The current study examines the performance of 76 Japanese equity Exchange Traded Funds (ETFs) over the period 1/1/2018-12/31/2022. Performance is estimated in several ways, that is, raw returns, alphas from single- and multi-factor regression models, and risk-adjusted returns. The market timing skills of ETF managers are examined too. The results reveal that, on average, the examined ETFs do not produce any material alpha. The results also indicate that the risk factors suggested by Fama and French (1993 & 2015) are more or less capable of explaining the performance of the Japanese ETFs. Finally, the findings show that 21% of ETF managers possess some sort of market timing skills. However, the managers fail to time the volatility of the stock market.

Information leakage in the stock market has been widely proven. Information disclosure is sometimes uneven, and there is significant information asymmetry between ordinary investors and professional institutional investors. In this paper, Regression Discontinuity design (RDD) model is first employed to analyze the information leakage issues. Based on the daily closing stock prices of 15 capital service listed companies, we analyze the difference between the market reaction time and the disclosure time of two stamp tax policies. We found that the sample policies information may leaked to the market about two days earlier. This paper provides a new method analyzing information leakage.

This paper intends to analyze efficiency, in its weak form, in the stock markets of Austria (ATX), Poland (WIG), the Czech Republic (PX Prague), Hungary (BUX), Croatia (CROBEX), Serbia (BELEX 15), Romania (BET), and Slovenia (SBI TOP), from February 16, 2018, to February 15, 2023. To achieve the research aim, we intend to answer the following research question: i) Have events in 2020 and 2022 heightened the persistence of Central European stock markets? Results suggest that persistence in returns has increased significantly during the first wave of Covid-19 and the Russian invasion in the year 2023, but we also saw that most stock markets already exhibit long memories, implying that the research question has been partially validated. This research can provide valuable insights to investors, policymakers, and others interested in financial risk management.

With the daily data from Nov 20, 2019 to Oct 31, 2022, this paper examines the dynamic nonlinear effects of RCEP on Dual Circulation and Greater Bay Area stock market from a quantile perspective. The rolling window quantile regressions detect the positive effects of RCEP on Dual Circulation and Greater Bay Area stock markets with significant time-varying characteristics. Meanwhile, QQ results show that the impacts from RCEP index are more significant under extreme conditions. In addition, we further use a nonparametric QC test to provide evidence on the predictive power of RCEP for Dual Circulation and Greater Bay Area with stock market.

This study considers the effects of disclosure conditions on firms' investment decisions when facing an identical competitor in multiple markets. Assuming that there are congestion costs between multiple investments to reduce marginal cost for each market, this study focuses on the cases where the disclosure conditions may differ by market. Like previous studies on single Cournot competition, these results show that firms invest more in the observable investment markets than in the unobservable markets under symmetric disclosure conditions. However, firms invest more in the unobservable market if there are asymmetric disclosure conditions.

Previous literature shows that the price-discovery ability of options market varies substantially over time. Using data of Shanghai Stock Exchange 50 exchange-traded fund options, this paper shows that options prices contribute relatively less to price discovery during low-sentiment periods, but the price-discovery ability of options market remains unchanged during high-sentiment periods. These results suggest that change in aggregate investor sentiment is an important source of the time variation in options’ price discovery ability. Moreover, the options market experiences greater bid-ask spreads when investor sentiment is lower, supporting a “transaction costs mechanism.” This paper fulfills related literature on the time variation in options’ price-discovery ability.

Cryptocurrencies have gained popularity over the past five to six years. Most recently, events like the FTX bankruptcy fueled the interest in regulation. Moreover, it is possible that the FTX event disrupting the cryptocurrency market was a factor in Silicon Valley Bank's failure. While several countries consider regulation, from soft regulation, like Japan, to more rigid standards, like the total ban in China, we study the effect of other news or events on cryptocurrency prices. This paper looks at historical closing prices for Bitcoin, the largest of the cryptocurrencies, and how prices react to various events. Then we focus on modeling the time series considering an 'event,' China's ban on cryptocurrency exchanges, using intervention analysis. We find that intervention analysis provides a reliable approach to quantifying the impact regulation may have on cryptocurrency pricing.

We examine the relationship between labour market flexibility, as measured by employment protection legislation (EPL), and long-term economic growth in developed economies from 1995 to 2022. We consider conflicting viewpoints on whether rigid labour market regulations hinder or promote economic growth. Employing a cross-country regression model, controlling for factors including initial GDP per capita, capital formation, human capital, research and development, and indicators of macroeconomic performance, we find that only initial income level and capital formation significantly influence long-run growth in real per capita GDP. EPL has no significant impact in the long run, challenging the pre-2000 advocacy of labour market deregulation by major international organisations. We conclude that policy should focus on supporting the investment decisions of the private sector without distorting market mechanisms.

This work investigates the strength and the pattern of linkages among the three markets of qualitatively differentiated milk (i.e., conventional, organic without heymilk, and organic with heymilk) in Austria using the flexible TVP-VAR frequency connectedness approach and information on prices from 2018 to 2023. The main empirical findings are: (a) Taken together, the markets have maintained a moderate degree of connectedness to each other.  (b) Price linkages have been frequency-dependent; much of the adjustments to incoming information have been completed within 3 months. (c) Connectedness has been asymmetric; the highest quality (organic with heymilk) has been a net transmitter of price shocks to organic without heymilk. (d) The intensity of connectedness has been time-varying; however, the internal structure of the market network (i.e., the net transmitters and receivers of price shocks) has remained fairly stable.

China's carbon emission trading market has been formally established, but few studies have been conducted to analyze the impact of this policy on the regional urbanization level. Therefore, this paper evaluates whether the carbon trading pilot policy can enhance the regional urbanization level in China through the difference-in-differences method and analyzes the mediating role of industrial structure upgrading in this process. The results prove that the carbon trading market policy can accelerate the transformation and upgrading of industrial structure in the region so that it promotes the development of regional urbanization. Moreover, the effects of the policy are concentratedly manifested in the eastern region of China.

We assess the impact of the Strategic Economic Plan on Singapore’s long-term GDP per capita. To our knowledge, we are the first to evaluate the effect of the 1991 plan on Singapore’s successful growth trajectory using methodologies aimed at causal identification. In other words, this article applies the Synthetic Control method and World Bank data from 1970 to 2018. We estimate an average increase of 6,641.71 US$ in Singapore’s GDP per capita. Results remain robust to placebo and leave-one-out tests and the Synthetic Difference-in-Differences method.

The implementation of environmental protection strategy necessarily requires mapping the amount of capital stock of environmental infrastructure. Through the Weibull distribution function and hyperbolic age-decreasing efficiency model, the provincial environmental infrastructure capital stock in China from 1980 to 2018 is measured cautiously, and its spatial dynamics with the generated pollutants is analyzed using the center of gravity method. It is found that: the spatial distribution of environmental infrastructure capital stock is uneven, and the unevenness in the east-west direction is greater than that in the north-south direction, but the unevenness in the east-west direction is narrowing while the north-south direction is widening; the spatial and temporal distribution of environmental infrastructure capital and environmental pollution vary greatly, and the spatial management of environmental pollution is less accurate.

Investment funds are increasingly focusing on ESG issues, seeking to contribute to improving environmental, social, and governance concerns. ESG-focused investing involves promoting good ESG performance and may result in a decrease in expected financial returns. This may lead to a conflict between solely profit-focused shareholders and ESG-focused investors, who may respond accordingly. As such, a firm's ESG commitment may trigger several events that can affect the stock price. A firm's ESG commitment may increase its stock price; however, the end of such commitment may also positively affect the stock price. Hedge funds may consider this in their activism which may reshape the way hedge funds target firms and influence their actions accordingly.

This paper shows mainly the following results. 1) The debt to GDP ratio cannot diverge to infinity, that is, fiscal collapse is impossible. The necessary condition for this result is that the propensity to consume from the asset is positive. 2) The divergence of the debt to GDP ratio is prevented by inflation when the interest rate on government bonds is considerably higher than the real growth rate, and the inflation rate which is sufficient to prevent divergence of the debt to GDP ratio is smaller than the interest rate on government bonds. Only an inflation rate slightly greater than the difference between the interest rate on government bonds and the sum of the real growth rate and the propensity to consume from the asset is required. This inflation is not caused by policy but occurs naturally.

I will show that if the propensity to consume from savings satisfies appropriate conditions, the debt-GDP ratio will not grow infinitely large and fiscal collapse will not occur. Using a basic macroeconomic model, with an overlapping generations model in mind, we show the following results: 1) The budget deficit including interest payments on the government bonds equals an increase in the savings from a period to the next period. 2) If the savings in the first period is positive, we need budget deficit to maintain full employment under constant prices or inflation in the later periods. 3) Under an appropriate assumption about the propensity to consume from savings, the debt-GDP ratio converges to a finite value. It does not diverge to infinity. The larger the propensity to consume from savings, the smaller the budget deficit required to achieve full employment. The larger the propensity to consume from savings, the less likely it is that the debt-GDP ratio will become large.

By an endogenous growth model with a two-period overlapping generations structure, I examine the existence of a budget deficit in an economy that endogenously grows by investments of firms. The consumers leave bequests to their descendants and hold money as a part of their savings. I use a Barro-type utility function, where people include the utility of their children in their own utility. The main results are as follows. 1) A budget deficit is necessary for full employment under constant prices. 2) Inflation is induced if the actual budget deficit is greater than the value at which full employment is achieved under constant prices. 3) If the actual budget deficit is smaller than the value which is necessary and sufficient for full employment under constant prices, a recession occurs. Therefore, a balanced budget cannot achieve full employment under constant prices. I do not assume that the budget deficit must later be made up by a budget surplus. I use a Barro-type utility function to prove the necessity (or inevitability) of a budget deficit instead of the neutrality of government debt. In the appendix of this paper, I show that if money, as well as goods, are produced by capital and labor, a budget deficit is not necessary for full employment under constant prices.

This study aims to examine the effects of student loan debt on the decisions of U.S. married households to invest in stocks located in non-retirement accounts. Using longitudinal datasets from the 2011 to 2017 U.S. Panel Study of Income Dynamics and a fixed effects logit model, the results show mixed findings. The presence of student debt decreases the probability that married households will own stocks, but the amount of student debt does not show a statistically significant effect. The findings suggest that the incidence of student debt raises the perception of liquidity constraints and debt burden among married households.

Bank deposit is closely related to systemic risks. In addition, considering that resident deposits in China have significant seasonal characteristics, this paper focuses on which component of deposits drives the systemic risk volatility, that is, it can supplement the existing forecast information. We use X-13ARIMA-SEATS to decompose deposit into three subsequences. The research findings show that the forecast effect of subsequence models is better than that of benchmark series. Most importantly, the model with trend component has the best forecast performance.

Based on provincial panel data from 1998-2018, this paper estimates research and development (R&D) factors, and a stochastic frontier analysis (SFA) model is constructed to examine the effects of R&D factors on regional total factor productivity (TFP). The results show that both R&D capital stock and R&D personnel can significantly promote regional TFP, but the productivity-enhancing effect of R&D factors is different between regions. Specifically, R&D capital and R&D personnel can promote TFP in eastern and central provinces, and the promotion effect is not significant in western provinces. In addition, compared with investment-driven regions, innovation-driven regions are more likely to enhance TFP by R&D factors.

The precise prediction of carbon emissions trading prices is the foundation for the stable and sustainable development of the carbon financial market. In recent years, influenced by a combination of factors such as the pandemic, trading regulations, and policies, carbon prices have exhibited strong random volatility and clear non-stationary characteristics. Traditional single-perspective prediction methods based on conventional statistical models are increasingly inadequate due to the homogenization of features and are struggling to adapt to China's regional carbon emissions trading market. Therefore, this paper proposes a multi-perspective fusion-based prediction method tailored to the Chinese market. It leverages carbon emissions trading information from key cities as relevant features to predict the price changes in individual cities. Inspired by the development of artificial intelligence, this paper implements various time series models based on deep neural networks. The effectiveness of the multi-perspective approach is validated through multiple metrics. It provides scientific decision-making tools for domestic carbon emissions trading investors, making a significant contribution to strengthening carbon market risk management and promoting the establishment and rational development of a unified carbon market in China.