Yıl: 2020 Cilt: 12 Sayı: 23 Sayfa Aralığı: 653 - 671 Metin Dili: Türkçe DOI: 10.14784/marufacd.785878 İndeks Tarihi: 29-09-2022

YATIRIMCILAR İÇİN TEKNİK ANALİZ: BITCOIN VE ETHEREUM UYGULAMALARI

Öz:
Bireysel ve kurumsal yatırımcıların finansal piyasalarda yatırım kararları alırken sıklıkla kullandıkları ana- lizler temel analiz ve teknik analiz şeklinde ikiye ayrılmaktadır. Temel analiz; makroekonomik gidişatı, sektörel gelişmeleri ve spesifik olarak yatırım yapılacak varlığın finansal göstergelerini dikkate alırken, teknik analiz; fi- nansal varlıkların geçmiş fiyat hareketlerinden yola çıkarak bu finansal varlığın gelecekteki fiyat hareketlerini tahminlemeye çalışmaktadır. Teorik altyapısı Dow Teorisine dayanan ve “finansal varlığın geçmiş fiyat hareket- leri zamanla tekrarlanacaktır” gibi bir takım varsayımlar barındıran teknik analiz yöntemine göre yatırım kararı alınırken çeşitli indikatörler, osilatörler ve formasyonlar kullanılmaktadır. Bu göstergelerden Hareketli Ortala- maların Yakınsaması/Uzaklaşması (MACD), Bollinger Band (BBand), Göreceli Güç Endeksi (RSI) yatırımcıla- rın sıklıkla kullandıkları göstergeler arasındadır. Bu çalışmada 2014-2018 Bitcoin (BTC) ve Ethereum (ETH) günlük fiyat verileri kullanılarak MACD, BBand ve RSI test edilmiş, BTC ve ETH Al/Sat kararları tahmin edil- meye çalışılmıştır. Çıkan sonuçlar neticesinde kripto paraların yatırımcılara sağlayacağı getiriler hesaplanmış- tır. Finansal piyasalarda en fazla işlem gören kripto paraların analiz edildiği çalışmada, yatırım kararlarında tek- nik analizin ne derece etkili olduğu ve bu yatırımlardan teknik analiz kullanılarak herhangi bir getiri sağlanıp sağlanamayacağı irdelenmiştir. Elde edilen bulgulara göre BBand, RSI ve MACD yöntemleri birbirleri ile çeliş- kili sinyaller verebilmektedir. Bu nedenle yatırımcıların kullanacakları analiz yöntemine göre kazanç ve kayıp- larının farklılaşabileceğini söylemek mümkündür.
Anahtar Kelime: Kripto Para Teknik Analiz MACD RSI

TECHNICAL ANALYSIS FOR INVESTORS: BITCOIN AND ETHEREUM APPLICATIONS

Öz:
Analyzes that are frequently used by individual and institutional investors when making investment de- cisions in financial markets are divided into fundamental analysis and technical analysis. While fundamental analysis evaluating financial instruments based on macroeconomic factors, sectorial developments, and finan- cial data of the instruments, technical analysis; tries to forecast the future price of this financial instrument us- ing its historical price movements. The theoretical background of the technical analysis is based on the Dow Theory and there are some assumptions such as “historical price movements of financial assets will be repeated over time”. There are also some indicators such as Moving Average Convergence Divergence (MACD), Bollinger Band (BBand), and the Relative Strength Index (RSI) frequently used by investors. In this study, MACD, BBand and RSI tested using 2014-2018 Bitcoin (BTC), Ethereum (ETH) daily price data. BTC and ETH Buy / Sell de- cisions have been tried to be estimated and the return of the cryptocurrencies for investors has been calculated. Analyzing the most frequently traded cryptocurrencies in financial markets, it has been examined how effec- tive the technical analysis is in investment decisions and whether any returns can be obtained by using techni- cal analysis from these investments. According to the findings obtained, BBand, RSI, and MACD methods can give conflicting signals. Therefore, it is possible to say that earnings and losses may differ according to the anal- ysis method used by investors.
Anahtar Kelime: Cryptocurrency Technical Analysis MACD RSI

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
  • ACHELIS, Steven. (2001), Technical Analysis from A to Z. New York: McGraw Hill.
  • AKOĞUZ, Ufuk; AKKAN, Taner. (2018), “Tendency Monitoring and Nearest-Time Estimation of Rapid Chan- ging Data: Cryptocurrency Example” 26th Signal Processing and Communications Applications Confe- rence (SIU). IEEE, 1-3.
  • APPEL, Gerald. (2005), Technical Analysis: Power Tools for Active Investors. FT Press.
  • APPEL, Gerald; HITSCHLER, Frederic. (1980), Stock Market Trading Systems. Homewood, IL: Dow Jo- nes-Irwin.
  • ATZEI, Nicola; BARTOLETTI, Massimo; CIMOLI, Tiziana. (2017), A survey of Attacks on Ethereum Smart Contracts (SoK), In: MAFFEI Matteo; RYAN, Mark (eds) Principles of Security and Trust, Lecture No- tes in Computer Science, Vol 10204. Springer, Berlin.
  • BADEV, Anton; CHEN, Matthew. (2014), “Bitcoin: Technical Background and Data Analysis”, FEDS Working Paper No. 2014-104. Available at SSRN: https://ssrn.com/abstract=2544331
  • BAYRAKTAR, Ahmet. (2012), “Etkin Piyasalar Hipotezi”, Aksaray Üniversitesi İktisadi ve İdari Bilimler Fakül- tesi Dergisi, 4(1), 37-47.
  • BÖHME, Rainer; CHRISTIN, Nicolas; EDELMAN, Benjamin; MOORE, Tyler. (2015), “Bitcoin: Economics, Te- chnology, and Governance”, Journal of Economic Perspectives, 29(2), 213-38.
  • BOLLINGER, John. (1992), “Using Bollinger Bands”, Stocks & Commodities, 10(2), 47-51.
  • BOLLİNGER, John. (2001), Bollinger on Bollinger Bands, 1st Edition, McGraw-Hill Education.
  • BOXER, Harry. (2014), Profitable Day and Swing Trading: Using Price/volume Surges and Pattern Recognition to Catch Big Moves in the Stock Market, John Wiley & Sons.
  • BRYANS, Danton. (2014), “Bitcoin and Money Laundering: Mining for an Effective Solution”, Ind. LJ, 89, 441.
  • CHEN, Shaozhen; ZHANG, Bangqian; ZHOU, GengJian; QIN, Qiaoxu. (2018), “Bollinger Bands Trading Stra- tegy Based on Wavelet Analysis”, Applied Economics and Finance, 5(3), 49-58.
  • CHONG, Terence Tai-Leung; NG, Wing-Kam. (2008), “Technical Analysis and the London Stock Exchange: Testing the MACD and RSI Rules Using the FT30”, Applied Economics Letters, 15(14), 1111-1114.
  • CORBET, Shaen; LUCEY, Brian; YAROVAYA, Larisa. (2018), “Datestamping the Bitcoin and Ethereum Bubb- les”, Finance Research Letters, 26, 81-88.
  • DEGUTIS, Augustas; NOVICKYTĖ, Lina. (2014), “The Efficient Market Hypothesis: A Critical Review of Lite- rature and Methodology”, Ekonomika, 93(2).
  • DEVRIES, Peter. (2016), “An Analysis of Cryptocurrency, Bitcoin, and the Future”, International Journal of Bu- siness Management and Commerce, 1(2), 1-9.
  • DURANTIN, Gautier; SCANNELLA, Sebastien; GATEAU, Thibault; DELORME, Arnaud; DEHAIS, Frede- ric. (2014), “Moving Average Convergence Divergence Filter Preprocessing for Real-Time Event-Rela- ted Peak Activity Onset Detection: Application to fNIRS Signals”, 2014 36th Annual International Con- ference of the IEEE, 2107-2110.
  • FAMA, Eugene. (1965), “The Behavior of Stock-Market Prices”, The Journal of business, 38(1), 34-105.
  • GARAY, Juan; KIAYIAS, Aggelos; LEONARDOS, Nikos. (2015), The Bitcoin Backbone Protocol: Analysis and Applications, In: OSWALD, Elisabeth; FISCHLIN, Marc (eds) Advances in Cryptology – EUROCRYPT 2015. Lecture Notes in Computer Science, Vol 9057. Springer, Berlin.
  • KARAME, Ghassan; ANDROULAKI, Elli; CAPKUN, Srdjan. (2012), “Two Bitcoins at the Price of One? Doub- le-Spending Attacks on Fast Payments in Bitcoin”, IACR Cryptology ePrint Archive, 2012(248).
  • KLASSEN, Myungsook. (2005), “Investigation of Some Technical Indexes in Stock Forecasting Using Neural Networks”, WEC, 5, 75-79.
  • KONDOR, Dániel; PÓSFAI, Márton; CSABAI, István; VATTAY, Gábor. (2014), “Do the Rich Get Richer? An Empirical Analysis of the Bitcoin Transaction Network”, PloS one, 9(2), e86197.
  • KROLL, Joshua; DAVEY, Ian; FELTEN, Edward. (2013), “The Economics of Bitcoin Mining, or Bitcoin In The Presence of Adversaries”, Proceedings of WEIS, 2013, 11.
  • LEUNG, Joseph Man-Joe; CHONG, Terence Tai-Leung. (2003), “An Empirical Comparison of Moving Average Envelopes and Bollinger Bands”, Applied Economics Letters, 10(6), 339-341.
  • LIM, Mark Andrew. (2015), The Handbook of Technical Analysis+ Test Bank: The Practitioner’s Comprehensive Guide to Technical Analysis, John Wiley & Sons.
  • MOORE Tyler; CHRISTIN Nikolas. (2013), Beware the Middleman: Empirical Analysis of Bitcoin-Exchange Risk, In: SADEGHI, Ahmad-Reza (eds) Financial Cryptography and Data Security. FC 2013. Lecture Notes in Computer Science, Vol 7859. Springer, Berlin.
  • OMOHUNDRO, Steve. (2014), “Cryptocurrencies, Smart Contracts, and Artificial Intelligence”, AI mat- ters, 1(2), 19-21.
  • ÖZARI, Çiğdem; TURAN, Kemal; DEMİR, Esra. (2016), “Teknik İndikatörlerin Etkinliği: Bıst30 Ve Bıst100 En- deksleri Üzerine Bir Uygulama”, Nevşehir Hacı Bektaş Veli Üniversitesi SBE Dergisi, 6(1).
  • PONSİ, Ed. (2016), Technical Analysis and Chart Interpretations: A Comprehensive Guide to Understanding Es- tablished Trading Tactics for Ultimate Profit, John Wiley & Sons.
  • REID, Fergal; HARRIGAN, Martin. (2013), An Analysis of Anonymity in the Bitcoin System, In: ALTSHULER, Yaniv; ELOVICI, Yuval; CREMERS, Armin; AHARONY, Nadav; PENTLAND, Alex (eds) Security and Privacy in Social Networks. Springer, New York.
  • SEO, Yunbeom; HWANG, Changha. (2018), “Predicting Bitcoin Market Trend with Deep Learning Models”, Qu- antitative Bio-Science, 37(1), 65-71.
  • SOVBETOV, Yhlas. (2018), “Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litcoin, and Monero”, Journal of Economics and Financial Analysis, 2(2), 1-27
  • VICTOR, Alexander. (2017), Introducing Cryptocurrency, “https://www.researchgate.net/publica- tion/320616742”, Erişim tarihi: 09.10.2018
  • WILDER, J. Welles. (1978), New Concepts in Technical Trading System, Greensboro, NC: Trend Research.
APA UYAR U, KELTEN G, Moralı T (2020). YATIRIMCILAR İÇİN TEKNİK ANALİZ: BITCOIN VE ETHEREUM UYGULAMALARI. , 653 - 671. 10.14784/marufacd.785878
Chicago UYAR UMUT,KELTEN GÖKSAL SELAHATDİN,Moralı Tuncay YATIRIMCILAR İÇİN TEKNİK ANALİZ: BITCOIN VE ETHEREUM UYGULAMALARI. (2020): 653 - 671. 10.14784/marufacd.785878
MLA UYAR UMUT,KELTEN GÖKSAL SELAHATDİN,Moralı Tuncay YATIRIMCILAR İÇİN TEKNİK ANALİZ: BITCOIN VE ETHEREUM UYGULAMALARI. , 2020, ss.653 - 671. 10.14784/marufacd.785878
AMA UYAR U,KELTEN G,Moralı T YATIRIMCILAR İÇİN TEKNİK ANALİZ: BITCOIN VE ETHEREUM UYGULAMALARI. . 2020; 653 - 671. 10.14784/marufacd.785878
Vancouver UYAR U,KELTEN G,Moralı T YATIRIMCILAR İÇİN TEKNİK ANALİZ: BITCOIN VE ETHEREUM UYGULAMALARI. . 2020; 653 - 671. 10.14784/marufacd.785878
IEEE UYAR U,KELTEN G,Moralı T "YATIRIMCILAR İÇİN TEKNİK ANALİZ: BITCOIN VE ETHEREUM UYGULAMALARI." , ss.653 - 671, 2020. 10.14784/marufacd.785878
ISNAD UYAR, UMUT vd. "YATIRIMCILAR İÇİN TEKNİK ANALİZ: BITCOIN VE ETHEREUM UYGULAMALARI". (2020), 653-671. https://doi.org/10.14784/marufacd.785878
APA UYAR U, KELTEN G, Moralı T (2020). YATIRIMCILAR İÇİN TEKNİK ANALİZ: BITCOIN VE ETHEREUM UYGULAMALARI. Finansal Araştırmalar ve Çalışmalar Dergisi, 12(23), 653 - 671. 10.14784/marufacd.785878
Chicago UYAR UMUT,KELTEN GÖKSAL SELAHATDİN,Moralı Tuncay YATIRIMCILAR İÇİN TEKNİK ANALİZ: BITCOIN VE ETHEREUM UYGULAMALARI. Finansal Araştırmalar ve Çalışmalar Dergisi 12, no.23 (2020): 653 - 671. 10.14784/marufacd.785878
MLA UYAR UMUT,KELTEN GÖKSAL SELAHATDİN,Moralı Tuncay YATIRIMCILAR İÇİN TEKNİK ANALİZ: BITCOIN VE ETHEREUM UYGULAMALARI. Finansal Araştırmalar ve Çalışmalar Dergisi, vol.12, no.23, 2020, ss.653 - 671. 10.14784/marufacd.785878
AMA UYAR U,KELTEN G,Moralı T YATIRIMCILAR İÇİN TEKNİK ANALİZ: BITCOIN VE ETHEREUM UYGULAMALARI. Finansal Araştırmalar ve Çalışmalar Dergisi. 2020; 12(23): 653 - 671. 10.14784/marufacd.785878
Vancouver UYAR U,KELTEN G,Moralı T YATIRIMCILAR İÇİN TEKNİK ANALİZ: BITCOIN VE ETHEREUM UYGULAMALARI. Finansal Araştırmalar ve Çalışmalar Dergisi. 2020; 12(23): 653 - 671. 10.14784/marufacd.785878
IEEE UYAR U,KELTEN G,Moralı T "YATIRIMCILAR İÇİN TEKNİK ANALİZ: BITCOIN VE ETHEREUM UYGULAMALARI." Finansal Araştırmalar ve Çalışmalar Dergisi, 12, ss.653 - 671, 2020. 10.14784/marufacd.785878
ISNAD UYAR, UMUT vd. "YATIRIMCILAR İÇİN TEKNİK ANALİZ: BITCOIN VE ETHEREUM UYGULAMALARI". Finansal Araştırmalar ve Çalışmalar Dergisi 12/23 (2020), 653-671. https://doi.org/10.14784/marufacd.785878