An empirical comparison of stock market bubbles

Financial asset bubbles occur due to systematic and continuous differences between fundamental and market values. Due to high growth periods and foreign capital inflows, bubbles are also seen in stock market indexes, especially in emerging market economies. This study analyzes the existence of bubbles in BIST100, IDX COMPOSITE, BOVESPA, MDEX, NIFTY 50, SHANGAI, and S&P 500 stock markets for the period 2009:01-2021:06. RADF, SADF, and GSADF tests are applied to detect bubbles on stock market closing prices. In addition, the emergence and demise dates of the bubbles are determined by employing the date-stamping method. The GSADF test gives more effective results and determines bubbles with different durations in all stock markets, except the S&P 500. The results reveal that the most inefficient market is IDX COMPOSITE, and S&P 500is the most efficient market. The analysis includes the S&P 500, the world's most liquid and most prominent stock market, for comparison. In this respect, bubbles occur more in emerging market exchanges. The findings also confirm the validity of the rational bubble law.

Inflation and Hyperinflation Countries in 2018–2020: Risks of Different Assets and Foreign Trade

Since the global financial crisis (2008–2009), central banks and governments in developed countries have relied upon loose monetary and financial policy. In the coronavirus pandemic era, these policies were taken even more to the extreme. In 2021, countries around the world started to experience product availability issues, and inflation in some cases was extremely high. There has been debate about the possibility of persistent high inflation. However, risks to assets and foreign trade in this new situation are unknown as all important hyperinflation cases are from decades to century-old. It is important to know what kind of implications high inflation has on modern economies. Therefore, in this study, 10 countries with the highest inflation were selected to be examined in the period of 2018–2020. In these countries, currencies lost a considerable amount of their value against US dollar in 2018–2020. Stock market indexes in many cases provided very high returns in local currency terms; however, against the US dollar, the index yield changed for the substantially negative. Apartment prices in general declined as well. In foreign trade, imports generally declined, while exports were mixed or even increased. However, it should be noted that all of these observations are influenced by the pandemic era and special circumstances of a particular country.

Changes in the Stock Market of Food Industry Companies during the COVID-19 Pandemic—A Comparative Analysis of Poland and Germany

The COVID-19 pandemic had a dramatic effect on the world economy, leading to disturbances in the global agri-food system. Disrupted supply chains caused instability in the market resulting in mixed reactions among market participants. The balance in the access and availability of food was disturbed at various levels starting from local up to international. Partial lockdowns of economies affected the equilibrium on the labor market in the food sector, the level of income and food security. The aim of this study was to determine the effect of shock caused by the COVID-19 pandemic on rates of return from shares of companies in the agri-food sector listed in Poland and Germany, as well as indicate dependencies between restrictions imposed by the investigated countries and changes in the rates of return from shares as a result of the pandemic. The source of data for the analyses of the capital markets in Poland and Germany was the Thomson Reuters database. In order to determine the effect of shock caused by the coronavirus pandemic and restrictions imposed by the states on the capital market the abnormal rates of return were calculated for shares of 24 Polish and 23 German companies from the food sector. The investigated Polish companies were listed on the Warsaw Stock Exchange, while the German companies were listed on the Frankfurt Stock Exchange and other stock exchanges in Germany. Calculations were based on stock market indexes: for the Polish stock exchange it was WIG and WIG-food, while for the German capital market it was DAX and DAX Food & Beverages. In this study the Stringency Index was also used as a tool to follow the response of the governments to the coronavirus pandemic. The results indicate that following the pandemic outbreak large reductions were observed for cumulative rates of return from shares as a consequence of the pandemic both in Poland and Germany. Abnormal cumulative rates of return for the investigated companies were comparable. Markedly greater increases in abnormal rates of return were recorded for the Polish companies of the food sector listed at the Warsaw Stock Exchange. The Stringency Index indicates that restrictions imposed by the German authorities in response to the coronavirus pandemic were slightly more radical than those introduced by the Polish government.

Efficient or Fractal Market Hypothesis? A Stock Indexes Modelling Using Geometric Brownian Motion and Geometric Fractional Brownian Motion

In this article, we propose a test of the dynamics of stock market indexes typical of the US and EU capital markets in order to determine which of the two fundamental hypotheses, efficient market hypothesis (EMH) or fractal market hypothesis (FMH), best describes market behavior. The article’s major goal is to show how to appropriately model return distributions for financial market indexes, specifically which geometric Brownian motion (GBM) and geometric fractional Brownian motion (GFBM) dynamic equations best define the evolution of the S&P 500 and Stoxx Europe 600 stock indexes. Daily stock index data were acquired from the Thomson Reuters Eikon database during a ten-year period, from January 2011 to December 2020. The main contribution of this work is determining whether these markets are efficient (as defined by the EMH), in which case the appropriate stock indexes dynamic equation is the GBM, or fractal (as described by the FMH), in which case the appropriate stock indexes dynamic equation is the GFBM. In this paper, we consider two methods for calculating the Hurst exponent: the rescaled range method (RS) and the periodogram method (PE). To determine which of the dynamics (GBM, GFBM) is more appropriate, we employed the mean absolute percentage error (MAPE) method. The simulation results demonstrate that the GFBM is better suited for forecasting stock market indexes than the GBM when the analyzed markets display fractality. However, while these findings cannot be generalized, they are verisimilar.

An Empirical Study on Movement of Stock Market of BRIC Economies- Are they Co-Integrated?

The major objective of this article is to assist the BRICS nations’ foreign investment decisionmaking process, as well as the creation or changes in policies by these nations’ characteristics. The context is crucial for foreign investors considering diversification advantages internationally, as well as policymakers responding to the aforesaid economies’ growth. This study examines the interconnections between the stock indexes of the BRIC economies. The goal of the research is to look at the long-term link between stock market indexes. From January 2010 to December 2020, the researcher utilized the index’s monthly closing price. To get the ADF at the first-order difference, all of the data is utilized in its raw form. The co-integration method is employed to determine the connection between stock indexes. The causal influence on stock market indices is studied using Granger causality. The sample considers countries such as Brazil, Russia, India, and China. The goal of the research is to look at the long-term link between stock market indexes. It is found that Sensex has the highest return among others, followed by SHCOMP, MOEX and BOVESPA. It is also found that the standard deviation of MOEX is high, followed by SENSEX, SHCOMP and BOVESPA. From the causality analysis, it is found Bi-directional relationship between India and China stock market. Whereas in the case of the other two markets, i.e., Brazil and Russia, the relationship with the Indian stock market are neither Uni-directional nor Bi-directional.

Predicting equity premium with adjusted dividend-price ratio: the USA and international evidence

Purpose This paper aims to achieve two main objectives. The first is to introduce a suitable adjustment to the conventional dividend-price ratio, which would address econometric concerns and improve the predictability of the equity premium. The second is to compare the predictive performance of the newly introduced adjusted dividend-price ratio with the conventional dividend-price ratio. Design/methodology/approach The authors hypothesize that the adjusted dividend-price ratio will have better predictive power and forecasting quality for equity premium compared to the conventional dividend-price ratio. To test the hypothesis, the authors predict equity premium with both variables on a sample of 11 developed and emerging market indexes over a period spanning June 1995 to March 2017. To accommodate time variation in parameter values or structural breaks in the data, the authors conducted a fixed window rolling regressions using both variables. A variety of forecast techniques including magnitude and sign accuracy measures are applied to compare the performance of forecasts. Findings The adjusted dividend-price ratio is shown to be stationary and has both lower persistence and variability compared with the conventional dividend-price ratio. The authors find that the adjusted dividend-price ratio provides superior out-of-sample (OOS) performance compared to the conventional dividend-price ratio, for both size and sign accuracy, in forecasting equity premium for the majority of the countries in the sample. Research limitations/implications This paper introduces an easy-to-follow modification in the conventional dividend-price ratio that can be replicated by researchers and practitioners alike. However, the study has a limitation in that it does not capture the impact of dividend-paying firms within each index on the predictive ability of the adjusted dividend-price ratio. Practical implications The knowledge of equity premium predictability is important in implementing market-timing strategies and could be beneficial for portfolio and risk management. The newly introduced variable is easy to construct using widely available data without the need for complex econometric estimation. Investors can use this variable to predict equity premiums in international markets, both developed and emerging. The findings of this paper will be relevant to financial analysts, portfolio managers, investors and researchers in international finance. For example, by using the adjusted dividend-price ratio, investors would see up to 0.5% improvement in their OOS monthly forecasts of the equity premium. Originality/value To the best of the authors’ knowledge, this is the first paper that proposes adjustment in the conventional dividend-price ratio based on the past observations of the most recent quarter. In this way, the paper offers fresh insight that dividend-price ratio is still useful to predict equity premium albeit, after some adjustments and modifications. The findings of the paper would result in renewed interest in using the dividend-price ratio as a predictor of the equity premium.

Quantifying Time-Frequency Co-movement Impact of COVID-19 on U.S. and China Stock Market Toward Investor Sentiment Index

The worldwide spread of COVID-19 dramatically influences the world economic landscape. In this paper, we have quantitatively investigated the time-frequency co-movement impact of COVID-19 on U.S. and China stock market since early 2020 in terms of daily observation from National Association of Securities Dealers Automated Quotations Index (NDX), Dow Jones Industrial Average (DJIA), Standard & Poor's 500 Index (SPX), Shanghai Securities Composite Index (SSEC), Shenzhen Securities Component Index (SZI), in favor of spatiotemporal interactions over investor sentiment index, and propose to explore the divisibility and the predictability to the volatility of stock market during the development of COVID-19. We integrate evidence yielded from wavelet coherence and phase difference to suggest the responses of stock market indexes to the COVID-19 epidemic in a long-term band, which could be roughly divided into three distinguished phases, namely, 30–75, 110–150, and 220–280 business days for China, and 80–125 and 160–175 after 290 business days for the U.S. At the first phase, the reason for the extreme volatility of stock market mainly attributed to the sudden emergence of the COVID-19 epidemic due to the pessimistic expectations from investors; China and U.S. stock market shared strongly negative correlation with the growing number of COVID-19 cases. At the second phase, the revitalization of stock market shared strong simultaneous moves but exhibited opposite responses to the COVID-19 impact on China and U.S. stock market; the former retained a significant negative correlation, while the latter turned to positively correlated throughout the period. At the third phase, the progress in vaccine development and economic stimulus began to impose forces to stock market; the vulnerability to COVID-19 diminished to some extent as the investor sentiment indexes rebounded. Finally, we attempted to initially establish a coarse-grained representation to stock market indexes and investor sentiment indexes, which demonstrated the homogenous spacial distribution in the vectorgraph after normalization and quantization, implying the strong consistency when filtering the frequent small fluctuations during the evolution of the COVID-19 pandemic, which might help insights into the prediction of possible status transition in stock market performance under the public health issues, potentially performing as the quantitative references in reasonably deducing the economic influences.

Sensitivity of the Art Market to Price Volatility

The purpose of the article: The art market becomes very popular among investors, when there is strong turbulence on the stock market. In times of calm, the art market is used by investors to diversify risk and build more efficient investment portfolios according to the Markovitz’s theory. The aim of this paper is to: (i) present the peculiarity of investment on the art market, represented by art market indexes in comparison to traditional investments in other financial market segments (money market, equity indexes and commodity market), (ii) to verify the hypothesis of normality of the distribution of rates of return of the analyzed art market indices as well as (iii) to analyze calendar effects occurrence on the art market. Methodology: Comparison of rates of return on the stock, bond, commodity and money markets with rates on the art market in four different time intervals. For each of the analyzed periods, an income-risk map was presented, taking into account the spectrum of financial instruments, including six art indexes: Old Masters, 19th Century, Modern art, Post War art, Contemporary art and Global art. The hypothesis of normality of the distribution of rates of return of the art market indices for four analyzed periods was verified with the use of Jarque-Bera test. Results of the research: Comparison of rates of return on the stock market and art market leads to the conclusion that their relationship depends on the period chosen. For two of the analyzed periods, the rates of return on the stock market were higher than on the art market, but for others periods, the opposite. The distribution of quarterly rates of return resulted to be a normal distribution for almost all of analyzed indices and time periods. Calendar effects were observed in the case of four analyzed indexes.

Composition of portfolios by pairs trading with volatility criteria in the Brazilian market,

ABSTRACT The objective of this study was to understand how the shares’ volatility affects the portfolios’ dynamics formed using the model of pairs trading in the Brazilian stock market. This article distinguished itself by bringing new evidence about the effects of volatility in the pairs trading model not covered by previous studies, expanding the sample size analyzed in the Brazilian stock market. The chosen theme’s relevance is that investors can use pairs trading or long-short models to build their portfolios. The use of cointegration concepts probabilistically contributes to portfolios’ formation weakly correlated to the market indexes with superior performance. This article impacts the area by contributing new evidence for better use of the model in the analysis of investments. From January 2016 to December 2018, the 90 most liquid assets of Bolsa, Brasil, Balcão (B3) were analyzed, totaling 5,927,400 possible pairs. The Augmented Dickey-Fuller test and subsequent backtesting of the pairs in the proposed period were used to evaluate the cointegration criteria. Statistical analysis was performed by parametric and non-parametric tests and Pearson and Spearman correlation analyses. The results found indicated that the formation of portfolios by pairs trading with dependent assets with the criterion of higher levels of volatility (20 periods) presented a superior performance. These findings can be justified by a better risk and return ratio for the portfolio, measured by the Sharpe Index of the returns obtained concerning the portfolio’s volatility, compared to a portfolio formation based on a random selection of the pairs. In addition, the results also showed a low correlation of returns concerning the market index. Therefore, the application of the statistical cointegration analysis methodology alone does not guarantee results that are different from the market average.

The USA–China trade policy uncertainty and inference for the major global south indexes

PurposeThe recent dynamics of trade policy, especially that is associated with the United States of America (USA) and China, has not only triggered policy adjustments in two economies, it has also implied an uncertainty spillover to other economies across the globe. Consequently, the current study attempts to examine the effect of uncertainties in the USA–China trade policies on stock market indexes. In addition, the cointegration evidence between the USA–China trade policy uncertainty index and of the leading Global South fragile quintet (Brazil, Indonesia, South Africa, India and Turkey) stock market indices is investigated.Design/methodology/approachMainly, the FMOLS and DOLS Granger causality analysis with cointegration coefficient estimators were employed for the dataset over the monthly data period of March 2003 and July 2019.FindingsAccordingly, the study found a long-term relationship between the USA–China Trade Policy Uncertainty index and the stock exchange indexes. In addition, a causal relationship was established from the change in the USA–China Trade Policy Uncertainty index to the change in the stock market indexes of almost all of the examined countries (Brazil, Indonesia, South Africa, India and Turkey). In addition, the nonlinear Autoregressive Distributed Lag approach further offers evidence of asymmetric relationship among the examined indicators.Originality/valueMoreover, this study contributed to the existing literature because it employed the indexes of BIST100, BOVESPA, BSE Sensex 30, IDX Composite and South Africa 40 in a novel approach. Thus, the study posited a useful policy guideline for associated economic uncertainties arising from the trade dispute, such as the case of the world’s two largest trading giants or partners (i.e. the USA and China).