On the Safe-Haven Ability of Bitcoin, Gold, and Commodities for International Stock Markets: Evidence from Spillover Index Analysis

Stock market is susceptible to various external shocks for its tight dependence on economic fundamentals, financial speculation, and fragile emotions in massive traders, making it a very risky market for investors. In this paper, we aim to identify whether commonly recognized safe-haven assets, that is, bitcoin, gold, and commodities, can provide investors with effective hedging utility in international stock markets, especially during periods of extreme market turbulence. By using the spillover index method based on the TVP-VAR model, we find that firstly, bitcoin, gold, and commodities can only offer weak hedging effects on stock markets. Furthermore, their abilities to act as a safe haven are ranked as: commodities > gold > bitcoin. Secondly, in general, we have observed the increasing hedging ability of these safe-haven assets in times of extreme market turmoil. Thirdly, among international stock and safe-haven asset markets, the world and the developed stock markets act as the net spillover transmitters, while bitcoin, gold, and commodities are the net recipients. Lastly, the total spillover effects are time-varying and increase significantly after the outbreak of extreme events.

Are initial public offerings significant to firm performance in an emerging stock market? Evidence from China

urpose:This study investigates firm performance after going public and explores whether Initial Public Offerings (IPOs) contribute to it.Design/methodology/approach: This study employs comprehensive regression models to examine IPO significance to both operating performance and market performance.Findings/results: It suggests that IPO firms retain their growth over the first 3 years after going public, but the growth does not sustain after the third year in terms of profit-related indicators, which is distinguishing from prior research. IPOs may contribute to firms’ market performance only, they are insignificant to firms’ operating performance in general, whilst industry-adjusted evidence suggests that IPOs are negatively associated with operating performance in terms of return on assets, return on sales and debt to assets.Practical implications: The practical implication for managers is to spend more IPO capitals on business operations to maximise firm value.Originality/value: Market value is taken into account, whilst operating performance is considered only by prior research, and it presents some different findings from prior studies based on developed stock markets.

Stocks Abnormal Returns and Rate of Dividend Announcements

The present research study examined the impact of different dividend rate announcements on stocks prices in the Indian stock market. Stocks selected from S&P BSE 500 index and study period from 2008 – 2017. The sample used for this study is 1755 pure cash dividend announcements (492 large-caps, 425 mid-caps, and 838 small-caps). Dividend rates are classified into six classifications to test the stocks' abnormal returns to different dividend classifications. Event methodology market model used to calculate Average Abnormal Returns (AAR) and Cumulative Average Abnormal Returns (CAAR). The results were observed twenty-one times based on market capitalization and dividend rate wise for a final dividend announcement. The results of the study are not the same for different dividend rate classifications and different market capitalizations. The study found positive abnormal returns on event day in most of the classifications, and it is similar to Litzenberger and Ramaswamy (1982), Asquith and Mullins Jr (1983), Grinblatt, Masulis and Titman (1984), Chen, Nieh, Da Chen, and Tang (2009) and many previous research results studied in major developed stock markets and emerging stock markets. Full sample and small-cap final dividend rate 100 percent to 199 percent average abnormal returns are positively significant, and other final dividend rate classification abnormal returns are positive in most of the observations, but returns are not significant. Large-cap average abnormal returns are more sensitive to different dividend rates, and small-cap reacts positively in all classifications. So, different market capitalization final dividend actions impact on stocks in India varies in different dividend rate classifications.

Artificial intelligence applied to investment in variable income through the MACD (moving average convergence/divergence) indicator

PurposeThis study aims to determine whether, by means of the application of genetic algorithms (GA) through the traditional technical analysis (TA) using moving average convergence/divergence (MACD), is possible to achieve higher yields than those that would be obtained using technical analysis investment strategies following a traditional approach (TA) and the buy and hold (B&H) strategy.Design/methodology/approachThe study was carried out based on the daily price records of the NASDAQ financial asset during 2013–2017. TA approach was carried out under graphical analysis applying the standard MACD. GA approach took place by chromosome encoding, fitness evaluation and genetic operators. Traditional genetic operators (i.e. crossover and mutation) were adopted as based on the chromosome customization and fitness evaluation. The chromosome encoding stage used MACD to represent the genes of each chromosome to encode the parameters of MACD in a chromosome. For each chromosome, buy and sell indexes of the strategy were considered. Fitness evaluation served to defining the evaluation strategy of the chromosomes in the population according to the fitness function using the returns gained in each chromosome.FindingsThe paper provides empirical-theoretical insights about the effectiveness of GA to overcome the investment strategies based on MACD and B&H by achieving 5 and 11% higher returns per year, respectively. GA-based approach was additionally capable of improving the return-to-risk ratio of the investment.Research limitations/implicationsLimitations deal with the fact that the study was carried out on US markets conditions and data which hamper its application in some extend to markets with not as much development.Practical implicationsThe findings suggest that not only skilled but also amateur investors may opt for investment strategies based on GA aiming at refining profitable financial signals to their advantage.Originality/valueThis paper looks at machine learning as an up-to-date tool with great potential for increasing effectiveness in profits when applied into TA investment approaches using MACD in well-developed stock markets.

INVESTIGATION OF THE RELATIONSHIP BETWEEN TURKEY AND DEVELOPED STOCK MARKETS IN THE PANDEMIC PERIOD: ARDL BOUND TESTING APPROACH

The integration of stock markets is an essential issue for international investors who aim to make short and long term investments. This paper examines Turkey and developed stock markets co-movements during the pandemic. International portfolio diversification advantages are investigated for Turkish investors who have a portfolio in developed markets. For this purpose, the long-term relationship between stock markets is analyzed using the Autoregressive Distributed Lag (ARDL) bound test. The study covers January 2019 and April 2021, and this period is divided into two separate periods, pre-pandemic and pandemic. The results of ARDL bounds tests have not found a cointegration relationship between stock markets in both the pre-pandemic period and the pandemic period. Granger causality test results show that NIKKEI 225 (Japan), DAX (Germany), FTSE 100 (United Kingdom) and CAC 40 (France) are the cause of BIST 100 (Turkey) in the pre-pandemic period. However, Granger causality test results show that there is no causality relationship during the pandemic period. Turkish stock market investors investing in developed stock markets will benefit from portfolio diversification in the long term.

COVID-19 and overconfidence bias: the case of developed, emerging and frontier markets

PurposeThe main purpose of the present study is to delve into the overconfidence bias in global stock markets during both pre COVID-19 and COVID-19 phases.Design/methodology/approachThe present study makes use of daily adjusted closing prices and volume of the broad market indices of 46 global stock markets over a period ranging from July 2015 till June 2020. The sample period is split into pre COVID-19 and COVID-19 phases. In order to test the overconfidence fallacy in the chosen stock markets, bivariate market-wide vector auto regression (VAR) models and impulse response functions (IRFs) have been employed in both phases.FindingsA highly significant contemporaneous relationship between market return and volume appears to be more pronounced in the Japanese, US, Chinese and Vietnamese stock markets in the pre COVID-19 era for the relevant coefficients are positive and highly significant for most lags. Coming to the period of turbulence, the present study discovers strong overconfident behavior in the Chinese, Taiwanese, Turkish, Jordanian and Vietnamese stock markets during COVID-19 phase.Practical implicationsA stark finding is that none of the developed stock markets reveal strong overconfidence bias during pandemic, suggesting a loss or decline in the investors' confidence. Therefore, the regulators should try to regain the investors' trust and confidence in the markets by ensuring honest, fair and transparent practices. The money managers should reduce the transaction cost to encourage trading and educate investors to hold a well-diversified portfolio to mitigate risk in the long run. The governments may launch recovery packages focusing on sustaining and improving economic activities. Finally, a better investment culture may be built by the corporate houses through good corporate governance practices to regain lost trust.Originality/valueThe present study appears to be the very first attempt to gauge overconfidence bias in the wake of a recent COVID-19 pandemic.

Forecasting developed and BRICS stock markets with cryptocurrencies and gold: generalized orthogonal generalized autoregressive conditional heteroskedasticity and generalized autoregressive score analysis

PurposeThe purpose of this paper is threefold. First, it models and forecasts the risk of the five leading cryptocurrencies, stock market indices (developed and BRICS) and gold returns. Second, it conducts different backtesting procedures forecasts. Third, it focuses on the hedging potential of cryptocurrencies and gold.Design/methodology/approachThe authors used the generalized autoregressive score (GAS) models to model and forecast the risk of cryptocurrencies, stock market indices and gold returns. They conduct different backtesting procedures of the 1% and 5%-value-at-risk (VaR) forecasts. They also use the generalized orthogonal generalized autoregressive conditional heteroskedasticity (GO-GARCH) model to explore the hedging potential of cryptocurrencies by estimating the dynamic conditional correlation between cryptocurrencies and gold, on the one hand, and stock markets on the other hand.FindingsWhen conducting different backtesting procedures of VaR, our finding suggests that Bitcoin has the highest VaR among cryptocurrencies and Gold and the BRICS indices returns have lower VaR compared to the developed countries. Finally, we provide evidence that the risks among developed stock markets can be hedged by Bitcoin and Gold. Bitcoin can be considered as the new Gold for these economies. Unlike Bitcoin, Gold can be considered as a hedge for Chinese and Indian investors. However, Gold and Bitcoin can be considered as diversifier assets for the other BRICS economies while Dash and Monero are diversifier assets for developed stock markets.Originality/valueThe first paper's empirical contribution lies in analyzing optimal forecast models for cryptocurrencies (other than Bitcoin) returns and risk. The second contribution consists of studying the hedging potential of five leading cryptocurrencies. To the best of our knowledge, no previous studies have investigated the role of cryptocurrencies for BRICS investors.