{"id":5039,"date":"2023-11-22T16:02:55","date_gmt":"2023-11-22T13:02:55","guid":{"rendered":"https:\/\/datakapital.com\/blog\/?p=5039"},"modified":"2025-07-19T01:27:12","modified_gmt":"2025-07-18T22:27:12","slug":"rsi-goreli-guc-endeksi-makine-ogrenimi-modelleri","status":"publish","type":"post","link":"https:\/\/datakapital.com\/blog\/rsi-goreli-guc-endeksi-makine-ogrenimi-modelleri\/","title":{"rendered":"RSI G\u00f6reli G\u00fc\u00e7 Endeksi Makine \u00d6\u011frenimi Modelleri"},"content":{"rendered":"<p><strong>RSI G\u00f6reli G\u00fc\u00e7 Endeksi<\/strong> Borsa \u0130stanbul\u2019da yat\u0131r\u0131mc\u0131lara potansiyel f\u0131rsatlar\u0131 belirlemek i\u00e7in kulland\u0131\u011f\u0131 \u00e7e\u015fitli teknik indikat\u00f6rlerden birisidir. Bu yaz\u0131da <a href=\"https:\/\/datakapital.com\/blog\/rsi-goreli-guc-endeksi-nedir\/\">RSI (Relative Strength Index &#8211; G\u00f6receli G\u00fc\u00e7 Endeksi)<\/a>\u00a0indikat\u00f6r\u00fc nas\u0131l kullan\u0131labilir bilimsel \u00e7al\u0131\u015fmalardan yararlanarak anlatmaya \u00e7al\u0131\u015ft\u0131k. Tabi ki tek bir teknik indikat\u00f6r her zaman do\u011fru bilgi vermez bu sebeple genellikle birden fazla indikat\u00f6r birlikte de\u011ferlendirilir. \u0130ndikat\u00f6rlerin bir\u00e7o\u011fu hissenin kapan\u0131\u015f, a\u00e7\u0131l\u0131\u015f, en d\u00fc\u015f\u00fck, en y\u00fcksek ve hacim de\u011ferlerini temel alarak hesaplanmaktad\u0131r.<\/p>\n<p><a href=\"https:\/\/www.researchgate.net\/publication\/331147202_Predicting_the_Turkish_Stock_Market_BIST_30_Index_using_Deep_Learning\" target=\"_blank\" rel=\"noopener\">RSI Demirci &amp; Ra\u015fo<\/a> taraf\u0131ndan \u00e7ok say\u0131da indikat\u00f6r aras\u0131ndan derin \u00f6\u011frenme y\u00f6ntemleri ile \u00f6znitelik se\u00e7imi yap\u0131larak BIST tahminlemede teknik indikat\u00f6rlerin etkileri modellenmi\u015ftir. \u00c7al\u0131\u015fmada RSI indikat\u00f6r\u00fc d\u0131\u015f\u0131nda Bollinger Bands, Stochastic Oscillator, Stochastic Oscillator, Simple Moving Average gibi bir \u00e7ok g\u00f6sterge de\u011ferlendirmeye al\u0131nm\u0131\u015ft\u0131r. \u00c7al\u0131\u015fma iki y\u0131ldan fazla bir s\u00fcre i\u00e7in finansal veriler toplanarak yap\u0131lm\u0131\u015ft\u0131r ve BIST 30 i\u00e7in endeks de\u011fer tahminleme ger\u00e7ekle\u015ftirilmi\u015ftir. \u00c7ok say\u0131da indikat\u00f6r\u00fcn birbiri ile korelasyon durumu de\u011ferlendirmesi \u0131s\u0131 haritas\u0131 \u00fczerinden ger\u00e7ekle\u015ftirilmi\u015ftir (Tablo 1). RSI indikat\u00f6r\u00fc \u0131s\u0131 haritas\u0131na g\u00f6re Comodity Channel Index, Moving average convergence divergence, Price Rate of Change ve William_R indikat\u00f6rleri ile y\u00fcksek korelasyona sahiptir.<\/p>\n<figure id=\"attachment_5040\" aria-describedby=\"caption-attachment-5040\" style=\"width: 624px\" class=\"wp-caption alignnone\"><img fetchpriority=\"high\" decoding=\"async\" class=\"wp-image-5040 size-full\" src=\"https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/RSI-korelasyonlar.jpg\" alt=\"G\u00f6reli G\u00fc\u00e7 Endeksi Is\u0131 Haritas\u0131\" width=\"624\" height=\"333\" title=\"\" srcset=\"https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/RSI-korelasyonlar.jpg 624w, https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/RSI-korelasyonlar-300x160.jpg 300w, https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/RSI-korelasyonlar-150x80.jpg 150w, https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/RSI-korelasyonlar-450x240.jpg 450w\" sizes=\"(max-width: 624px) 100vw, 624px\" \/><figcaption id=\"caption-attachment-5040\" class=\"wp-caption-text\">RSI &#8211; Is\u0131 Haritas\u0131<\/figcaption><\/figure>\n<p>Sonu\u00e7lar incelendi\u011finde hata oranlar\u0131n\u0131n 0.0332 ortalama kare hatas\u0131 (mean squared error &#8211; MSE) seviyelerinde oldu\u011fu g\u00f6r\u00fclmektedir.<\/p>\n<p>Ta\u015f &amp; G\u00fcrsoy BIST-30 ve \u0130slami Kat\u0131l\u0131m Endeks verileri \u00fczerinde bulan\u0131k mant\u0131k ile yeni bir teknik g\u00f6sterge \u00fcretmeye \u00e7al\u0131\u015fm\u0131\u015flard\u0131r. \u00c7al\u0131\u015fmada 2012-2014 y\u0131llar\u0131 aras\u0131ndaki veriler kullan\u0131lm\u0131\u015ft\u0131r. G\u00fcnl\u00fck kapan\u0131\u015f ve a\u00e7\u0131l\u0131\u015f fiyatlar\u0131 kullan\u0131larak hesaplanan pop\u00fcler g\u00f6stergeler ve RSI indikat\u00f6r\u00fc d\u0131\u015f\u0131nda; Moving-Average-Convergence-Divergence (MACD), Stochastic-Oscillator (SO) ve On-Balance-Volume (OBV) indikat\u00f6rleri kullan\u0131larak bulan\u0131k mant\u0131k tabanl\u0131 yeni bir g\u00f6sterge olu\u015fturulmu\u015ftur. \u00d6nerilen sistem, \u00fc\u00e7 mod\u00fclden olu\u015fmaktad\u0131r: teknik analiz mod\u00fcl\u00fc, yakla\u015fma mod\u00fcl\u00fc ve bulan\u0131k \u00e7\u0131kar\u0131m mod\u00fcl\u00fc.<\/p>\n<ul>\n<li>Teknik analizde, g\u00f6stergeleri hesaplamak i\u00e7in tarihsel veriler kullan\u0131l\u0131r. Bu \u00e7al\u0131\u015fmada, 2012&#8217;den 2014&#8217;e kadar olan d\u00f6nem i\u00e7in her endeks i\u00e7in fiyatlar kullan\u0131lm\u0131\u015ft\u0131r.<\/li>\n<li>Kapsama mod\u00fcl\u00fc, hesaplanan teknik g\u00f6stergeleri \u00f6nceden belirlenmi\u015f kurallar \u00e7er\u00e7evesinde yeni bir bulan\u0131k g\u00f6stergeye d\u00f6n\u00fc\u015ft\u00fcr\u00fcr.<\/li>\n<li>Bulan\u0131k \u00c7\u0131kar\u0131m Sistemi (BCS) mod\u00fcl\u00fc, yeni bulan\u0131k g\u00f6stergeye dayal\u0131 yeni bir ticaret sinyali olu\u015fturur.<\/li>\n<\/ul>\n<p>Bulan\u0131k mant\u0131k temelli modelin performans\u0131 risk getirisi \u00fczerinden a\u015fa\u011f\u0131daki tabloda de\u011ferlendirilmi\u015ftir.<\/p>\n<figure id=\"attachment_5041\" aria-describedby=\"caption-attachment-5041\" style=\"width: 624px\" class=\"wp-caption alignnone\"><img decoding=\"async\" class=\"wp-image-5041 size-full\" src=\"https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/Borsa-Istanbulda-Teknik-Indikatorlerin-Performansi.png\" alt=\"Bist Teknik \u0130ndikat\u00f6rler\" width=\"624\" height=\"108\" title=\"\" srcset=\"https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/Borsa-Istanbulda-Teknik-Indikatorlerin-Performansi.png 624w, https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/Borsa-Istanbulda-Teknik-Indikatorlerin-Performansi-300x52.png 300w, https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/Borsa-Istanbulda-Teknik-Indikatorlerin-Performansi-150x26.png 150w, https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/Borsa-Istanbulda-Teknik-Indikatorlerin-Performansi-450x78.png 450w\" sizes=\"(max-width: 624px) 100vw, 624px\" \/><figcaption id=\"caption-attachment-5041\" class=\"wp-caption-text\">Teknik \u0130ndikat\u00f6rlerin Bist-30 Performans\u0131<\/figcaption><\/figure>\n<figure id=\"attachment_5042\" aria-describedby=\"caption-attachment-5042\" style=\"width: 624px\" class=\"wp-caption alignnone\"><img decoding=\"async\" class=\"wp-image-5042 size-full\" src=\"https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/RSI-Bist-Performansi.png\" alt=\"G\u00f6reli G\u00fc\u00e7 Endeksi Performans\u0131 Bist\" width=\"624\" height=\"111\" title=\"\" srcset=\"https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/RSI-Bist-Performansi.png 624w, https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/RSI-Bist-Performansi-300x53.png 300w, https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/RSI-Bist-Performansi-150x27.png 150w, https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/RSI-Bist-Performansi-450x80.png 450w\" sizes=\"(max-width: 624px) 100vw, 624px\" \/><figcaption id=\"caption-attachment-5042\" class=\"wp-caption-text\">Teknik \u0130ndikat\u00f6rlerin Kat\u0131l\u0131m Endeksi Performans\u0131<\/figcaption><\/figure>\n<p>Ayy\u0131ld\u0131z &amp; \u0130skendero\u011flu RSI g\u00f6stergesi ile birlikte 9 farkl\u0131 indikat\u00f6r kullanm\u0131\u015ft\u0131r. Bunlar Simple Moving Average (MA), Weighted Moving Average (WMA), Exponential Moving Average (EMA), Momentum (Mom), Stochastic K% (K%), Stochastic D% (D%), Moving Average Convergence\/Divergence (MACD), Larry William\u2019s R% (LW), Commodity Channel Index (CCI) g\u00f6stergeleridir. Her bir g\u00f6sterge ayr\u0131 bir \u00f6znitelik olarak Decision Trees (DT), Random Forest (RF), K-Nearest Neighbors (KNN), Naive Bayes (NB), Logistic Regression (LR), Support Vector Machines (SVM) ve Artificial Neural Networks (ANN) makine \u00f6\u011frenmesi algoritmalar\u0131na g\u00f6nderilmi\u015ftir. Sonu\u00e7lar Tablo 4\u2019te g\u00f6r\u00fclmektedir. Dadece do\u011fruluk (accuracy) de\u011ferleri incelenmi\u015ftir.<\/p>\n<figure id=\"attachment_5043\" aria-describedby=\"caption-attachment-5043\" style=\"width: 580px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-5043 size-full\" src=\"https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/Bist-Makine-Ogrenimi-Dogruluk-Oranlari.png\" alt=\"Teknik Analiz Makine \u00d6\u011frenimi\" width=\"580\" height=\"149\" title=\"\" srcset=\"https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/Bist-Makine-Ogrenimi-Dogruluk-Oranlari.png 580w, https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/Bist-Makine-Ogrenimi-Dogruluk-Oranlari-300x77.png 300w, https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/Bist-Makine-Ogrenimi-Dogruluk-Oranlari-150x39.png 150w, https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/Bist-Makine-Ogrenimi-Dogruluk-Oranlari-450x116.png 450w\" sizes=\"(max-width: 580px) 100vw, 580px\" \/><figcaption id=\"caption-attachment-5043\" class=\"wp-caption-text\">Makine \u00f6\u011frenmesi algoritmalar\u0131n\u0131n do\u011fruluk oranlar\u0131<\/figcaption><\/figure>\n<p>G\u00fcnd\u00fcz, \u00c7ataltepe &amp; Yaslan taraf\u0131ndan Tablo 5\u2019te g\u00f6r\u00fclen t\u00fcm teknik indikat\u00f6rler ilk olarak bir \u00f6znitelik se\u00e7me a\u015famas\u0131ndan ge\u00e7irilerek makine \u00f6\u011frenmesi algoritmalar\u0131 ile AL\/SAT tahminleri yap\u0131lm\u0131\u015ft\u0131r. 2011-2016 y\u0131llar\u0131 aras\u0131nda <a href=\"https:\/\/datakapital.com\/bist\">BIST verilerinden<\/a> yakla\u015f\u0131k 1000 veriden olu\u015fan bir \u00f6rneklem kullan\u0131lm\u0131\u015ft\u0131r.<\/p>\n<figure id=\"attachment_5044\" aria-describedby=\"caption-attachment-5044\" style=\"width: 624px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-5044 size-full\" src=\"https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/Bist-Teknik-Indikatorler.png\" alt=\"Bist&#039;te kullan\u0131lan indikat\u00f6rler\" width=\"624\" height=\"269\" title=\"\" srcset=\"https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/Bist-Teknik-Indikatorler.png 624w, https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/Bist-Teknik-Indikatorler-300x129.png 300w, https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/Bist-Teknik-Indikatorler-150x65.png 150w, https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/Bist-Teknik-Indikatorler-450x194.png 450w\" sizes=\"(max-width: 624px) 100vw, 624px\" \/><figcaption id=\"caption-attachment-5044\" class=\"wp-caption-text\">Kullan\u0131lan teknik indikat\u00f6rler<\/figcaption><\/figure>\n<p>Hasan, Kal\u0131ps\u0131z &amp; Akyoku\u015f taraf\u0131ndan Borsa \u0130stanbul&#8217;dan elde edilen BIST 100 endeksi verileri kullan\u0131larak ger\u00e7ekle\u015ftirilen ba\u015fka bir \u00e7al\u0131\u015fmada endeks verilerinin g\u00fcnl\u00fck, saatlik ve 30 dakikal\u0131k periyotlarda analizi ger\u00e7ekle\u015ftirilmi\u015ftir. Kullan\u0131lan veriler 2008-2016 y\u0131llar\u0131 aras\u0131ndan al\u0131nm\u0131\u015ft\u0131r. Bu veri setleri \u00fczerinde, SVM, Random Forest ve Logistic Regression gibi makine \u00f6\u011frenimi teknikleri kullan\u0131larak tahmin modelleri olu\u015fturulmu\u015ftur. Bu modeller, endeks verilerini s\u0131n\u0131fland\u0131rmak ve BIST 100 endeksinin gelecekteki y\u00f6n\u00fcn\u00fc tahmin etmek amac\u0131yla de\u011ferlendirilmi\u015ftir. Bu \u00e7al\u0131\u015fmada G\u00fcnd\u00fcz, \u00c7ataltepe &amp; Yaslan taraf\u0131ndan kullan\u0131lan teknik indikat\u00f6rler kullan\u0131lm\u0131\u015ft\u0131r. Sonu\u00e7larda saatlik verilerle ile en ba\u015far\u0131l\u0131 sonu\u00e7lar elde edilmi\u015ftir.<\/p>\n<p>T\u00fcfek\u00e7i &amp; Abul ayn\u0131 teknik indikat\u00f6rleri kullanarak bir AL\/SAT karar destek sistemi geli\u015ftirmi\u015ftir. Bu ara\u015ft\u0131rma ba\u011flam\u0131nda, 9 adet BIST-100 hisse senedi kullan\u0131lm\u0131\u015ft\u0131r: ADEL, ARCLK, ASELS, EGEEN, FENER, GOLTS, GOODY, THYAO, TTRAK ve BIST100. Veri seti, on y\u0131l (2006-2016) g\u00fcnl\u00fck kapan\u0131\u015f fiyatlar\u0131n\u0131 i\u00e7ermektedir.<\/p>\n<p>Bu yaz\u0131da <a href=\"https:\/\/datakapital.com\/backtest\/rsi\">RSI<\/a> ile birlikte s\u0131k kullan\u0131lan teknik indikat\u00f6rlerin BIST hisse senetleri i\u00e7in tahminlemede bulan\u0131k mant\u0131k, derin \u00f6\u011frenme ve makina \u00f6\u011frenmesi y\u00f6ntemleri ile nas\u0131l kullan\u0131ld\u0131\u011f\u0131na de\u011findik. Teknik g\u00f6stergeler d\u0131\u015f\u0131nda kullan\u0131lan \u00e7evresel indikat\u00f6rleri bir sonraki yaz\u0131m\u0131zda derleyece\u011fiz.<\/p>\n<p><strong>Referanslar<\/strong><\/p>\n<p>[1] Halil, R. A. \u015e. O., &amp; Demirci, M. (2019). Predicting the Turkish stock market bist 30 index using deep learning. International Journal of Engineering Research and Development, 11(1), 253-265.<\/p>\n<p>[2] Ta\u015f, O., &amp; G\u00fcrsoy, \u00d6. Z. (2016). A fuzzy logic based technical indicator for B\u0130ST 30 index and islamic index. Procedia economics and finance, 38, 203-212.<\/p>\n<p>[3] Ayy\u0131ld\u0131z, N., &amp; \u0130skendero\u011flu, \u00d6. Prediction Of Stock Index Movement Using Machine Learning Methods: An Application On Bist 100 Index.<\/p>\n<p>[4] G\u00fcnd\u00fcz, H., \u00c7ataltepe, Z., &amp; Yaslan, Y. (2017). Stock daily return prediction using expanded features and feature selection. Turkish Journal of Electrical Engineering and Computer Sciences, 25(6), 4829-4840.<\/p>\n<p>[5] HASAN, A., Kal\u0131ps\u0131z, O., &amp; Akyokus, S. Application of Machine Learning Techniques for the Prediction of Financial Market Direction on BIST 100 Index. book of, 78.<\/p>\n<p>[6] T\u00fcfekci, Z., &amp; Abul, O. (2020, October). Distinguishing True and False Buy\/Sell Triggers from Financial Technical Indicators. In 2020 Innovations in Intelligent Systems and Applications Conference (ASYU) (pp. 1-6). IEEE.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>RSI G\u00f6reli G\u00fc\u00e7 Endeksi Borsa \u0130stanbul\u2019da yat\u0131r\u0131mc\u0131lara potansiyel f\u0131rsatlar\u0131 belirlemek i\u00e7in kulland\u0131\u011f\u0131 \u00e7e\u015fitli teknik indikat\u00f6rlerden birisidir. Bu yaz\u0131da RSI (Relative Strength Index &#8211; G\u00f6receli G\u00fc\u00e7 Endeksi)\u00a0indikat\u00f6r\u00fc nas\u0131l kullan\u0131labilir bilimsel \u00e7al\u0131\u015fmalardan yararlanarak anlatmaya \u00e7al\u0131\u015ft\u0131k. Tabi ki tek bir teknik indikat\u00f6r her zaman do\u011fru bilgi vermez bu sebeple genellikle birden fazla indikat\u00f6r birlikte de\u011ferlendirilir. \u0130ndikat\u00f6rlerin bir\u00e7o\u011fu hissenin<\/p>\n","protected":false},"author":13,"featured_media":5040,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6,40,38,522,41],"tags":[480,479,481,482],"class_list":{"0":"post-5039","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-finansal-veri-okuryazarligi","8":"category-finansal-otomasyon","9":"category-python-ile-veri-isleme","10":"category-temel-teknik-analiz","11":"category-veri-turleri-ve-kavramlar","12":"tag-bist","13":"tag-osilatorler","14":"tag-rsi","15":"tag-teknik-indikatorler"},"better_featured_image":{"id":5040,"alt_text":"G\u00f6reli G\u00fc\u00e7 Endeksi Is\u0131 Haritas\u0131","caption":"","description":"","media_type":"image","media_details":{"width":624,"height":333,"file":"2023\/11\/RSI-korelasyonlar.jpg","filesize":73719,"sizes":{"medium":{"file":"RSI-korelasyonlar-300x160.jpg","width":300,"height":160,"mime-type":"image\/jpeg","filesize":13834,"source_url":"https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/RSI-korelasyonlar-300x160.jpg"},"thumbnail":{"file":"RSI-korelasyonlar-150x150.jpg","width":150,"height":150,"mime-type":"image\/jpeg","filesize":7598,"source_url":"https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/RSI-korelasyonlar-150x150.jpg"},"bunyad-small":{"file":"RSI-korelasyonlar-150x80.jpg","width":150,"height":80,"mime-type":"image\/jpeg","filesize":4512,"source_url":"https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/RSI-korelasyonlar-150x80.jpg"},"bunyad-medium":{"file":"RSI-korelasyonlar-450x240.jpg","width":450,"height":240,"mime-type":"image\/jpeg","filesize":28459,"source_url":"https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/RSI-korelasyonlar-450x240.jpg"}},"image_meta":{"aperture":"0","credit":"","camera":"","caption":"","created_timestamp":"0","copyright":"","focal_length":"0","iso":"0","shutter_speed":"0","title":"","orientation":"0","keywords":[]}},"post":5039,"source_url":"https:\/\/datakapital.com\/blog\/wp-content\/uploads\/2023\/11\/RSI-korelasyonlar.jpg"},"amp_enabled":true,"_links":{"self":[{"href":"https:\/\/datakapital.com\/blog\/wp-json\/wp\/v2\/posts\/5039","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/datakapital.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/datakapital.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/datakapital.com\/blog\/wp-json\/wp\/v2\/users\/13"}],"replies":[{"embeddable":true,"href":"https:\/\/datakapital.com\/blog\/wp-json\/wp\/v2\/comments?post=5039"}],"version-history":[{"count":4,"href":"https:\/\/datakapital.com\/blog\/wp-json\/wp\/v2\/posts\/5039\/revisions"}],"predecessor-version":[{"id":5375,"href":"https:\/\/datakapital.com\/blog\/wp-json\/wp\/v2\/posts\/5039\/revisions\/5375"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/datakapital.com\/blog\/wp-json\/wp\/v2\/media\/5040"}],"wp:attachment":[{"href":"https:\/\/datakapital.com\/blog\/wp-json\/wp\/v2\/media?parent=5039"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/datakapital.com\/blog\/wp-json\/wp\/v2\/categories?post=5039"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/datakapital.com\/blog\/wp-json\/wp\/v2\/tags?post=5039"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}