from 2001 to 2010.

The authors find that the adverse selection cost of trading significantly decreases post-addition and increases post-deletion. However, the intraday price dynamics of additions to the index seem to be distinct from those of deletions from the index. The event period cumulative abnormal returns (CARs) for additions are significantly associated with the change in the adverse selection cost of trading. However, this association is non-significant for deletions. The CARs for deletion events are found to be significantly associated with the change in realized spreads. Realized spreads are a measure of revenue earned by liquidity providers in the market.

This study helps better understand the dynamics of two types of IA – one from a firm to investor and the other between investors – and presents evidence of the role of adverse selection in index changes. By doing so, it helps better understand the mechanism driving price formation post-addition to and deletion from an index.