بررسی راهبردهای معاملاتی در مبادله اختیار خرید سهامهای ریلی و تحلیل فرصتهای سوداگری | ||
| سیاست گذاری اقتصادی | ||
| دوره 17، شماره 33، فروردین 1404، صفحه 148-179 اصل مقاله (796.3 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22034/epj.2024.20854.2533 | ||
| نویسندگان | ||
| سهیلا اجاقی1؛ کاظم یاوری* 2؛ محمد علی فیض پور3؛ حبیب انصاری سامانی3 | ||
| 1دانشجوی دکتری اقتصاد مالی،دانشکده اقتصاد، مدیریت، حسابداری، دانشگاه یزد، یزد، ایران | ||
| 2. استاد گروه اقتصاد، دانشکده اقتصاد، مدیریت، حسابداری، دانشگاه یزد، یزد، ایران | ||
| 3دانشیار گروه اقتصاد، دانشکده اقتصاد، مدیریت، حسابداری، دانشگاه یزد، یزد، ایران | ||
| چکیده | ||
| در دنیای مالی، مدیریت ریسک در واقع یک نوع فرایند شناسایی، تجزیه وتحلیل و پذیرش یا کاهش نااطمینانی در تصمیمات سرمایهگذاری است. میتوان با مدلهایی برای پوشش ریسک، زمینههای مناسب را برای مدیریت ریسک و فرصتهای سودآوری و ایجاد بازده فراهم ساخت. به این منظور قیمت سهامهای فرابورسی شرکتهای حمل و نقل ریلی برای سالهای 1400 تا 1402 استخراج شده است. در این مطالعه پس از محاسبه قیمت اختیارخرید سهام شرکتهای ریلی با توجه به مدل قیمتگذاری درخت دوجملهای، استراتژی معاملاتی متقارن استردال و استراتژی معاملاتی نامتقارن بدبینانه و بازدهی مناسب معاملهگران باتوجه به نوسانات قیمت سهام برآورد میشود. نتایج به دست آمده از این مطالعه نشان میدهد که راهبرد بدبینانه، زمانی استفاده میشود که انتظار کاهش قیمت سهام وجود دارد که در شرایط حاضر که بازار بورس در رکود به سر میبرد این استراتژی مناسب است و بازدهی ناشی از راهبرد بدبینانه مثبت خواهد شد و برای سرمایهگذار سودآوری خواهد داشت. استراتژی متقارن استرادل نیز میتواند در بازه مشخصی هم در جهت افزایش قیمت سهام و هم در کاهش قیمت سهام برای سرمایهگذار سودآوری داشته باشد. افزایش قیمت سهام را میتوان برای زمانی پیشبینی کرد که توافق برای کشور رخ دهد که تأثیرات مثبت خود را بر بازار سرمایه خواهد داشت. | ||
| کلیدواژهها | ||
| اختیار معامله"؛ استراتژی استرادل"؛ استراتژی معاملاتی بدبینانه"؛ شبیهسازی مونت کارلو"؛ "؛ مدل درخت دوجملهای" | ||
| عنوان مقاله [English] | ||
| Investigating Trading Strategies in Call Option Exchange of Rail Stock and Analyzing Exchange Opportunities | ||
| نویسندگان [English] | ||
| Soheila Ojaghi1؛ Kazem Yvari2؛ Mohammad Ali Feizpour3؛ Habib Ansari Samani3 | ||
| 1Ph.D. student in financial economics, Faculty of Economics, Management and Accounting, Yazd University, Yazd, Iran | ||
| 2Professor, Department of Economis, Faculty of Economics, Management and Accounting, Yazd University, Yazd, Iran. | ||
| 3Associate Professor, Department of Economics, Faculty of Economics, Management and Accounting, Yazd University, Yazd, Iran | ||
| چکیده [English] | ||
| Purpose: Investors seek solutions in order to manage risks and create security in the market so as to have more control over the value of investment during market fluctuations. For this purpose, various derivatives have been designed. One of them is option. In option markets, those who want to have a lower risk can transfer their risk to those who seek more risk. These markets will provide risk distribution among investors, and no investment has to bear an unfavorable level of risk. Gaining profit with higher returns is one of the attractions of option trading. Investors can often have investment opportunities with the aim of playing the stock market or staying safe from risk by simultaneously buying and selling option contracts. In general, different combinations of option trade strategies provide investors with a suitable basis to earn profit. Recently, Heril rail stock has started to use options in the OTC. Due to the newness of these derivative instruments in the rail sector, no research has been done in this regard. So far, studies have been conducted on the use of trading strategies abroad, but domestic studies are very limited, which is mostly due to asymmetric strategies. No study is yet done on symmetric trading strategies. So, the present study can claim novelty. Methodology: This study focuses on over-the-counter (OTC) railway transportation companies. The OTC shares of railway transportation are for Toka, Hasa, Heparsa, Haseer, Hegardesh, Heril and Heafarin companies. The data of the stock exchange companies of railway transport from 2021 to 2023 were taken from the TseClient 2.0 software, and the stock price information was collected as a daily time series. To calculate the price fluctuations from Excel and to draw a chart related to stock options, the DerivaGem calculation software, which is related to option pricing, and the Python software were used in addition to reviewing the appropriate strategy for risk management and opportunity analysis. This study analyzes the binomial tree pricing model and the strategies adopted on the option to buy rail shares. Among the trading strategies, symmetric straddle and asymmetric Bear Call Spread strategies have been chosen. For analysis, one of the railway companies is selected as an example. This analysis is the same for the other rail stocks, but the outputs are different. Findings and discussion: For the purpose of Binomial option pricing, the exercise price for Heparsa shares is considered to be 77951 Rials. This is based on the maturity of four months and according to Monte Carlo simulation. The annual volatility of Heparsa shares at the chosen time is found to be 39% based on volatility calculation formulas. Also, according to the straddle formulas and the prices resulting from the valuation of the option through the binomial model at the maturity of four months, Long Call Option return of Heparsa stock, Long Put Option return of Heparsa stock, and the total output of the Call option strategy were calculated. The results of the Straddle strategy calculations show that from 64000 to 91300 Rials in the price range of Heparsa shares, there is a negative return on investment. The Call option of Heparsa shares has a positive return at purchase prices lower than 64,000 Rials and at prices higher than 91300 Rials. Recession in the Iranian stock market and the use of Bear Call Spread asymmetric strategy can reconcile investors with this market. According to the Bear Call Spread asymmetric strategy, the Call option of shares of Heparsa with a maturity of four months at the exercise price of 77951 Rials (X2) and the Call option of the same share with a maturity of four months at the exercise price of 64544 Rials (X1) are sold to another investor at less than the price of the previous actions. According to the binomial put option pricing model, the selling price of this Call option is 4.15378 Rials. The closing price of this company's stock at the maturity of four months is estimated by the binomial tree model and found to be 115989, 92708, 74100, 59227 and 47339 Rials. Finally, according to the calculations related to the Bear Call Spread asymmetric strategy, the distance between the exercise prices of 77951 and 64544 rials is a downward trend of returns. The Call option of Heparsa shares will have a positive and constant return of 8126 Rials at the agreed purchase price of less than 64544 Rials, and at a price higher than 77951 Rials will have a negative and constant return of -5281 Rials. Conclusions and policy implications: In this study, profit models resulting from the adoption of symmetric and asymmetric strategies were analyzed. In the last few years, Iran’s stock market has experienced severe fluctuations, and its trend cannot be predicted by any technical or fundamental analysis. For this reason, among options trading strategies, symmetric strategies, straddle model, asymmetric strategies, and Bear Call Spread strategy for risk management in the current market conditions have been selected for investigation. The Bear Call Spread strategy is used when there is an expectation of a decrease in the stock price, which is more appropriate in the current situation when the stock market is in recession, and the return of the Bear Call Spread strategy can be positive and profitable for the investor. The symmetric straddle strategy can be profitable for the investor both in increasing the stock price and in decreasing the stock price. An increase in stock prices can be predicted for the time when an agreement is reached for the country, which will have positive effects on the capital market. In general, it is not possible to find a strategy that works successfully for all conditions and reasons such as risk aversion and risk tolerance of the investor. Also, stock price fluctuations can be influential in choosing the type of strategy | ||
| کلیدواژهها [English] | ||
| Bear Call Spread strategies", Binomial tree model, Monte Carlo simulation", ", Straddle strategy" | ||
| مراجع | ||
|
Abdoh Tabrizi, H., & Asadi Gharehjeloo, B. (2019). An Evaluation of Mutual Funds Performance in Iranian Capital Market by Combining Market Timing Models with the Fama and French three Factor Model. Journal of Investment Knowledge, 8(31), 175-192. (In Persian) Abu Nouri, I., Keshavarz Haddad, GH., & Mirza Aqansab, I. (2020). Export Transfer of Turbulence between Exchange Rate and Stock Market Returns to Industrial Companies in Iran. Economic Policy, 12(23), 253-27. (In Persian) Amiri, M., Mirzapour Babajan, A., & Akbari Moghadam, B. (2019). Investigation of Investment Strategy in Option Contracts with Black-Scholes Pricing Method (Case Study: Gold Coin Option Contracts in Iran Commodity Exchange). Financial Science of Securities Analysis, 11(40), 3-47 (In Persian). Asadi, G. H., Abdoh Tabrizi, H., Hamidizade, M. R., & Farazmand, S. (2023). Investigation of Stock Price Herding in Tehran Stock Exchange. Quarterly Journal of Quantitative Economics, 20(3), 1-34. doi:10.22055/jqe.2021.36054.2310. (In Persian) Badiei, M., Ebrahimi Sarovalia, M. H., & Sargolzaei, M. (2024). Investigating the Effect of Investment on the Efficiency of Factor Pricing Models. Economic Policy, doi:10.22034/epj.2024.20221.2444. (In Persian) Banz, R.W. (1981). The Relationship between Return and Market Value of Common Stocks. Journal of Financial Economics, 9(1), 3-18. Brandimarte, P. (2006). Numerical Methods in Finance and Economics: a MATLABbased Introduction. John Wiley & Sons. Chen, B., Gan, Q., & Vasquez, A. (2023). Anticipating Jumps: Decomposition of Straddle Price. Journal of Banking & Finance, 149, 106755. Derakhshan, M. (2018). Derivatives and Risk Management in Oil Markets (VOL.2). Tehran:Institute of International Energy Studies. (In Persian) Fahlenbrach, R., & Sandas, P. (2010). Does Information Drive Trading in Option Strategies?. Journal of Banking & Finance, 34(10), 2370-2385. Gordiakova, Z., & Lalic, M. (2014). Long Strangle Strategy Using Barrier Options and its Application in Hedging Against a Price Increase. Procedia Economics and Finance, 15, 1438-1446. Guo, J., Li, L., Zhang, J., Shen, Q., Xie, Z., & Li, Q. (2021). A Theory Approach Towards Tradable Rail Freight Option. Discrete Dynamics in Nature and Society, 2021, 1-11. Hajian,M,H.(2013). Risk Delay in Oil Markets Using Financial Derivatives with Emphasis on Option Contracts and Takht. PhD Dissertation, The University of Tarbiat Modares. (In Persian) Hendrawan, R., & Maharsasi, D. E. (2022). Testing Black Scholes and GARCH Model Options on Gold Price Index with Long Strangle Strategy Using 1985-2020 Data. Journal of Finance & Banking Review (JFBR), 7(3), 160-174. Hull, J. (2012). Risk Management and Financial Institutions,+Web Site (Vol.733). John Wiley & Sons. Jeon, J., & Kim, G. (2019). Pricing European Continuous-Installment Strangle Options. The North American Journal of Economics and Finance, 50, 101049. Kiesel, R., & Rahe, F. (2017). Option Pricing Under Time-Varying Risk-Aversion with Applications to Risk Forecasting. Journal of Banking & Finance, 76, 120-138. Kim, K. H., Kim, S. H., & Jo, H. B. (2022). Option Pricing Under Mixed Hedging Strategy in Time-Changed Mixed Fractional Brownian Model. Journal of Computational and Applied Mathematics, 416, 114496. Lai, S., Qiu, J., Tao, Y., & Liu, Y. (2022). Risk Hedging Strategies For Electricity Retailers Using Insurance and Strangle Weather Derivatives. International Journal of Electrical Power & Energy Systems, 134, 107372. Lema, D., & Grandes, M. (2020). Derivatives and Economic Growth: Links and Evidence the Impact of the Financial Derivatives on the Real Economy. Ciencias Administrativas, (16), 44-57. Ling, J., Ni, X., Zhang, Y., & Shen, Z. (2000). Monte Carlo Simulation of Gas Phase Polymerization of 1, 3-Butadiene Part I. Modeling and Programming. Polymer, 41(24), 8703-8707. Liu, D., Liang, Y., Zhang, L., Lung, P., & Ullah, R. (2021). Implied Volatility Forecast and Option Trading Strategy. International Review of Economics & Finance, 71, 943-954. Nabavi Chashmi,S. A., & A. F. (2018). Investigating and Comparing Patterns of Asian, European and American Stock Options in Tehran Stock Exchange. Financial Engineering and Eecurities Management (Portfolio Management). 9(34), 359-380. (In Persian) Rai, R. & Pouyan Far, A. (2009), Advanced Investment Management, Tehran, Samit Publishing House, p. 552. (In Persian) Rostami,M., Makian,N., & Roozegar, R. (2021). Bayesian Modeling of Volatility of Stock Returns with Symmetric and Asymmetric GARCH Models. Economic Policy, 12(24), 171-206. Sadeghi, S.K., Abdulmaleki, H., & Vafai, E. (2014). Asymmetric Investigation of Uncertainty on Macroeconomic Performance in Iran: Observations Based on VARMA, MVGARCH-M Model. Economic Policy, 7(14), 159-181. (In Persian) Shivaprasad, S. P., Geetha, E., Kishore, L., & Matha, R. (2022). Choosing the Right Options Trading Strategy: Risk-Return Trade-off and Performance in Different Market Conditions. Investment Management and Financial Innovations, 19(2), 37-50. TSETMC(2022). Tehran Securities Exchange Technology Management Co, https://www.tsetmc.com/. (In Persian) Vine, S. (2011). Options: Trading Strategy and Risk Management (Vol. 288). John Wiley & Sons. Wang, W. Su, Ch. & Duxbury, D. (2022). The Conditional Impact of Investor Sentiment in Global Stock Markets: A Two-Channel Examination. Journal of Banking & Finance, 138(C). Wang, X. T., Zhao, Z. F., & Fang, X. F. (2015). Option Pricing and Portfolio Hedging Under the Mixed Hedging Strategy. Physica A: Statistical Mechanics and its Applications, 424, 194-206. Wang, X. X., & Huang, J. W. (2009, January). Risk Analysis of Construction Schedule Based on Monte Carlo Simulation. In 2009 International Symposium on Computer Network and Multimedia Technology (pp. 1-4). IEEE. | ||
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