Asia-Pacific Financial Markets最新文献

In this study, we employ statistical analysis, hypothesis testing, and regression models to investigate the characteristics of opening price gap rates and price gaps in the stock market indices of Mainland China, utilizing historical data. To clarify, while both ’opening price gap rate’ and ’price gaps’ are central to our analysis, they represent distinct concepts. The opening price gap rate refers to the rate at which a stock’s opening price differs from its previous closing price, indicating initial market sentiment and potential momentum for the trading day. In contrast, price gaps, as defined in technical analysis, are specific chart patterns formed by two adjacent candlesticks on consecutive trading days. These patterns are characterized either by one candlestick’s low being higher than the following day’s high, or one candlestick’s high being lower than the following day’s low, creating a "blank" area on the price chart. This signifies a price range with no trading activity and is a crucial indicator of market sentiment and potential directional moves. Our study tested and validated thirteen related hypotheses. The findings reveal a significant correlation between the directionality of price gaps and the fluctuations in opening price gap rates, highlighting key characteristics of the market. Notably, price gaps significantly impact daily changes in trading volume and turnover. Furthermore, we validated the efficacy of the opening price gap rate as a stock-picking factor through back-testing. This research offers a new perspective for understanding stock market behaviors and has considerable implications for investment decisions and market analysis.

This study investigates the relationship between digital currency and broad financial markets covering equities, currencies, bonds, crude oil, and gold. It uses the Non-linear Autoregressive Distributed Lag model and wavelet coherence. The results demonstrate some relationships between digital currencies and other financial assets, with some evidence of asymmetry and a lead-lag relationship that is mostly significant at the medium timescales. The results provide useful insights for various market participants.

BRICS nations are playing a critical role in the global economic setting, but to maintain sustained economic growth they are required to make relentless efforts towards certain challenges. These challenges pertain to diverse governance areas including political, socio-economic, and legal conditions. This paper unfolds the impact of the level of governance quality indicators on stock market development for BRICS nations during the period from 2007 to 2021. Using panel data regression, our empirical findings confirm that governance indicators are critical for the development of the stock market. Our results show that governance indicators such as Government Effectiveness, Rule of Law, and Voice and Accountability are significant variables affecting the stock market development. We find that giving citizens more autonomy to participate in the formulation and execution of policies, improves the development of stock markets. Similarly, lesser political influence will also lead to better growth of the stock market. Additionally, the study evidence that a stronger legal environment in BRICS nations promotes lesser corrupt practices such as insider trading, but at the same time hinders the growth of the stock market. Policymakers in BRICS nations should follow a consistent policy to improve their governance indicators which are now becoming essential for stock market development.

The article aims to empirically examine the determinants of the 10-, 7-, and 5-year Indian government bond yields over the study period of 1999–2021. For this purpose, three equations were modeled using various independent variables to account for relevant global and domestic drivers. The results were estimated using the ARDL model to identify the long and short-run determinants of the bond yields. The findings demonstrate differences between domestic and global factors' long- and short-term effects across various bond maturities. The long-run drivers of Indian government bond yields include short-term interest rates, economic policy uncertainty, foreign exchange reserves, GDP growth rate, VIX, and oil prices. However, in the short run, all the domestic and global variables affected the bond yields, including external debt, inflation, and general government debt, which did not impact the yields in the long run. These findings have substantial policy implications for the central bank and government in formulating appropriate monetary and fiscal policy mixes while considering global risk scenarios and also for the international and domestic investors for better portfolio allocation.

The primary purpose of this paper is to analyze the connectedness between edible oils and oilseeds from various international commodity markets and the U.S. Economic Policy Uncertainty Index (EPU). The TVP-VAR method has been adopted in this paper to analyze the inter-commodity connectedness and spillover relationships among them. We also study how the effect on the price of one edible oil or oilseed affects other edible oils in the international markets. For this purpose, daily closing prices of near-month contracts of 6 edible oil commodities and the Economic Policy Uncertainty (EPU) index have been considered for a period that starts from January 2013 to April 2023. Results show a moderate level of connectedness among the edible oil and oilseed commodities; however, connectedness increases during times of economic or geopolitical crisis. Results also show that soybean is the most dominant commodity in the edible oil and oilseed commodity nexus, and rapeseed meal is the commodity with the lowest transmission power.

This document investigates the potential for international portfolio diversification between G7 stock markets and the BRICS counties, that is, Brazil, Russia, India, China, and South Africa. The authors propose a theoretical model that suggests risk-averse investors would seek diversification internationally. The study examines the long-term causality and short run causality between the stock market indices of G7 countries and the stock markets of each BRICS nation. Through unit root tests, the authors check the stationarity of the series. The study also employs the Johansen cointegration tests to examine the cointegration between the variables. Additionally, VECM is employed to assess the long-run causality and Wald test is used to understand short-run causality of the stock market indices. The results indicate a mixed response, revealing both short and long-run associations between the stock market indices of Brazil and Russia with the G7 stock market. The document provides valuable insights into the co-movement of G7 and BRICS stock markets, highlighting the potential for diversification benefits and identifying specific countries with stronger correlations. Policy-makers and capital market regulators can use the findings to develop robust policy frameworks and regulatory mechanisms to prevent potential stock market crashes and systemic failures.

This paper proposes a fuzzy jump-diffusion (FJD) option pricing model based on Merton (J Financ Econ 3:125–144, 1976) normal jump-diffusion price dynamics. The logarithm of the stock price is assumed to be a Gaussian fuzzy number and the risk-free interest rate, diffusion, and jump parameters of the Merton model are assumed to be triangular fuzzy numbers to model the impreciseness which occurs due to the variation in financial markets. Using these assumptions, a fuzzy formula for the European call option price has been proposed. Given any value of the option price, its belief degree is obtained by using the bisection search algorithm. Our FJD model is an extension of Xu et al. (Insur Math Econ 44:337–344, 2009) fuzzy normal jump-diffusion model and has been tested on NIFTY 50 and Nikkei 225 indices options. The fuzzy call option prices are defuzzified and it has been found that our FJD model outperforms Wu et al. (Comput Oper Res 31:069–1081, 2004) fuzzy Black-Scholes model for in-the-money (ITM) and near-the-money (NTM) options as well as outperforms Xu et al. (Insur Math Econ 44:337– 344, 2009) model for both ITM and out-of-the-money (OTM) options.

Using a sample of 16 international stock market indices spanning the period of January 2015 to June 2022, we examine how global equity markets interact with respect to volatility spillover, with a special focus on types of investment horizons, and how the connectedness structure evolves during the COVID-19 outbreak. Empirical results suggest that there is strong evidence of volatility spillovers among global stock markets, and the COVID-19 pandemic further strengthens such volatility spillovers. However, the structure of the frequency connectedness changes gradually when compared to the full sample period. We further investigate if economic policy uncertainty (EPU) affects volatility spillovers among global stock markets. The results suggest that EPU significantly affects the connectedness among global stock markets, particularly during the COVID-19 pandemic period. Overall, the findings suggest that volatility spillovers across international stock markets vary with time horizons and market conditions, which contributes to the academic literature on modelling global volatility spillovers. Practically, the findings of the study contribute to investors and policymakers in adjusting trading strategies and monitoring market risks.

The ESG ratings have been focused in response to the requirements for green development. However, the uncertainty created by ESG disagreements has caused market participants to question their reliability. This study empirically examines how ESG disagreements affect stock price crash risk based on data from Shanghai and Shenzhen A-share listed companies. We find that ESG disagreement significantly reduces stock price crash risk and that this relationship is largely driven by environmental disagreement. The mechanism analysis suggests that ESG disagreement increases media attention, subsequently leading to a reduction in stock price crash risk. Additional analysis shows that the driving effect of environmental disagreement is more significant in non-heavy-polluting industries. Positive environmental protection policies help reduce stock price crash risk.

This study examines the effects of political affiliations as an external governance element on various aspects of the IPO procedure in China. Within China, the significance of political connections is widely recognized as a notable external governance factor capable of exerting influence over both the IPO process. Utilizing a distinctive dataset comprising IPO information from 1856 firms in China spanning the period between 2014 and 2021, the primary objective of this research is to demonstrate that companies with political affiliations have a higher probability of experiencing underpricing, coupled with an increased likelihood of attracting investments from retail investors. Furthermore, these firms tend to attract prestigious underwriters and more underwriter subscriptions, despite having to pay higher floating costs and underwriting fees. Lastly, the study demonstrates that political connections are especially beneficial for firms during market uncertainty, such as the recent pandemic. Political connections act as monitors, reducing information asymmetry and signaling positive aspects of the firms to investors. To strengthen the main conclusions, the study conducts various robustness tests, including PSM and subsample analysis. Overall, the research adds to the existing literature on the crucial role of political connections in promoting IPO practices and reducing information asymmetry through monitoring and support.