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[quote=unlimitted;183283]acil yaklaşık 68,100'e inmemiz lazım.
turbo parası lazım.
acil 4.291 puan lazım. sadece bugünlük. :D[/quote]
herkes kendine yontuyo.heyk acil ımf+efg+ sp hatta höküümet gelsin de bu bitik piysa anca 70200 e maliyetime gelsin::: sabah geldi gerçi ama almadık işte +.
Gelene geçene beton..Çimento stokları dağ gibim birikmiş..Tepkiye oynayanlar şantiyenin temeline gomulurler.
Aynı hatayı 57000 de yaptık.
[QUOTE=enorton;183280]Abi ema 20 dedik diye o kadar fark var, ema 40 desek fark daha da büyük... Hem sonuçta fark farktır... :) Bu fark giderek azalıyor, bir yerde eşitlenecekler... Benim merak ettiğim hangi barda eşitlenecekler... Matriks den ses yok ikinci mailimden sonra... Şuanda hindistandaki uzmanlar bunun üzerine çalışıyor olmalılar :)[/QUOTE]
parababası:))))))))))))))))))))))
ENorton hadi iyisin;
A type of moving average that is similar to a simple moving average, except that more weight is given to the latest data (bizde yalan yok :))
Uğraşacam diyosan gerisi aşağıda...ehuehue
[B][[URL="http://en.wikipedia.org/w/index.php?title=Moving_average&action=edit§ion=4"][COLOR=#002bb8]edit[/COLOR][/URL]] Exponential moving average[/B]
[URL="http://en.wikipedia.org/wiki/File:Exponential_moving_average_weights_N%3D15.png"][IMG]http://upload.wikimedia.org/wikipedia/commons/thumb/b/ba/Exponential_moving_average_weights_N%3D15.png/180px-Exponential_moving_average_weights_N%3D15.png[/IMG][/URL] [URL="http://en.wikipedia.org/wiki/File:Exponential_moving_average_weights_N%3D15.png"][IMG]http://en.wikipedia.org/skins-1.5/common/images/magnify-clip.png[/IMG][/URL]
EMA weights [I]N[/I]=15
An [B]exponential moving average[/B] (EMA), sometimes also called an [B]exponentially weighted moving average[/B] (EWMA), applies weighting factors which decrease [URL="http://en.wikipedia.org/wiki/Exponentiation"][COLOR=#002bb8]exponentially[/COLOR][/URL]. The weighting for each older data point decreases exponentially, giving much more importance to recent observations while still not discarding older observations entirely. The graph at right shows an example of the weight decrease.
[B]Parameters:[/B]
[LIST][*]The degree of weighing decrease is expressed as a constant smoothing factor [I]α[/I], a number between 0 and 1. The smoothing factor may be expressed as a percentage, so a value of 10% is equivalent to [I]α[/I] = 0.1. A higher [I]α[/I] discounts older observations faster. Alternatively, [I]α[/I] may be expressed in terms of [I]N[/I] time periods, where [I]α[/I] = 2/([I]N[/I]+1). For example, [I]N[/I] = 19 is equivalent to [I]α[/I] = 0.1. The half-life of the weights (the interval over which the weights decrease by a factor of two) is approximately [I]N[/I]/2.8854 (within 1% if [I]N[/I] > 5).[*]The observation at a time period [I]t[/I] is designated [B][I]Y[/I][I]t[/I][/B], and the value of the EMA at any time period [I]t[/I] is designated [B][I]S[/I][I]t[/I][/B].[/LIST][I]S[/I]1 is undefined. [I]S[/I]2 may be initialized in a number of different ways, most commonly by setting [I]S[/I]2 to [I]Y[/I]1, though other techniques exist, such as setting [I]S[/I]2 to an average of the first 4 or 5 observations. The prominence of the [I]S[/I]2 initialization's effect on the resultant moving average depends on [I]α[/I]; smaller [I]α[/I] values make the choice of [I]S[/I]2 relatively more important than larger [I]α[/I] values, since a higher [I]α[/I] discounts older observations faster.
[B]Formula:[/B]
The formula for calculating the EMA at time periods [I]t[/I] > 2 is
[IMG]http://upload.wikimedia.org/math/3/4/2/3422cc705bde2398c0b1de1e91827c12.png[/IMG] This formulation is according to Hunter (1986)[URL="http://en.wikipedia.org/wiki/Moving_average#cite_note-1"][COLOR=#002bb8][2][/COLOR][/URL]. The weights will obey [FONT=Times New Roman]α(1 − α)[I]x[/I][I]Y[/I][I]t[/I] − ([I]x[/I] + 1)[/FONT]. An alternate approach by Roberts (1959) uses Yt in lieu of [I]Y[/I][I]t[/I]−1[URL="http://en.wikipedia.org/wiki/Moving_average#cite_note-2"][COLOR=#002bb8][3][/COLOR][/URL]:
[IMG]http://upload.wikimedia.org/math/5/b/9/5b9038a28e203e93b2b306a1fced5ff9.png[/IMG] This formula can also be expressed in technical analysis terms as follows, showing how the EMA steps towards the latest data point, but only by a proportion of the difference (each time):[URL="http://en.wikipedia.org/wiki/Moving_average#cite_note-stockcharts-3"][COLOR=#002bb8][4][/COLOR][/URL]
[COLOR=#002bb8][IMG]http://upload.wikimedia.org/math/7/d/9/7d9048ec588c5f82276d177c4fccd8c2.png[/IMG][/COLOR] Expanding out [FONT=Times New Roman]EMAyesterday[/FONT] each time results in the following power series, showing how the weighting factor on each data point [I]p[/I]1, [I]p[/I]2, etc, decrease exponentially:
[IMG]http://upload.wikimedia.org/math/a/0/7/a076c1a3bb3afcd27a939b3afbfaac48.png[/IMG][URL="http://en.wikipedia.org/wiki/Moving_average#cite_note-4"][COLOR=#002bb8][5][/COLOR][/URL] This is an [URL="http://en.wikipedia.org/wiki/Series_(mathematics)"][COLOR=#002bb8]infinite sum[/COLOR][/URL] with decreasing terms.
The [I]N[/I] periods in an [I]N[/I]-day EMA only specify the [I]α[/I] factor. [I]N[/I] is not a stopping point for the calculation in the way it is in an [URL="http://en.wikipedia.org/wiki/Moving_average#Simple_moving_average"][COLOR=#002bb8]SMA[/COLOR][/URL] or [URL="http://en.wikipedia.org/wiki/Moving_average#Weighted_moving_average"][COLOR=#002bb8]WMA[/COLOR][/URL]. For sufficiently large [I]N[/I], The first [I]N[/I] data points in an EMA represent about 86% of the total weight in the calculation[URL="http://en.wikipedia.org/wiki/Moving_average#cite_note-5"][COLOR=#002bb8][6][/COLOR][/URL]:
[IMG]http://upload.wikimedia.org/math/9/4/9/949ac6b6ad9322808768e679213bf930.png[/IMG] i.e. [IMG]http://upload.wikimedia.org/math/c/d/a/cdac07382eae3818db8b424de8a79f33.png[/IMG] simplified[URL="http://en.wikipedia.org/wiki/Moving_average#cite_note-6"][COLOR=#002bb8][7][/COLOR][/URL], tends to [IMG]http://upload.wikimedia.org/math/5/0/a/50a3fb6921d6f4c857bba1f08b4bd110.png[/IMG]. The [URL="http://en.wikipedia.org/wiki/Power_series"][COLOR=#002bb8]power formula[/COLOR][/URL] above gives a starting value for a particular day, after which the successive days formula shown first can be applied. The question of how far back to go for an initial value depends, in the worst case, on the data. If there are huge [I]p[/I] price values in old data then they'll have an effect on the total even if their weighting is very small. If one assumes prices don't vary too wildly then just the weighting can be considered. The weight omitted by stopping after [I]k[/I] terms is
[IMG]http://upload.wikimedia.org/math/a/a/7/aa72df51d6510d9bba7be912d428697e.png[/IMG] which is
[IMG]http://upload.wikimedia.org/math/6/3/d/63dd3d3290a82ae6820e186416ae3eb8.png[/IMG] i.e. a fraction
[IMG]http://upload.wikimedia.org/math/2/c/4/2c48307734366f01c63127c220e2a8af.png[/IMG] out of the total weight.
For example, to have 99.9% of the weight,
[IMG]http://upload.wikimedia.org/math/6/9/b/69baa475a173d987d4b429e414bba389.png[/IMG] terms should be used. Since [IMG]http://upload.wikimedia.org/math/3/0/4/304d45b965f2a4bb8ee66cf8c9755a87.png[/IMG] approaches [IMG]http://upload.wikimedia.org/math/b/2/6/b26657e18ad4a47a17c2bcbb3da6862d.png[/IMG] as N increases[URL="http://en.wikipedia.org/wiki/Moving_average#cite_note-7"][COLOR=#002bb8][8][/COLOR][/URL], this simplifies to approximately[URL="http://en.wikipedia.org/wiki/Moving_average#cite_note-8"][COLOR=#002bb8][9][/COLOR][/URL]
[COLOR=#002bb8][IMG]http://upload.wikimedia.org/math/2/4/7/247fa75273ed4be33a1cac92df6fa22b.png[/IMG][/COLOR] for this example (99.9% weight).
[QUOTE=Astatin;183289]ENorton hadi iyisin;
A type of moving average that is similar to a simple moving average, except that more weight is given to the latest data (bizde yalan yok :))
Uğraşacam diyosan gerisi aşağıda...ehuehue
[B][[URL="http://en.wikipedia.org/w/index.php?title=Moving_average&action=edit§ion=4"][COLOR=#002bb8]edit[/COLOR][/URL]] Exponential moving average[/B]
[URL="http://en.wikipedia.org/wiki/File:Exponential_moving_average_weights_N%3D15.png"][IMG]http://upload.wikimedia.org/wikipedia/commons/thumb/b/ba/Exponential_moving_average_weights_N%3D15.png/180px-Exponential_moving_average_weights_N%3D15.png[/IMG][/URL] [URL="http://en.wikipedia.org/wiki/File:Exponential_moving_average_weights_N%3D15.png"][IMG]http://en.wikipedia.org/skins-1.5/common/images/magnify-clip.png[/IMG][/URL]
EMA weights [I]N[/I]=15
An [B]exponential moving average[/B] (EMA), sometimes also called an [B]exponentially weighted moving average[/B] (EWMA), applies weighting factors which decrease [URL="http://en.wikipedia.org/wiki/Exponentiation"][COLOR=#002bb8]exponentially[/COLOR][/URL]. The weighting for each older data point decreases exponentially, giving much more importance to recent observations while still not discarding older observations entirely. The graph at right shows an example of the weight decrease.
[B]Parameters:[/B]
[LIST][*]The degree of weighing decrease is expressed as a constant smoothing factor [I]α[/I], a number between 0 and 1. The smoothing factor may be expressed as a percentage, so a value of 10% is equivalent to [I]α[/I] = 0.1. A higher [I]α[/I] discounts older observations faster. Alternatively, [I]α[/I] may be expressed in terms of [I]N[/I] time periods, where [I]α[/I] = 2/([I]N[/I]+1). For example, [I]N[/I] = 19 is equivalent to [I]α[/I] = 0.1. The half-life of the weights (the interval over which the weights decrease by a factor of two) is approximately [I]N[/I]/2.8854 (within 1% if [I]N[/I] > 5).[*]The observation at a time period [I]t[/I] is designated [B][I]Y[/I][I]t[/I][/B], and the value of the EMA at any time period [I]t[/I] is designated [B][I]S[/I][I]t[/I][/B].[/LIST][I]S[/I]1 is undefined. [I]S[/I]2 may be initialized in a number of different ways, most commonly by setting [I]S[/I]2 to [I]Y[/I]1, though other techniques exist, such as setting [I]S[/I]2 to an average of the first 4 or 5 observations. The prominence of the [I]S[/I]2 initialization's effect on the resultant moving average depends on [I]α[/I]; smaller [I]α[/I] values make the choice of [I]S[/I]2 relatively more important than larger [I]α[/I] values, since a higher [I]α[/I] discounts older observations faster.
[B]Formula:[/B]
The formula for calculating the EMA at time periods [I]t[/I] > 2 is
[IMG]http://upload.wikimedia.org/math/3/4/2/3422cc705bde2398c0b1de1e91827c12.png[/IMG] This formulation is according to Hunter (1986)[URL="http://en.wikipedia.org/wiki/Moving_average#cite_note-1"][COLOR=#002bb8][2][/COLOR][/URL]. The weights will obey [FONT=Times New Roman]α(1 − α)[I]x[/I][I]Y[/I][I]t[/I] − ([I]x[/I] + 1)[/FONT]. An alternate approach by Roberts (1959) uses Yt in lieu of [I]Y[/I][I]t[/I]−1[URL="http://en.wikipedia.org/wiki/Moving_average#cite_note-2"][COLOR=#002bb8][3][/COLOR][/URL]:
[IMG]http://upload.wikimedia.org/math/5/b/9/5b9038a28e203e93b2b306a1fced5ff9.png[/IMG] This formula can also be expressed in technical analysis terms as follows, showing how the EMA steps towards the latest data point, but only by a proportion of the difference (each time):[URL="http://en.wikipedia.org/wiki/Moving_average#cite_note-stockcharts-3"][COLOR=#002bb8][4][/COLOR][/URL]
[COLOR=#002bb8][IMG]http://upload.wikimedia.org/math/7/d/9/7d9048ec588c5f82276d177c4fccd8c2.png[/IMG][/COLOR] Expanding out [FONT=Times New Roman]EMAyesterday[/FONT] each time results in the following power series, showing how the weighting factor on each data point [I]p[/I]1, [I]p[/I]2, etc, decrease exponentially:
[IMG]http://upload.wikimedia.org/math/a/0/7/a076c1a3bb3afcd27a939b3afbfaac48.png[/IMG][URL="http://en.wikipedia.org/wiki/Moving_average#cite_note-4"][COLOR=#002bb8][5][/COLOR][/URL] This is an [URL="http://en.wikipedia.org/wiki/Series_(mathematics)"][COLOR=#002bb8]infinite sum[/COLOR][/URL] with decreasing terms.
The [I]N[/I] periods in an [I]N[/I]-day EMA only specify the [I]α[/I] factor. [I]N[/I] is not a stopping point for the calculation in the way it is in an [URL="http://en.wikipedia.org/wiki/Moving_average#Simple_moving_average"][COLOR=#002bb8]SMA[/COLOR][/URL] or [URL="http://en.wikipedia.org/wiki/Moving_average#Weighted_moving_average"][COLOR=#002bb8]WMA[/COLOR][/URL]. For sufficiently large [I]N[/I], The first [I]N[/I] data points in an EMA represent about 86% of the total weight in the calculation[URL="http://en.wikipedia.org/wiki/Moving_average#cite_note-5"][COLOR=#002bb8][6][/COLOR][/URL]:
[IMG]http://upload.wikimedia.org/math/9/4/9/949ac6b6ad9322808768e679213bf930.png[/IMG] i.e. [IMG]http://upload.wikimedia.org/math/c/d/a/cdac07382eae3818db8b424de8a79f33.png[/IMG] simplified[URL="http://en.wikipedia.org/wiki/Moving_average#cite_note-6"][COLOR=#002bb8][7][/COLOR][/URL], tends to [IMG]http://upload.wikimedia.org/math/5/0/a/50a3fb6921d6f4c857bba1f08b4bd110.png[/IMG]. The [URL="http://en.wikipedia.org/wiki/Power_series"][COLOR=#002bb8]power formula[/COLOR][/URL] above gives a starting value for a particular day, after which the successive days formula shown first can be applied. The question of how far back to go for an initial value depends, in the worst case, on the data. If there are huge [I]p[/I] price values in old data then they'll have an effect on the total even if their weighting is very small. If one assumes prices don't vary too wildly then just the weighting can be considered. The weight omitted by stopping after [I]k[/I] terms is
[IMG]http://upload.wikimedia.org/math/a/a/7/aa72df51d6510d9bba7be912d428697e.png[/IMG] which is
[IMG]http://upload.wikimedia.org/math/6/3/d/63dd3d3290a82ae6820e186416ae3eb8.png[/IMG] i.e. a fraction
[IMG]http://upload.wikimedia.org/math/2/c/4/2c48307734366f01c63127c220e2a8af.png[/IMG] out of the total weight.
For example, to have 99.9% of the weight,
[IMG]http://upload.wikimedia.org/math/6/9/b/69baa475a173d987d4b429e414bba389.png[/IMG] terms should be used. Since [IMG]http://upload.wikimedia.org/math/3/0/4/304d45b965f2a4bb8ee66cf8c9755a87.png[/IMG] approaches [IMG]http://upload.wikimedia.org/math/b/2/6/b26657e18ad4a47a17c2bcbb3da6862d.png[/IMG] as N increases[URL="http://en.wikipedia.org/wiki/Moving_average#cite_note-7"][COLOR=#002bb8][8][/COLOR][/URL], this simplifies to approximately[URL="http://en.wikipedia.org/wiki/Moving_average#cite_note-8"][COLOR=#002bb8][9][/COLOR][/URL]
[COLOR=#002bb8][IMG]http://upload.wikimedia.org/math/2/4/7/247fa75273ed4be33a1cac92df6fa22b.png[/IMG][/COLOR] for this example (99.9% weight).[/QUOTE]
teprik ederim .. çok teorik bir açıklamma olmuş asteton patron... :D:D:D
[quote=tutku;183284]DENİZ FENERİNİ ARA Kİ BULASIN
Vatan yazarı Güngör Mengi’nin bugünkü yazısı şu cümleyle başlıyor: “[B]Askeri kötülemeye yarayacak malzemenin bini bir para ama [COLOR=red]Deniz Feneri’ni ara ki bulasın![/COLOR][/B][COLOR=red]” [/COLOR]
Alman tarihinin en büyük yardım skandalı olan Deniz Feneri davasının Türkiye ayağının kör topal ilerlemesinden şikayet eden yazar, konuyu merak edenlere de “[B]gizlilik kararı[/B]” ile gözdağı verildiğini yazdı. “[B]Bu oyalama siyaseti, suçlanan kişiler önümüzdeki seçimlerde milletvekili yapılarak dokunulmaz hale getirilene kadar sürecek[/B]” diyenler bakalım haklı çıkacak mı? diye sordu. Alman yargısının misilleme yapıp Türk savcılarına mahkum olanları sorgulama izni vermemesinin de suçluları koruyanlara yarayacağını belirtti.
Güngör Mengi‘nin “[B]Olmadı hakim bey![/B]” başlıklı yazısı şöyle:
"TSK’ya yönelik psikolojik savaşa katılmak isteyenler, adeta özel merkezlerde üretilip servise sunulan bilgi ve belgeler içinde yüzerken Deniz Feneri’nin ışığını arayanlar, dalgalı bir denizde mide bulantısı çekiyorlar.
[URL]http://www.odatv.com/n.php?n=deniz-fenerini-ara-ki-bulasin--1001101200[/URL][/quote]
Var olan şey kaybolmaz,çıkar bir yerden..:)))
Yav dikkatli olun benim grafiklerde hala bozulma yok! 70250 den 69250 ye kadar 1000 puan haşırt diye verdiler panik yaptırıp piyasaya shortör çekiyolar diye düşünüyorum!
[quote=KIZILAGA;183287]Gelene geçene beton..Çimento stokları dağ gibim birikmiş..Tepkiye oynayanlar şantiyenin temeline gomulurler.
Aynı hatayı 57000 de yaptık.[/quote]
beni huylandıran tek şey var.
cuma günkü düşüşe "bu düzeltme" diyenler vardı. elbet olacak. o yüzden rahattım. hatta diyenler çoğaldıkça daha bi güzelleşiyordu olay.
emme bugünkü ani düşüş, "bu düzeltme olmayabilir" diyen sayısını çoğalttı.
önemli olan sayının çoğalması değil. elbet düştükçe o sayı çoğalacak.
önemli olan sayının çoğalma hızı...
hoşuma gitmedi. fazla hızlı oldu.
[QUOTE=AMON RA;183292]Yav dikkatli olun benim grafiklerde hala bozulma yok! 70250 den 69250 ye kadar 1000 puan haşırt diye verdiler panik yaptırıp piyasaya shortör çekiyolar diye düşünüyorum![/QUOTE]
teprik ederim Aman RA patron .. güzel tespit olmuş .. :D.brv.brv
[QUOTE=selçuklu;183294]teprik ederim Aman RA patron .. güzel tespit olmuş .. :D.brv.brv[/QUOTE]
EYVALLAH patron! .lelele.brv+.
[QUOTE=Astatin;183282]MTX dir ne yapsa yeridir..bir zaman hatırlıyorum, üşenmeyip 21 lik c,21,s hesapladım hesap makinasıyla..farklı çıkmıştı MTX den :)
Fark gittikçe azalıyorsa, şöyle bir şey olabilir ; [B]misal 14 barın içindeki her bir bar kendisinden geriye dönük 14 barlık birşeyler yapıyor olabilirmi.[/B].yok yaww sanmam...işte yaşasın şeffaflık :) akşam ema nın açık formülünü bularsam yollarsam[/QUOTE]
Abi ben de öyle bir şeyden şüphelendim ve o yüzden matrikse mail attım ama gelen cevap verileri gücelle oldu :D
Mesela mav 10 eşitlendi şimdi... Baktım cuma 11 barında eşitlenmiş yani 40 bar sonra... belki yine de fark vardır ama virgülden sonra 3 basamak gösterdiği için aynı gibi gösteriyor da olabilir :) O kadar fark olsun...
Ekim 2009 vade sonundaki sert düşüş hareketi gibi bir hareket görmezsek 2.seans bence de bu cortlar fazla dayanmayacak