Investigating the Dynamic Relationship between Bit coin and Stock Index, Gold and Dollar in Iran: An Application of the Wavelet Coherency Approach

Document Type : Research Paper

Authors

1 Ph.D. Candidate, Department of Economics, Aligudarz Branch, Islamic Azad University, Aligudarz, Iran.

2 Assistant Professor, Department of Economics, Ayatollah Boroujerdi University, Boroujerd, Iran.

3 Assistant Professor of Applied Mathematics, Aligudarz Branch, Islamic Azad University, Aligudarz, Iran.

10.22103/jdc.2022.19251.1224

Abstract

Objective The main purpose of this study is to investigate the co-movement analysis of bitcoin, gold, stocks and dollars markets in the Iranian economy. The reason for focusing on this goal is high inflation in the country and the influx of investors into the financial markets. In addition, given the current state of the global economy and all the economic crises caused by Covid-19, these markets are affected. The results of this study provide new interpretations of the return of financial markets for investment in the society.
Method: To achieve this goal, the analysis of the wavelet coherence analysis and perspectives in wavelet, mobility and two-way relationship of these markets in the Iranian economy in the period September 2011 to January 2022 was studied. Wavelet coherence, wavelet energy spectrum and opposite phase are some of the techniques that have been used to interpret the relationship mutually between different markets. The methodology of wavelet coherence has gained immense popularity over the last few years in the domain of finance and economics. Wavelet Coherence a bi-variate framework used to study the interaction between different time series and their evolution over a continuous time and frequency space. Some of useful wavelet coherence technical interpretations are: it indicates the direction of co-movement between variables and the right indicate perfectly phased variables.
Results: The results show that the co-movement between the bitcoin market and stocks in Iran in different periods have moved in different directions. This is because the bitcoin market is a global market whose changes in performance are not very affected by changes in domestic demand, and in addition, the demand of the Iranian society for bitcoin does not have a long history.
The co-movement between the Bitcoin and exchange rate and Bitcoin and gold markets is similar specially it is more in the short and medium term than in the long term.
The strongest correlation between the studied markets has been between gold and foreign exchange. In this regard, gold moves after the dollar exchange rate and their relationship are direct, that is, with the increase of the dollar exchange rate, the price of gold has also increased. After these years, during the years between 2016 to 2017, the intensity of the relationship between gold coins and the dollar exchange rate has not been high, especially in the long run, but after 2016 and with the intensification of banking sanctions and severe fluctuations in the coin and gold markets, in addition to the high intensity of the coherence of these markets at all time scales, the movement of the two variables is also in phase. In other words, in the years after the sanctions, coin prices and exchange rates have had a direct and high movement with each other, and this movement and its intensity has continued in the short run, medium run and long run horizons in 2012 and 2013, which is consistent with real evidence. Iran's economy is over the years. From 2014 to 2018, after the start of negotiations and the gradual lifting of some sanctions and then the severe application of sanctions during the BARJAM agreements (Joint Comprehensive Plan of Action(, stability returned to the gold and foreign exchange markets, and then again fluctuations affect the market so the dollar has depreciated significantly. The periods of coherence between the stock market and gold have been similar to the two gold and foreign exchange markets, but with less intensity.
Conclusion: The results of the study offer new interpretations of the return of financial markets for investors. In their investment decisions, economic actors need to base the type and changes between markets, knowing that investing in gold, currency and stock markets in the country is largely influenced by political changes and investments. The bitcoin market is largely influenced by the rules and regulations of the central banks of the world's top economies such as the United States and China, and the world's major policies in buying this cryptocurrency and selling our own products in return. It is suggested that when investing in the cryptocurrency market, the economic policies and programs of the central banks of the world's top economies and the position of the world's largest companies (such as Tesla) against this cryptocurrency must be taken into account. Also, it seems that due to the stronger correlation between the bitcoin, gold and dollar markets and the relatively low correlation between bitcoin and stock returns, economic policymakers need to consider the impact of the bitcoin in their monetary policy. It is an externalization that can affect the monetary policy of the central bank, especially in the medium term, due to the phenomena of financial transmission.

Keywords

Main Subjects


پازوکی، نیما؛ حمیدیان، اکرم؛ محمدی، شاپور و محمود، وحید (1392). استفاده از تبدیل موجک جهت بررسی میزان همبستگی نرخ ارزهای مختلف، قیمت نفت، قیمت طلا و شاخص بورس اوراق بهادار تهران در مقیاس‌های زمانی مختلف. دانش سرمایه‌گذاری، 2(7)، 148-131.
جهانشاد، آزیتا و خلیلی، احد (1392). رابطه بین بازده سهام و نرخ رشد دارایی های ثابت در بازه های زمانی مختلف با استفاده از تبدیل موجک. مهندسی مالی و مدیریت اوراق بهادار، 15، 16-1.
صالحی‌فر، محمد (1397). بررسی رفتار بازده و ریسک بیت‌‌‍کوین درمقایسه با بازارهای طلا، ارز و بورس با رویکرد GARCH GJR مدل‌های و گارچ آستانه. فصلنامه مهندسی مالی و مدیریت اوراق بهادار، 40، 168-152.
صمدی، سعید؛ نظیفی نایینی، مینو (1392). تحلیل عوامل موثر بر نوسان‌های قیمت طلا با استفاده از مدل‌های رگرسیون سوئیچینگ مارکوف و شبکه عصبی. دوفصلنامه اقتصاد پولی و مالی، 20(6)، 146-121.
مرادزاده، منصوره، (1395). بیت کوین در اقتصاد جهانی. دومین همایش چشم انداز تکنولوژی کامپیوتر و شبکه در 2030، میبد، https://civilica.com/doc/654998
مرادی، مهوش؛ آهنگری، عبدالمجید و آرمن، سید عزیز (1397). هم حرکتی و علیت بازار دارایی‌ها (بازار مسکن و دارایی‌های مالی) در اقتصاد ایران: رویکرد موجک. مطالعات اقتصاد کاربردی ایران، 7(28)، 181-163.
مصلی، مهسا؛ روحانی، آرمین و محمدی، مجید. (1397). پول دیجیتال بیت کوین و بررسی نقش آن در توسعه تجارت الکترونیک ایران. هفتمین کنفرانس ملی کاربردهای حسابداری و مدیریت،تهران، https://civilica.com/doc/807478.
نادمی، یونس و خوچیانی، رامین (1396). هم‌حرکتی بازارهای سهام، ارز و طلا در ایران، تحلیل اکنو فیزیک. مهندس مالی و مدیریت اوراق بهادار، 8(31)، 141-111.
References
Aguiar-Conraria, L., & Soares, M.J. (2011). The continuous wavelet transform: A primer (No. 16/2011). NIPE-Universidade do Minho.
Ammous, S. (2018). Can cryptocurrencies fulfil the functions of money? The Quarterly Review of Economics and Finance, 70, 38–51.
Baars, W.J., Talluru, K.M., Hutchins, N., & Marusic I. (2015). Wavelet analysis of wall turbulence to study large-scale modulation of small scales. Experiments in Fluids, 188, 1-15.
Balcilar, M., Gupta, R., Jooste, C., & Wohar, M.E. (2016). Periodically collapsing bubbles in the South African stock market. Research in International Business and Finance, 38, 191-201.
Baur, D., & Dimpfl, Th. (2021). The volatility of Bitcoin and its role as a medium of exchange and a store of value. Empirical Economics, 61, 2663–2683.
Baur, D.G., Dimpfl, T., & Kuck, K. (2018). Bitcoin, gold and the US dollar–A replication and extension. Finance Research Letters, 25, 103–110.
Beneki, C., Koulis, A., Kyriazis, N.A., & Papadamou, S. (2019). Investigating volatility transmission and hedging properties between Bitcoin and Ethereum. Research in International Business and Finance, 48, 219–227.
Bhuiyan, R.A., Afzol, H., & Changyong, Z. (2021). A wavelet approach for causal relationship between bitcoin and conventional asset classes. Resources Policy, 71(C), 101971.
Böhme, R., Christin, N., Edelman, B., & Moore, T. (2015). Bitcoin: Economics, technology, and governance. Journal of Economic Perspectives, 29, 213–38.
Bouri, E., Molnar, P., Azzi, G., Roubaud, D., & Hagfors, L.I. (2017). On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier? Finance Research Letters, 20, 192–198.
Brandner, P., Venning, J., & Pearce, B. (2018). Wavelet analysis techniques in cavitating flows. The Royal Society publishing, 1-21.
Chiu, J. (2018). The economics of crypto currencies– bit coin and beyond. Financial Review, 53(2), 217-229.
Conlon, Th., & McGee, R. (2020). Safe haven or risky hazard? Bitcoin during the Covid-19 bear market. Finance Research Letter, 35, 1-5.
Demir, E., Mehmet, H., Gokhan, K., & Asli Cansin, D. (2020). The relationship between crypto currencies and COVID-19 pandemic. Eurasian Economic Review, 10(3), 349–360.
Dyhrberg, A.H. (2016a). Bitcoin, gold and the dollar–A GARCH volatility analysis. Finance Research Letters, 16, 85–92.
Dyhrberg, A.H. (2016b). Hedging capabilities of bitcoin. Is it the virtual gold? Finance Research Letters 16: 139–44.
Fassas, A.P., Papadamou, S., & Koulis, A. (2020). Price discovery in bit coin futures. Research in International Business and Finance, 52, 101-116.
Fischer, T.G., Krauss, C., & Deinert, A. (2019). Statistical arbitrage in cryptocurrency markets. Journal of Risk and Financial Management, 12(1), 31.
Frisby, D. (2014). Bitcoin: The future of money? Unbound, London.
Gallegati, M., Gallegati, M., James, B., & Semmler, R.W. (2017). Long waves in prices: New evidence from wavelet analysis, Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), 11(1), 127-151.
Gans, J.S., & Halaburda, H. (2015). Some economics of private digital currency. In Economic Analysis of the Digital Economy. Chicago: University of Chicago Press, 257–276.
Ghorbel, A., & Jeribi, A. (2021). Investigating the relationship between volatilities of cryptocurrencies and other financial assets. Decisions in Economics and Finance, 44, 817–843.
Glaser, F., Haferhorn, M., Weber, M.C., Zimmarmann, K., & Siering, M.B. (2014). Bitcoin– Asset or currency? Revealing users’ hidden intentions. ECIS 2014 Tel Aviv.
Goodel, J. (2020). Co-movement of COVID-19 and Bitcoin: Evidence from wavelet coherence analysis. Finance Research Letters, 32(3), 211-226.
Grinberg, R. (2012). Bitcoin: An innovative alternative digital currency. Hastings Sci. & Tech. LJ, 4, 159.
Grinsted, A., Moore, J.C., & Jevrejeva, S. (2004). Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Process. Geophys. 11, 561–566.
Jahanshad, A., & Khalili, A (2012). The relationship between stock returns and the growth rate of fixed assets in different time frames using wavelet transformation. Financial Engineering and Securities Management, 15, 1-16 [In Persian].
KhamisHamed, A.Y., Mobeen Ur, R., Walid, M., Idries, A.J., & Wanas, M. (2019). Can uncertainty indices predict Bitcoin prices? A revisited analysis using partial and multivariate wavelet approaches. The North American Journal of Economics and Finance,  49(C), 47-56.
Kim, J.M., Kim. S.T., & Kim, S. (2020). On the relationship of crypto currency price with US stock and gold price using copula models. Mathematics, MDPI, 8(11), 1-15.
Kristoufek, L. (2013). BitCoin meets Google trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era. Scientific reports, 3, 3415.
Kwon, J. (2020). Tail behavior of Bitcoin, the dollar, gold and the stock market index? Journal of International Financial Markets, Institutions & Money, 67, 1-14.
Kyriazis, N.A., & Prassa, P. (2019). Which cryptocurrencies are mostly traded in distressed times? Journal of Risk and Financial Management, 12, 135.
Kyriazis, N.A., Daskalou, K., Arampatzis, M., Prassa, P., & Papaioannou, E. (2019). Estimating the volatility of cryptocurrencies during bearish markets by employing GARCH models. Heliyon, 5: e02239.
Maese, V.A., Avery, A.W., Naftalis, B.A., Wink, S.P., & Valdez, Y.D. (2016). Cryptocurrency: A Primer. Banking LJ 133, 468.
Moradzadeh, Mansoura, (2015). Bitcoin in the global economy. The second conference on the vision of computer and network technology in 2030, Meibod, https://civilica.com/doc/654998 [In Persian].
Mosslla, M., Rouhani, A., & Mohammadi, M. (2017). Bitcoin digital currency and its role in the development of Iran's e-commerce. The 7th National Conference on Accounting and Management Applications. Tehran, https://civilica.com/doc/807478 [In Persian].
Nadami, Y., & Khochiani, R. (2016). Co-movement of stock, currency and gold markets in Iran, economic analysis. Financial Engineer and Securities Management, 8(31), 111-141 [In Persian].
Pazoki, N., Hamidian, A., Mohammadi, S., & Mahmoudi, V. (2013). Correlation analysis of stock exchange index, oil price, exchange rate and gold price: A wavelet decomposition method. Journal of Investment Knowledge, 2, 131-148 [In Persian].
Plassaras, N.A. (2013). Regulating digital currencies: Bringing Bitcoin within the reach of IMF. Chi. J. Int'l L., 14, 377.
Salehifar, M. (2017). Investigating the return and risk behavior of Bitcoin in comparison with the gold, foreign exchange and stock markets with the GARCH GJR approach- models and GARCH Astana. Financial Engineering and Securities Management Quarterly, 40, 168-152 [In Persian].
Samadi, S., & Nazifi Naeini, M. (2012). Analysis of factors affecting gold price fluctuations using Markov switching regression and neural network models. Quarterly Journal of Monetary and Financial Economics, 20(6), 121-146 [In Persian].
Schneider, K., & Vasilyev, O. V. (2010). Wavelet methods in computational fluid dynamics. Annual review of fluid mechanics, 42, 473-503.Selgin, G. (2015). Synthetic commodity money. Journal of Financial Stability, 17, 92–99.
Simoni, D., Lengani D., & Guida, R. (2016). A wavelet-based intermittency detection technique frompiv investigations in transitional boundary layers. Experiments in Fluids, 57, 145.
Stengos, Th. (2021). Recent developments in cryptocurrency markets: Co-Movements, spillovers and forecasting. Journal of Risk and Financial Management, 14(91), 1-3.
Tiwari, A.K., Kumar, S., & Pathak, R. (2019). Modelling the dynamics of Bitcoin and Litecoin: GARCH versus stochastic volatility models. Applied Economics, 51, 4073–4082.
Torrence, C., & Webster, P.J. (1999). Interdecadal changes in the ENSO–monsoon system. Journal of Climate, 12(8), 2679-2690.
Wei, W.C. (2018). Liquidity and market efficiency in cryptocurrencies. Economics Letters, 168, 21–24.
Whelan, K. (2013). How is bitcoin different from the dollar? Forbes. URL: http://www.forbes.com/sites/karlwhelan/ 2013/11/19/how-is-bitcoin-different-from-the-dollar.