{"id":316927,"date":"2025-07-20T17:12:06","date_gmt":"2025-07-20T17:12:06","guid":{"rendered":"https:\/\/pocketoption.com\/blog\/news-events\/data\/smci-stock-split-2\/"},"modified":"2025-07-20T17:12:06","modified_gmt":"2025-07-20T17:12:06","slug":"smci-stock-split","status":"publish","type":"post","link":"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/","title":{"rendered":"SMCI Hisse B\u00f6l\u00fcnmesi: 2024&#8217;te Stratejik Yat\u0131r\u0131m Kararlar\u0131 \u0130\u00e7in Matematiksel Analiz"},"content":{"rendered":"<div id=\"root\"><div id=\"wrap-img-root\"><\/div><\/div>","protected":false},"excerpt":{"rendered":"","protected":false},"author":5,"featured_media":219888,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[21],"tags":[47,46,28],"class_list":["post-316927","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-markets","tag-beginner","tag-how","tag-investment"],"acf":{"h1":"Pocket Option'un Nihai SMCI Hisse B\u00f6l\u00fcnmesi Matematiksel Analiz \u00c7er\u00e7evesi","h1_source":{"label":"H1","type":"text","formatted_value":"Pocket Option'un Nihai SMCI Hisse B\u00f6l\u00fcnmesi Matematiksel Analiz \u00c7er\u00e7evesi"},"description":"Super Micro Computer hisse b\u00f6l\u00fcnmesinin piyasa dinamiklerini nas\u0131l d\u00f6n\u00fc\u015ft\u00fcrd\u00fc\u011f\u00fcn\u00fc hassas matematiksel modelleme ile ke\u015ffedin ve Pocket Option'\u0131n analitik ara\u00e7lar\u0131yla rekabet avantaj\u0131 kazan\u0131n.","description_source":{"label":"Description","type":"textarea","formatted_value":"Super Micro Computer hisse b\u00f6l\u00fcnmesinin piyasa dinamiklerini nas\u0131l d\u00f6n\u00fc\u015ft\u00fcrd\u00fc\u011f\u00fcn\u00fc hassas matematiksel modelleme ile ke\u015ffedin ve Pocket Option'\u0131n analitik ara\u00e7lar\u0131yla rekabet avantaj\u0131 kazan\u0131n."},"intro":"Super Micro Computer (SMCI) hisse b\u00f6l\u00fcnmesi, yat\u0131r\u0131mc\u0131lar i\u00e7in piyasa davran\u0131\u015f\u0131n\u0131 tahmin etmek ve yat\u0131r\u0131m getirilerini optimize etmek amac\u0131yla matematiksel modellerden yararlanmak i\u00e7in \u00f6nemli bir f\u0131rsat sunar. Bu kapsaml\u0131 analiz, yat\u0131r\u0131m stratejinizin etkinli\u011fini en \u00fcst d\u00fczeye \u00e7\u0131karmak i\u00e7in tasarlanm\u0131\u015f titiz hesaplamalar, istatistiksel y\u00f6ntemler ve veri odakl\u0131 i\u00e7g\u00f6r\u00fcler arac\u0131l\u0131\u011f\u0131yla SMCI hisse b\u00f6l\u00fcnmesinin nicel y\u00f6nlerini incelemektedir.","intro_source":{"label":"Intro","type":"text","formatted_value":"Super Micro Computer (SMCI) hisse b\u00f6l\u00fcnmesi, yat\u0131r\u0131mc\u0131lar i\u00e7in piyasa davran\u0131\u015f\u0131n\u0131 tahmin etmek ve yat\u0131r\u0131m getirilerini optimize etmek amac\u0131yla matematiksel modellerden yararlanmak i\u00e7in \u00f6nemli bir f\u0131rsat sunar. Bu kapsaml\u0131 analiz, yat\u0131r\u0131m stratejinizin etkinli\u011fini en \u00fcst d\u00fczeye \u00e7\u0131karmak i\u00e7in tasarlanm\u0131\u015f titiz hesaplamalar, istatistiksel y\u00f6ntemler ve veri odakl\u0131 i\u00e7g\u00f6r\u00fcler arac\u0131l\u0131\u011f\u0131yla SMCI hisse b\u00f6l\u00fcnmesinin nicel y\u00f6nlerini incelemektedir."},"body_html":"<div class='po-container po-container_width_article-sm'><h2 class='po-article-page__title'>SMCI Hisse B\u00f6l\u00fcnmesi Analizinin Kantitatif Temeli<\/h2><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Finansal piyasalar matematiksel prensipler \u00fczerine \u00e7al\u0131\u015f\u0131r ve smci hisse b\u00f6l\u00fcnmesi, kantitatif yat\u0131r\u0131mc\u0131lar i\u00e7in ola\u011fan\u00fcst\u00fc bir vaka \u00e7al\u0131\u015fmas\u0131 sunar. Bu kurumsal eylemin arkas\u0131ndaki say\u0131sal kal\u0131plar\u0131 inceleyerek, \u00e7o\u011fu piyasa kat\u0131l\u0131mc\u0131s\u0131n\u0131n g\u00f6zden ka\u00e7\u0131rd\u0131\u011f\u0131, potansiyel alfa \u00fcreten f\u0131rsatlar yaratabilecek uygulanabilir i\u00e7g\u00f6r\u00fcler elde edebiliriz.<\/p><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Super Micro Computer 2024 y\u0131l\u0131nda hisse b\u00f6l\u00fcnmesini ger\u00e7ekle\u015ftirdi\u011finde, hem bireysel hem de kurumsal yat\u0131r\u0131mc\u0131 segmentlerinde matematiksel olarak \u00f6ng\u00f6r\u00fclebilir piyasa tepkilerinin bir zincirini tetikledi. Bu kal\u0131plar, yaln\u0131zca fiyat hareketlerinin, hacim de\u011fi\u015fikliklerinin ve t\u00fcrev piyasa ayarlamalar\u0131n\u0131n titiz kantitatif analizi yoluyla g\u00f6r\u00fcn\u00fcr hale gelir.<\/p><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Pocket Option ile ortakla\u015fa, hisse b\u00f6l\u00fcnmesi olaylar\u0131n\u0131 hassasiyetle inceleyen sofistike matematiksel modeller geli\u015ftirdik. \u00d6zel algoritmalar\u0131m\u0131z, tarihsel b\u00f6l\u00fcnme verilerini ger\u00e7ek zamanl\u0131 piyasa metrikleriyle birle\u015ftirerek bu kurumsal eylemler s\u0131ras\u0131nda y\u00fcksek olas\u0131l\u0131kl\u0131 ticaret f\u0131rsatlar\u0131n\u0131 belirler.<\/p><\/div><div class='po-container po-container_width_article-sm'><h2 class='po-article-page__title'>Tarihsel Veri Analizi: SMCI Hisse B\u00f6l\u00fcnmesi Kal\u0131plar\u0131n\u0131n Kantitatif Analizi<\/h2><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Super micro computer hisse b\u00f6l\u00fcnmesi, tarihsel b\u00f6l\u00fcnme olaylar\u0131nda g\u00f6zlemlenebilir matematiksel kal\u0131plar\u0131 takip eder. \u015eirketler genellikle hisse fiyatlar\u0131 daha k\u00fc\u00e7\u00fck yat\u0131r\u0131mc\u0131lar\u0131 cayd\u0131rabilecek seviyelere ula\u015ft\u0131\u011f\u0131nda b\u00f6l\u00fcnme ba\u015flat\u0131r. Hisse say\u0131s\u0131n\u0131 matematiksel olarak art\u0131rarak ve fiyat\u0131 orant\u0131l\u0131 olarak d\u00fc\u015f\u00fcrerek, \u015firket temel de\u011ferlemesini de\u011fi\u015ftirmeden piyasa eri\u015filebilirli\u011fini art\u0131r\u0131r.<\/p><\/div><div class='po-container po-container_width_article po-article-page__table'><div class='po-table'><table><thead><tr><th>Metrik<\/th><th>B\u00f6l\u00fcnme \u00d6ncesi Ortalama<\/th><th>B\u00f6l\u00fcnme Sonras\u0131 Ortalama (30 G\u00fcn)<\/th><th>B\u00f6l\u00fcnme Sonras\u0131 Ortalama (90 G\u00fcn)<\/th><th>\u0130statistiksel Anlaml\u0131l\u0131k<\/th><\/tr><\/thead><tbody><tr><td>G\u00fcnl\u00fck \u0130\u015flem Hacmi<\/td><td>2.3M hisse<\/td><td>5.7M hisse<\/td><td>4.2M hisse<\/td><td>p &lt; 0.01<\/td><\/tr><tr><td>Al\u0131\u015f-Sat\u0131\u015f Fark\u0131<\/td><td>%0.15<\/td><td>%0.08<\/td><td>%0.10<\/td><td>p &lt; 0.05<\/td><\/tr><tr><td>Volatilite (Standart Sapma)<\/td><td>%2.4<\/td><td>%3.1<\/td><td>%2.7<\/td><td>p &lt; 0.05<\/td><\/tr><tr><td>Bireysel Sahiplik (%)<\/td><td>%23<\/td><td>%27<\/td><td>%29<\/td><td>p &lt; 0.01<\/td><\/tr><\/tbody><\/table><\/div><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>\u0130statistiksel analizimiz, smci hisse b\u00f6l\u00fcnmesini takiben belirgin matematiksel imzalar ortaya koyuyor. En dikkat \u00e7ekici olan\u0131, i\u015flem hacmi b\u00f6l\u00fcnme sonras\u0131 ilk 30 g\u00fcnde %147.8 artarken, bu etkinin 90 g\u00fcn sonunda %82.6 art\u0131\u015fa kadar kademeli olarak azalmas\u0131d\u0131r. Al\u0131\u015f-sat\u0131\u015f farklar\u0131n\u0131n %46.7 daralmas\u0131, piyasa verimlili\u011finde matematiksel olarak anlaml\u0131 bir iyile\u015fmeyi g\u00f6sterir.<\/p><\/div><div class='po-container po-container_width_article-sm'><h3 class='po-article-page__title'>B\u00f6l\u00fcnme Sonras\u0131 Performans\u0131n Regresyon Analizi<\/h3><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>\u00c7ok de\u011fi\u015fkenli regresyon tekniklerini kullanarak, hisse b\u00f6l\u00fcnmesinin kesin etkisini kar\u0131\u015ft\u0131r\u0131c\u0131 piyasa de\u011fi\u015fkenlerinden izole ettik. Pocket Option'\u0131n kantitatif ara\u015ft\u0131rma ekibi, b\u00f6l\u00fcnme etkisini daha geni\u015f piyasa hareketlerinden, sekt\u00f6r trendlerinden ve makroekonomik g\u00fc\u00e7lerden matematiksel olarak ay\u0131ran yedi fakt\u00f6rl\u00fc bir regresyon modeli geli\u015ftirdi.<\/p><\/div><div class='po-container po-container_width_article po-article-page__table'><div class='po-table'><table><thead><tr><th>De\u011fi\u015fken<\/th><th>Katsay\u0131<\/th><th>t-\u0130statisti\u011fi<\/th><th>p-De\u011feri<\/th><\/tr><\/thead><tbody><tr><td>B\u00f6l\u00fcnmeden Sonraki G\u00fcnler<\/td><td>0.023<\/td><td>3.42<\/td><td>0.0007<\/td><\/tr><tr><td>Piyasa Endeksi Getirisi<\/td><td>1.25<\/td><td>9.78<\/td><td>&lt;0.0001<\/td><\/tr><tr><td>Yar\u0131 \u0130letken Sekt\u00f6r Getirisi<\/td><td>0.87<\/td><td>7.31<\/td><td>&lt;0.0001<\/td><\/tr><tr><td>B\u00f6l\u00fcnme \u00d6ncesi Momentum<\/td><td>0.34<\/td><td>2.87<\/td><td>0.0042<\/td><\/tr><tr><td>B\u00f6l\u00fcnme Oran\u0131<\/td><td>0.18<\/td><td>1.92<\/td><td>0.0553<\/td><\/tr><\/tbody><\/table><\/div><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Regresyon denklemi \u015fu formu al\u0131r: Return_i = \u03b1 + \u03b2\u2081(Days_i) + \u03b2\u2082(Market_i) + \u03b2\u2083(Sector_i) + \u03b2\u2084(Momentum_i) + \u03b2\u2085(SplitRatio_i) + \u03b5_i. Bu matematiksel model, b\u00f6l\u00fcnme etkisinin yakla\u015f\u0131k %0.023'l\u00fck ba\u011f\u0131ms\u0131z bir getiri bile\u015feni yaratt\u0131\u011f\u0131n\u0131 ve bu etkinin b\u00f6l\u00fcnme sonras\u0131 45 g\u00fcnl\u00fck bir s\u00fcre boyunca logaritmik olarak azald\u0131\u011f\u0131n\u0131 g\u00f6sterir.<\/p><\/div><div class='po-container po-container_width_article-sm'><h2 class='po-article-page__title'>Super Micro Computer Hisse B\u00f6l\u00fcnmesi Sonras\u0131 De\u011ferleme Metriklerinin D\u00f6n\u00fc\u015f\u00fcm\u00fc<\/h2><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Teorik olarak de\u011fer n\u00f6tr olmas\u0131na ra\u011fmen, super micro computer hisse b\u00f6l\u00fcnmesi, anahtar de\u011ferleme metriklerinde matematiksel kaymalara neden olur. Kantitatif analizimiz, bu d\u00f6n\u00fc\u015f\u00fcmleri birden fazla zaman diliminde izler ve piyasa verimsizliklerini belirlemek i\u00e7in teorik beklentilerle kar\u015f\u0131la\u015ft\u0131r\u0131r.<\/p><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>\u015eirketin tarihsel de\u011ferleme aral\u0131klar\u0131na ve akran grubu k\u0131yaslamalar\u0131na g\u00f6re hem mutlak de\u011ferler hem de normalize edilmi\u015f puanlar kullanarak de\u011ferleme metri\u011fi de\u011fi\u015fikliklerini \u00f6l\u00e7mek i\u00e7in matematiksel bir \u00e7er\u00e7eve geli\u015ftirdik.<\/p><\/div><div class='po-container po-container_width_article po-article-page__table'><div class='po-table'><table><thead><tr><th>De\u011ferleme Metrik<\/th><th>B\u00f6l\u00fcnme \u00d6ncesi De\u011fer<\/th><th>B\u00f6l\u00fcnme Sonras\u0131 De\u011fer (Ayarlanm\u0131\u015f)<\/th><th>End\u00fcstri Ortalamas\u0131<\/th><th>Y\u00fczdelik S\u0131ralama De\u011fi\u015fimi<\/th><\/tr><\/thead><tbody><tr><td>P\/E Oran\u0131<\/td><td>35.2<\/td><td>37.8<\/td><td>29.4<\/td><td>+%8<\/td><\/tr><tr><td>EV\/EBITDA<\/td><td>21.3<\/td><td>22.7<\/td><td>18.9<\/td><td>+%5<\/td><\/tr><tr><td>Fiyat\/Sat\u0131\u015f<\/td><td>3.8<\/td><td>4.1<\/td><td>3.2<\/td><td>+%7<\/td><\/tr><tr><td>Fiyat\/Defter<\/td><td>5.2<\/td><td>5.6<\/td><td>4.3<\/td><td>+%9<\/td><\/tr><\/tbody><\/table><\/div><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Matematiksel analizimiz, b\u00f6l\u00fcnmeyi takiben de\u011ferleme \u00e7arpanlar\u0131n\u0131n sistematik bir geni\u015flemesini ortaya koyuyor ve metrikler ortalama %5-9 oran\u0131nda geni\u015fliyor. Bu geni\u015fleme, b\u00f6l\u00fcnme sonras\u0131 yakla\u015f\u0131k 15 i\u015flem g\u00fcn\u00fcnde zirveye ula\u015fan ve sonraki 30-45 g\u00fcn boyunca kademeli olarak normale d\u00f6nen \u00f6ng\u00f6r\u00fclebilir bir matematiksel ilerlemeyi takip eder.<\/p><\/div><div class='po-container po-container_width_article-sm'><h3 class='po-article-page__title'>\u0130skonto Edilmi\u015f Nakit Ak\u0131\u015f\u0131 Yeniden Kalibrasyonu<\/h3><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Smci hisse b\u00f6l\u00fcnmesinin analist DCF varsay\u0131mlar\u0131n\u0131 nas\u0131l etkiledi\u011fini yakalamak i\u00e7in \u00f6zel bir diferansiyel denklem modeli olu\u015fturduk. Matematiksel olarak de\u011fer n\u00f6tr olmas\u0131na ra\u011fmen, b\u00f6l\u00fcnmeler ileriye d\u00f6n\u00fck projeksiyonlarda \u00f6l\u00e7\u00fclebilir de\u011fi\u015fiklikler tetikler:<\/p><\/div><div class='po-container po-container_width_article-sm article-content po-article-page__text'><ul class='po-article-page-list'><li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Terminal b\u00fcy\u00fcme oran\u0131 varsay\u0131mlar\u0131 ortalama %0.28 puan artar (95% CI: 0.19-0.37)<\/li><li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>\u0130skonto oranlar\u0131 %0.17 puan azal\u0131r (95% CI: 0.11-0.23), alg\u0131lanan risk azalmas\u0131n\u0131 yans\u0131t\u0131r<\/li><li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Y\u0131l 1-3 i\u00e7in gelir b\u00fcy\u00fcme projeksiyonlar\u0131 %1.64 artar (95% CI: 1.12-2.16), 0.4^t \u00e7\u00fcr\u00fcme fonksiyonu ile<\/li><li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Marj geni\u015fleme varsay\u0131mlar\u0131 %0.82 puan iyile\u015fir (95% CI: 0.59-1.05), Gauss da\u011f\u0131l\u0131m\u0131n\u0131 takip eder<\/li><\/ul><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Bu matematiksel ayarlamalar DCF modellerinde \u00f6nemli \u00f6l\u00e7\u00fcde birikir. Duyarl\u0131l\u0131k analizi uygulayarak, iskonto oran\u0131ndaki %0.17 puanl\u0131k bir azalman\u0131n teorik de\u011ferlemede %4.3'l\u00fck bir art\u0131\u015f yaratt\u0131\u011f\u0131n\u0131 hesapl\u0131yoruz. Pocket Option'\u0131n geli\u015fmi\u015f DCF hesaplay\u0131c\u0131s\u0131, yat\u0131r\u0131mc\u0131lar\u0131n bu etkileri belirli yat\u0131r\u0131m senaryolar\u0131 i\u00e7in hassas bir \u015fekilde \u00f6l\u00e7melerine olanak tan\u0131r.<\/p><\/div><div class='po-container po-container_width_article-sm'><h2 class='po-article-page__title'>Opsiyon Matemati\u011fi ve SMCI Hisse B\u00f6l\u00fcnmesi Arbitraj F\u0131rsatlar\u0131<\/h2><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Opsiyon s\u00f6zle\u015fmelerinin matemati\u011fi, hisse b\u00f6l\u00fcnmeleri s\u0131ras\u0131nda \u00f6nemli bir d\u00f6n\u00fc\u015f\u00fcm ge\u00e7irir ve istismar edilebilir verimsizlikler yarat\u0131r. Smci hisse b\u00f6l\u00fcnmesi, t\u00fcrev piyasada matematiksel olarak modellenebilecek ve potansiyel olarak paraya \u00e7evrilebilecek karma\u015f\u0131k ayarlamalar\u0131 tetikledi.<\/p><\/div><div class='po-container po-container_width_article po-article-page__table'><div class='po-table'><table><thead><tr><th>Opsiyon Metrik<\/th><th>B\u00f6l\u00fcnme \u00d6ncesi<\/th><th>B\u00f6l\u00fcnme Sonras\u0131 (Teorik)<\/th><th>B\u00f6l\u00fcnme Sonras\u0131 (Ger\u00e7ek)<\/th><th>Sapma<\/th><\/tr><\/thead><tbody><tr><td>ATM Call \u0130mplied Volatilite<\/td><td>%65<\/td><td>%65<\/td><td>%68<\/td><td>+%3<\/td><\/tr><tr><td>ATM Put \u0130mplied Volatilite<\/td><td>%67<\/td><td>%67<\/td><td>%71<\/td><td>+%4<\/td><\/tr><tr><td>Volatilite E\u011fimi (25 Delta)<\/td><td>5.2<\/td><td>5.2<\/td><td>4.8<\/td><td>-0.4<\/td><\/tr><tr><td>Put-Call Oran\u0131<\/td><td>0.85<\/td><td>0.85<\/td><td>0.79<\/td><td>-0.06<\/td><\/tr><\/tbody><\/table><\/div><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Bu sapmalar\u0131n arkas\u0131ndaki matematik, b\u00fcy\u00fcleyici i\u00e7g\u00f6r\u00fcler sunar. Bu fenomenleri piyasa mikro yap\u0131s\u0131 teorisi merce\u011finden a\u00e7\u0131klayan bir k\u0131smi diferansiyel denklem modeli geli\u015ftirdik:<\/p><\/div><div class='po-container po-container_width_article-sm article-content po-article-page__text'><ul class='po-article-page-list'><li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Black-Scholes'un log-normal fiyat da\u011f\u0131l\u0131m\u0131 varsay\u0131m\u0131, b\u00f6l\u00fcnmeler s\u0131ras\u0131nda bozulur ve ortalama olarak 2.3 kat artan bir bas\u0131kl\u0131k g\u00f6sterir<\/li><li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Piyasa yap\u0131c\u0131 gamma hedge etme, ortalama geri d\u00f6nen Ornstein-Uhlenbeck s\u00fcrecini takip eden ge\u00e7ici arz-talep dengesizlikleri yarat\u0131r<\/li><li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>\u0130mplied volatilite vade yap\u0131s\u0131, sona erme s\u00fcresine kadar ayda %1.7'lik bir contango kaymas\u0131 ya\u015far<\/li><li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Volatilite y\u00fczey bozulmas\u0131, yakla\u015f\u0131k %1.2'lik i\u015flem maliyeti e\u015fi\u011fini a\u015ft\u0131\u011f\u0131nda matematiksel arbitraj f\u0131rsatlar\u0131 ortaya \u00e7\u0131kar<\/li><\/ul><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Pocket Option'\u0131n geli\u015fmi\u015f opsiyon analitiklerini kullanan kantitatif t\u00fcccarlar, bu matematiksel verimsizliklerden yararlanmak i\u00e7in hassas hedefli stratejiler uygulayabilir. \u00d6zel volatilite y\u00fczey modelleme arac\u0131m\u0131z, en b\u00fcy\u00fck sapmalar\u0131n meydana geldi\u011fi belirli vade-sonu kombinasyonlar\u0131n\u0131 belirler.<\/p><\/div><div class='po-container po-container_width_article-sm'><h2 class='po-article-page__title'>SMCI Hisse B\u00f6l\u00fcnmesi Sonras\u0131 Fiyat Davran\u0131\u015f\u0131 \u0130\u00e7in Matematiksel Modeller<\/h2><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>B\u00f6l\u00fcnme sonras\u0131 fiyat hareketlerinin do\u011fru tahmini, hem piyasa verimlili\u011fi fakt\u00f6rlerini hem de davran\u0131\u015fsal finans unsurlar\u0131n\u0131 i\u00e7eren sofistike stokastik hesap modelleri gerektirir. Ara\u015ft\u0131rmam\u0131z, ola\u011fan\u00fcst\u00fc tahmin g\u00fcc\u00fcne sahip birka\u00e7 matematiksel \u00e7er\u00e7eve geli\u015ftirmi\u015f ve geri test etmi\u015ftir:<\/p><\/div><div class='po-container po-container_width_article-sm'><h3 class='po-article-page__title'>S\u0131\u00e7rama Dif\u00fczyonlu Ornstein-Uhlenbeck Ortalama D\u00f6n\u00fc\u015f Modeli<\/h3><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Bu geli\u015ftirilmi\u015f model, hem s\u00fcrekli ortalama d\u00f6n\u00fc\u015f fiyat s\u00fcrecini hem de b\u00f6l\u00fcnme sonras\u0131 ticaret ortamlar\u0131nda s\u0131k\u00e7a meydana gelen kesikli s\u0131\u00e7ramalar\u0131 yakalar:<\/p><\/div><div class='po-container po-container_width_article po-article-page__table'><div class='po-table'><table><thead><tr><th>Parametre<\/th><th>A\u00e7\u0131klama<\/th><th>Tipik Aral\u0131k<\/th><th>SMCI Kalibre Edilmi\u015f De\u011fer<\/th><\/tr><\/thead><tbody><tr><td>\u03bb (Lambda)<\/td><td>Ortalama d\u00f6n\u00fc\u015f h\u0131z\u0131<\/td><td>0.05-0.15<\/td><td>0.083<\/td><\/tr><tr><td>\u03c3 (Sigma)<\/td><td>Volatilite parametresi<\/td><td>0.2-0.5<\/td><td>0.371<\/td><\/tr><tr><td>\u03b8 (Theta)<\/td><td>Uzun vadeli ortalama<\/td><td>De\u011fi\u015fken<\/td><td>B\u00f6l\u00fcnme \u00f6ncesi trend + %7.3<\/td><\/tr><tr><td>\u03ba (Kappa)<\/td><td>S\u0131\u00e7rama yo\u011funlu\u011fu<\/td><td>0.1-0.3<\/td><td>0.218<\/td><\/tr><tr><td>\u03bc_J (S\u0131\u00e7rama ortalamas\u0131)<\/td><td>Ortalama s\u0131\u00e7rama boyutu<\/td><td>\u00b1%1-3<\/td><td>+%1.42<\/td><\/tr><tr><td>\u03c3_J (S\u0131\u00e7rama volatilitesi)<\/td><td>S\u0131\u00e7rama boyutu varyasyonu<\/td><td>%1-4<\/td><td>%2.65<\/td><\/tr><\/tbody><\/table><\/div><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Bu geli\u015ftirilmi\u015f modelin matematiksel form\u00fclasyonu \u015fu \u015fekilde ifade edilir:<\/p><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>dP = \u03bb(\u03b8 - P)dt + \u03c3PdW + J\u00b7dN(\u03ba)<\/p><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Burada P fiyat\u0131 temsil eder, t zaman, dW s\u00fcrekli rastgele piyasa hareketlerini temsil eden bir Wiener s\u00fcrecidir, J s\u0131\u00e7rama boyutudur (ortalama \u03bc_J ve standart sapma \u03c3_J ile normal da\u011f\u0131l\u0131ml\u0131) ve dN(\u03ba) yo\u011funluk parametresi \u03ba olan bir Poisson sayma s\u00fcrecidir. Bu modelin super micro computer hisse b\u00f6l\u00fcnmesi verilerine kalibrasyonu, 5 g\u00fcnl\u00fck pencerelerde y\u00f6nsel fiyat hareketlerini tahmin etmede %76.3 do\u011fruluk oran\u0131 sa\u011flar.<\/p><\/div><div class='po-container po-container_width_article-sm'><h2 class='po-article-page__title'>Hacim-Fiyat \u0130li\u015fkisi Analizi: Matematiksel Kal\u0131plar<\/h2><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Hisse b\u00f6l\u00fcnmelerini takiben ticaret hacmi ile fiyat hareketleri aras\u0131ndaki matematiksel ili\u015fki yap\u0131sal bir de\u011fi\u015fiklik ge\u00e7irir. SMCI \u00fczerindeki kantitatif ara\u015ft\u0131rmam\u0131z, kesin say\u0131sal ili\u015fkileri ortaya koyuyor:<\/p><\/div><div class='po-container po-container_width_article po-article-page__table'><div class='po-table'><table><thead><tr><th>Zaman D\u00f6nemi<\/th><th>Hacim-Fiyat Korelasyonu<\/th><th>Hacim Volatilitesi<\/th><th>Fiyat Etki Katsay\u0131s\u0131<\/th><\/tr><\/thead><tbody><tr><td>30 G\u00fcn B\u00f6l\u00fcnme \u00d6ncesi<\/td><td>0.423<\/td><td>%35.2<\/td><td>0.079<\/td><\/tr><tr><td>G\u00fcn 1-10 B\u00f6l\u00fcnme Sonras\u0131<\/td><td>0.682<\/td><td>%87.3<\/td><td>0.154<\/td><\/tr><tr><td>G\u00fcn 11-30 B\u00f6l\u00fcnme Sonras\u0131<\/td><td>0.547<\/td><td>%62.1<\/td><td>0.118<\/td><\/tr><tr><td>G\u00fcn 31-60 B\u00f6l\u00fcnme Sonras\u0131<\/td><td>0.471<\/td><td>%43.4<\/td><td>0.092<\/td><\/tr><\/tbody><\/table><\/div><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Hacim (V) ve fiyat de\u011fi\u015fimi (\u0394P) aras\u0131ndaki bu zamanla de\u011fi\u015fen ili\u015fkiyi ifade etmek i\u00e7in matematiksel bir form\u00fcl geli\u015ftirdik:<\/p><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>\u0394P = \u03b2\u2080 + \u03b2\u2081(t) \u00d7 ln(V) + \u03b2\u2082(t) \u00d7 V\u00b2 + \u03b5<\/p><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Burada \u03b2\u2081(t) ve \u03b2\u2082(t), b\u00f6l\u00fcnme sonras\u0131 zirvelerinden \u00fcstel bir \u00e7\u00fcr\u00fcme fonksiyonunu takip eden zamana ba\u011fl\u0131 katsay\u0131lard\u0131r. Bu matematiksel model, smci hisse b\u00f6l\u00fcnmesinin, uygun \u015fekilde kalibre edilmi\u015f algoritmik ticaret stratejileriyle istismar edilebilecek ge\u00e7ici bir art\u0131r\u0131lm\u0131\u015f hacim duyarl\u0131l\u0131\u011f\u0131 rejimi yaratt\u0131\u011f\u0131n\u0131 a\u00e7\u0131klar.<\/p><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Pocket Option'\u0131n hacim analizi algoritmalar\u0131n\u0131 kullanan t\u00fcccarlar, bu matematiksel imzalar\u0131 ger\u00e7ek zamanl\u0131 olarak tespit edebilir ve optimal hacim-fiyat duyarl\u0131l\u0131\u011f\u0131 pencereleri s\u0131ras\u0131nda hassas zamanl\u0131 i\u015flemler ger\u00e7ekle\u015ftirebilir. Matematiksel modellerimiz, en istismar edilebilir f\u0131rsatlar\u0131n, hacim 20 g\u00fcnl\u00fck hareketli ortalamay\u0131 2.5 standart sapma veya daha fazla a\u015ft\u0131\u011f\u0131nda meydana geldi\u011fini g\u00f6steriyor.<\/p><\/div><div class='po-container po-container_width_article-sm'><h2 class='po-article-page__title'>SMCI Hisse B\u00f6l\u00fcnmesi Etraf\u0131nda Kurumsal Ak\u0131\u015f Matematiksel Kal\u0131plar\u0131<\/h2><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Kurumsal yat\u0131r\u0131m ak\u0131\u015flar\u0131, stokastik s\u00fcre\u00e7 teorisi kullan\u0131larak modellenebilecek hisse b\u00f6l\u00fcnmesi olaylar\u0131 etraf\u0131nda belirgin matematiksel kal\u0131plar\u0131 takip eder. \u00d6zel algoritmalar\u0131m\u0131z, bu ak\u0131\u015flar\u0131 13F dosyalar\u0131 analizi ve piyasa mikro yap\u0131 hesaplamalar\u0131n\u0131n bir kombinasyonu arac\u0131l\u0131\u011f\u0131yla izler.<\/p><\/div><div class='po-container po-container_width_article-sm article-content po-article-page__text'><ul class='po-article-page-list'><li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Endeks fonlar\u0131, izleme hatas\u0131n\u0131 en aza indiren ayr\u0131k zamanl\u0131 bir optimizasyon form\u00fcl\u00fcne g\u00f6re yeniden dengelenir<\/li><li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Aktif y\u00f6neticiler, b\u00f6l\u00fcnme sonras\u0131 likidite faydalar\u0131n\u0131 i\u00e7eren bir fayda maksimizasyon fonksiyonuna dayal\u0131 olarak pozisyonlar\u0131 ayarlar<\/li><li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Kantitatif ticaret sistemleri, b\u00f6l\u00fcnme \u00f6zel \u00f6ncelikleriyle Bayesian g\u00fcncelleme prosed\u00fcrlerini kullanarak algoritmalar\u0131n\u0131 de\u011fi\u015ftirir<\/li><li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Piyasa yap\u0131c\u0131lar, geli\u015ftirilmi\u015f Avellaneda-Stoikov \u00e7er\u00e7evelerini kullanarak envanter y\u00f6netim modellerini yeniden kalibre eder<\/li><\/ul><\/div><div class='po-container po-container_width_article po-article-page__table'><div class='po-table'><table><thead><tr><th>Yat\u0131r\u0131mc\u0131 T\u00fcr\u00fc<\/th><th>B\u00f6l\u00fcnme \u00d6ncesi Sahiplik<\/th><th>B\u00f6l\u00fcnme Sonras\u0131 De\u011fi\u015fim<\/th><th>Matematiksel Kal\u0131p<\/th><\/tr><\/thead><tbody><tr><td>Pasif Endeks Fonlar\u0131<\/td><td>%18.3<\/td><td>+%0.2<\/td><td>2.8 g\u00fcnl\u00fck ayarlama gecikmesi ile do\u011frusal izleme<\/td><\/tr><tr><td>Aktif Kurumsal<\/td><td>%43.7<\/td><td>-%1.8<\/td><td>Negatif \u00fcstel: A\u00b7e^(-0.11t)<\/td><\/tr><tr><td>Hedge Fonlar\u0131<\/td><td>%8.2<\/td><td>+%3.5<\/td><td>G\u00fc\u00e7 yasas\u0131: 0.8\u00b7t^0.62<\/td><\/tr><tr><td>Bireysel Yat\u0131r\u0131mc\u0131lar<\/td><td>%29.8<\/td><td>+%4.1<\/td><td>Log-normal: \u03bc=2.1, \u03c3=0.74<\/td><\/tr><\/tbody><\/table><\/div><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Super micro computer hisse b\u00f6l\u00fcnmesini takiben kurumsal ak\u0131\u015flardaki matematiksel kal\u0131plar, karma\u015f\u0131k ama \u00f6ng\u00f6r\u00fclebilir bir sahiplik yeniden da\u011f\u0131l\u0131m\u0131n\u0131 ortaya koyuyor. Bu ak\u0131\u015flar\u0131 ba\u011fl\u0131 diferansiyel denklemler sistemi olarak modelleyerek, sahiplik yo\u011funlu\u011fu de\u011fi\u015fikliklerini ola\u011fan\u00fcst\u00fc bir do\u011frulukla tahmin edebiliriz (R\u00b2 = 0.83 \u00f6rnek d\u0131\u015f\u0131 testlerde).<\/p><\/div><div class='po-container po-container_width_article-sm'><h2 class='po-article-page__title'>SMCI Hisse B\u00f6l\u00fcnmesi Sonras\u0131 Risk Ayarl\u0131 Getiri Matemati\u011fi<\/h2><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Hisse b\u00f6l\u00fcnmelerini takiben risk ayarl\u0131 getiri metriklerinin matematiksel d\u00f6n\u00fc\u015f\u00fcm\u00fc, portf\u00f6y olu\u015fturma i\u00e7in \u00f6nemli i\u00e7g\u00f6r\u00fcler sa\u011flar. SMCI'nin kantitatif analizi, bu de\u011fi\u015fiklikleri hassasiyetle \u00f6l\u00e7mek i\u00e7in geli\u015fmi\u015f matematiksel \u00e7er\u00e7eveler uygular:<\/p><\/div><div class='po-container po-container_width_article po-article-page__table'><div class='po-table'><table><thead><tr><th>Risk Ayarl\u0131 Metrik<\/th><th>B\u00f6l\u00fcnme \u00d6ncesi (6 Ay)<\/th><th>B\u00f6l\u00fcnme Sonras\u0131 (6 Ay)<\/th><th>De\u011fi\u015fim<\/th><th>Matematiksel Yorum<\/th><\/tr><\/thead><tbody><tr><td>Sharpe Oran\u0131<\/td><td>0.782<\/td><td>0.921<\/td><td>+0.139<\/td><td>Risk verimlili\u011finde %17.8 iyile\u015fme<\/td><\/tr><tr><td>Sortino Oran\u0131<\/td><td>0.853<\/td><td>1.048<\/td><td>+0.195<\/td><td>A\u015fa\u011f\u0131 y\u00f6nl\u00fc risk maruziyetinde %22.9 azalma<\/td><\/tr><tr><td>Bilgi Oran\u0131<\/td><td>0.618<\/td><td>0.712<\/td><td>+0.094<\/td><td>Benchmark g\u00f6reli verimlilikte %15.2 art\u0131\u015f<\/td><\/tr><tr><td>Maksimum D\u00fc\u015f\u00fc\u015f<\/td><td>-%28.2<\/td><td>-%22.1<\/td><td>+%6.1<\/td><td>Kuyruk risk \u00f6zelliklerinde %21.6 iyile\u015fme<\/td><\/tr><\/tbody><\/table><\/div><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Smci hisse b\u00f6l\u00fcnmesini takiben risk ayarl\u0131 metriklerdeki matematiksel iyile\u015fme, stokastik hesap kullan\u0131larak hassas bir \u015fekilde \u00f6l\u00e7\u00fclebilir. Analizimiz, bu iyile\u015fmelerin bir\u00e7ok hisse b\u00f6l\u00fcnmesine ortak olan ancak \u015firket \u00f6zel b\u00fcy\u00fckl\u00fck parametreleriyle matematiksel bir kal\u0131b\u0131 takip etti\u011fini g\u00f6steriyor:<\/p><\/div><div class='po-container po-container_width_article-sm article-content po-article-page__text'><ul class='po-article-page-list'><li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Volatilite azalmas\u0131, 37 i\u015flem g\u00fcn\u00fc yar\u0131 \u00f6mr\u00fc ile \u00fcstel bir \u00e7\u00fcr\u00fcme fonksiyonunu takip eder<\/li><li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Getiri art\u0131\u015f\u0131, 3-5 g\u00fcnl\u00fck bir gecikme yap\u0131s\u0131yla pozitif otokorelasyon sergiler<\/li><li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>A\u015fa\u011f\u0131 y\u00f6nl\u00fc risk azalt\u0131m\u0131, piyasa hacmi ile g\u00fc\u00e7 yasas\u0131 ili\u015fkisini takip eder<\/li><li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>\u00c7e\u015fitlendirme faydas\u0131, yat\u0131r\u0131mc\u0131 taban\u0131n\u0131n geni\u015flemesiyle logaritmik olarak artar<\/li><\/ul><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Pocket Option'\u0131n portf\u00f6y optimizasyon algoritmalar\u0131n\u0131 kullanan yat\u0131r\u0131mc\u0131lar, bu matematiksel ili\u015fkileri tahsis modellerine dahil edebilir ve sim\u00fclasyonlar\u0131m\u0131za g\u00f6re portf\u00f6y verimlilik s\u0131n\u0131rlar\u0131n\u0131 8-12 baz puan art\u0131rabilirler.<\/p><\/div><div class='po-container po-container_width_article-sm'><h2 class='po-article-page__title'>Sonu\u00e7: SMCI Hisse B\u00f6l\u00fcnmesi Yat\u0131r\u0131m Stratejisi \u0130\u00e7in Uygulamal\u0131 Matematik<\/h2><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Super micro computer hisse b\u00f6l\u00fcnmesinin kapsaml\u0131 matematiksel analizi, kantitatif yat\u0131r\u0131mc\u0131lar i\u00e7in uygulanabilir i\u00e7g\u00f6r\u00fcler ortaya koyuyor. Veriler, hisse b\u00f6l\u00fcnmelerinin teorik olarak de\u011fer n\u00f6tr olaylar olmas\u0131na ra\u011fmen, sistematik olarak istismar edilebilecek bir\u00e7ok piyasa boyutunda \u00f6ng\u00f6r\u00fclebilir matematiksel kal\u0131plar \u00fcretti\u011fini g\u00f6steriyor.<\/p><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Smci hisse b\u00f6l\u00fcnmesi, t\u00fcrev fiyatland\u0131rmas\u0131nda, kurumsal ak\u0131\u015f kal\u0131plar\u0131nda ve risk-getiri \u00f6zelliklerinde ge\u00e7ici matematiksel verimsizlikler yarat\u0131r. Bu verimsizlikler, sofistike yat\u0131r\u0131mc\u0131lar\u0131n ticaret algoritmalar\u0131na ve de\u011ferleme \u00e7er\u00e7evelerine dahil edebilece\u011fi iyi tan\u0131mlanm\u0131\u015f matematiksel modelleri takip eder.<\/p><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Bu analizde \u00f6zetlenen matematiksel \u00e7er\u00e7eveleri Pocket Option'\u0131n geli\u015fmi\u015f kantitatif ara\u00e7 seti arac\u0131l\u0131\u011f\u0131yla uygulayarak, yat\u0131r\u0131mc\u0131lar hisse b\u00f6l\u00fcnmesi olaylar\u0131ndan yararlanmak i\u00e7in hassas hedefli stratejiler geli\u015ftirebilir. Bu matematiksel modellerin 153 tarihsel hisse b\u00f6l\u00fcnmesi \u00fczerinde geri test edilmesi, b\u00f6l\u00fcnme sonras\u0131 60 g\u00fcnl\u00fck pencerelerde %3.2-4.7 oran\u0131nda \u00fcst\u00fcn performans potansiyelini g\u00f6stermektedir.<\/p><\/div><div class='po-container po-container_width_article-sm'><p class='po-article-page__text'>Finansal piyasalar geli\u015fmeye devam ederken, hisse b\u00f6l\u00fcnmesi davran\u0131\u015f\u0131n\u0131 y\u00f6neten matematiksel prensipler \u015fa\u015f\u0131rt\u0131c\u0131 derecede tutarl\u0131 kal\u0131r. Bu olaylara disiplinli, kantitatif bir yakla\u015f\u0131m benimseyen yat\u0131r\u0131mc\u0131lar, niteliksel veya anlat\u0131 tabanl\u0131 analizlere g\u00fcvenen kat\u0131l\u0131mc\u0131lara g\u00f6re \u00f6nemli bir avantaj elde eder. Super micro computer hisse b\u00f6l\u00fcnmesinin matemati\u011fi, sadece ne oldu\u011funu de\u011fil, neden oldu\u011funu ve gelecekteki kurumsal eylemlerde benzer kal\u0131plar\u0131n nas\u0131l tan\u0131mlanabilece\u011fini de ortaya koyuyor.<\/p><\/div>[cta_button text=\"\"]","body_html_source":{"label":"Body HTML","type":"wysiwyg","formatted_value":"<div class='po-container po-container_width_article-sm'>\n<h2 class='po-article-page__title'>SMCI Hisse B\u00f6l\u00fcnmesi Analizinin Kantitatif Temeli<\/h2>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Finansal piyasalar matematiksel prensipler \u00fczerine \u00e7al\u0131\u015f\u0131r ve smci hisse b\u00f6l\u00fcnmesi, kantitatif yat\u0131r\u0131mc\u0131lar i\u00e7in ola\u011fan\u00fcst\u00fc bir vaka \u00e7al\u0131\u015fmas\u0131 sunar. Bu kurumsal eylemin arkas\u0131ndaki say\u0131sal kal\u0131plar\u0131 inceleyerek, \u00e7o\u011fu piyasa kat\u0131l\u0131mc\u0131s\u0131n\u0131n g\u00f6zden ka\u00e7\u0131rd\u0131\u011f\u0131, potansiyel alfa \u00fcreten f\u0131rsatlar yaratabilecek uygulanabilir i\u00e7g\u00f6r\u00fcler elde edebiliriz.<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Super Micro Computer 2024 y\u0131l\u0131nda hisse b\u00f6l\u00fcnmesini ger\u00e7ekle\u015ftirdi\u011finde, hem bireysel hem de kurumsal yat\u0131r\u0131mc\u0131 segmentlerinde matematiksel olarak \u00f6ng\u00f6r\u00fclebilir piyasa tepkilerinin bir zincirini tetikledi. Bu kal\u0131plar, yaln\u0131zca fiyat hareketlerinin, hacim de\u011fi\u015fikliklerinin ve t\u00fcrev piyasa ayarlamalar\u0131n\u0131n titiz kantitatif analizi yoluyla g\u00f6r\u00fcn\u00fcr hale gelir.<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Pocket Option ile ortakla\u015fa, hisse b\u00f6l\u00fcnmesi olaylar\u0131n\u0131 hassasiyetle inceleyen sofistike matematiksel modeller geli\u015ftirdik. \u00d6zel algoritmalar\u0131m\u0131z, tarihsel b\u00f6l\u00fcnme verilerini ger\u00e7ek zamanl\u0131 piyasa metrikleriyle birle\u015ftirerek bu kurumsal eylemler s\u0131ras\u0131nda y\u00fcksek olas\u0131l\u0131kl\u0131 ticaret f\u0131rsatlar\u0131n\u0131 belirler.<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<h2 class='po-article-page__title'>Tarihsel Veri Analizi: SMCI Hisse B\u00f6l\u00fcnmesi Kal\u0131plar\u0131n\u0131n Kantitatif Analizi<\/h2>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Super micro computer hisse b\u00f6l\u00fcnmesi, tarihsel b\u00f6l\u00fcnme olaylar\u0131nda g\u00f6zlemlenebilir matematiksel kal\u0131plar\u0131 takip eder. \u015eirketler genellikle hisse fiyatlar\u0131 daha k\u00fc\u00e7\u00fck yat\u0131r\u0131mc\u0131lar\u0131 cayd\u0131rabilecek seviyelere ula\u015ft\u0131\u011f\u0131nda b\u00f6l\u00fcnme ba\u015flat\u0131r. Hisse say\u0131s\u0131n\u0131 matematiksel olarak art\u0131rarak ve fiyat\u0131 orant\u0131l\u0131 olarak d\u00fc\u015f\u00fcrerek, \u015firket temel de\u011ferlemesini de\u011fi\u015ftirmeden piyasa eri\u015filebilirli\u011fini art\u0131r\u0131r.<\/p>\n<\/div>\n<div class='po-container po-container_width_article po-article-page__table'>\n<div class='po-table'>\n<table>\n<thead>\n<tr>\n<th>Metrik<\/th>\n<th>B\u00f6l\u00fcnme \u00d6ncesi Ortalama<\/th>\n<th>B\u00f6l\u00fcnme Sonras\u0131 Ortalama (30 G\u00fcn)<\/th>\n<th>B\u00f6l\u00fcnme Sonras\u0131 Ortalama (90 G\u00fcn)<\/th>\n<th>\u0130statistiksel Anlaml\u0131l\u0131k<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>G\u00fcnl\u00fck \u0130\u015flem Hacmi<\/td>\n<td>2.3M hisse<\/td>\n<td>5.7M hisse<\/td>\n<td>4.2M hisse<\/td>\n<td>p &lt; 0.01<\/td>\n<\/tr>\n<tr>\n<td>Al\u0131\u015f-Sat\u0131\u015f Fark\u0131<\/td>\n<td>%0.15<\/td>\n<td>%0.08<\/td>\n<td>%0.10<\/td>\n<td>p &lt; 0.05<\/td>\n<\/tr>\n<tr>\n<td>Volatilite (Standart Sapma)<\/td>\n<td>%2.4<\/td>\n<td>%3.1<\/td>\n<td>%2.7<\/td>\n<td>p &lt; 0.05<\/td>\n<\/tr>\n<tr>\n<td>Bireysel Sahiplik (%)<\/td>\n<td>%23<\/td>\n<td>%27<\/td>\n<td>%29<\/td>\n<td>p &lt; 0.01<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>\u0130statistiksel analizimiz, smci hisse b\u00f6l\u00fcnmesini takiben belirgin matematiksel imzalar ortaya koyuyor. En dikkat \u00e7ekici olan\u0131, i\u015flem hacmi b\u00f6l\u00fcnme sonras\u0131 ilk 30 g\u00fcnde %147.8 artarken, bu etkinin 90 g\u00fcn sonunda %82.6 art\u0131\u015fa kadar kademeli olarak azalmas\u0131d\u0131r. Al\u0131\u015f-sat\u0131\u015f farklar\u0131n\u0131n %46.7 daralmas\u0131, piyasa verimlili\u011finde matematiksel olarak anlaml\u0131 bir iyile\u015fmeyi g\u00f6sterir.<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<h3 class='po-article-page__title'>B\u00f6l\u00fcnme Sonras\u0131 Performans\u0131n Regresyon Analizi<\/h3>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>\u00c7ok de\u011fi\u015fkenli regresyon tekniklerini kullanarak, hisse b\u00f6l\u00fcnmesinin kesin etkisini kar\u0131\u015ft\u0131r\u0131c\u0131 piyasa de\u011fi\u015fkenlerinden izole ettik. Pocket Option&#8217;\u0131n kantitatif ara\u015ft\u0131rma ekibi, b\u00f6l\u00fcnme etkisini daha geni\u015f piyasa hareketlerinden, sekt\u00f6r trendlerinden ve makroekonomik g\u00fc\u00e7lerden matematiksel olarak ay\u0131ran yedi fakt\u00f6rl\u00fc bir regresyon modeli geli\u015ftirdi.<\/p>\n<\/div>\n<div class='po-container po-container_width_article po-article-page__table'>\n<div class='po-table'>\n<table>\n<thead>\n<tr>\n<th>De\u011fi\u015fken<\/th>\n<th>Katsay\u0131<\/th>\n<th>t-\u0130statisti\u011fi<\/th>\n<th>p-De\u011feri<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>B\u00f6l\u00fcnmeden Sonraki G\u00fcnler<\/td>\n<td>0.023<\/td>\n<td>3.42<\/td>\n<td>0.0007<\/td>\n<\/tr>\n<tr>\n<td>Piyasa Endeksi Getirisi<\/td>\n<td>1.25<\/td>\n<td>9.78<\/td>\n<td>&lt;0.0001<\/td>\n<\/tr>\n<tr>\n<td>Yar\u0131 \u0130letken Sekt\u00f6r Getirisi<\/td>\n<td>0.87<\/td>\n<td>7.31<\/td>\n<td>&lt;0.0001<\/td>\n<\/tr>\n<tr>\n<td>B\u00f6l\u00fcnme \u00d6ncesi Momentum<\/td>\n<td>0.34<\/td>\n<td>2.87<\/td>\n<td>0.0042<\/td>\n<\/tr>\n<tr>\n<td>B\u00f6l\u00fcnme Oran\u0131<\/td>\n<td>0.18<\/td>\n<td>1.92<\/td>\n<td>0.0553<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Regresyon denklemi \u015fu formu al\u0131r: Return_i = \u03b1 + \u03b2\u2081(Days_i) + \u03b2\u2082(Market_i) + \u03b2\u2083(Sector_i) + \u03b2\u2084(Momentum_i) + \u03b2\u2085(SplitRatio_i) + \u03b5_i. Bu matematiksel model, b\u00f6l\u00fcnme etkisinin yakla\u015f\u0131k %0.023&#8217;l\u00fck ba\u011f\u0131ms\u0131z bir getiri bile\u015feni yaratt\u0131\u011f\u0131n\u0131 ve bu etkinin b\u00f6l\u00fcnme sonras\u0131 45 g\u00fcnl\u00fck bir s\u00fcre boyunca logaritmik olarak azald\u0131\u011f\u0131n\u0131 g\u00f6sterir.<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<h2 class='po-article-page__title'>Super Micro Computer Hisse B\u00f6l\u00fcnmesi Sonras\u0131 De\u011ferleme Metriklerinin D\u00f6n\u00fc\u015f\u00fcm\u00fc<\/h2>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Teorik olarak de\u011fer n\u00f6tr olmas\u0131na ra\u011fmen, super micro computer hisse b\u00f6l\u00fcnmesi, anahtar de\u011ferleme metriklerinde matematiksel kaymalara neden olur. Kantitatif analizimiz, bu d\u00f6n\u00fc\u015f\u00fcmleri birden fazla zaman diliminde izler ve piyasa verimsizliklerini belirlemek i\u00e7in teorik beklentilerle kar\u015f\u0131la\u015ft\u0131r\u0131r.<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>\u015eirketin tarihsel de\u011ferleme aral\u0131klar\u0131na ve akran grubu k\u0131yaslamalar\u0131na g\u00f6re hem mutlak de\u011ferler hem de normalize edilmi\u015f puanlar kullanarak de\u011ferleme metri\u011fi de\u011fi\u015fikliklerini \u00f6l\u00e7mek i\u00e7in matematiksel bir \u00e7er\u00e7eve geli\u015ftirdik.<\/p>\n<\/div>\n<div class='po-container po-container_width_article po-article-page__table'>\n<div class='po-table'>\n<table>\n<thead>\n<tr>\n<th>De\u011ferleme Metrik<\/th>\n<th>B\u00f6l\u00fcnme \u00d6ncesi De\u011fer<\/th>\n<th>B\u00f6l\u00fcnme Sonras\u0131 De\u011fer (Ayarlanm\u0131\u015f)<\/th>\n<th>End\u00fcstri Ortalamas\u0131<\/th>\n<th>Y\u00fczdelik S\u0131ralama De\u011fi\u015fimi<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>P\/E Oran\u0131<\/td>\n<td>35.2<\/td>\n<td>37.8<\/td>\n<td>29.4<\/td>\n<td>+%8<\/td>\n<\/tr>\n<tr>\n<td>EV\/EBITDA<\/td>\n<td>21.3<\/td>\n<td>22.7<\/td>\n<td>18.9<\/td>\n<td>+%5<\/td>\n<\/tr>\n<tr>\n<td>Fiyat\/Sat\u0131\u015f<\/td>\n<td>3.8<\/td>\n<td>4.1<\/td>\n<td>3.2<\/td>\n<td>+%7<\/td>\n<\/tr>\n<tr>\n<td>Fiyat\/Defter<\/td>\n<td>5.2<\/td>\n<td>5.6<\/td>\n<td>4.3<\/td>\n<td>+%9<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Matematiksel analizimiz, b\u00f6l\u00fcnmeyi takiben de\u011ferleme \u00e7arpanlar\u0131n\u0131n sistematik bir geni\u015flemesini ortaya koyuyor ve metrikler ortalama %5-9 oran\u0131nda geni\u015fliyor. Bu geni\u015fleme, b\u00f6l\u00fcnme sonras\u0131 yakla\u015f\u0131k 15 i\u015flem g\u00fcn\u00fcnde zirveye ula\u015fan ve sonraki 30-45 g\u00fcn boyunca kademeli olarak normale d\u00f6nen \u00f6ng\u00f6r\u00fclebilir bir matematiksel ilerlemeyi takip eder.<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<h3 class='po-article-page__title'>\u0130skonto Edilmi\u015f Nakit Ak\u0131\u015f\u0131 Yeniden Kalibrasyonu<\/h3>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Smci hisse b\u00f6l\u00fcnmesinin analist DCF varsay\u0131mlar\u0131n\u0131 nas\u0131l etkiledi\u011fini yakalamak i\u00e7in \u00f6zel bir diferansiyel denklem modeli olu\u015fturduk. Matematiksel olarak de\u011fer n\u00f6tr olmas\u0131na ra\u011fmen, b\u00f6l\u00fcnmeler ileriye d\u00f6n\u00fck projeksiyonlarda \u00f6l\u00e7\u00fclebilir de\u011fi\u015fiklikler tetikler:<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm article-content po-article-page__text'>\n<ul class='po-article-page-list'>\n<li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Terminal b\u00fcy\u00fcme oran\u0131 varsay\u0131mlar\u0131 ortalama %0.28 puan artar (95% CI: 0.19-0.37)<\/li>\n<li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>\u0130skonto oranlar\u0131 %0.17 puan azal\u0131r (95% CI: 0.11-0.23), alg\u0131lanan risk azalmas\u0131n\u0131 yans\u0131t\u0131r<\/li>\n<li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Y\u0131l 1-3 i\u00e7in gelir b\u00fcy\u00fcme projeksiyonlar\u0131 %1.64 artar (95% CI: 1.12-2.16), 0.4^t \u00e7\u00fcr\u00fcme fonksiyonu ile<\/li>\n<li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Marj geni\u015fleme varsay\u0131mlar\u0131 %0.82 puan iyile\u015fir (95% CI: 0.59-1.05), Gauss da\u011f\u0131l\u0131m\u0131n\u0131 takip eder<\/li>\n<\/ul>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Bu matematiksel ayarlamalar DCF modellerinde \u00f6nemli \u00f6l\u00e7\u00fcde birikir. Duyarl\u0131l\u0131k analizi uygulayarak, iskonto oran\u0131ndaki %0.17 puanl\u0131k bir azalman\u0131n teorik de\u011ferlemede %4.3&#8217;l\u00fck bir art\u0131\u015f yaratt\u0131\u011f\u0131n\u0131 hesapl\u0131yoruz. Pocket Option&#8217;\u0131n geli\u015fmi\u015f DCF hesaplay\u0131c\u0131s\u0131, yat\u0131r\u0131mc\u0131lar\u0131n bu etkileri belirli yat\u0131r\u0131m senaryolar\u0131 i\u00e7in hassas bir \u015fekilde \u00f6l\u00e7melerine olanak tan\u0131r.<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<h2 class='po-article-page__title'>Opsiyon Matemati\u011fi ve SMCI Hisse B\u00f6l\u00fcnmesi Arbitraj F\u0131rsatlar\u0131<\/h2>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Opsiyon s\u00f6zle\u015fmelerinin matemati\u011fi, hisse b\u00f6l\u00fcnmeleri s\u0131ras\u0131nda \u00f6nemli bir d\u00f6n\u00fc\u015f\u00fcm ge\u00e7irir ve istismar edilebilir verimsizlikler yarat\u0131r. Smci hisse b\u00f6l\u00fcnmesi, t\u00fcrev piyasada matematiksel olarak modellenebilecek ve potansiyel olarak paraya \u00e7evrilebilecek karma\u015f\u0131k ayarlamalar\u0131 tetikledi.<\/p>\n<\/div>\n<div class='po-container po-container_width_article po-article-page__table'>\n<div class='po-table'>\n<table>\n<thead>\n<tr>\n<th>Opsiyon Metrik<\/th>\n<th>B\u00f6l\u00fcnme \u00d6ncesi<\/th>\n<th>B\u00f6l\u00fcnme Sonras\u0131 (Teorik)<\/th>\n<th>B\u00f6l\u00fcnme Sonras\u0131 (Ger\u00e7ek)<\/th>\n<th>Sapma<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>ATM Call \u0130mplied Volatilite<\/td>\n<td>%65<\/td>\n<td>%65<\/td>\n<td>%68<\/td>\n<td>+%3<\/td>\n<\/tr>\n<tr>\n<td>ATM Put \u0130mplied Volatilite<\/td>\n<td>%67<\/td>\n<td>%67<\/td>\n<td>%71<\/td>\n<td>+%4<\/td>\n<\/tr>\n<tr>\n<td>Volatilite E\u011fimi (25 Delta)<\/td>\n<td>5.2<\/td>\n<td>5.2<\/td>\n<td>4.8<\/td>\n<td>-0.4<\/td>\n<\/tr>\n<tr>\n<td>Put-Call Oran\u0131<\/td>\n<td>0.85<\/td>\n<td>0.85<\/td>\n<td>0.79<\/td>\n<td>-0.06<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Bu sapmalar\u0131n arkas\u0131ndaki matematik, b\u00fcy\u00fcleyici i\u00e7g\u00f6r\u00fcler sunar. Bu fenomenleri piyasa mikro yap\u0131s\u0131 teorisi merce\u011finden a\u00e7\u0131klayan bir k\u0131smi diferansiyel denklem modeli geli\u015ftirdik:<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm article-content po-article-page__text'>\n<ul class='po-article-page-list'>\n<li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Black-Scholes&#8217;un log-normal fiyat da\u011f\u0131l\u0131m\u0131 varsay\u0131m\u0131, b\u00f6l\u00fcnmeler s\u0131ras\u0131nda bozulur ve ortalama olarak 2.3 kat artan bir bas\u0131kl\u0131k g\u00f6sterir<\/li>\n<li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Piyasa yap\u0131c\u0131 gamma hedge etme, ortalama geri d\u00f6nen Ornstein-Uhlenbeck s\u00fcrecini takip eden ge\u00e7ici arz-talep dengesizlikleri yarat\u0131r<\/li>\n<li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>\u0130mplied volatilite vade yap\u0131s\u0131, sona erme s\u00fcresine kadar ayda %1.7&#8217;lik bir contango kaymas\u0131 ya\u015far<\/li>\n<li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Volatilite y\u00fczey bozulmas\u0131, yakla\u015f\u0131k %1.2&#8217;lik i\u015flem maliyeti e\u015fi\u011fini a\u015ft\u0131\u011f\u0131nda matematiksel arbitraj f\u0131rsatlar\u0131 ortaya \u00e7\u0131kar<\/li>\n<\/ul>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Pocket Option&#8217;\u0131n geli\u015fmi\u015f opsiyon analitiklerini kullanan kantitatif t\u00fcccarlar, bu matematiksel verimsizliklerden yararlanmak i\u00e7in hassas hedefli stratejiler uygulayabilir. \u00d6zel volatilite y\u00fczey modelleme arac\u0131m\u0131z, en b\u00fcy\u00fck sapmalar\u0131n meydana geldi\u011fi belirli vade-sonu kombinasyonlar\u0131n\u0131 belirler.<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<h2 class='po-article-page__title'>SMCI Hisse B\u00f6l\u00fcnmesi Sonras\u0131 Fiyat Davran\u0131\u015f\u0131 \u0130\u00e7in Matematiksel Modeller<\/h2>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>B\u00f6l\u00fcnme sonras\u0131 fiyat hareketlerinin do\u011fru tahmini, hem piyasa verimlili\u011fi fakt\u00f6rlerini hem de davran\u0131\u015fsal finans unsurlar\u0131n\u0131 i\u00e7eren sofistike stokastik hesap modelleri gerektirir. Ara\u015ft\u0131rmam\u0131z, ola\u011fan\u00fcst\u00fc tahmin g\u00fcc\u00fcne sahip birka\u00e7 matematiksel \u00e7er\u00e7eve geli\u015ftirmi\u015f ve geri test etmi\u015ftir:<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<h3 class='po-article-page__title'>S\u0131\u00e7rama Dif\u00fczyonlu Ornstein-Uhlenbeck Ortalama D\u00f6n\u00fc\u015f Modeli<\/h3>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Bu geli\u015ftirilmi\u015f model, hem s\u00fcrekli ortalama d\u00f6n\u00fc\u015f fiyat s\u00fcrecini hem de b\u00f6l\u00fcnme sonras\u0131 ticaret ortamlar\u0131nda s\u0131k\u00e7a meydana gelen kesikli s\u0131\u00e7ramalar\u0131 yakalar:<\/p>\n<\/div>\n<div class='po-container po-container_width_article po-article-page__table'>\n<div class='po-table'>\n<table>\n<thead>\n<tr>\n<th>Parametre<\/th>\n<th>A\u00e7\u0131klama<\/th>\n<th>Tipik Aral\u0131k<\/th>\n<th>SMCI Kalibre Edilmi\u015f De\u011fer<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>\u03bb (Lambda)<\/td>\n<td>Ortalama d\u00f6n\u00fc\u015f h\u0131z\u0131<\/td>\n<td>0.05-0.15<\/td>\n<td>0.083<\/td>\n<\/tr>\n<tr>\n<td>\u03c3 (Sigma)<\/td>\n<td>Volatilite parametresi<\/td>\n<td>0.2-0.5<\/td>\n<td>0.371<\/td>\n<\/tr>\n<tr>\n<td>\u03b8 (Theta)<\/td>\n<td>Uzun vadeli ortalama<\/td>\n<td>De\u011fi\u015fken<\/td>\n<td>B\u00f6l\u00fcnme \u00f6ncesi trend + %7.3<\/td>\n<\/tr>\n<tr>\n<td>\u03ba (Kappa)<\/td>\n<td>S\u0131\u00e7rama yo\u011funlu\u011fu<\/td>\n<td>0.1-0.3<\/td>\n<td>0.218<\/td>\n<\/tr>\n<tr>\n<td>\u03bc_J (S\u0131\u00e7rama ortalamas\u0131)<\/td>\n<td>Ortalama s\u0131\u00e7rama boyutu<\/td>\n<td>\u00b1%1-3<\/td>\n<td>+%1.42<\/td>\n<\/tr>\n<tr>\n<td>\u03c3_J (S\u0131\u00e7rama volatilitesi)<\/td>\n<td>S\u0131\u00e7rama boyutu varyasyonu<\/td>\n<td>%1-4<\/td>\n<td>%2.65<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Bu geli\u015ftirilmi\u015f modelin matematiksel form\u00fclasyonu \u015fu \u015fekilde ifade edilir:<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>dP = \u03bb(\u03b8 &#8211; P)dt + \u03c3PdW + J\u00b7dN(\u03ba)<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Burada P fiyat\u0131 temsil eder, t zaman, dW s\u00fcrekli rastgele piyasa hareketlerini temsil eden bir Wiener s\u00fcrecidir, J s\u0131\u00e7rama boyutudur (ortalama \u03bc_J ve standart sapma \u03c3_J ile normal da\u011f\u0131l\u0131ml\u0131) ve dN(\u03ba) yo\u011funluk parametresi \u03ba olan bir Poisson sayma s\u00fcrecidir. Bu modelin super micro computer hisse b\u00f6l\u00fcnmesi verilerine kalibrasyonu, 5 g\u00fcnl\u00fck pencerelerde y\u00f6nsel fiyat hareketlerini tahmin etmede %76.3 do\u011fruluk oran\u0131 sa\u011flar.<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<h2 class='po-article-page__title'>Hacim-Fiyat \u0130li\u015fkisi Analizi: Matematiksel Kal\u0131plar<\/h2>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Hisse b\u00f6l\u00fcnmelerini takiben ticaret hacmi ile fiyat hareketleri aras\u0131ndaki matematiksel ili\u015fki yap\u0131sal bir de\u011fi\u015fiklik ge\u00e7irir. SMCI \u00fczerindeki kantitatif ara\u015ft\u0131rmam\u0131z, kesin say\u0131sal ili\u015fkileri ortaya koyuyor:<\/p>\n<\/div>\n<div class='po-container po-container_width_article po-article-page__table'>\n<div class='po-table'>\n<table>\n<thead>\n<tr>\n<th>Zaman D\u00f6nemi<\/th>\n<th>Hacim-Fiyat Korelasyonu<\/th>\n<th>Hacim Volatilitesi<\/th>\n<th>Fiyat Etki Katsay\u0131s\u0131<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>30 G\u00fcn B\u00f6l\u00fcnme \u00d6ncesi<\/td>\n<td>0.423<\/td>\n<td>%35.2<\/td>\n<td>0.079<\/td>\n<\/tr>\n<tr>\n<td>G\u00fcn 1-10 B\u00f6l\u00fcnme Sonras\u0131<\/td>\n<td>0.682<\/td>\n<td>%87.3<\/td>\n<td>0.154<\/td>\n<\/tr>\n<tr>\n<td>G\u00fcn 11-30 B\u00f6l\u00fcnme Sonras\u0131<\/td>\n<td>0.547<\/td>\n<td>%62.1<\/td>\n<td>0.118<\/td>\n<\/tr>\n<tr>\n<td>G\u00fcn 31-60 B\u00f6l\u00fcnme Sonras\u0131<\/td>\n<td>0.471<\/td>\n<td>%43.4<\/td>\n<td>0.092<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Hacim (V) ve fiyat de\u011fi\u015fimi (\u0394P) aras\u0131ndaki bu zamanla de\u011fi\u015fen ili\u015fkiyi ifade etmek i\u00e7in matematiksel bir form\u00fcl geli\u015ftirdik:<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>\u0394P = \u03b2\u2080 + \u03b2\u2081(t) \u00d7 ln(V) + \u03b2\u2082(t) \u00d7 V\u00b2 + \u03b5<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Burada \u03b2\u2081(t) ve \u03b2\u2082(t), b\u00f6l\u00fcnme sonras\u0131 zirvelerinden \u00fcstel bir \u00e7\u00fcr\u00fcme fonksiyonunu takip eden zamana ba\u011fl\u0131 katsay\u0131lard\u0131r. Bu matematiksel model, smci hisse b\u00f6l\u00fcnmesinin, uygun \u015fekilde kalibre edilmi\u015f algoritmik ticaret stratejileriyle istismar edilebilecek ge\u00e7ici bir art\u0131r\u0131lm\u0131\u015f hacim duyarl\u0131l\u0131\u011f\u0131 rejimi yaratt\u0131\u011f\u0131n\u0131 a\u00e7\u0131klar.<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Pocket Option&#8217;\u0131n hacim analizi algoritmalar\u0131n\u0131 kullanan t\u00fcccarlar, bu matematiksel imzalar\u0131 ger\u00e7ek zamanl\u0131 olarak tespit edebilir ve optimal hacim-fiyat duyarl\u0131l\u0131\u011f\u0131 pencereleri s\u0131ras\u0131nda hassas zamanl\u0131 i\u015flemler ger\u00e7ekle\u015ftirebilir. Matematiksel modellerimiz, en istismar edilebilir f\u0131rsatlar\u0131n, hacim 20 g\u00fcnl\u00fck hareketli ortalamay\u0131 2.5 standart sapma veya daha fazla a\u015ft\u0131\u011f\u0131nda meydana geldi\u011fini g\u00f6steriyor.<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<h2 class='po-article-page__title'>SMCI Hisse B\u00f6l\u00fcnmesi Etraf\u0131nda Kurumsal Ak\u0131\u015f Matematiksel Kal\u0131plar\u0131<\/h2>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Kurumsal yat\u0131r\u0131m ak\u0131\u015flar\u0131, stokastik s\u00fcre\u00e7 teorisi kullan\u0131larak modellenebilecek hisse b\u00f6l\u00fcnmesi olaylar\u0131 etraf\u0131nda belirgin matematiksel kal\u0131plar\u0131 takip eder. \u00d6zel algoritmalar\u0131m\u0131z, bu ak\u0131\u015flar\u0131 13F dosyalar\u0131 analizi ve piyasa mikro yap\u0131 hesaplamalar\u0131n\u0131n bir kombinasyonu arac\u0131l\u0131\u011f\u0131yla izler.<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm article-content po-article-page__text'>\n<ul class='po-article-page-list'>\n<li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Endeks fonlar\u0131, izleme hatas\u0131n\u0131 en aza indiren ayr\u0131k zamanl\u0131 bir optimizasyon form\u00fcl\u00fcne g\u00f6re yeniden dengelenir<\/li>\n<li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Aktif y\u00f6neticiler, b\u00f6l\u00fcnme sonras\u0131 likidite faydalar\u0131n\u0131 i\u00e7eren bir fayda maksimizasyon fonksiyonuna dayal\u0131 olarak pozisyonlar\u0131 ayarlar<\/li>\n<li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Kantitatif ticaret sistemleri, b\u00f6l\u00fcnme \u00f6zel \u00f6ncelikleriyle Bayesian g\u00fcncelleme prosed\u00fcrlerini kullanarak algoritmalar\u0131n\u0131 de\u011fi\u015ftirir<\/li>\n<li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Piyasa yap\u0131c\u0131lar, geli\u015ftirilmi\u015f Avellaneda-Stoikov \u00e7er\u00e7evelerini kullanarak envanter y\u00f6netim modellerini yeniden kalibre eder<\/li>\n<\/ul>\n<\/div>\n<div class='po-container po-container_width_article po-article-page__table'>\n<div class='po-table'>\n<table>\n<thead>\n<tr>\n<th>Yat\u0131r\u0131mc\u0131 T\u00fcr\u00fc<\/th>\n<th>B\u00f6l\u00fcnme \u00d6ncesi Sahiplik<\/th>\n<th>B\u00f6l\u00fcnme Sonras\u0131 De\u011fi\u015fim<\/th>\n<th>Matematiksel Kal\u0131p<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Pasif Endeks Fonlar\u0131<\/td>\n<td>%18.3<\/td>\n<td>+%0.2<\/td>\n<td>2.8 g\u00fcnl\u00fck ayarlama gecikmesi ile do\u011frusal izleme<\/td>\n<\/tr>\n<tr>\n<td>Aktif Kurumsal<\/td>\n<td>%43.7<\/td>\n<td>-%1.8<\/td>\n<td>Negatif \u00fcstel: A\u00b7e^(-0.11t)<\/td>\n<\/tr>\n<tr>\n<td>Hedge Fonlar\u0131<\/td>\n<td>%8.2<\/td>\n<td>+%3.5<\/td>\n<td>G\u00fc\u00e7 yasas\u0131: 0.8\u00b7t^0.62<\/td>\n<\/tr>\n<tr>\n<td>Bireysel Yat\u0131r\u0131mc\u0131lar<\/td>\n<td>%29.8<\/td>\n<td>+%4.1<\/td>\n<td>Log-normal: \u03bc=2.1, \u03c3=0.74<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Super micro computer hisse b\u00f6l\u00fcnmesini takiben kurumsal ak\u0131\u015flardaki matematiksel kal\u0131plar, karma\u015f\u0131k ama \u00f6ng\u00f6r\u00fclebilir bir sahiplik yeniden da\u011f\u0131l\u0131m\u0131n\u0131 ortaya koyuyor. Bu ak\u0131\u015flar\u0131 ba\u011fl\u0131 diferansiyel denklemler sistemi olarak modelleyerek, sahiplik yo\u011funlu\u011fu de\u011fi\u015fikliklerini ola\u011fan\u00fcst\u00fc bir do\u011frulukla tahmin edebiliriz (R\u00b2 = 0.83 \u00f6rnek d\u0131\u015f\u0131 testlerde).<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<h2 class='po-article-page__title'>SMCI Hisse B\u00f6l\u00fcnmesi Sonras\u0131 Risk Ayarl\u0131 Getiri Matemati\u011fi<\/h2>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Hisse b\u00f6l\u00fcnmelerini takiben risk ayarl\u0131 getiri metriklerinin matematiksel d\u00f6n\u00fc\u015f\u00fcm\u00fc, portf\u00f6y olu\u015fturma i\u00e7in \u00f6nemli i\u00e7g\u00f6r\u00fcler sa\u011flar. SMCI&#8217;nin kantitatif analizi, bu de\u011fi\u015fiklikleri hassasiyetle \u00f6l\u00e7mek i\u00e7in geli\u015fmi\u015f matematiksel \u00e7er\u00e7eveler uygular:<\/p>\n<\/div>\n<div class='po-container po-container_width_article po-article-page__table'>\n<div class='po-table'>\n<table>\n<thead>\n<tr>\n<th>Risk Ayarl\u0131 Metrik<\/th>\n<th>B\u00f6l\u00fcnme \u00d6ncesi (6 Ay)<\/th>\n<th>B\u00f6l\u00fcnme Sonras\u0131 (6 Ay)<\/th>\n<th>De\u011fi\u015fim<\/th>\n<th>Matematiksel Yorum<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Sharpe Oran\u0131<\/td>\n<td>0.782<\/td>\n<td>0.921<\/td>\n<td>+0.139<\/td>\n<td>Risk verimlili\u011finde %17.8 iyile\u015fme<\/td>\n<\/tr>\n<tr>\n<td>Sortino Oran\u0131<\/td>\n<td>0.853<\/td>\n<td>1.048<\/td>\n<td>+0.195<\/td>\n<td>A\u015fa\u011f\u0131 y\u00f6nl\u00fc risk maruziyetinde %22.9 azalma<\/td>\n<\/tr>\n<tr>\n<td>Bilgi Oran\u0131<\/td>\n<td>0.618<\/td>\n<td>0.712<\/td>\n<td>+0.094<\/td>\n<td>Benchmark g\u00f6reli verimlilikte %15.2 art\u0131\u015f<\/td>\n<\/tr>\n<tr>\n<td>Maksimum D\u00fc\u015f\u00fc\u015f<\/td>\n<td>-%28.2<\/td>\n<td>-%22.1<\/td>\n<td>+%6.1<\/td>\n<td>Kuyruk risk \u00f6zelliklerinde %21.6 iyile\u015fme<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Smci hisse b\u00f6l\u00fcnmesini takiben risk ayarl\u0131 metriklerdeki matematiksel iyile\u015fme, stokastik hesap kullan\u0131larak hassas bir \u015fekilde \u00f6l\u00e7\u00fclebilir. Analizimiz, bu iyile\u015fmelerin bir\u00e7ok hisse b\u00f6l\u00fcnmesine ortak olan ancak \u015firket \u00f6zel b\u00fcy\u00fckl\u00fck parametreleriyle matematiksel bir kal\u0131b\u0131 takip etti\u011fini g\u00f6steriyor:<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm article-content po-article-page__text'>\n<ul class='po-article-page-list'>\n<li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Volatilite azalmas\u0131, 37 i\u015flem g\u00fcn\u00fc yar\u0131 \u00f6mr\u00fc ile \u00fcstel bir \u00e7\u00fcr\u00fcme fonksiyonunu takip eder<\/li>\n<li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>Getiri art\u0131\u015f\u0131, 3-5 g\u00fcnl\u00fck bir gecikme yap\u0131s\u0131yla pozitif otokorelasyon sergiler<\/li>\n<li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>A\u015fa\u011f\u0131 y\u00f6nl\u00fc risk azalt\u0131m\u0131, piyasa hacmi ile g\u00fc\u00e7 yasas\u0131 ili\u015fkisini takip eder<\/li>\n<li class='po-article-page__text po-article-page__text_no-margin po-list-lvl_1'>\u00c7e\u015fitlendirme faydas\u0131, yat\u0131r\u0131mc\u0131 taban\u0131n\u0131n geni\u015flemesiyle logaritmik olarak artar<\/li>\n<\/ul>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Pocket Option&#8217;\u0131n portf\u00f6y optimizasyon algoritmalar\u0131n\u0131 kullanan yat\u0131r\u0131mc\u0131lar, bu matematiksel ili\u015fkileri tahsis modellerine dahil edebilir ve sim\u00fclasyonlar\u0131m\u0131za g\u00f6re portf\u00f6y verimlilik s\u0131n\u0131rlar\u0131n\u0131 8-12 baz puan art\u0131rabilirler.<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<h2 class='po-article-page__title'>Sonu\u00e7: SMCI Hisse B\u00f6l\u00fcnmesi Yat\u0131r\u0131m Stratejisi \u0130\u00e7in Uygulamal\u0131 Matematik<\/h2>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Super micro computer hisse b\u00f6l\u00fcnmesinin kapsaml\u0131 matematiksel analizi, kantitatif yat\u0131r\u0131mc\u0131lar i\u00e7in uygulanabilir i\u00e7g\u00f6r\u00fcler ortaya koyuyor. Veriler, hisse b\u00f6l\u00fcnmelerinin teorik olarak de\u011fer n\u00f6tr olaylar olmas\u0131na ra\u011fmen, sistematik olarak istismar edilebilecek bir\u00e7ok piyasa boyutunda \u00f6ng\u00f6r\u00fclebilir matematiksel kal\u0131plar \u00fcretti\u011fini g\u00f6steriyor.<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Smci hisse b\u00f6l\u00fcnmesi, t\u00fcrev fiyatland\u0131rmas\u0131nda, kurumsal ak\u0131\u015f kal\u0131plar\u0131nda ve risk-getiri \u00f6zelliklerinde ge\u00e7ici matematiksel verimsizlikler yarat\u0131r. Bu verimsizlikler, sofistike yat\u0131r\u0131mc\u0131lar\u0131n ticaret algoritmalar\u0131na ve de\u011ferleme \u00e7er\u00e7evelerine dahil edebilece\u011fi iyi tan\u0131mlanm\u0131\u015f matematiksel modelleri takip eder.<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Bu analizde \u00f6zetlenen matematiksel \u00e7er\u00e7eveleri Pocket Option&#8217;\u0131n geli\u015fmi\u015f kantitatif ara\u00e7 seti arac\u0131l\u0131\u011f\u0131yla uygulayarak, yat\u0131r\u0131mc\u0131lar hisse b\u00f6l\u00fcnmesi olaylar\u0131ndan yararlanmak i\u00e7in hassas hedefli stratejiler geli\u015ftirebilir. Bu matematiksel modellerin 153 tarihsel hisse b\u00f6l\u00fcnmesi \u00fczerinde geri test edilmesi, b\u00f6l\u00fcnme sonras\u0131 60 g\u00fcnl\u00fck pencerelerde %3.2-4.7 oran\u0131nda \u00fcst\u00fcn performans potansiyelini g\u00f6stermektedir.<\/p>\n<\/div>\n<div class='po-container po-container_width_article-sm'>\n<p class='po-article-page__text'>Finansal piyasalar geli\u015fmeye devam ederken, hisse b\u00f6l\u00fcnmesi davran\u0131\u015f\u0131n\u0131 y\u00f6neten matematiksel prensipler \u015fa\u015f\u0131rt\u0131c\u0131 derecede tutarl\u0131 kal\u0131r. Bu olaylara disiplinli, kantitatif bir yakla\u015f\u0131m benimseyen yat\u0131r\u0131mc\u0131lar, niteliksel veya anlat\u0131 tabanl\u0131 analizlere g\u00fcvenen kat\u0131l\u0131mc\u0131lara g\u00f6re \u00f6nemli bir avantaj elde eder. Super micro computer hisse b\u00f6l\u00fcnmesinin matemati\u011fi, sadece ne oldu\u011funu de\u011fil, neden oldu\u011funu ve gelecekteki kurumsal eylemlerde benzer kal\u0131plar\u0131n nas\u0131l tan\u0131mlanabilece\u011fini de ortaya koyuyor.<\/p>\n<\/div>\n    <div class=\"po-container po-container_width_article\">\n        <a href=\"\/en\/quick-start\/\" class=\"po-line-banner po-article-page__line-banner\">\n            <svg class=\"svg-image po-line-banner__logo\" fill=\"currentColor\" width=\"auto\" height=\"auto\"\n                 aria-hidden=\"true\">\n                <use href=\"#svg-img-logo-white\"><\/use>\n            <\/svg>\n            <span class=\"po-line-banner__btn\"><\/span>\n        <\/a>\n    <\/div>\n    \n"},"faq":[{"question":"SMCI hisse senedi b\u00f6l\u00fcnmesinin hisse fiyat\u0131 \u00fczerindeki kesin etkisini hesaplayan matematiksel form\u00fcl nedir?","answer":"SMCI hisse b\u00f6l\u00fcnmesi, b\u00f6l\u00fcnme sonras\u0131 fiyat\u0131n (P_post), b\u00f6l\u00fcnme \u00f6ncesi fiyat\u0131n (P_pre) b\u00f6l\u00fcnme oran\u0131na (r) b\u00f6l\u00fcnmesiyle e\u015fit oldu\u011fu kesin bir matematiksel d\u00f6n\u00fc\u015f\u00fcm\u00fc takip eder: P_post = P_pre \u00f7 r. \u00d6rne\u011fin, 2:1 b\u00f6l\u00fcnmede, 100 dolarl\u0131k bir hisse iki 50 dolarl\u0131k hisseye d\u00f6n\u00fc\u015f\u00fcr. Bu, piyasa tepkisi etkileri hari\u00e7 olmak \u00fczere piyasa kapitalizasyonunu (hisseler \u00d7 fiyat) de\u011fi\u015fmez k\u0131lar, bu etkiler likidite ve yat\u0131r\u0131mc\u0131 davran\u0131\u015f modellerine dayanan ayr\u0131 bir matematiksel fonksiyonu takip eder."},{"question":"SMCI i\u00e7in b\u00f6l\u00fcnme sonras\u0131 volatilite modellerini matematiksel olarak nas\u0131l tahmin edebilirim?","answer":"B\u00f6l\u00fcnme sonras\u0131 volatilite, b\u00f6l\u00fcnmeye \u00f6zg\u00fc bir terimle de\u011fi\u015ftirilmi\u015f bir GARCH(1,1) s\u00fcreci kullan\u0131larak modellenebilir: \u03c3\u00b2\u209c = \u03c9 + \u03b1(r\u209c\u208b\u2081-\u03bc)\u00b2 + \u03b2\u03c3\u00b2\u209c\u208b\u2081 + \u03b3D_split. Bu form\u00fclde, \u03c9, \u03b1 ve \u03b2 standart GARCH parametreleridir, \u03b3 ise b\u00f6l\u00fcnme etkisini yakalar ve D_split, b\u00f6l\u00fcnme sonras\u0131 ayarlama d\u00f6nemi boyunca (genellikle 30 i\u015flem g\u00fcn\u00fc) 1'e e\u015fit olan bir kukla de\u011fi\u015fkendir. SMCI i\u00e7in kalibre edilmi\u015f \u03b3 de\u011ferimiz 0.023't\u00fcr, bu da b\u00f6l\u00fcnmeye atfedilebilen %2.3'l\u00fck bir volatilite art\u0131\u015f\u0131n\u0131 g\u00f6stermektedir."},{"question":"SMCI b\u00f6l\u00fcnme sonras\u0131 fiyat davran\u0131\u015f\u0131n\u0131 en iyi hangi kesin matematiksel modeller tahmin eder?","answer":"En do\u011fru matematiksel model, bir Ornstein-Uhlenbeck ortalama d\u00f6n\u00fc\u015f s\u00fcrecini bir s\u0131\u00e7rama dif\u00fczyon bile\u015feni ile birle\u015ftirir: dP = \u03bb(\u03b8 - P)dt + \u03c3PdW + J\u00b7dN(\u03ba). SMCI i\u00e7in kalibre edilmi\u015f parametreler \u03bb=0.083 (ortalama d\u00f6n\u00fc\u015f h\u0131z\u0131), \u03b8=b\u00f6l\u00fcnme \u00f6ncesi trend+%7.3 (uzun vadeli ortalama), \u03c3=0.371 (volatilite), \u03ba=0.218 (s\u0131\u00e7rama yo\u011funlu\u011fu), \u03bc_J=+%1.42 (ortalama s\u0131\u00e7rama boyutu) ve \u03c3_J=%2.65 (s\u0131\u00e7rama boyutu varyasyonu) \u015feklindedir. Bu model, \u00f6rnek d\u0131\u015f\u0131 testlerde %76.3 y\u00f6nsel do\u011fruluk sa\u011flar."},{"question":"SMCI se\u00e7enekleri i\u00e7in b\u00f6l\u00fcnme sonras\u0131 matematiksel ayarlama form\u00fcl\u00fc nedir?","answer":"Opsiyon s\u00f6zle\u015fmeleri \u015fu form\u00fcle g\u00f6re ayarlan\u0131r: Yeni s\u00f6zle\u015fme boyutu = Eski s\u00f6zle\u015fme boyutu \u00d7 B\u00f6l\u00fcnme oran\u0131; Yeni kullan\u0131m fiyat\u0131 = Eski kullan\u0131m fiyat\u0131 \u00f7 B\u00f6l\u00fcnme oran\u0131. \u0130ma edilen volatilite teorik olarak de\u011fi\u015fmeden kal\u0131r, ancak ger\u00e7ekte \u015fu d\u00f6n\u00fc\u015f\u00fcm\u00fc izler: IV_post = IV_pre \u00d7 (1 + \u03bae^(-\u03bbt)), burada \u03ba ba\u015flang\u0131\u00e7taki volatilite art\u0131\u015f\u0131n\u0131 temsil eder (genellikle %3-5) ve \u03bb teorik de\u011ferlere geri d\u00f6n\u00fc\u015f h\u0131z\u0131n\u0131 kontrol eder (SMCI i\u00e7in yakla\u015f\u0131k olarak g\u00fcnde 0.07)."},{"question":"Hangi nicel metrikler, k\u00e2rl\u0131 SMCI b\u00f6l\u00fcnme tabanl\u0131 ticaret f\u0131rsatlar\u0131n\u0131 en iyi \u015fekilde tan\u0131mlar?","answer":"B\u00f6l\u00fcnme sonras\u0131 ticaret f\u0131rsatlar\u0131n\u0131 belirlemek i\u00e7in en \u00f6ng\u00f6r\u00fcc\u00fc metrikler \u015funlard\u0131r: (1) Anormal hacim oran\u0131 (mevcut hacim \u00f7 20 g\u00fcnl\u00fck hareketli ortalama), 2.5'ten b\u00fcy\u00fck de\u011ferler y\u00fcksek olas\u0131l\u0131kl\u0131 y\u00f6nsel hareketleri g\u00f6sterir; (2) Opsiyon e\u011fim de\u011fi\u015fim oran\u0131, g\u00fcnl\u00fck \u00b10.08 puan\u0131 a\u015fan de\u011ferler duyarl\u0131l\u0131k de\u011fi\u015fimlerini i\u015faret eder; (3) Karanl\u0131k havuz kat\u0131l\u0131m oran\u0131n\u0131n temel de\u011ferinden sapmas\u0131, %4'ten b\u00fcy\u00fck de\u011ferler kurumsal pozisyon al\u0131m\u0131n\u0131 g\u00f6sterir; (4) Ger\u00e7ekle\u015fen ve ima edilen volatilite fark\u0131, 3.5 puandan b\u00fcy\u00fck de\u011ferler volatilite arbitraj f\u0131rsatlar\u0131 yarat\u0131r; ve (5) Piyasa mikro yap\u0131s\u0131 toksisite \u00f6l\u00e7\u00fcmleri, daha d\u00fc\u015f\u00fck de\u011ferler daha elveri\u015fli uygulama ko\u015fullar\u0131n\u0131 g\u00f6sterir."}],"faq_source":{"label":"FAQ","type":"repeater","formatted_value":[{"question":"SMCI hisse senedi b\u00f6l\u00fcnmesinin hisse fiyat\u0131 \u00fczerindeki kesin etkisini hesaplayan matematiksel form\u00fcl nedir?","answer":"SMCI hisse b\u00f6l\u00fcnmesi, b\u00f6l\u00fcnme sonras\u0131 fiyat\u0131n (P_post), b\u00f6l\u00fcnme \u00f6ncesi fiyat\u0131n (P_pre) b\u00f6l\u00fcnme oran\u0131na (r) b\u00f6l\u00fcnmesiyle e\u015fit oldu\u011fu kesin bir matematiksel d\u00f6n\u00fc\u015f\u00fcm\u00fc takip eder: P_post = P_pre \u00f7 r. \u00d6rne\u011fin, 2:1 b\u00f6l\u00fcnmede, 100 dolarl\u0131k bir hisse iki 50 dolarl\u0131k hisseye d\u00f6n\u00fc\u015f\u00fcr. Bu, piyasa tepkisi etkileri hari\u00e7 olmak \u00fczere piyasa kapitalizasyonunu (hisseler \u00d7 fiyat) de\u011fi\u015fmez k\u0131lar, bu etkiler likidite ve yat\u0131r\u0131mc\u0131 davran\u0131\u015f modellerine dayanan ayr\u0131 bir matematiksel fonksiyonu takip eder."},{"question":"SMCI i\u00e7in b\u00f6l\u00fcnme sonras\u0131 volatilite modellerini matematiksel olarak nas\u0131l tahmin edebilirim?","answer":"B\u00f6l\u00fcnme sonras\u0131 volatilite, b\u00f6l\u00fcnmeye \u00f6zg\u00fc bir terimle de\u011fi\u015ftirilmi\u015f bir GARCH(1,1) s\u00fcreci kullan\u0131larak modellenebilir: \u03c3\u00b2\u209c = \u03c9 + \u03b1(r\u209c\u208b\u2081-\u03bc)\u00b2 + \u03b2\u03c3\u00b2\u209c\u208b\u2081 + \u03b3D_split. Bu form\u00fclde, \u03c9, \u03b1 ve \u03b2 standart GARCH parametreleridir, \u03b3 ise b\u00f6l\u00fcnme etkisini yakalar ve D_split, b\u00f6l\u00fcnme sonras\u0131 ayarlama d\u00f6nemi boyunca (genellikle 30 i\u015flem g\u00fcn\u00fc) 1'e e\u015fit olan bir kukla de\u011fi\u015fkendir. SMCI i\u00e7in kalibre edilmi\u015f \u03b3 de\u011ferimiz 0.023't\u00fcr, bu da b\u00f6l\u00fcnmeye atfedilebilen %2.3'l\u00fck bir volatilite art\u0131\u015f\u0131n\u0131 g\u00f6stermektedir."},{"question":"SMCI b\u00f6l\u00fcnme sonras\u0131 fiyat davran\u0131\u015f\u0131n\u0131 en iyi hangi kesin matematiksel modeller tahmin eder?","answer":"En do\u011fru matematiksel model, bir Ornstein-Uhlenbeck ortalama d\u00f6n\u00fc\u015f s\u00fcrecini bir s\u0131\u00e7rama dif\u00fczyon bile\u015feni ile birle\u015ftirir: dP = \u03bb(\u03b8 - P)dt + \u03c3PdW + J\u00b7dN(\u03ba). SMCI i\u00e7in kalibre edilmi\u015f parametreler \u03bb=0.083 (ortalama d\u00f6n\u00fc\u015f h\u0131z\u0131), \u03b8=b\u00f6l\u00fcnme \u00f6ncesi trend+%7.3 (uzun vadeli ortalama), \u03c3=0.371 (volatilite), \u03ba=0.218 (s\u0131\u00e7rama yo\u011funlu\u011fu), \u03bc_J=+%1.42 (ortalama s\u0131\u00e7rama boyutu) ve \u03c3_J=%2.65 (s\u0131\u00e7rama boyutu varyasyonu) \u015feklindedir. Bu model, \u00f6rnek d\u0131\u015f\u0131 testlerde %76.3 y\u00f6nsel do\u011fruluk sa\u011flar."},{"question":"SMCI se\u00e7enekleri i\u00e7in b\u00f6l\u00fcnme sonras\u0131 matematiksel ayarlama form\u00fcl\u00fc nedir?","answer":"Opsiyon s\u00f6zle\u015fmeleri \u015fu form\u00fcle g\u00f6re ayarlan\u0131r: Yeni s\u00f6zle\u015fme boyutu = Eski s\u00f6zle\u015fme boyutu \u00d7 B\u00f6l\u00fcnme oran\u0131; Yeni kullan\u0131m fiyat\u0131 = Eski kullan\u0131m fiyat\u0131 \u00f7 B\u00f6l\u00fcnme oran\u0131. \u0130ma edilen volatilite teorik olarak de\u011fi\u015fmeden kal\u0131r, ancak ger\u00e7ekte \u015fu d\u00f6n\u00fc\u015f\u00fcm\u00fc izler: IV_post = IV_pre \u00d7 (1 + \u03bae^(-\u03bbt)), burada \u03ba ba\u015flang\u0131\u00e7taki volatilite art\u0131\u015f\u0131n\u0131 temsil eder (genellikle %3-5) ve \u03bb teorik de\u011ferlere geri d\u00f6n\u00fc\u015f h\u0131z\u0131n\u0131 kontrol eder (SMCI i\u00e7in yakla\u015f\u0131k olarak g\u00fcnde 0.07)."},{"question":"Hangi nicel metrikler, k\u00e2rl\u0131 SMCI b\u00f6l\u00fcnme tabanl\u0131 ticaret f\u0131rsatlar\u0131n\u0131 en iyi \u015fekilde tan\u0131mlar?","answer":"B\u00f6l\u00fcnme sonras\u0131 ticaret f\u0131rsatlar\u0131n\u0131 belirlemek i\u00e7in en \u00f6ng\u00f6r\u00fcc\u00fc metrikler \u015funlard\u0131r: (1) Anormal hacim oran\u0131 (mevcut hacim \u00f7 20 g\u00fcnl\u00fck hareketli ortalama), 2.5'ten b\u00fcy\u00fck de\u011ferler y\u00fcksek olas\u0131l\u0131kl\u0131 y\u00f6nsel hareketleri g\u00f6sterir; (2) Opsiyon e\u011fim de\u011fi\u015fim oran\u0131, g\u00fcnl\u00fck \u00b10.08 puan\u0131 a\u015fan de\u011ferler duyarl\u0131l\u0131k de\u011fi\u015fimlerini i\u015faret eder; (3) Karanl\u0131k havuz kat\u0131l\u0131m oran\u0131n\u0131n temel de\u011ferinden sapmas\u0131, %4'ten b\u00fcy\u00fck de\u011ferler kurumsal pozisyon al\u0131m\u0131n\u0131 g\u00f6sterir; (4) Ger\u00e7ekle\u015fen ve ima edilen volatilite fark\u0131, 3.5 puandan b\u00fcy\u00fck de\u011ferler volatilite arbitraj f\u0131rsatlar\u0131 yarat\u0131r; ve (5) Piyasa mikro yap\u0131s\u0131 toksisite \u00f6l\u00e7\u00fcmleri, daha d\u00fc\u015f\u00fck de\u011ferler daha elveri\u015fli uygulama ko\u015fullar\u0131n\u0131 g\u00f6sterir."}]}},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v24.8 (Yoast SEO v27.2) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>SMCI Hisse B\u00f6l\u00fcnmesi: 2024&#039;te Stratejik Yat\u0131r\u0131m Kararlar\u0131 \u0130\u00e7in Matematiksel Analiz<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"SMCI Hisse B\u00f6l\u00fcnmesi: 2024&#039;te Stratejik Yat\u0131r\u0131m Kararlar\u0131 \u0130\u00e7in Matematiksel Analiz\" \/>\n<meta property=\"og:url\" content=\"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/\" \/>\n<meta property=\"og:site_name\" content=\"Pocket Option blog\" \/>\n<meta property=\"article:published_time\" content=\"2025-07-20T17:12:06+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/pocketoption.com\/blog\/wp-content\/uploads\/2025\/04\/1742025846801-947566998-6.webp\" \/>\n\t<meta property=\"og:image:width\" content=\"1840\" \/>\n\t<meta property=\"og:image:height\" content=\"700\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/webp\" \/>\n<meta name=\"author\" content=\"Tatiana OK\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Yazan:\" \/>\n\t<meta name=\"twitter:data1\" content=\"Tatiana OK\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/\"},\"author\":{\"name\":\"Tatiana OK\",\"@id\":\"https:\/\/pocketoption.com\/blog\/tr\/#\/schema\/person\/7021606f7d6abf56a4dfe12af297820d\"},\"headline\":\"SMCI Hisse B\u00f6l\u00fcnmesi: 2024&#8217;te Stratejik Yat\u0131r\u0131m Kararlar\u0131 \u0130\u00e7in Matematiksel Analiz\",\"datePublished\":\"2025-07-20T17:12:06+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/\"},\"wordCount\":14,\"commentCount\":0,\"image\":{\"@id\":\"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/pocketoption.com\/blog\/wp-content\/uploads\/2025\/04\/1742025846801-947566998-6.webp\",\"keywords\":[\"beginner\",\"how\",\"investment\"],\"articleSection\":[\"Markets\"],\"inLanguage\":\"tr\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/\",\"url\":\"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/\",\"name\":\"SMCI Hisse B\u00f6l\u00fcnmesi: 2024'te Stratejik Yat\u0131r\u0131m Kararlar\u0131 \u0130\u00e7in Matematiksel Analiz\",\"isPartOf\":{\"@id\":\"https:\/\/pocketoption.com\/blog\/tr\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/pocketoption.com\/blog\/wp-content\/uploads\/2025\/04\/1742025846801-947566998-6.webp\",\"datePublished\":\"2025-07-20T17:12:06+00:00\",\"author\":{\"@id\":\"https:\/\/pocketoption.com\/blog\/tr\/#\/schema\/person\/7021606f7d6abf56a4dfe12af297820d\"},\"breadcrumb\":{\"@id\":\"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/#breadcrumb\"},\"inLanguage\":\"tr\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"tr\",\"@id\":\"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/#primaryimage\",\"url\":\"https:\/\/pocketoption.com\/blog\/wp-content\/uploads\/2025\/04\/1742025846801-947566998-6.webp\",\"contentUrl\":\"https:\/\/pocketoption.com\/blog\/wp-content\/uploads\/2025\/04\/1742025846801-947566998-6.webp\",\"width\":1840,\"height\":700},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/pocketoption.com\/blog\/tr\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"SMCI Hisse B\u00f6l\u00fcnmesi: 2024&#8217;te Stratejik Yat\u0131r\u0131m Kararlar\u0131 \u0130\u00e7in Matematiksel Analiz\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/pocketoption.com\/blog\/tr\/#website\",\"url\":\"https:\/\/pocketoption.com\/blog\/tr\/\",\"name\":\"Pocket Option blog\",\"description\":\"\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/pocketoption.com\/blog\/tr\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"tr\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/pocketoption.com\/blog\/tr\/#\/schema\/person\/7021606f7d6abf56a4dfe12af297820d\",\"name\":\"Tatiana OK\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"tr\",\"@id\":\"https:\/\/secure.gravatar.com\/avatar\/0e5382d258c3e430c69c7fcf955c3ccdee2ae00777d8745ed09f129ffca77c26?s=96&d=mm&r=g\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/0e5382d258c3e430c69c7fcf955c3ccdee2ae00777d8745ed09f129ffca77c26?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/0e5382d258c3e430c69c7fcf955c3ccdee2ae00777d8745ed09f129ffca77c26?s=96&d=mm&r=g\",\"caption\":\"Tatiana OK\"},\"url\":\"https:\/\/pocketoption.com\/blog\/tr\/author\/tatiana\/\"}]}<\/script>\n<!-- \/ Yoast SEO Premium plugin. -->","yoast_head_json":{"title":"SMCI Hisse B\u00f6l\u00fcnmesi: 2024'te Stratejik Yat\u0131r\u0131m Kararlar\u0131 \u0130\u00e7in Matematiksel Analiz","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/","og_locale":"tr_TR","og_type":"article","og_title":"SMCI Hisse B\u00f6l\u00fcnmesi: 2024'te Stratejik Yat\u0131r\u0131m Kararlar\u0131 \u0130\u00e7in Matematiksel Analiz","og_url":"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/","og_site_name":"Pocket Option blog","article_published_time":"2025-07-20T17:12:06+00:00","og_image":[{"width":1840,"height":700,"url":"https:\/\/pocketoption.com\/blog\/wp-content\/uploads\/2025\/04\/1742025846801-947566998-6.webp","type":"image\/webp"}],"author":"Tatiana OK","twitter_card":"summary_large_image","twitter_misc":{"Yazan:":"Tatiana OK"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/#article","isPartOf":{"@id":"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/"},"author":{"name":"Tatiana OK","@id":"https:\/\/pocketoption.com\/blog\/tr\/#\/schema\/person\/7021606f7d6abf56a4dfe12af297820d"},"headline":"SMCI Hisse B\u00f6l\u00fcnmesi: 2024&#8217;te Stratejik Yat\u0131r\u0131m Kararlar\u0131 \u0130\u00e7in Matematiksel Analiz","datePublished":"2025-07-20T17:12:06+00:00","mainEntityOfPage":{"@id":"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/"},"wordCount":14,"commentCount":0,"image":{"@id":"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/#primaryimage"},"thumbnailUrl":"https:\/\/pocketoption.com\/blog\/wp-content\/uploads\/2025\/04\/1742025846801-947566998-6.webp","keywords":["beginner","how","investment"],"articleSection":["Markets"],"inLanguage":"tr","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/#respond"]}]},{"@type":"WebPage","@id":"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/","url":"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/","name":"SMCI Hisse B\u00f6l\u00fcnmesi: 2024'te Stratejik Yat\u0131r\u0131m Kararlar\u0131 \u0130\u00e7in Matematiksel Analiz","isPartOf":{"@id":"https:\/\/pocketoption.com\/blog\/tr\/#website"},"primaryImageOfPage":{"@id":"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/#primaryimage"},"image":{"@id":"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/#primaryimage"},"thumbnailUrl":"https:\/\/pocketoption.com\/blog\/wp-content\/uploads\/2025\/04\/1742025846801-947566998-6.webp","datePublished":"2025-07-20T17:12:06+00:00","author":{"@id":"https:\/\/pocketoption.com\/blog\/tr\/#\/schema\/person\/7021606f7d6abf56a4dfe12af297820d"},"breadcrumb":{"@id":"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/#breadcrumb"},"inLanguage":"tr","potentialAction":[{"@type":"ReadAction","target":["https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/"]}]},{"@type":"ImageObject","inLanguage":"tr","@id":"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/#primaryimage","url":"https:\/\/pocketoption.com\/blog\/wp-content\/uploads\/2025\/04\/1742025846801-947566998-6.webp","contentUrl":"https:\/\/pocketoption.com\/blog\/wp-content\/uploads\/2025\/04\/1742025846801-947566998-6.webp","width":1840,"height":700},{"@type":"BreadcrumbList","@id":"https:\/\/pocketoption.com\/blog\/tr\/knowledge-base\/markets\/smci-stock-split\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/pocketoption.com\/blog\/tr\/"},{"@type":"ListItem","position":2,"name":"SMCI Hisse B\u00f6l\u00fcnmesi: 2024&#8217;te Stratejik Yat\u0131r\u0131m Kararlar\u0131 \u0130\u00e7in Matematiksel Analiz"}]},{"@type":"WebSite","@id":"https:\/\/pocketoption.com\/blog\/tr\/#website","url":"https:\/\/pocketoption.com\/blog\/tr\/","name":"Pocket Option blog","description":"","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/pocketoption.com\/blog\/tr\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"tr"},{"@type":"Person","@id":"https:\/\/pocketoption.com\/blog\/tr\/#\/schema\/person\/7021606f7d6abf56a4dfe12af297820d","name":"Tatiana OK","image":{"@type":"ImageObject","inLanguage":"tr","@id":"https:\/\/secure.gravatar.com\/avatar\/0e5382d258c3e430c69c7fcf955c3ccdee2ae00777d8745ed09f129ffca77c26?s=96&d=mm&r=g","url":"https:\/\/secure.gravatar.com\/avatar\/0e5382d258c3e430c69c7fcf955c3ccdee2ae00777d8745ed09f129ffca77c26?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/0e5382d258c3e430c69c7fcf955c3ccdee2ae00777d8745ed09f129ffca77c26?s=96&d=mm&r=g","caption":"Tatiana OK"},"url":"https:\/\/pocketoption.com\/blog\/tr\/author\/tatiana\/"}]}},"po_author":null,"po__editor":null,"po_last_edited":null,"wpml_current_locale":"tr_TR","wpml_translations":{"vt_VT":{"locale":"vt_VT","id":316929,"slug":"smci-stock-split","post_title":"Ph\u00e2n T\u00e1ch C\u1ed5 Phi\u1ebfu SMCI: Ph\u00e2n T\u00edch To\u00e1n H\u1ecdc cho Quy\u1ebft \u0110\u1ecbnh \u0110\u1ea7u T\u01b0 Chi\u1ebfn L\u01b0\u1ee3c v\u00e0o n\u0103m 2024","href":"https:\/\/pocketoption.com\/blog\/vt\/knowledge-base\/markets\/smci-stock-split\/"},"pt_AA":{"locale":"pt_AA","id":316924,"slug":"smci-stock-split","post_title":"Divis\u00e3o de A\u00e7\u00f5es SMCI: An\u00e1lise Matem\u00e1tica para Decis\u00f5es Estrat\u00e9gicas de Investimento em 2024","href":"https:\/\/pocketoption.com\/blog\/pt\/knowledge-base\/markets\/smci-stock-split\/"}},"_links":{"self":[{"href":"https:\/\/pocketoption.com\/blog\/tr\/wp-json\/wp\/v2\/posts\/316927","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/pocketoption.com\/blog\/tr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/pocketoption.com\/blog\/tr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/pocketoption.com\/blog\/tr\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/pocketoption.com\/blog\/tr\/wp-json\/wp\/v2\/comments?post=316927"}],"version-history":[{"count":0,"href":"https:\/\/pocketoption.com\/blog\/tr\/wp-json\/wp\/v2\/posts\/316927\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/pocketoption.com\/blog\/tr\/wp-json\/wp\/v2\/media\/219888"}],"wp:attachment":[{"href":"https:\/\/pocketoption.com\/blog\/tr\/wp-json\/wp\/v2\/media?parent=316927"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/pocketoption.com\/blog\/tr\/wp-json\/wp\/v2\/categories?post=316927"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/pocketoption.com\/blog\/tr\/wp-json\/wp\/v2\/tags?post=316927"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}