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Showing 10 results for Stock Market
Reza Tehrani, Vahid Abbasion,
Volume 8, Issue 1 (4-2008)
Volume 8, Issue 1 (4-2008)
Abstract
Stock market timing is a very difficult task because of the complexity of the market. Since there are various factors affecting the market and therefore it is not a simple task to predict future stock price and its trend. This paper aims to apply advanced tools and algorithms such as the artificial neural networks (ANN) to model nonlinear processes and predict future stock price and its trend. More specifically, this study explores the abilities of the ANN to enhance the effectiveness of the technical analysis indicators to predict stock trend signals. Using a sample of 50 companies in the Tehran Stock Exchange (TSE), the results indicate that the ANN is capable to predict the direction of the short term movement in the future stock price. After considering the transaction costs, the results confirm that there is not significant difference among the returns gained from the ANN method, buy and hold strategy, and the most profitable technical indicators in the market when the trend is increasing. While, the ANN model yields higher returns compared to buy and hold strategy in the market when the trend is decreasing. Nevertheless, in the case of decreasing trend, the finding confirms the trend indicators (moving averages) achieve the highest returns.
Volume 12, Issue 2 (9-2022)
Abstract
The probability of stock prices crash has great importance in portfolio analysis and pricing of capital assets. Therefore, one of the major issues that investors face in the capital markets is predicting the fall of stocks. Given this necessity, the purpose of this study is to provide an approach to estimate the risk of stock price crashes. Recently, methods called "artificial neural networks" have been used to predict monetary and financial variables in parallel with structural models and time series. These models, which are actually derived from the brain learning process, use computer computational speed to learn complex relationships between variables and use them to predict the future. Using the data of 20 companies listed in the Tehran Stock Exchange, the present study presents models to estimate the probability of stock prices crash in the Iranian stock market using artificial neural networks. The results indicate that artificial neural networks have good performance in estimating the probability of stock prices crash in the Iranian stock market.
Nemat Falihi, Shamsi Morovat,
Volume 12, Issue 3 (9-2012)
Volume 12, Issue 3 (9-2012)
Abstract
The relationship between privatization and economic growth is the main focus of this research. A system dynamics approach and theoretical relationships in macro economics to growth patterns is used to study the impact of privatization through stock market on economic growth in Iran. The output calculation is done by human capital indicators such as the cost of investment in research and development, life expectancy, the rate of education and standard of living which are regularly published by the United Nations Organization. For estimating the rate of privatization, private investment and demand for stock, the statistics are provided by the Central Bank of Iran, the Organization for Privatization and the Stock Market Organization. Using a system dynamics approach to macroeconomics and the above-mentioned indicators the interaction and relationships between privatization and economic growth is explored in this paper. This approach which was firstly introduced by Forrester in 1973 can potentially improve and reform the unsuitable monetary and fiscal policies. In this regard the VENSIM and econometrics software packages are applied to simulate the results till the year 2020. Moreover, the economy is divided into many sections as stock market, investment and production. The results indicate that the rate of privatization in the stock market has a positive effect on economic growth. Finally, it is believed that more attention to private investment can result into increase in economic growth.
Zarifeh Jalili, Abbas Asari Arani, Kazem Yavari, Hassan Heydari,
Volume 17, Issue 4 (3-2018)
Volume 17, Issue 4 (3-2018)
Abstract
Expansion of financial markets including capital market is a key factor in increasing investment, which affects significantly the economic growth and development. Any change in monetary policy will influence real sector of economy, prices and returns on stocks. The performance of stock market is of considerable effect on macro economy, and plays substantial role in the monetary policy transmission process. In this paper, we examine the effect of monetary policy on the stock market using a five-variable structural vector auto-regressive model by applying monthly data during March 2005 to March 2013. The results suggest that the monetary policy through liquidity and loans directed to private sector is of significantly positive effect on the stock market index. As a result, expansionary monetary policy by increasing the liquidity and loans directed to the private sector improves stock market general index. In addition, changes in monetary policy through exchange rate and real interest rate have significant and negative effects on this index. The contractionary monetary policy through interest rate improves stock market index. Finally, shocks resulting from changes in exchange rate exacerbate the monetary policy in the short term, which in turn worsen the stock market index.
Dr. Soheil Roudari, Masoud Homayounifar, Professor Mostafa Salimifar,
Volume 21, Issue 1 (3-2021)
Volume 21, Issue 1 (3-2021)
Abstract
In this research, the impact of social capital through influencing the efficiency of government expenditure is investigated using three-stage least-squares model in Iran during 2005: Q1 to 2018: Q2. The effects of exchange rate, stock market index and oil revenues on non-performing loans of public and private sectors are also examined. Results suggest that given the increased efficiency of government expenditure, social capital has a significant negative impact on non-performing loans of public and private sectors. In addition, exchange rate has a significant negative impact on banking system’s receivables from public sector and a significant negative impact on banks’ receivables from private sector. Stock market index has no significant impact on non-performing loans of both public and private sector, since stock market is not liquid enough and has low share in financing businesses. Economic growth has also no significant impact on non-performing loans of both sectors, which can be explained by the impact of improvement in business environment and individuals’ purchasing power on their ability to repay their loans. Thus, by stabilizing economy (controlling the fluctuations of exchange-rate, stock market and so forth) and by improving social capital, it is expected that efficiency of government expenditure is increased and non-performing loans of both sectors is decreased.
Volume 21, Issue 3 (7-2014)
Abstract
This paper investigates the key factors affecting the foreign direct investment (FDI) inflow to developing countries during the period (1995-2010) with emphasis on the financial development. Financial development, as an important factor in FDI absorption and a prerequisite for utilizing the benefits of FDI, not only increases the FDI inflow in developing countries, but also improve the absorption capacity and ability of these countries to utilize the benefits of FDI. Since the financial system consists of several components and provides a variety of services, various indicators, which represent the development of different aspects and components of financial system, have been applied in order to assess the impact of financial development on the FDI. Results indicate that development of various components of financial system (stock market and banking sector) as well as different aspects of financial development (size and activity level of financial system) all have positive and significant impact on the FDI inflow in developing countries during the studied period.
Volume 22, Issue 3 (7-2015)
Abstract
This paper investigates the key factors affecting the foreign direct investment (FDI) inflow to developing countries during the period (1995-2010) with emphasis on the financial development. Financial development, as an important factor in FDI absorption and a prerequisite for utilizing the benefits of FDI, not only increases the FDI inflow in developing countries, but also improve the absorption capacity and ability of these countries to utilize the benefits of FDI. Since the financial system consists of several components and provides a variety of services, various indicators, which represent the development of different aspects and components of financial system, have been applied in order to assess the impact of financial development on the FDI. Results indicate that development of various components of financial system (stock market and banking sector) as well as different aspects of financial development (size and activity level of financial system) all have positive and significant impact on the FDI inflow in developing countries during the studied period.
Mrs. Mina Naderi, Dr Arash Hadizadeh, Dr Akbar Mirzapour Babajan,
Volume 23, Issue 2 (5-2023)
Volume 23, Issue 2 (5-2023)
Abstract
Introduction
In developing countries, the shocks that enter the economy due to capital market fluctuations have more depth and durability. Because of the two-way connection between the stock market and the real sector of the economy and public attention to this market, examining the stock market shocks is of great importance. Therefore, the present study investigated the extreme fluctuations of the stock market index, which suspected the existence of bubbles. Timing of these bubbles in the market is one of the goals of this study, which was carried out by using the right-tailed unit root tests based on the augmented Dickey-Fuller test. A stock price bubble may be affected by monetary policy. This issue is influenced by the size of the bubble and the type and strength of the applied monetary policy. The impact of monetary policy fluctuations and especially interest rates on stock price bubbles is theoretically uncertain and should be determined empirically. Therefore, another goal of this study is to examine the effects of monetary policy shocks on the formation and timing of the stock market bubble.
Methodology
The method of Phillips et al. (2015) has been used to identify and time the stock market bubble. Galli and Gambeti model and TVP-SVAR method were also used to investigate the effect of monetary policy on the stock market bubble.
Results and Discussion
BSADF (Backward Supreme Augmented Dicky-Fuller) test has been used to determine the dates when the stock market had a bubble. According to this test, in three short periods, from July to September 2005, from April to May 2011, and from October to November 2018, the stock market behaved like a bubble. Regarding the impact of the interest rate shock on the stock market bubble, it can be said that the monetary expansion shock (decrease in the real interest rate) causes the bubble part of the stock price to become larger. In all periods, the response of the bubble part was positive, but over time, has increased, and since the beginning of the 2010s, its response to the shock of interest rate reduction has completely changed. The liquidity shock, also strengthens the size of the bubble. The amount of this influence has also increased greatly over time and has reached its peak in 2017 (the year of the formation of the price bubble in the stock market based on the BSADF test). Therefore, it can be claimed that the increase in the bubble part of the stock price was caused by a positive shock or an increase in liquidity. Regarding the effect of the credit shock on the stock market bubble, it can be said that credits has affected the fundamental part of the stock price, but it does not have much effect on the bubble part of the stock price. In fact, the increase in credits has caused the liquidity restrictions of economic enterprises to be removed and has an effect on their production and sales and finally on their profitability. Therefore, it is expected that with an increase in credits (positive credit shock), most of the fundamental part (current and future profitability) of companies will be affected.
Conclusion
During the last decade, the public attention to the stock market in Iran increased significantly. This issue caused the entry of new funds into this market, which was seen in the bubble-like behavior of the stock price index. In the conventional economic theory, the positive impact of expansionary monetary policies on the bubble is expected, but there are other theories that make the long-term impact of the monetary policy shock on the size of the bubble uncertain and dependent on factors such as the size of the bubble, the stability of the monetary policy, and the type of monetary tool. In order to solve this theoretical ambiguity, the effect of one of these cases, i.e., changing the monetary policy tool, on the stock price bubble was investigated. Before that, the existence of a bubble in the stock market had been checked. Regarding the impact of monetary shocks on the stock price bubble, according to the type of monetary policy instrument, the reaction of the stock price bubble has been different. Interest rate policy and liquidity have had a positive effect on the bubble, but credit policy has not had such an effect. In most of the developed economies, the interest rate change is the most powerful monetary policy tool, as a small change in it can have a large impact on the real sector of these economies. But in our country, according to the empirical findings of this article, the effect of liquidity on the stock market bubbles has been greater than the effect of changing the interest rates on it. This result is a proof of the dominance of liquidity over monetary policies in Iran.
Keywords: Monetary policy, interest rate, liquidity, stock market price bubble, Vector Autoregressive with Time Varying Parameter
JEL Classification: C22, E32, E44, G14
In developing countries, the shocks that enter the economy due to capital market fluctuations have more depth and durability. Because of the two-way connection between the stock market and the real sector of the economy and public attention to this market, examining the stock market shocks is of great importance. Therefore, the present study investigated the extreme fluctuations of the stock market index, which suspected the existence of bubbles. Timing of these bubbles in the market is one of the goals of this study, which was carried out by using the right-tailed unit root tests based on the augmented Dickey-Fuller test. A stock price bubble may be affected by monetary policy. This issue is influenced by the size of the bubble and the type and strength of the applied monetary policy. The impact of monetary policy fluctuations and especially interest rates on stock price bubbles is theoretically uncertain and should be determined empirically. Therefore, another goal of this study is to examine the effects of monetary policy shocks on the formation and timing of the stock market bubble.
Methodology
The method of Phillips et al. (2015) has been used to identify and time the stock market bubble. Galli and Gambeti model and TVP-SVAR method were also used to investigate the effect of monetary policy on the stock market bubble.
Results and Discussion
BSADF (Backward Supreme Augmented Dicky-Fuller) test has been used to determine the dates when the stock market had a bubble. According to this test, in three short periods, from July to September 2005, from April to May 2011, and from October to November 2018, the stock market behaved like a bubble. Regarding the impact of the interest rate shock on the stock market bubble, it can be said that the monetary expansion shock (decrease in the real interest rate) causes the bubble part of the stock price to become larger. In all periods, the response of the bubble part was positive, but over time, has increased, and since the beginning of the 2010s, its response to the shock of interest rate reduction has completely changed. The liquidity shock, also strengthens the size of the bubble. The amount of this influence has also increased greatly over time and has reached its peak in 2017 (the year of the formation of the price bubble in the stock market based on the BSADF test). Therefore, it can be claimed that the increase in the bubble part of the stock price was caused by a positive shock or an increase in liquidity. Regarding the effect of the credit shock on the stock market bubble, it can be said that credits has affected the fundamental part of the stock price, but it does not have much effect on the bubble part of the stock price. In fact, the increase in credits has caused the liquidity restrictions of economic enterprises to be removed and has an effect on their production and sales and finally on their profitability. Therefore, it is expected that with an increase in credits (positive credit shock), most of the fundamental part (current and future profitability) of companies will be affected.
Conclusion
During the last decade, the public attention to the stock market in Iran increased significantly. This issue caused the entry of new funds into this market, which was seen in the bubble-like behavior of the stock price index. In the conventional economic theory, the positive impact of expansionary monetary policies on the bubble is expected, but there are other theories that make the long-term impact of the monetary policy shock on the size of the bubble uncertain and dependent on factors such as the size of the bubble, the stability of the monetary policy, and the type of monetary tool. In order to solve this theoretical ambiguity, the effect of one of these cases, i.e., changing the monetary policy tool, on the stock price bubble was investigated. Before that, the existence of a bubble in the stock market had been checked. Regarding the impact of monetary shocks on the stock price bubble, according to the type of monetary policy instrument, the reaction of the stock price bubble has been different. Interest rate policy and liquidity have had a positive effect on the bubble, but credit policy has not had such an effect. In most of the developed economies, the interest rate change is the most powerful monetary policy tool, as a small change in it can have a large impact on the real sector of these economies. But in our country, according to the empirical findings of this article, the effect of liquidity on the stock market bubbles has been greater than the effect of changing the interest rates on it. This result is a proof of the dominance of liquidity over monetary policies in Iran.
Keywords: Monetary policy, interest rate, liquidity, stock market price bubble, Vector Autoregressive with Time Varying Parameter
JEL Classification: C22, E32, E44, G14
Mrs Roghayeh Mohseninia, Dr Ali Rezazadeh, Dr Yousef Mohammadzadeh, Dr Shahab Jahangiri,
Volume 24, Issue 2 (5-2024)
Volume 24, Issue 2 (5-2024)
Abstract
Introduction
In recent years, cryptocurrency analysis has become increasingly popular both in academic research and in the financial system as a whole. Cryptocurrencies are a globally spreading phenomenon that is frequently and also prominently addressed by media, venture capitalists, financial institutions, and governments alike (Glasser et al., 2014). Knowing the relationship between cryptocurrency market, stock market or commodity market will be very useful for managing investors’ portfolios and how much of their investment will be allocated to cryptocurrencies for their assets to be secure.
The possible interdependence of stock markets and cryptocurrencies is a crucial concern in the financial market literature due to its paramount importance for investors and portfolio managers. Although cryptocurrencies are a recent phenomenon, with the first cryptocurrency, Bitcoin, appearing in January 2016, they quickly become a worldwide phenomenon that is broadly discussed in the finance literature (Glaser et al., 2014).
Many scholars in recent times explored the correlation between cryptocurrencies and stock market. Several studies (see Conrad et al., 2018; Jiang et al., 2021; Tiwari et al., 2019; Corbet et al., 2018; Salisu et al., 2019) considered advanced economies to explore the impact of cryptocurrency and stock market, provided important insightful stories. Few others (see Lahiani and Jlassi, 2021; Dasman, 2021; Vardar and Aydogan et al., 2019; Sami and Abdallah, 2020) explored the association in emerging economies. Additionally, the association between cryptocurrency and stock market also received considerable attention among the scholars in the time of COVID-19 (see Mariana et al., 2021; Grobys, 2021; Nguyen, 2021; Kumah, 2021). The issue discussed in these studies is mainly based on the fact that cryptocurrencies are gradually establishing themselves as a new class of assets with unique characteristics, although skepticism and lack of understanding of their nature still exist. These new financial assets (tokens) can offer new opportunities for portfolio diversification and risk hedging. The common consensus regarding weak correlations between cryptocurrencies and stock markets has recently been challenged by their synchronous downturn during the COVID-19 pandemic.
Any financial instrument such as stocks and cryptocurrencies traded in the markets may be subject to price fluctuations based on several factors. Factors such as positive and negative news, financial status of stock companies traded in stock markets, political events, global changes and environmental conditions including market risks. With the globalization of the use of cryptocurrencies, the popularity and use of cryptocurrencies has been steadily increasing in Iran over the past few years. In this new situation, investors are looking to reduce their investment risk and achieve optimal portfolio diversification with the participation of new financial assets. Considering the direct and indirect influence of Iran's economy on global financial markets and the expansion of activities related to cryptocurrencies in the context of international sanctions, the question is raised whether there is a relationship between stock returns and cryptocurrencies returns? This study combines the Variational Mode Decomposition (VMD) method and symmetric and asymmetric copula functions to examine the dependence structure between cryptocurrency and stock markets under different investment horizons.
Methodology
The fundamental aim of this study is to investigate the structural dependence between the cryptocurrency market and the Iran Stock Market Index using daily data (common trading days) during the period from 8 August 2015 to 21 February 2023. This study combines VMD method and various symmetric and asymmetric copula functions to examine the short-term and long-term dependence structure between the cryptocurrency markets and the Iranian stock market under different investment horizons. In this study, the Normal copula, the student-t copula and the Archimedean copula family functions such as the Frank copula, the Gumbel copula and the Clayton copula have been used. Also, the dependence structure between markets is investigated with one subroutines of the Vine copula functions, namely C-Vine.
Discussion and Results
The results show that there is no structural dependence between the return Bitcoin and Iran stock market using the Archimedean copula function, either in the short term or in the long term. In other words, the changes domain in return of Bitcoin during the low and high ranges on the return of the mentioned index are insignificant. The results indicate that the cryptocurrencies researced are strongly correlated. However, the associations between cryptocurrencies and conventional financial assets are negligible. These results are consistent with the findings of Gil-Alana et al. (2020); Tiwari et al. (2019) and Corbet et al. (2018) which reveal that there is no correlation between the cryptocurrency and stock markets.
Conclusion
The results indicate that the cryptocurrency market is separated from the main class of financial and economic assets and hence offers various benefits to investors. Structural dependence using Vine copula functions is better than Archimedean copula in identifying the structural dependence between cryptocurrency and the Iranian Stock Market Index during the period under study. Based on the research findings, the Clayton copula has been chosen as the suitable model to explain the correlation between the return of Bitcoin and the stock market index on the condition of the growth price Ethereum. This point indicates asymmetric effects the dependence on the negative tail is more than the positive one. The findings in this paper indicate the significant role of cryptocurrencies in investor portfolios since they serve as a diversification option for investors, confirming that cryptocurrency is a new investment asset class.
In recent years, cryptocurrency analysis has become increasingly popular both in academic research and in the financial system as a whole. Cryptocurrencies are a globally spreading phenomenon that is frequently and also prominently addressed by media, venture capitalists, financial institutions, and governments alike (Glasser et al., 2014). Knowing the relationship between cryptocurrency market, stock market or commodity market will be very useful for managing investors’ portfolios and how much of their investment will be allocated to cryptocurrencies for their assets to be secure.
The possible interdependence of stock markets and cryptocurrencies is a crucial concern in the financial market literature due to its paramount importance for investors and portfolio managers. Although cryptocurrencies are a recent phenomenon, with the first cryptocurrency, Bitcoin, appearing in January 2016, they quickly become a worldwide phenomenon that is broadly discussed in the finance literature (Glaser et al., 2014).
Many scholars in recent times explored the correlation between cryptocurrencies and stock market. Several studies (see Conrad et al., 2018; Jiang et al., 2021; Tiwari et al., 2019; Corbet et al., 2018; Salisu et al., 2019) considered advanced economies to explore the impact of cryptocurrency and stock market, provided important insightful stories. Few others (see Lahiani and Jlassi, 2021; Dasman, 2021; Vardar and Aydogan et al., 2019; Sami and Abdallah, 2020) explored the association in emerging economies. Additionally, the association between cryptocurrency and stock market also received considerable attention among the scholars in the time of COVID-19 (see Mariana et al., 2021; Grobys, 2021; Nguyen, 2021; Kumah, 2021). The issue discussed in these studies is mainly based on the fact that cryptocurrencies are gradually establishing themselves as a new class of assets with unique characteristics, although skepticism and lack of understanding of their nature still exist. These new financial assets (tokens) can offer new opportunities for portfolio diversification and risk hedging. The common consensus regarding weak correlations between cryptocurrencies and stock markets has recently been challenged by their synchronous downturn during the COVID-19 pandemic.
Any financial instrument such as stocks and cryptocurrencies traded in the markets may be subject to price fluctuations based on several factors. Factors such as positive and negative news, financial status of stock companies traded in stock markets, political events, global changes and environmental conditions including market risks. With the globalization of the use of cryptocurrencies, the popularity and use of cryptocurrencies has been steadily increasing in Iran over the past few years. In this new situation, investors are looking to reduce their investment risk and achieve optimal portfolio diversification with the participation of new financial assets. Considering the direct and indirect influence of Iran's economy on global financial markets and the expansion of activities related to cryptocurrencies in the context of international sanctions, the question is raised whether there is a relationship between stock returns and cryptocurrencies returns? This study combines the Variational Mode Decomposition (VMD) method and symmetric and asymmetric copula functions to examine the dependence structure between cryptocurrency and stock markets under different investment horizons.
Methodology
The fundamental aim of this study is to investigate the structural dependence between the cryptocurrency market and the Iran Stock Market Index using daily data (common trading days) during the period from 8 August 2015 to 21 February 2023. This study combines VMD method and various symmetric and asymmetric copula functions to examine the short-term and long-term dependence structure between the cryptocurrency markets and the Iranian stock market under different investment horizons. In this study, the Normal copula, the student-t copula and the Archimedean copula family functions such as the Frank copula, the Gumbel copula and the Clayton copula have been used. Also, the dependence structure between markets is investigated with one subroutines of the Vine copula functions, namely C-Vine.
Discussion and Results
The results show that there is no structural dependence between the return Bitcoin and Iran stock market using the Archimedean copula function, either in the short term or in the long term. In other words, the changes domain in return of Bitcoin during the low and high ranges on the return of the mentioned index are insignificant. The results indicate that the cryptocurrencies researced are strongly correlated. However, the associations between cryptocurrencies and conventional financial assets are negligible. These results are consistent with the findings of Gil-Alana et al. (2020); Tiwari et al. (2019) and Corbet et al. (2018) which reveal that there is no correlation between the cryptocurrency and stock markets.
Conclusion
The results indicate that the cryptocurrency market is separated from the main class of financial and economic assets and hence offers various benefits to investors. Structural dependence using Vine copula functions is better than Archimedean copula in identifying the structural dependence between cryptocurrency and the Iranian Stock Market Index during the period under study. Based on the research findings, the Clayton copula has been chosen as the suitable model to explain the correlation between the return of Bitcoin and the stock market index on the condition of the growth price Ethereum. This point indicates asymmetric effects the dependence on the negative tail is more than the positive one. The findings in this paper indicate the significant role of cryptocurrencies in investor portfolios since they serve as a diversification option for investors, confirming that cryptocurrency is a new investment asset class.
Volume 27, Issue 4 (12-2023)
Abstract
The contents of the Legal Bill to amend a part of the Trade Law act 1968 which have been affected by the Stock Market act 2005 in the realm of legal deadlines in relation to the regulations of public joint-stock companies as one of the most important elements in the stock market, have undergone changes. These changes have been studied in the present research in two categories: Institutional and abrogator categories. Institutional issues include cases for which basically no deadline has been established in the Legal Bill Act 1968 and was considered for the first time in the Stock Market Act 2005, and the abrogator cases are those deadlines for which due date has been assigned and by approving the Stock Market Act 2005 has been abrogated. The philosophy of the mentioned effects, both in the field of institution and abrogation, can be found in the goal of the legislator to protect the rights of shareholders and the transparency of capital market information. Determining the period of subscription, determining the period to return the funds, the period for dealing with the obligations of the subscriber, changing the time for using the funds paid by investors, changing the time for withdrawing the funds in case of no increasing the capital, changing the period for the board of directors to deal with the obligations of the underwriters, and determining the period for disclosure of the board of directors' decisions, are the dates studied in this research.
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