{"id":44135,"date":"2026-06-22T22:09:07","date_gmt":"2026-06-23T03:09:07","guid":{"rendered":"https:\/\/library-staging.tradingtechnologies.com\/doc\/moving-average-ma-2\/"},"modified":"2026-06-22T22:09:08","modified_gmt":"2026-06-23T03:09:08","slug":"moving-average-ma-2","status":"publish","type":"doc","link":"https:\/\/library-staging.tradingtechnologies.com\/ja\/moving-average-ma-2\/","title":{"rendered":"\u79fb\u52d5\u5e73\u5747 (MA)"},"content":{"rendered":"<p class=\"BodyOther\">\u79fb\u52d5\u5e73\u5747\u306f\u7570\u306a\u3063\u305f\u30b5\u30d6\u30bb\u30c3\u30c8\u306e\u4e00\u9023\u306e\u5e73\u5747\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002\u5404\u65b0\u898f\u306e\u30b5\u30d6\u30bb\u30c3\u30c8\u306f\u3001\u65b0\u898f\u306e\u5024\u3092\u8ffd\u52a0\u3057\u3066\u53e4\u3044\u5024\u3092\u53d6\u308a\u9664\u304f\u3053\u3068\u3067\u3001\u4e00\u5b9a\u306e\u9577\u3055\u3092\u4fdd\u6301\u3057\u307e\u3059\u3002\u79fb\u52d5\u5e73\u5747\u306f\u3001N-\u671f\u9593\u306e\u30c7\u30fc\u30bf\u304c\u30e6\u30fc\u30b6\u30fc\u306b\u5b9a\u7fa9\u3055\u308c\u307e\u3059\u3002\u4ed6\u306e\u30c6\u30af\u30cb\u30ab\u30eb\u6307\u6a19\u306b\u52a0\u3048\u3053\u306e\u30c6\u30af\u30cb\u30ab\u30eb\u5206\u6790\u6307\u6a19\u306f\u3001\u30e6\u30fc\u30b6\u30fc\u304c\u8a08\u7b97\u3067\u4f7f\u7528\u3059\u308b\u79fb\u52d5\u5e73\u5747\u306e\u30bf\u30a4\u30d7\u3092\u9078\u629e\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u3063\u3066\u3044\u307e\u3059\u3002[<a href=\"#formula\">\u6570\u5f0f<\/a>] \u30bb\u30af\u30b7\u30e7\u30f3\u306b\u306f\u3001\u5404\u30bf\u30a4\u30d7\u306e\u6570\u5f0f\u304c\u8868\u793a\u3055\u308c\u307e\u3059\u3002<\/p>\n<p>\u79fb\u52d5\u5e73\u5747\u306e\u65b9\u5411 (\u9ad8\u5024\u3001\u5b89\u5024\u3001\u30d5\u30e9\u30c3\u30c8\u5024) \u306f\u3001\u5e02\u5834\u306e\u52d5\u5411\u3092\u793a\u3057\u3001\u30b9\u30ed\u30fc\u30d7\u306f\u52d5\u5411\u306e\u5f37\u3055\u3092\u793a\u3057\u307e\u3059\u3002\u9577\u671f\u306e\u5e73\u5747\u306f\u3001\u3088\u308a\u9577\u671f\u9593\u306e\u52d5\u5411\u3092\u8b58\u5225\u3059\u308b\u306e\u306b\u4f7f\u7528\u3055\u308c\u3001\u77ed\u671f\u306e\u5e73\u5747\u306f\u3001\u3088\u308a\u77ed\u671f\u9593\u306e\u52d5\u5411\u3092\u8b58\u5225\u3059\u308b\u306e\u306b\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002<\/p>\n<p><!--\n\n\n<p>Typical analysis involves price crossovers with the average. It is a lagging indicator but can confirm that a change in trend has taken place. When coupled with a trend line or support\/resistance violation, the signal becomes quite reliable. Averages give traders an idea of support and resistance areas but they should not be used alone to determine trade triggers. Overshoots of averages are common although using an envelope of the averages of highs and of lows can help mitigate this.<\/p>\n\n\n--> <\/p>\n<p><img decoding=\"async\" class=\"img-responsive\" src=\"https:\/\/library-staging.tradingtechnologies.com\/wp-content\/uploads\/2026\/06\/moving-average-2.png\" alt=\"\"><\/p>\n<h2>Configuration Options<\/h2>\n<p><img decoding=\"async\" class=\"img-responsive\" src=\"https:\/\/library-staging.tradingtechnologies.com\/wp-content\/uploads\/2026\/06\/moving-average-3.png\" alt=\"\"><\/p>\n<ul>\n<li><strong>Period<\/strong> (\u30d4\u30ea\u30aa\u30c9): \u8a08\u7b97\u3067\u4f7f\u7528\u3055\u308c\u308b\u30d0\u30fc\u6570\u3002<\/li>\n<li>  \t<strong>\u6b04<\/strong>: \u5e73\u5747\u8a08\u7b97\u306e\u30d9\u30fc\u30b9\u306b\u4f7f\u7528\u3059\u308b\u4fa1\u683c\u3001\u307e\u305f\u306f\u4fa1\u683c\u306e\u7d44\u307f\u5408\u308f\u305b\u3002\u4ee5\u4e0b\u306e\u5024\u304c\u3042\u308a\u307e\u3059\u3002\n<ul>\n<li>Open (\u59cb\u5024)<\/li>\n<li>High (\u9ad8\u5024)<\/li>\n<li>Low (\u5b89\u5024)<\/li>\n<li>Close (\u7d42\u5024)<\/li>\n<li>Adjusted Close (\u8abf\u6574\u7d42\u5024)<\/li>\n<li>HL\/2 ( left ( frac{High + Low}{2} right ) )<\/li>\n<li>HLC\/3 ( left ( frac{High + Low + Close}{3} right ) )<\/li>\n<li>HLCC\/4 ( left ( frac{High + Low + Close + Close}{4} right ) )<\/li>\n<li>OHLC\/4 ( left ( frac{Open + High + Low + Close}{4} right ) )<\/li>\n<\/ul>\n<\/li>\n<li>  \t<strong>Moving Average Type<\/strong>: Type of moving average to use in the calculations:\n<ul hidden>\n<li><strong>Simple<\/strong>: Mean (average) of the data.<\/li>\n<li><strong>Exponential<\/strong>: Newer data are weighted more heavily geometrically.<\/li>\n<li><strong>Time Series<\/strong>: Calculates a linear regression trendline using the \u201cleast squares fit\u201d method.<\/li>\n<li><strong>Triangular<\/strong>: Weighted average where the middle data are given the most weight, decreasing linearly to the end points.<\/li>\n<li><strong>Variable<\/strong>: An exponential moving average with a volatility index factored into the smoothing formula.  The Variable Moving average uses the Chande Momentum Oscillator as the volatility index.<\/li>\n<li><strong>VIDYA<\/strong>: An exponential moving average with a volatility index factored into the smoothing formula.  The VIDYA moving average uses the Standard Deviation as the volatility index. (Volatility Index DYnamic Average).<\/li>\n<li><strong>Weighted<\/strong>: Newer data are weighted more heavily arithmetically.<\/li>\n<li><strong>Welles Winder<\/strong>:The standard exponential moving average formula converts the time period to a fraction using the formula EMA% = 2\/(n + 1) where n is the number of days. For example, the EMA% for 14 days is 2\/(14 days +1) = 13.3%. Wilder, however, uses an EMA% of 1\/14 (1\/n) which equals 7.1%. This equates to a 27-day exponential moving average using the standard formula.<\/li>\n<li><strong>Hull<\/strong>: The Hull Moving Average makes a moving average more responsive while maintaining a curve smoothness. The formula for calculating this average is as follows: HMA[i] = MA( (2*MA(input, period\/2) \u2013 MA(input, period)), SQRT(period)) where MA is a moving average and SQRT is square root.<\/li>\n<li><strong>Double Exponential<\/strong>: The Double Exponential moving average attempts to remove the inherent lag associated to Moving Averages by placing more weight on recent values.<\/li>\n<li><strong>Triple Exponential<\/strong>: TBD<\/li>\n<\/ul>\n<ul>\n<li>Simple<\/li>\n<li>Exponential<\/li>\n<li>Time Series<\/li>\n<li>Triangular<\/li>\n<li>Variable<\/li>\n<li>VIDYA<\/li>\n<li>Weighted<\/li>\n<li>Welles Winder<\/li>\n<li>Hull<\/li>\n<li>Double Exponential<\/li>\n<li>Triple Exponential<\/li>\n<\/ul>\n<\/li>\n<li hidden><strong>\u30bf\u30a4\u30d7<\/strong>: \u79fb\u52d5\u5e73\u5747\u306e\u30bf\u30a4\u30d7\n<ul>\n<li><strong>\u5358\u7d14\u79fb\u52d5\u5e73\u5747 (Simple): <\/strong>\u30c7\u30fc\u30bf\u306e\u5e73\u5747\u3002<\/li>\n<li><strong>\u6307\u6570\u79fb\u52d5\u5e73\u5747 (Exponential)<\/strong>\u3088\u308a\u65b0\u3057\u3044\u30c7\u30fc\u30bf\u306f\u3001\u5e7e\u4f55\u5b66\u7684\u306b\u3088\u308a\u52a0\u91cd\u3055\u308c\u3066\u3044\u307e\u3059\u3002<\/li>\n<li>\u6642\u7cfb\u5217 (Time Series): \u300c\u6700\u5c0f\u4e8c\u4e57\u6cd5\u30d5\u30a3\u30c3\u30c8\u300d \u3092\u4f7f\u3063\u3066\u7dda\u5f62\u56de\u5e30\u52d5\u5411\u3092\u8a08\u7b97\u3057\u307e\u3059\u3002<\/li>\n<li><strong>Triangular (\u4e09\u89d2\u5f62):<\/strong> \u4e2d\u592e\u30c7\u30fc\u30bf\u306b\u3082\u3063\u3068\u3082\u52a0\u91cd\u304c\u304a\u304b\u308c\u308b\u52a0\u91cd\u5e73\u5747\u3067\u3001\u6700\u7d42\u70b9\u307e\u3067\u306e\u4e0b\u964d\u306e\u7dda\u5f62\u3067\u3059\u3002<\/li>\n<li><strong>\u5909\u6570 (Variable): <\/strong>\u5e73\u6e96\u5316\u6570\u5f0f\u306b\u30dc\u30e9\u30c6\u30a3\u30ea\u30c6\u30a3\u6307\u6570\u304c\u8003\u616e\u3055\u308c\u305f\u6307\u6570\u79fb\u52d5\u5e73\u5747\u3002\u5909\u6570\u79fb\u52d5\u5e73\u5747 (Variable Moving average) \u306f\u3001\u30dc\u30e9\u30c6\u30a3\u30ea\u30c6\u30a3\u6307\u6570\u3068\u3057\u3066\u30b7\u30e3\u30f3\u30c7\u30fb\u30e2\u30e1\u30f3\u30bf\u30e0\u30fb\u30aa\u30b7\u30ec\u30fc\u30bf\u30fc\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/li>\n<li><strong>VIDYA: <\/strong>\u5e73\u6e96\u5316\u6570\u5f0f\u306b\u30dc\u30e9\u30c6\u30a3\u30ea\u30c6\u30a3\u6307\u6570\u304c\u8003\u616e\u3055\u308c\u305f\u6307\u6570\u79fb\u52d5\u5e73\u5747\u3002VIDYA \u79fb\u52d5\u5e73\u5747 (VIDYA Moving average) \u306f\u3001\u30dc\u30e9\u30c6\u30a3\u30ea\u30c6\u30a3\u6307\u6570\u3068\u3057\u3066\u6a19\u6e96\u504f\u5dee\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002(Volatility Index DYnamic Average).<\/li>\n<li><strong>\u52a0\u91cd\u5e73\u5747\u4fa1\u683c\u6307\u6a19 (Weighted): <\/strong>\u3088\u308a\u65b0\u3057\u3044\u30c7\u30fc\u30bf\u306f\u3001\u7b97\u8853\u7684\u306b\u3088\u308a\u52a0\u91cd\u3055\u308c\u3066\u3044\u307e\u3059\u3002<\/li>\n<li><strong>\u30a6\u30a7\u30eb\u30ba\u30fb\u30ef\u30a4\u30eb\u30c0\u30fc (Welles Wilder): <\/strong>\u6a19\u6e96\u6307\u6570\u79fb\u52d5\u5e73\u5747\u306f\u3001\u6570\u5f0f EMA% = 2\/(n + 1) \u3092\u4f7f\u3063\u3066\u3001\u6642\u9593\u306e\u671f\u9593\u3092\u5206\u6570\u306b\u5909\u63db\u3057\u307e\u3059\u3002n \u306f\u65e5\u6570\u3092\u793a\u3057\u307e\u3059\u3002\u4f8b\u3048\u3070\u300114\u65e5\u9593\u306e EMA% \u306f 2\/(14 \u65e5 +1) = 13.3% \u3068\u306a\u308a\u307e\u3059\u3002\u30ef\u30a4\u30eb\u30c0\u30fc\u306f\u30011\/14 (1\/n) \u306e EMA% \u3067\u30017.1% \u3092\u4f7f\u7528\u3057\u307e\u3059\u3002\u3053\u308c\u306f\u3001\u6a19\u6e96\u306e\u6570\u5f0f\u3092\u4f7f\u3046\u306827\u65e5\u306e\u6307\u6570\u79fb\u52d5\u5e73\u5747\u3068\u7b49\u3057\u304f\u306a\u308a\u307e\u3059\u3002<\/li>\n<li>Hull<\/li>\n<li>\u4e8c\u91cd\u6307\u6570\u79fb\u52d5\u5e73\u5747 (Double Exponential)<\/li>\n<li>\u4e09\u91cd\u6307\u6570\u79fb\u52d5\u5e73\u5747 (Triple Exponential)<\/li>\n<\/ul>\n<\/li>\n<li><strong>Offset<\/strong> (\u30aa\u30d5\u30bb\u30c3\u30c8):<\/li>\n<li><strong>Underlay<\/strong>: \u30c1\u30e3\u30fc\u30c8\u306e\u4e0b\u306b\u79fb\u52d5\u5e73\u5747\u3092\u8868\u793a\u3059\u308b\u304b\u3069\u3046\u304b\u3002<\/li>\n<li><strong>Color Selectors<\/strong> (\u914d\u8272\u30bb\u30ec\u30af\u30bf\u30fc): \u30b0\u30e9\u30d5\u8981\u7d20\u306b\u4f7f\u7528\u3059\u308b\u914d\u8272\u3002<\/li>\n<li><strong>Display Axis Label<\/strong> (\u8ef8\u30e9\u30d9\u30eb\u306e\u8868\u793a): Y \u8ef8\u306b\u6700\u65b0\u5024\u3092\u8868\u793a\u3059\u308b\u304b\u3069\u3046\u304b\u3002<\/li>\n<\/ul>\n<h2 id=\"formula\" class=\"Blurb\">\u6570\u5f0f<\/h2>\n<p class=\"BodyOther\">[Simple = MA = frac{sum_{i=1}^{n} Close_{i}}{n}]<\/p>\n<p class=\"BodyOther\">\n<p class=\"BodyOther\">[Exponential = EMA = (Close_{n} &#8211; EMA_{t-1}) times k + EMA_{n-1}]<\/p>\n<p class=\"BodyOther\">k = \u5e73\u6ed1\u5316\u5b9a\u6570\u3001( frac{2}{n+1}) \u3068\u540c\u7b49<\/p>\n<p class=\"BodyOther\">n = \u5358\u7d14\u79fb\u52d5\u5e73\u5747\u306e\u671f\u9593\u6570\u3067\u3001EMA \u306b\u3088\u308a\u307b\u307c\u8fd1\u4f3c<\/p>\n<p class=\"BodyOther\">\n<p class=\"BodyOther\">\n<p class=\"BodyOther\">[Time;Series = TSMA = frac{sum_{i=1}^{n} Close_{i}}{n}]<\/p>\n<p class=\"BodyOther\">\n<p class=\"BodyOther\">\n<p class=\"BodyOther\">[Triangular = TMA = frac{sum_{i=1}^{n} MA_{i}}{n} ]<\/p>\n<p class=\"BodyOther\">where (MA = frac{sum_{i=1}^{n} Close_{i}}{n} )<\/p>\n<p class=\"BodyOther\">\n<p class=\"BodyOther\">\n<p class=\"BodyOther\">[Variable = VMA = frac{P + (a times b)P1 + {(a times b)^2}P2 +&#8230;+{(a times b)^{(n-1)}}P(n-1)}{1 + (a times b) + (a times b)^2 +&#8230;+ (a times b)^{(n-1)}}]<\/p>\n<p class=\"BodyOther\">\n<p class=\"BodyOther\">\n<p class=\"BodyOther\">[Weighted = WMA = frac{n times P + {(n-1) times P1} + {(n-2) times P2} +&#8230;+ P(n-1)}{1 + 2 +3 + &#8230; +n}]+n}]<\/p>\n<p class=\"BodyOther\">\n<p class=\"BodyOther\">\n<p class=\"BodyOther\">[Welles;Wilder Smoothing = WWS_{n} = WWS_{n-1} &#8211; left ( frac{WWS_{n-1}}{n} right )+(Value_{n})]<\/p>\n<p class=\"BodyOther\">( WWS_{1} = frac{sum_{i=1}^{n} Close_{i}}{n})frac{sum_{i=1}^{n} Close_{i}}{n})<\/p>\n<p><!--\n<a name=\"Example\"><\/a>\n        \n\n<h5 class=\"Blurb\">Example<\/h5>\n\n\n\n\n<p class=\"\">\n          <img decoding=\"async\" src=\"\">\n         \n          <\/img>\n        <\/p>\n\n--><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u79fb\u52d5\u5e73\u5747\u306f\u7570\u306a\u3063\u305f\u30b5\u30d6\u30bb\u30c3\u30c8\u306e\u4e00\u9023\u306e\u5e73\u5747\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002\u5404\u65b0\u898f\u306e\u30b5\u30d6\u30bb\u30c3\u30c8\u306f\u3001\u65b0\u898f\u306e\u5024\u3092\u8ffd\u52a0\u3057\u3066\u53e4\u3044\u5024\u3092\u53d6\u308a\u9664\u304f\u3053\u3068\u3067\u3001\u4e00\u5b9a\u306e\u9577\u3055\u3092\u4fdd\u6301\u3057\u307e\u3059\u3002\u79fb\u52d5\u5e73\u5747\u306f\u3001N-\u671f\u9593\u306e\u30c7\u30fc\u30bf\u304c\u30e6\u30fc\u30b6\u30fc\u306b\u5b9a\u7fa9\u3055\u308c\u307e\u3059\u3002\u4ed6\u306e\u30c6\u30af\u30cb\u30ab\u30eb\u6307\u6a19\u306b\u52a0\u3048 [&hellip;]<\/p>\n","protected":false},"author":2,"template":"","meta":{"_acf_changed":false,"footnotes":""},"docs-category":[375],"class_list":["post-44135","doc","type-doc","status-publish","hentry","docs-category-technical-indicators"],"acf":[],"_links":{"self":[{"href":"https:\/\/library-staging.tradingtechnologies.com\/ja\/wp-json\/wp\/v2\/doc\/44135","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/library-staging.tradingtechnologies.com\/ja\/wp-json\/wp\/v2\/doc"}],"about":[{"href":"https:\/\/library-staging.tradingtechnologies.com\/ja\/wp-json\/wp\/v2\/types\/doc"}],"author":[{"embeddable":true,"href":"https:\/\/library-staging.tradingtechnologies.com\/ja\/wp-json\/wp\/v2\/users\/2"}],"version-history":[{"count":0,"href":"https:\/\/library-staging.tradingtechnologies.com\/ja\/wp-json\/wp\/v2\/doc\/44135\/revisions"}],"wp:attachment":[{"href":"https:\/\/library-staging.tradingtechnologies.com\/ja\/wp-json\/wp\/v2\/media?parent=44135"}],"wp:term":[{"taxonomy":"docs-category","embeddable":true,"href":"https:\/\/library-staging.tradingtechnologies.com\/ja\/wp-json\/wp\/v2\/docs-category?post=44135"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}