ABSTRACT
Purpose: The present study aims to test the Quadratic Programming model for Optimal Portfolio selection empirically. Need for the Study: All the investors who buy financial products are motivated to obtain higher profits or, in other words, to maximise their returns. However, the high returns are often accompanied by higher risks, and avoiding such risks has become the primary concern for all investors. There is a great need for such a model to maximise profits and minimise risk, which can help design an investment portfolio with minimum risk and maximum return. The Quadratic Programming model is one such model which can be applied for selected shares to build an optimised portfolio. Methodology: This study optimises the stock samples using a two-level screening of correlation coefficient and coefficient of variation. The monthly closing prices of the NSE-listed Indian pharmaceutical stocks from December 2019 to January 2022 have been used as sample data. The Lagrange Multiplier method is used to apply the model to achieve the optimal portfolio solution. Based on the market reality, the transaction costs have also been considered. The Quadratic programming model is further optimised to achieve the optimal portfolio for the select stocks. Findings: The traditional portfolio theory and the modified quadratic model gives similar and consistent results. In other words, the modified quadratic model asserts the accuracy of the conventional portfolio model. The portfolio constructed in the present study gives a return much higher than the return of the benchmark portfolio of Nifty Fifty, indicating the usefulness of applying the Quadratic Programming model. Practical Implications: The construction of an optimal portfolio using the traditional or modified Quadratic model can help investors make rational investment decisions for better returns with lower risks. © 2023 by Chetna and Dhiraj Sharma.
ABSTRACT
Purpose: This work investigates the relationships between stock exchange crashes and accounting scandals.Design/methodology: We analyze the main accounting scandals and stock exchange crashes that occurred between 1980 and 2020. Findings: First of all, it was verified that a stock market crash occurred in the years in which most of the accounting scandals took place (or within the next three years). This evidence is consistent with much of the previous literature. Second, an average of 5.4 years has been estimated as the period of time that elapses between the time a company starts engaging in accounting deception and the moment when it is discovered and the scandal breaks out. Third, it has been found that accounting deception is more likely to occur in years with stock market crashes and in the years immediately following. The literature review revealed no evidence supporting the two latter hypotheses.Research limitations/implications: This exploratory work has several limitations. First of all, only scandals that have been reported on websites in Spanish and English have been analyzed. Therefore, the sample may be biased, giving more weight to companies from Anglo-Saxon and Spanish-speaking countries. Second, the sample was made up of a small number of companies (53), which are those that have met the search criteria used.Practical implications: The findings of this work are relevant today, since a major stock exchange crash has occurred as a result of the coronavirus. Therefore, if the pattern of the most recent decades is repeated, it would be expected that more accounting scandals will come to light in the coming years.Social implications: The conclusions obtained are of great relevance for the different users of the financial information from companies, and also for auditors, consultants and supervisory bodies, since due to the stock exchange crash triggered by COVID-19, they will need to exercise extreme caution in the coming years in relation to financial information.Originality/value: The work provides evidence on the relationship between stock market crashes and accounting scandals, which is a highly relevant topic. The literature review revealed no study using the same methodology or a similar sample of companies.
ABSTRACT
This study examines the tendency of short-term return spillover across Bahrain stocks, bitcoin, and other commodity assets factoring in the dynamic effect of the COVID-19 pandemic. The study employed vector autoregression (VAR) model using the daily returns of Bahrain All Shares Index, bitcoin, crude oil, and gold futures from January 2018 to March 2022. The results showed a persistent unidirectional short-term spillover of return from the Bahrain stock market to the futures gold market for both the period before and during the pandemic. Moreover, the results also showed that the significant positive shock in the bitcoin returns as granger-caused by the returns of the Bahrain stock market is only during the period before the pandemic. Finally, a significant negative contemporaneous short-term effect on the crude oil market returns can be statistically explained by the shocks in the Bahrain stock market only during the COVID-19 period. © 2023 IGI Global. All rights reserved.
ABSTRACT
If the market is efficient, with stock prices accurately reflecting the true risk of an investment, then the issue becomes simpler. While this is true, investors may have a window of opportunity to discover a successful investing strategy if the market is inefficient. The primary goal of this research is to use the Support Vector Machine (SVM) algorithm to predict daily cycles of price increases for the ten largest-cap companies trading on the Hanoi Stock Exchange (HNX) over the Covid-19 timeframe (January 1st, 2019, to December 1st, 2022). Study how the model performs when trained and tested with a moving window. The outcome was an impressive average accuracy of 81.68 percent for the predicting model. © 2023 IEEE.
ABSTRACT
This research analyses the relative efficacy of gold price, financial market, and stock exchange hedging against sectoral and industry-level global stock market returns. Incorporating Gold into equity-based asset allocation techniques and assessing the stock market and financial sector during the COVID-19 epidemic is one way to diversify your portfolio and reduce risk. After orthogonalizing raw returns concerning a robust collection of relevant universal variables, we conduct our analysis inside a bivariate GARCH(p, q) framework. To further assess ideal portfolio proportions and the efficacy of hedging methods, we expand the volatility spillovers study by calculating the optimal weights for a minimal risk portfolio and determining the hedge ratio. In high-volatility environments, our results show which financial market and stock exchange sectors and industries investors should prioritize to minimize the risk and maximize reward. Use of country-specific macroeconomic variables indices to supplement the worldwide index, (3) separate analysis for the COVID-19 first wave due to the existing argument that the pandemic raises unexpected market events and our early data showing co-movement among the three unpredictability metrics during the pandemic. These findings have important implications for portfolio entrepreneurs and business investors looking to buy international equities.
ABSTRACT
This study investigates the main financial technologies adopted by banks to improve their financial performance. The study population consists of commercial banks listed on the Amman Stock Exchange and Abu Dhabi Securities Exchange, and includes financial information and data from 2012 to 2020. A total of 115 questionnaires, consisting of five questionnaires for each bank, were distributed to the study population in Jordan and the United Arab Emirates. The dependent variable is financial performance, while the independent variable is financial technology (FinTech). Multiple linear regression analysis was conducted to test the hypotheses. The results showed that FinTech has a positive effect on both total deposit and net profits. This study recommends that banks be encouraged to adopt inclusive strategies to attain sustainable development.
ABSTRACT
The purpose of this research is to reveal the behaviour of the main Mexican exporting companies during the 2018-2020 period, which covers part of the COVID-19 pandemic phase. The results indicate that it is not viable to invest in this type of companies for the time being, and this is shown empirically through the traditional Markowitz investment portfolio selection methodology and its extension through the Sharpe model. © 2022 Emerald Publishing Limited. All rights reserved.
ABSTRACT
China's wolf warrior diplomacy has attracted worldwide attention since April 2020. There are discussions about the potential negative effects on the Chinese economy. Based on weekly Google Trends data during April 2020 to February 2022, this study creatively created a 'wolf warrior diplomacy index' used as a proxy measuring the aggressiveness or assertiveness of Chinese foreign policy. Using an exponential generalised autoregressive conditional heteroskedastic model, this study finds that the effects of the wolf warrior diplomacy index on the Chinese stock markets, i.e., a proxy variable for the Chinese economy, are insignificant. Various robustness tests and fundamental data also support this conclusion. The implication is that, while a country's foreign policy may potentially impact its economy, its decisive force may be primarily fundamental factors. Copyright © 2023 Inderscience Enterprises Ltd.
ABSTRACT
Human life was affected worldwide during the rough years of COVID-19, including the economic and social disruption that affected tens of millions of people. This research comes to a clear conclusion about which sectors are most affected, how it indirectly affects many other sectors, such as the financial stock exchange, and how it increases the risk of extreme poverty. This paper has arrived at a general conclusion about the stock market in the difficult years of 2019-21 of COVID-19. Different visualization techniques using some of the most popular libraries like Seaborn, Matplotlib, NumPy, and Pandas are used to know the accuracy and main content of a large, combined dataset. Before performing the visualization techniques, this study will combine datasets with different attributes and perform cleaning and integration methods on the combined dataset. The purpose of the project is to shed light on the stock market through an analysis of the daily closing prices of the market. The reason to take this project is for the overall growth of the economy and hope it will help many businesses developers. © 2023 IEEE.
ABSTRACT
This study investigates the influence of oil export and political issues on Iraq's stock exchange using various Ordinary Least Square regression models. The empirical results show that the model's effect is not similar based on the explanatory variables included, such as the Covid-19 outbreak, financial crisis, parliament elections, and ISIS emergence are not significant. In contrast, the internal conflict, oil export, and oil prices are substantial effects on the index of the Iraq stock exchange from (2004 to 2021);researchers in the literature have neglected this market due to its novel establishment after (2003). Moreover, the market capitalization still considers very small compared to the regional financial markets. The study contributes to the existing knowledge because most studies on stock market determinants consider political, economic, democratic, or governmental factors. In contrast, here, most elements included using new measurements, such as the internal conflict by cutting off the financial share of the Kurdistan region from the central state budget. Finally, the analysis incorporates the conclusions with straightforward suggestions that policymakers can use, government, investors, and supervisors to control the stock market risk. © Econjournals.
ABSTRACT
The present paper investigates the impact of the COVID-19 pandemic on the prices of the Italian stock exchange indices. During the pandemic, the global economy as well as financial markets suffered due to isolation and social distancing. Paired models of the dependence of the key indices of the Italian stock exchange on the number of patients, recovered and died were analysed using the least squares method. Further, various tests were performed to verify the feasibility of the Gauss-Markov conditions by applying Gretl tools: White Test for heteroskedasticity of residues, Durbin-Watson test for autocorrelation of residuals and normality of distribution of residuals. Statistically significant regression models were constructed that characterise the impact of morbidity and mortality in the Italian population during the COVID-19 pandemic on the price of 11 key stock exchange indices. Based on this, the study examined the COVID-19 pandemic period in the spring of 2020 in Italy, the results of which revealed a loss in stock returns and high volatility in stock returns during this period compared to the normal study period. The econometric model shows that COVID-19 had a negative impact on stock returns and a number of other stock market indicators in Italy. It was revealed that the number of deaths from coronavirus is statistically significantly interconnected with all key stock exchange indices. © Akbulaev N. N., Ahmadov F. S., Mammadova M. R. Text. 2022.
ABSTRACT
Purpose: The author examine the performance of a number of high short interest stocks along with the prices of the GameStop stock and three major stock exchange indices, particularly for the period after the eruption of the Covid-19 crisis. Design/methodology/approach: With the employment of the complexity–entropy causality plane approach, the author categorize the stock prices in terms of the level of informational efficiency. Findings: The author reported that the efficiency level for the index of the high short interest stocks falls considerably, not only at the onset of the Covid-19 crisis but during the health crisis period at hand. This is translated into proof of less uncertainty in predicting the stock prices of these specific stocks. On the other hand, the GameStop prices exhibit the same behavior as those with the high short interest firms, but change considerably in the middle of the crisis. The reversal of the behavior, by obtaining higher informational efficiency levels, is attributed to the short squeeze frenzy that increased the price of the stock many times over. Among the stock market indices, the Dow Jones Industrial Average and the S&P 500 decreased their efficiency levels marginally, after the surge of the crisis, while the Russell 2000 index kept the level intact. The high and stable degree of randomness could be attributed to the measures taken concurrently by the Federal Reserve and the government immediately after the outbreak of the crisis. Originality/value: This is one of the few studies that examine the impact of short selling behavior on the efficiency level of certain stocks' prices, particularly during the health public crisis. It provides an alternative approach to measuring quantitatively the degree of inefficiency and randomness. © 2023, Emerald Publishing Limited.
ABSTRACT
This paper examines the out-of-sample performance of thirteen portfolio strategies in the Spanish financial market (Ibex 35) during the COVID-19 pandemic (considering four different periods) by using three standard financial metrics. The main findings of the study are as follows: (i) the only methods outperforming Ibex 35 are those based on risk parity or diversification;(ii) unstable period data caused underperformance of strategies that require a previous estimation of certain hyper-parameters in their formulations.
ABSTRACT
Market practitioners and speculators attempt to make benefits from the existence of market price gaps and profit opportunities by arbitrage strategies. Although some investors trade stocks based on the available financial and fundamental information of a particular share, there are others who make profits by risk hedging and swing trading opportunities. One of these strategies is pairs trading, which is a sub‐category of statistical arbitrage. Pairs trading can assure reasonably a risk‐free profit gaining. This paper aims to make a hypothetical portfolio composed of pairs of stocks by exploring a significant association between their prices in the Toronto Stock Exchange, TSX. We compare the profitability of distance, co‐integration, and copula functions as the pair's selection and trading strategy devices in TSX over January 2017 to June 2020. Our results show that the highest profitability comes from trading by the copula method. Our time frame includes two heterogeneous pre and post COVID‐19 periods. Although the financial markets are struggling with a hard situation over the COVID‐19 days, the performance of the methodologies is not affected by the crisis.
ABSTRACT
This article investigates the reaction of integrated financial markets to the COVID-19 pandemic. Using a dynamic conditional correlation model on Euronext Stock Exchange, I find that the integration of financial markets can act as a buffer against negative shocks such as COVID-19. However, this benefit begins to fade as the number of deaths from COVID-19 increases. In this case, a negative relationship with the dynamic correlation is found in some pairs of member countries.
ABSTRACT
The global pandemic, coronavirus disease 2019 (COVID-19), has significantly affected tourism, especially in Spain, as it was among the first countries to be affected by the pandemic and is among the world's biggest tourist destinations. Stock market values are responding to the evolution of the pandemic, especially in the case of tourist companies. Therefore, being able to quantify this relationship allows us to predict the effect of the pandemic on shares in the tourism sector, thereby improving the response to the crisis by policymakers and investors. Accordingly, a dynamic regression model was developed to predict the behavior of shares in the Spanish tourism sector according to the evolution of the COVID-19 pandemic in the medium term. It has been confirmed that both the number of deaths and cases are good predictors of abnormal stock prices in the tourism sector.
ABSTRACT
Objective: The first objective of the article is to assess the benchmarks for the current ratio commonly provided in the accounting and financial analysis literature. The minor objective is to arrange a research methodology permitting the accomplishment of the first objective. Research Design & Methods: The paper, apart from the literature review and its critique, presents the results of descriptive, quantitative research. The research sample consists of 5 148 firm-years. Data were retrieved from Worldscope Database via Refinitiv Eikon for domestic, going concern, non-financial companies listed on the Warsaw Stock Exchange from 2005 to 2021. For comparison, the U.S.-related data was retrieved from Internet resources as ready-made ratios. Methods used in the analysis include descriptive statistics, parametric and nonparametric ANOVA, confidence intervals, and linear and parabolic trend analysis. Findings: The tests show that identifying a benchmark for the current ratio is problematic. Benchmarks vary between countries and industries;universal standards do not exist. The benchmark for the current ratio commonly suggested, 1.2-2.0, may be used only as a rough evaluation of the desired value. The findings indicate that the acceptable range for CR is much broader, from 1.1 (the first quartile) to 2.3 (the third quartile) for the total sample. Moreover, the SIC division's quartiles vary from 0.7 to 1.2 (the first) and from 1.6 to 3.6 (the third). Statistical tests indicate that benchmarks do not vary annually. However, the distribution's median and the third quartile change slowly over time toward higher values. The Covid-19 pandemic resulted in a substantial increase. On the contrary, the first quartile of about 1 remains relatively stable over time, indicating the reasonable lower bound for CR. The mean of the distribution is useless as a benchmark because of its sensitivity to outliers. Various techniques must be used to assess the benchmark. Implications & Recommendations: Since there are material between-industry and between-country differences in benchmarks, analysts and investors should be very sensitive to the standards suggested in the literature and interpret them cautiously. Variability over time exists but is low unless a shock in the economy appears. Contribution & Value Added: The main contribution of the paper is empirical verification of the benchmarks for the current ratio provided in the literature. Tests show that suggested benchmarks are not universal. Seeking a benchmark, an analyst must compare the firm's financial standing with other firms from the same country, industry, and period.
ABSTRACT
This study aims to verify the determining factors for the entry of small investors in the Brazilian Stock Exchange. For this, a questionnaire sent to respondents by electronic means was used. 698 valid responses were obtained. Homogeneity Analysis (HOMALS) was used to identify the association between the profile of investors and the determining factors for investors to enter the Stock Exchange. Through the results, it was found that the most important determining factors are: the possibility of obtaining extra income in the future, the fall in the price of shares, the low yield of savings and the drop in the SELIC rate. The factors that have less influence are: advertisements and encouragement from relatives and friends. In addition, almost half of the respondents agree that they see the Stock Exchange as an option to make quick money. It was identified that people with less knowledge about the market and a moderate risk profile disagree that the Stock Exchange is an opportunity to make quick money and that the more aggressive the investor's profile, the stronger the view that the fall in the price of shares is an opportunity for investments on the Stock Exchange. Differences were identified between the factors that determined the decision to invest in the Stock Exchange of investors who entered before and after the COVID-19 pandemic in Brazil. This study helps to fill the gaps in empirical research on the reasons that make small investors choose to invest in the Stock Exchange. It also contributes to the formulation of investment strategies and commercial strategies for those interested in increasing the number of Individual investors on the Stock Exchange..
ABSTRACT
Research background: The aim of the article is to compare Polish and US dividend companies with potential growth with dividend companies with potential value, including in the period of economic turbulence caused by the pandemic, and to identify macroeconomic determinants that affect changes in the level of share prices of dividend companies with potential value listed on the stock exchange in Poland and the US. An analysis of the literature and international studies conducted allows us to identify inflation, gross domestic product (GDP), interest rate levels, exchange rate changes, and market P/E and P/BV ratios, as well as the PMI index, as the most important macroeconomic factors. Purpose: The aim of the article was to present research on the impact of macroeconomic indicators on the prices of Polish and US shares of dividend companies, divided into shares with potential value and potential growth for the period 2016-2020. The research was enriched by analyzing the return rate on shares and the risk of the share prices of companies with potential value during the turbulence of the economy caused by the COVID-19 pandemic. Research methodology: The study was conducted using the Spearman rank correlation coefficient and significance test for the Spearman rank correlation coefficient. A non-parametric t-test was carried out to check whether the estimated correlation is statistically significant. Results: The research indicates that Polish and US dividend companies with potential value have lower average annual return rates than dividend companies with potential growth. Referring to the determinants of the share prices of US dividend companies with potential value, it was found that they are significantly determined by inflation and moderately determined by industrial production and GDP, as well as the P/BV ratio. Novelty: The added and application value are the recommendations regarding the attractiveness of investing in Polish dividend companies with potential value as compared to companies from the US market. © 2022 Bartłomiej Jabłoński et al.
ABSTRACT
This study aims to determine the effect of Bitcoin price, world commodity prices such as gold and crude oil, as well as the number of active cases of Covid-19 in Indonesia on the volatility of the Indonesia Stock Exchange. This study uses quantitative methods and the data collection used is secondary data with daily data and the period from March 2, 2020 - March 2, 2022. The number of observations used in this study amounted to 477 observations. Secondary data sources are obtained through the Yahoo Finance website and the official WHO website. The data processing technique will be carried out using Stata 16 software and using the Multiple Linear Regression method and also the Classical Assumption Test. The results of this study show that the price of Bitcoin, the price of gold, Crude oil prices have a positive and significant effect on the volatility of the Indonesia Stock Exchange and only the number of active cases of Covid-19 in Indonesia has a positive but not significant effect. This indicates that Bitcoin prices, world gold prices, and world oil prices are good market indicators. In this case, the results found can be useful information for investors and portfolio managers when they want to invest in the Indonesia Stock Exchange, especially in uncertain periods such as during the Covid-19 pandemic. © 2022 ACM.