Univrsity Of Tehran Press Financial Research Journal 1024-8153 22 3 2020 10 22 Evaluation of the Effect of the Banking Sector Systemic Risk on the Macroeconomic Performance of Iran Evaluation of the Effect of the Banking Sector Systemic Risk on the Macroeconomic Performance of Iran 297 319 78461 10.22059/frj.2019.276790.1006830 FA Reza Tehrani Prof., Department of Finance, Faculty of Management, University of Tehran, Tehran, Iran. Mostafa Seraj Ph.D. Candidate, Department of Finance, Faculty of Management, University of Tehran, Iran. Ali Foroush Bastani Assistant Prof., Department of Finance, Faculty of Mathematics, Institute for Advanced Studies in Basic Sciences, Zanjan, Iran. Saeed Fallahpour Assistant Prof., Department of Finance, Faculty of Management, University of Tehran, Tehran, Iran. Journal Article 2019 03 16 Objective: Systemic risk is the cause of many financial crises and has adverse effects on economic performance at the macro level. For effective policy-making of systemic risk management, it is necessary to measure and monitor systemic risk and to study the mechanism of its effect on macro-economy. This paper aims at investigating the relationship between banking sector systemic risk and the performance of macroeconomic indexes including Gross Domestic Production (GDP), GDP without oil, the components of GDP and the value added of the sectors. Methods: One of the best systemic risk measures is SRISK index which is used in this article, and the relationship between the changes of macroeconomic indexes and the changes of SRISK is evaluated using autoregressive distributed lags model. Results: There is a significant negative relationship between the banking sector systemic risk of Iran and GDP (with and without oil) for horizon of 12 months. Value added of construction, financial sector and industry sector is influenced more than other sectors from the changes of systemic risk of banking system. Furthermore, all of the components of GDP are influenced by the changes of systemic risk but this influence is stronger and more durable for the fixed investment component. Conclusion: In addition to the increase of the probability of financial crisis, the increasing of systemic risk has long-term adverse effects on macroeconomic performance and investments. In order to take a timely measure for decreasing the adverse effects of systemic risks, Policy-makers should monitor SRISK index continuously. Objective: Systemic risk is the cause of many financial crises and has adverse effects on economic performance at the macro level. For effective policy-making of systemic risk management, it is necessary to measure and monitor systemic risk and to study the mechanism of its effect on macro-economy. This paper aims at investigating the relationship between banking sector systemic risk and the performance of macroeconomic indexes including Gross Domestic Production (GDP), GDP without oil, the components of GDP and the value added of the sectors. Methods: One of the best systemic risk measures is SRISK index which is used in this article, and the relationship between the changes of macroeconomic indexes and the changes of SRISK is evaluated using autoregressive distributed lags model. Results: There is a significant negative relationship between the banking sector systemic risk of Iran and GDP (with and without oil) for horizon of 12 months. Value added of construction, financial sector and industry sector is influenced more than other sectors from the changes of systemic risk of banking system. Furthermore, all of the components of GDP are influenced by the changes of systemic risk but this influence is stronger and more durable for the fixed investment component. Conclusion: In addition to the increase of the probability of financial crisis, the increasing of systemic risk has long-term adverse effects on macroeconomic performance and investments. In order to take a timely measure for decreasing the adverse effects of systemic risks, Policy-makers should monitor SRISK index continuously.

https://jfr.ut.ac.ir/article_78461_7921feec0e204536d5ab9237258f5845.pdf

Univrsity Of Tehran Press Financial Research Journal 1024-8153 22 3 2020 10 22 The Style Momentum and Its Origin The Style Momentum and Its Origin 320 342 78462 10.22059/frj.2020.288887.1006924 FA Maryam Davallou Associate Prof., Department of Financial Management, Faculty of Management and Accounting, Shahid Beheshti University, Tehran, Iran. Bahareh Tabarsa Ph.D. Candidate, Department of Financial Management, Faculty of Management and Accounting, Shahid Beheshti University, Tehran, Iran. Journal Article 2019 09 15 Objective: Capital market investors have always sought to identify anomalies market and plan profitable trading strategies based on them. Momentum is one the most famous anomalies market. Momentum initially identified by Jagadeesh and Titman (1993) at the level of individual stocks, and recently has been examined at the level of style portfolios. The purpose of this study is to test the profitability of the style momentum strategy based on the size and book value to market value ratio style and its origin through decomposing the profit of strategy in Tehran Stock Exchange. Methods: To examine the profitability of style momentum used portfolio study method for 3, 6 and 12 ranking and holding period strategies. In this study the profitability of style momentum was attributed to risk factor, return continuation and excessive co-movement that unexplained the macroeconomic factors. Results: The results show that the style momentum strategy profitability is almost positive and significant for the short-terms and mid-terms periods, but for the long-terms period despite the positive profitability it has not been statically significant or become a reversal strategy. The results show that for 3 and 6 month strategies, the main benefits of style momentum are explained by return continuation theory and for 12 month strategy risk identified as a major component of style momentum. Conclusion: For 3 and 6 month strategies "risk" and "return continuation theory" are the main components of style momentum, but for the 12 month strategy "risk" is introduced as the sole cause of style momentum. Objective: Capital market investors have always sought to identify anomalies market and plan profitable trading strategies based on them. Momentum is one the most famous anomalies market. Momentum initially identified by Jagadeesh and Titman (1993) at the level of individual stocks, and recently has been examined at the level of style portfolios. The purpose of this study is to test the profitability of the style momentum strategy based on the size and book value to market value ratio style and its origin through decomposing the profit of strategy in Tehran Stock Exchange. Methods: To examine the profitability of style momentum used portfolio study method for 3, 6 and 12 ranking and holding period strategies. In this study the profitability of style momentum was attributed to risk factor, return continuation and excessive co-movement that unexplained the macroeconomic factors. Results: The results show that the style momentum strategy profitability is almost positive and significant for the short-terms and mid-terms periods, but for the long-terms period despite the positive profitability it has not been statically significant or become a reversal strategy. The results show that for 3 and 6 month strategies, the main benefits of style momentum are explained by return continuation theory and for 12 month strategy risk identified as a major component of style momentum. Conclusion: For 3 and 6 month strategies "risk" and "return continuation theory" are the main components of style momentum, but for the 12 month strategy "risk" is introduced as the sole cause of style momentum.

https://jfr.ut.ac.ir/article_78462_e7fc042cbb985533c5ae753dcebd0387.pdf

Univrsity Of Tehran Press Financial Research Journal 1024-8153 22 3 2020 10 22 Semi-parametric Model of Idiosyncratic Volatility Pricing by Explaining the Arbitrage Risk Semi-parametric Model of Idiosyncratic Volatility Pricing by Explaining the Arbitrage Risk 343 365 78463 10.22059/frj.2019.281494.1006869 FA Mehdi Asima PhD. Candidate, Department of Banking Finance, Faculty of Management, University of Tehran, Tehran, Iran. Reza Eyvazloo Assistant Prof., Department of Financial Management, Faculty of Management, University of Tehran, Tehran, Iran. Journal Article 2019 05 16 Objective: The relationship between idiosyncratic volatility and expected return in finance has become a puzzle. While, based on modern portfolio theory, the relationship between risk and expected return is positive, many studies find a negative relationship between these variables. In addition, many studies have examined the factors affecting this relationship. In this paper, we have examined the relationship between idiosyncratic volatility and the expected return through explanation of the arbitrage risk as a factor affecting the relationship in the period from 2007-2017. Methods: In this study, a five-factor Fama-French model has been used to estimate idiosyncratic volatility. In order to answer the research question and hypothesis testing, portfolio analysis and Fama-Macbeth regression methods have been used. Results: The idiosyncratic volatility was estimated using the Fama-French five-factor model, which was implemented based on the local polynomial kernel regression. Also, for estimating the arbitrage risk index, a trading limit on the Iran stock exchange and other common variables of arbitrage risk measurement are also used. Conclusion: The results show that in addition to idiosyncratic volatility pricing, the relationship between idiosyncratic volatility and expected return is negative. Also, the arbitrage risk is confirmed as an effective variable on the severity and significance of the relationship between idiosyncratic volatility and expected return. Objective: The relationship between idiosyncratic volatility and expected return in finance has become a puzzle. While, based on modern portfolio theory, the relationship between risk and expected return is positive, many studies find a negative relationship between these variables. In addition, many studies have examined the factors affecting this relationship. In this paper, we have examined the relationship between idiosyncratic volatility and the expected return through explanation of the arbitrage risk as a factor affecting the relationship in the period from 2007-2017. Methods: In this study, a five-factor Fama-French model has been used to estimate idiosyncratic volatility. In order to answer the research question and hypothesis testing, portfolio analysis and Fama-Macbeth regression methods have been used. Results: The idiosyncratic volatility was estimated using the Fama-French five-factor model, which was implemented based on the local polynomial kernel regression. Also, for estimating the arbitrage risk index, a trading limit on the Iran stock exchange and other common variables of arbitrage risk measurement are also used. Conclusion: The results show that in addition to idiosyncratic volatility pricing, the relationship between idiosyncratic volatility and expected return is negative. Also, the arbitrage risk is confirmed as an effective variable on the severity and significance of the relationship between idiosyncratic volatility and expected return.

https://jfr.ut.ac.ir/article_78463_12db96834d3a0ad655e26f85646b8fc7.pdf

Univrsity Of Tehran Press Financial Research Journal 1024-8153 22 3 2020 10 22 The Effect of Active Management on Mutual Fund Performance in Tehran Stock Exchange Market The Effect of Active Management on Mutual Fund Performance in Tehran Stock Exchange Market 366 387 78464 10.22059/frj.2020.291722.1006949 FA Ahmad Nabizade Assistant Prof., Department of Business Management, Faculty of Management, Kharazmi University, Tehran, Iran. Farshid Sepahvand Student, Department of Business Management, Faculty of Management, Kharazmi University, Tehran, Iran. Journal Article 2019 11 10 Objective: Mutual funds, by having a net asset value near to 102,771 thousands billiard Rial by the end of 2019 plays an important role in Iran's capital market. One of the factors affecting performance of these funds is the activity level of its portfolio compare to index. The fund managers, despite the mutual funds expenses, have been always questioned if they had been able to outscore the market or not? In this research, the impacts of active management, expenses ratio, turnover ratio, size, fund flow ratio and individual investor share ratio on mutual fund performance are studied. Methods: By using Fama – French five factors model and mutual funds monthly return, the value of alpha and R-Squared (R2) indicating the performance and passiveness of fund respectively, will be calculated. R2 value is always between zero and one. When R2 is close to one, it is indicating that fund’s performance is like market index and the portfolio is managed passively or the fund’s portfolio is a closet indexer. In other hand, when the value of R2 is near to zero, it shows that the fund’s portfolio is managed actively. Thus, the active management is proportional to (1 - R2) value. Finally by utilizing regression equation, the impact of mutual fund’s active management, expenses ratio, turnover ratio, size, fund flow ratio and individual investor share ratio on fund performance is investigated. Results: According to the results, there is a significant inverse relation between active management and mutual fund performance. Funds with larger size and higher expense ratio show improvement in performance, and increment of fund’s flow reduces its performance. In funds with weak performance, there is a reverse relation between turnover ratio and performance. Also, there is a significant direct relation between individual investor share and fund’s performance. Conclusion: Active management did not result in performance improvement in Tehran Stock Exchange Market. Objective: Mutual funds, by having a net asset value near to 102,771 thousands billiard Rial by the end of 2019 plays an important role in Iran's capital market. One of the factors affecting performance of these funds is the activity level of its portfolio compare to index. The fund managers, despite the mutual funds expenses, have been always questioned if they had been able to outscore the market or not? In this research, the impacts of active management, expenses ratio, turnover ratio, size, fund flow ratio and individual investor share ratio on mutual fund performance are studied. Methods: By using Fama – French five factors model and mutual funds monthly return, the value of alpha and R-Squared (R2) indicating the performance and passiveness of fund respectively, will be calculated. R2 value is always between zero and one. When R2 is close to one, it is indicating that fund’s performance is like market index and the portfolio is managed passively or the fund’s portfolio is a closet indexer. In other hand, when the value of R2 is near to zero, it shows that the fund’s portfolio is managed actively. Thus, the active management is proportional to (1 - R2) value. Finally by utilizing regression equation, the impact of mutual fund’s active management, expenses ratio, turnover ratio, size, fund flow ratio and individual investor share ratio on fund performance is investigated. Results: According to the results, there is a significant inverse relation between active management and mutual fund performance. Funds with larger size and higher expense ratio show improvement in performance, and increment of fund’s flow reduces its performance. In funds with weak performance, there is a reverse relation between turnover ratio and performance. Also, there is a significant direct relation between individual investor share and fund’s performance. Conclusion: Active management did not result in performance improvement in Tehran Stock Exchange Market.

https://jfr.ut.ac.ir/article_78464_f38854f22634e0f1a795002bfb058a56.pdf

Univrsity Of Tehran Press Financial Research Journal 1024-8153 22 3 2020 10 22 Herd Behavior Analysis in Tehran Stock Exchange with Chiang and Zheng Model Herd Behavior Analysis in Tehran Stock Exchange with Chiang and Zheng Model 388 407 78465 10.22059/frj.2020.292714.1006951 FA Hamed Vares Assistant Prof., Department of MBA, Faculty of Management, University of Tehran, Tehran, Iran. Hamidreza Arian Assistant Prof., Department of Economics, Graduate School of Management and Economics, Sharif University of Technology, Tehran, Iran. Benyamin Aryanayekta MSc Student, Department of MBA, Faculty of Management, University of Tehran, Tehran, Iran. Mohammad Javad Bannazadeh MSc, Department of MBA, Faculty of Management, University of Tehran, Tehran, Iran. Journal Article 2019 11 20 Objective: Behavioral finance, as a sub-field of behavioral economics, has posed many challenges to classic financial theories and market efficiency. In general, herd behavior emerges when investors decide to follow other investors rather than relying on their own analysis and knowledge and change their decisions based on other investors’ opinions. Even though this behavior may be rational for less sophisticated investors, the existence of wide herding may result in volatility in returns and instability of the capital market, which is known as a source of financial risk. The purpose of this study is to investigate the herd behavior among investors in Tehran Stock Exchange during the 4-year period from 23/05/2015 to 21/05/2019. Methods: This study examines the existence of wide herding among investors in Tehran Stock Exchange by using the Chiang and Zheng model which is an econometric model based on the daily return of sectors, the daily return of the selected portfolio and cross-sectional absolute deviation. Besides, Chiang and Zheng model is the only econometric based model which can detect herd behavior in up-markets and down-markets separately. Results: The findings of the study clearly illustrate that the assumption of investors herd behavior in the market has been confirmed. In addition, herd behavior is stronger in the up-markets than the down-markets during the mentioned 4-year period. It should be noted that herd behavior was detected in both up- markets and down- markets, but the intensity was higher in up-markets. Conclusion: With respect to the obtained coefficients in the regression equations and the type of herd behavior in terms of occurring in down markets or up markets, it can be concluded that investors in Tehran Stock Exchange are generally affected by herd behavior, but in periods of market decline, investors decide and act somewhat more rational, and they show lower intensity of herd behavior in their investments. Objective: Behavioral finance, as a sub-field of behavioral economics, has posed many challenges to classic financial theories and market efficiency. In general, herd behavior emerges when investors decide to follow other investors rather than relying on their own analysis and knowledge and change their decisions based on other investors’ opinions. Even though this behavior may be rational for less sophisticated investors, the existence of wide herding may result in volatility in returns and instability of the capital market, which is known as a source of financial risk. The purpose of this study is to investigate the herd behavior among investors in Tehran Stock Exchange during the 4-year period from 23/05/2015 to 21/05/2019. Methods: This study examines the existence of wide herding among investors in Tehran Stock Exchange by using the Chiang and Zheng model which is an econometric model based on the daily return of sectors, the daily return of the selected portfolio and cross-sectional absolute deviation. Besides, Chiang and Zheng model is the only econometric based model which can detect herd behavior in up-markets and down-markets separately. Results: The findings of the study clearly illustrate that the assumption of investors herd behavior in the market has been confirmed. In addition, herd behavior is stronger in the up-markets than the down-markets during the mentioned 4-year period. It should be noted that herd behavior was detected in both up- markets and down- markets, but the intensity was higher in up-markets. Conclusion: With respect to the obtained coefficients in the regression equations and the type of herd behavior in terms of occurring in down markets or up markets, it can be concluded that investors in Tehran Stock Exchange are generally affected by herd behavior, but in periods of market decline, investors decide and act somewhat more rational, and they show lower intensity of herd behavior in their investments.

https://jfr.ut.ac.ir/article_78465_46c8c98f648ffed70a76d3ac3cec3e8f.pdf

Univrsity Of Tehran Press Financial Research Journal 1024-8153 22 3 2020 10 22 Online Portfolio Selection Based on Follow-the-Loser Algorithms Online Portfolio Selection Based on Follow-the-Loser Algorithms 408 427 78466 10.22059/frj.2020.291101.1006941 FA Javad Validi Msc., Department of Financial Engineering, Faculty of Industrial Engineering, K.N. Toosi University of Technology, Tehran, Iran. Amir Abbas Najafi Associate Prof., Financial Engineering, Faculty of Industrial Engineering, K.N. Toosi University of Technology, Tehran, Iran. Alireza Validi Msc., Department of Financial Engineering, Faculty of Financial Sciences, Kharazmi University, Tehran, Iran. Journal Article 2019 10 21 Objective: Nowadays, the volume and speed of transactions in financial markets have grown dramatically and it is hard to track market changes by using traditional methods. Besides the efficiency of traditional methods, the low speed of these approaches is one of the most important deficiencies of them because they cannot adapt to high speed of transactions. To overcome this shortcoming, algorithmic trading techniques have been proposed which online portfolio selection is one of the most important of these techniques. So, the purpose of this research is to propose a new algorithm for online portfolio selection which leads to high risk-adjusted return and speeds up the process of portfolio selection. Methods: In this research, two algorithms have been proposed using multi-period mean reversion which is the basis of follow-the-loser algorithms. In these algorithms, a set of various experts predict the price relative vector of next period. Then, one of existing algorithms in prediction theory with expert advice is used to assign weights to experts. Then, a learning technique is used for portfolio optimization which leads to portfolio of next period. Results: The results show the superiority of the proposed algorithms to other algorithms existing in literature based on return and risk-adjusted return criteria. Conclusion: The concept of mean reversion can be better expressed by using multi-period mean reversion. In addition, using different experts’ advices make predictions more accurate and therefore better portfolios are suggested. Also, the use of weighting system indirectly brings robustness in the algorithms because it reduces the weights assigned to experts with poor predictions and transforms it to other experts with proper predictions. Objective: Nowadays, the volume and speed of transactions in financial markets have grown dramatically and it is hard to track market changes by using traditional methods. Besides the efficiency of traditional methods, the low speed of these approaches is one of the most important deficiencies of them because they cannot adapt to high speed of transactions. To overcome this shortcoming, algorithmic trading techniques have been proposed which online portfolio selection is one of the most important of these techniques. So, the purpose of this research is to propose a new algorithm for online portfolio selection which leads to high risk-adjusted return and speeds up the process of portfolio selection. Methods: In this research, two algorithms have been proposed using multi-period mean reversion which is the basis of follow-the-loser algorithms. In these algorithms, a set of various experts predict the price relative vector of next period. Then, one of existing algorithms in prediction theory with expert advice is used to assign weights to experts. Then, a learning technique is used for portfolio optimization which leads to portfolio of next period. Results: The results show the superiority of the proposed algorithms to other algorithms existing in literature based on return and risk-adjusted return criteria. Conclusion: The concept of mean reversion can be better expressed by using multi-period mean reversion. In addition, using different experts’ advices make predictions more accurate and therefore better portfolios are suggested. Also, the use of weighting system indirectly brings robustness in the algorithms because it reduces the weights assigned to experts with poor predictions and transforms it to other experts with proper predictions.

https://jfr.ut.ac.ir/article_78466_3aa379b5342699c8334ea58a23782761.pdf

Univrsity Of Tehran Press Financial Research Journal 1024-8153 22 3 2020 10 22 The Impact of Operational Diversification and Investment Opportunities on the Relationship between Cost of Capital and CEO Change The Impact of Operational Diversification and Investment Opportunities on the Relationship between Cost of Capital and CEO Change 428 450 78468 10.22059/frj.2020.279441.1006858 FA Mohsen Rashidi Assistant Prof., Department of Accounting, Faculty of Economics and Administrative Sciences, Lorestan University, Khoram Abad, Iran. Journal Article 2019 04 22 Objective: The opportunistic approach of managers leads to decisions on personal interests and the imposition of costs on the part of shareholders through increased agency costs. This paper, aims to examine the interaction between cost of capital and manager change based on operational diversification and investment opportunities. Methods: To empirically examine this effect, data on companies listed on the Tehran Stock Exchange for the period of 2009 to 2018 were collected and a hybrid data regression model was used to test the research hypotheses. Results: The results of the research show that cost of capital (expected returns) and investment opportunities have a significant effect on management turnover. On the other hand, we do not find evidence on the impact of under-investment and operational diversification on the possibility of CEO change. Furthermore, the interactive effect of investment opportunities and cost of capital on management turnover is also confirmed. Finally, our results Indicate that the change of CEO is a function of the interactive effect of operational diversification and cost of capital. Conclusion: Managerial opportunism and inefficiency of investment increase the cost of corporate capital because the manager's inappropriate decision leads to an increase in the risk of wrong choices for investors. Changing the managerial decision approach leads to the transmission of information to shareholders in order to maintain or change management. Objective: The opportunistic approach of managers leads to decisions on personal interests and the imposition of costs on the part of shareholders through increased agency costs. This paper, aims to examine the interaction between cost of capital and manager change based on operational diversification and investment opportunities. Methods: To empirically examine this effect, data on companies listed on the Tehran Stock Exchange for the period of 2009 to 2018 were collected and a hybrid data regression model was used to test the research hypotheses. Results: The results of the research show that cost of capital (expected returns) and investment opportunities have a significant effect on management turnover. On the other hand, we do not find evidence on the impact of under-investment and operational diversification on the possibility of CEO change. Furthermore, the interactive effect of investment opportunities and cost of capital on management turnover is also confirmed. Finally, our results Indicate that the change of CEO is a function of the interactive effect of operational diversification and cost of capital. Conclusion: Managerial opportunism and inefficiency of investment increase the cost of corporate capital because the manager's inappropriate decision leads to an increase in the risk of wrong choices for investors. Changing the managerial decision approach leads to the transmission of information to shareholders in order to maintain or change management.

https://jfr.ut.ac.ir/article_78468_a06eecfd7930daea9bb0bf2ea07b3689.pdf