بررسی سرایت پذیری تلاطم میان نرخ بازده دلار، شاخص هم وزن سهام، صندوق طلا و بیت کوین با استفاده از مدل DECO-GARCH
فصلنامه بورس اوراق بهادار

فصلنامه بورس اوراق بهادار

بررسی سرایت پذیری تلاطم میان نرخ بازده دلار، شاخص هم وزن سهام، صندوق طلا و بیت کوین با استفاده از مدل DECO-GARCH

نوع مقاله : مقاله پژوهشی

نویسندگان
1 استاد، گروه اقتصاد، دانشکده اقتصاد و مدیریت، دانشگاه سمنان، سمنان، ایران.
2 دانشیار، گروه مدیریت، دانشکده اقتصاد و مدیریت، دانشگاه سمنان، سمنان، ایران.
3 دانشجوی دکتری، گروه مهندسی مالی، دانشکده اقتصاد و مدیریت، دانشگاه سمنان، سمنان، ایران.
4 دانشجوی دکتری، گروه مهندسی مالی، دانشکده اقتصاد و مدیریت، دانشگاه سمنان، سمنان، ایران
چکیده
هدف اصلی مطالعه حاضر بررسی سرایت تلاطم میان نرخ دلار، صندوق طلا، شاخص هم وزن سهام و بیت کوین می باشد. در این پژوهش از داده های روزانه نرخ بازده دلار، صندوق طلا، شاخص هم وزن و بیت کوین طی دوره زمانی آبان ۱۳۹۶ تا تیر ماه ۱۴۰۲ مورد استفاده گردیده است. در این مطالعه ابتدا از مدل میانگین ARMA(1,1) جهت استخراج باقیمانده ها، استفاده شده است سپس برای بررسی سرریز تلاطم مدل DECO-GARCH به کارگرفته شد. نتایج حاصل از برآورد مدل DECO-GARCH، وجود اثر سرایت و انتقال تلاطم بین نرخ بازده دلار، صندوق طلای لوتوس، شاخص هم وزن و بیت کوین تایید می شود به صورتی که نوسان و تلاطم در قیمت هر یک از بازارها به صورت آنی بر نوسان سایر بازارها اثر می گذارد. شواهد نشان می دهد که بازارهای مالی از یکدیگر جدا نیستند و با هم در ارتباط هستند بنابرین تلاطم می تواند از بازاری به بازار دیگر منتقل شود در نتیجه تحلیل یک بازار دارایی مالی بدون در نظرگرفتن شرایط دیگر بازارها تقریبا فاقد اعتبار بوده و نیاز است تحلیل گران، سرمایه گذاران و سیاست گذاران تصمیمات و ارزیابی های خود را براساس روابط بین بازار دارایی های مالی مختلف انجام دهند با توجه به نتایج به دست آمده که حاکی از وجود انتقال تلاطم دارد سرمایه گذاران و مدیران پرتفوی جهت کاهش ریسک و همچنین جهت انتخاب سبد بهینه می توانند از یافته های پژوهش حاضر بهره-مند گردند.
کلیدواژه‌ها
موضوعات

عنوان مقاله English

Investigating The Volatility Transmissions among Exchange Rate, Equally weighted stock index, Gold ETF and Bitcoin Using the DECO-GARCH

نویسندگان English

Esmaiel abounoori 1
Gholamhosein Golarzi 2
Seyed Ramin Abolfazli 3
hossein veisi 4
1 Professor, Department of Economic, Faculty of Economic & Management, Semnan University, Semnan, Iran.
2 Associate Professor, Department of Management, Faculty of Economic & Management, Semnan University, Semnan, Iran
3 Ph.D. Student, Department of Financial Engineering, Faculty of Economic & Management, Semnan University, Semnan, Iran.
4 Ph.D. Student, Department of Financial Engineering, Faculty of Economic & Management, Semnan University, Semnan, Iran.
چکیده English

The main purpose of this study is to investigate the Volatility Spillovers between the Dollar/Rial, Gold ETF, equally weighted stock index and bitcoin. In this research, the daily data of return of dollar/rial, Gold ETF (LOTUS Gold Fund), the E-W Index and bitcoin during the period of November 2016 to July 2023 have been used. In this study, the ARMA (1,1) model was used to extract the residuals, then the DECO-GARCH model was used to check the volatility spillovers. The results of the estimation of the DECO-GARCH model confirm the existence of the spillover effect and the Volatility transmission between the Retuns of the dollar, the Lotus Gold Fund, the E-W Index, and bitcoin, so that the fluctuation and Volatility in the price of each of the markets fluctuate instantaneously, other markets are affected. The evidence shows that the financial markets are not separate from each other and relate to each other, so the Volatility can be transferred from one market to another market. As a result, the analysis of a financial asset market without considering the conditions of other markets is almost without credibility and analysts are needed. Investors and policy makers should make their decisions and evaluations based on the relationships between different financial asset markets, according to the results obtained, which indicate the existence of Volatility transmission, investors, and portfolio managers to reduce risk and to choose the optimal portfolio They can benefit from the findings of this research.

کلیدواژه‌ها English

volatility Spillover
GOLD ETF. Equally Weighted Stock Index
Bitcoin
DECO-GARCH Model
Abdullah, A. M; Saiti, B; & Masih, M. (2016). The impact of crude oil price on Islamic stock indices of South East Asian countries: Evidence from MGARCH-DCC and wavelet approaches. Borsa Istanbul Review, 16(4), 219-232
Abounoori, E; Abdollahi, M. (2013). Modeling Different Sector Volatility of Iran Stock Exchange Using Multivariate GARCH Model. Financial Research Journal, 14(1), 1-16. (In Persian).
Abounoori, E; Keshavarz Hadad, G; & Mirzaaghanasab, I. (2020). Estimation of the volatility transmissions between the exchange rate and the stock market returns in terms of individual industries in Iran. The Journal of Economic Policy, 12(23), 253-278. (In Persian).
Abounoori, E; Ziauddin, H. (2020). Return and Volatility of International Oil Price and Stock Index in OPEC Member Countries. Quarterly Journal of Economical Modeling, 14(1), 1-24. (In Persian).
Bala, D. A; & Takimoto, T. (2017). Stock market's volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach. Borsa Istanbul Review, 17(1), 25-48
Barkhordari, F; Pour azizi gelin gheshlaghi, S; Hoseini, A. (2017) The effect of exchange rate volatilities and it's spillover effect on the index of Tehran Stock Exchange. Journal of Investment knowledge, 6(21), 1-14. (In Persian).
Baruník, J; Kočenda, E; & Vácha, L. (2016). Gold, oil, and stocks: Dynamic correlations. International Review of Economics & Finance, 42, 186-201
BAutwens, L; & LAutrent, S. (2005). A new class of multivariate skew densities, with application to generalized Autoregressive conditional heteroscedasticity models. Journal of Business & Economic Statistics, 23(3), 346-354.
Bin. MO, H. Nie, Y. Jiang.(2018). Dynamic linkages among the gold market, US dollar and crude oil market, Physica A (491)
Bollerslev, T; Engle, R. F; & Wooldridge, J. M. (1988). A capital asset pricing model with time-varying covariance's. Journal of political Economy, 96(1), 116-131
Bonato, M; Caporin, M; & Ranaldo, A. (2013). Risk spillovers in international equity portfolios. Journal of Empirical Finance, 24, 121-137.
Dornbusch, R; Park, Y. C; & Claessens, S. (2000). Contagion: understanding how it spreads. The World Bank Research Observer, 15(2), 177-197.
Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized Autoregressive conditional heteroskedasticity models. Journal of Business & Economic Statistics, 20(3), 339-350.
Fallahi, F; Hghighat, J; Sanoubar, N; & Jahangiri, K. (2014). Study of Correlation between Volatility of Stock, Exchange and Gold Coin Markets in Iran with DCC-GARCH Model. Economics Research, 14(52), 147-123. . (In Persian).
Fioruci, J. A; Ehlers, R. S; & Andrade Filho, M. G. (2014). Bayesian multivariate GARCH models with dynamic correlations and asymmetric error distributions. Journal of Applied Statistics, 41(2), 320-331.
Hamao, Y; Masulis, R. W; & Ng, V. (1990). Correlations in price changes and volatility across international stock markets. The review of financial studies, 3(2), 281-307.
He, C; Silvennoinen, A; & Teräsvirta, T. (2008). Parameterizing unconditional skewness in models for financial time series. Journal of Financial Econometrics, 6(2), 208-230.
Hosseyni, S; Memarnejad, A; ghafari, F. (2023). The Transition Mechanism of Foreign Exchange Crisis on Iran Stock Market Using Markove Switching Approach. Journal of Securities Exchange, 15(60), 105-134(In Persian).
Hou, Y. G; & Li, S. (2020). Volatility and skewness spillover between stock index and stock index futures markets during a crash period: New evidence from China. International Review of Economics & Finance, 66, 166-188.
Kodres, L. E; & Pritsker, M. (2002). A rational expectations model of financial contagion. The journal of finance, 57(2), 769-799.
Koutmos, G; & Spillover Effect on Different industries For Capital MarketBooth, G. G. (1995). Asymmetric volatility transmission in international stock markets. Journal of international Money and Finance, 14(6), 747-762.
Lafuente, J. Á; & Ruiz, J. (2004). The New Market effect on return and volatility of Spanish stock indexes. Applied Financial Economics, 14(18), 1343-1350.
Malik, F; & Ewing, B. T. (2009). Volatility transmission between oil prices and equity sector returns. International Review of Financial Analysis, 3(18), 95-100.
Massacci, D. (2014). A two-regime threshold model with conditional skewed Student t distributions for stock returns. Economic Modelling, 43, 9-20.
Pouryaghoubi, H; Ashrafi, Y.(2020) Spillover Effect On Different industries For Capital Market. Journal of Investment knowledge, 9(34), 277-293. (In Persian).
Saiti, B; & Noordin, N. H. (2018). Does Islamic equity investment provide diversification benefits to conventional investors? Evidence from the multivariate GARCH analysis. International Journal of Emerging Markets.
Saiti, B; Bacha, O. I; & Masih, M. (2016). Testing the conventional and Islamic financial market contagion: evidence from wavelet analysis. Emerging Markets Finance and Trade, 52(8), 1832-1849
Salimi, S; Saeedi, A; Heidarzadeh, A; Emamverdi, G. (2023). Efficiency of dynamic econometric models to cover the cross-risk of stock returns and coin futures contracts in the capital market of Tehran. Journal of Securities Exchange, 15(60), 375-406. (In Persian).
Seyedhosseini, S; ebrahimi, S. (2013). Modeling and Evaluation of Volatility Transmission Using Multivariate GARCH, Case study: Iran, Emirates, Oil Global Price Index. Journal of Securities Exchange, 6(21), 64-137. (In Persian).
Valls Ruiz, N. (2014). Volatility in financial markets: The impact of the global financial crisis.
Wang, Y; & Liu, L. (2016). Spillover effect in Asian financial markets: A VAR-structural GARCH analysis. China Finance Review International, 6(2), 150-176.
Y, Jiang; F, Yuyuan; R, Weihuan. (2019). Risk Spillover and Portfolio management between precious metal and BRICS stock markets. Physica A (534)
Yin, K; Liu, Z; & Jin, X. (2020). Interindustry volatility spillover effects in China’s stock market. Physica A: Statistical Mechanics and its Applications, 539, 122936
Zamani, S; Souri, D; Sanaei Alam, M. (2011). A Dynamic Investigation to Indexes Spillovers in Tehran Stock Exchange Using a Multivariate Dynamic Model. Journal of Economic Research, 45(4), 29-54. (In Persian).