{"id":45466,"date":"2026-06-22T22:27:34","date_gmt":"2026-06-23T03:27:34","guid":{"rendered":"https:\/\/library-staging.tradingtechnologies.com\/doc\/ease-of-movement-eom-2\/"},"modified":"2026-06-22T22:27:34","modified_gmt":"2026-06-23T03:27:34","slug":"ease-of-movement-eom-2","status":"publish","type":"doc","link":"https:\/\/library-staging.tradingtechnologies.com\/ja\/ease-of-movement-eom-2\/","title":{"rendered":"\u30a4\u30fc\u30ba \u30aa\u30d6 \u30e0\u30fc\u30d6\u30e1\u30f3\u30c8 (EOM)"},"content":{"rendered":"<p class=\"BodyOther\">\u30ea\u30c1\u30e3\u30fc\u30c9\u30fbW\u30fb\u30a2\u30fc\u30e0\u30ba\u30fbJr (Richard W. Arms, Jr.) \u304c\u8003\u6848\u3057\u305f \u30a4\u30fc\u30ba \u30aa\u30d6 \u30e0\u30fc\u30d6\u30e1\u30f3\u30c8 (EOM\u3001Ease of Movement) \u6307\u6a19\u306f\u3001\u4fa1\u683c\u306e\u5909\u5316\u3068\u51fa\u6765\u9ad8\u3092\u95a2\u9023\u4ed8\u3051\u307e\u3059\u3002\u3053\u308c\u306f\u30c8\u30ec\u30f3\u30c9\u306e\u529b\u3092\u8a55\u4fa1\u3059\u308b\u969b\u306b\u7279\u306b\u4fbf\u5229\u3067\u3059\u3002\u6b63\u306e\u9ad8\u5024\u306f\u4fa1\u683c\u304c\u4f4e\u51fa\u6765\u9ad8\u3067\u5897\u52a0\u3057\u3064\u3064\u3042\u308b\u306e\u3092\u793a\u3057\u3001\u5f37\u3044\u8ca0\u306e\u5024\u306f\u4fa1\u683c\u304c\u4f4e\u51fa\u6765\u9ad8\u3067\u843d\u3061\u3064\u3064\u3042\u308b\u3053\u3068\u3092\u793a\u3057\u307e\u3059\u3002<\/p>\n<p><img decoding=\"async\" class=\"img-responsive\" src=\"https:\/\/library-staging.tradingtechnologies.com\/wp-content\/uploads\/2026\/06\/ease-of-movement-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\/ease-of-movement-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>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><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<p><a name=\"Formula\"><\/a><\/p>\n<h2 class=\"Blurb\">\u6570\u5f0f<\/h2>\n<p class=\"BodyOther\">\u4ee5\u4e0b\u306e4\u3064\u306e\u8a08\u7b97\u306f\u3001\u30a4\u30fc\u30ba \u30aa\u30d6 \u30e0\u30fc\u30d6\u30e1\u30f3\u30c8\u6307\u6a19\u306b\u5fc5\u8981\u3067\u3059\u3002<\/p>\n<p class=\"BodyChapterLevel\">[Distance;Moved = DM = left(frac{High_{current} &#8211; Low_{current}}{2}right) &#8211; left(frac{High_{previous} &#8211; Low_{previous}}{2}right) ]<\/p>\n<p class=\"BodyChapterLevel\">[Box Ratio = BR = left(frac{frac{Volume_{current}}{1,000,000,000}}{High_{current} &#8211; Low_{current}}right) ]<\/p>\n<p class=\"BodyOther\">1\u671f\u9593\u306e EOM \u3092\u8a08\u7b97:<\/p>\n<p class=\"BodyOther\">[EOM_{1} = frac{DM}{BR}]<\/p>\n<p class=\"BodyChapterLevel\">\u79fb\u52d5\u5e73\u5747\u3092\u8a08\u7b97\u3057\u307e\u3059\u3002\u3053\u3053\u3067\u30e6\u30fc\u30b6\u30fc\u306f\u591a\u69d8\u306a\u79fb\u52d5\u5e73\u5747\u30bf\u30a4\u30d7\u304b\u3089\u9078\u629e\u3067\u304d\u307e\u3059\u3002<\/p>\n<p class=\"BodyChapterLevel\">[EOM_{n-period MA} = MA(EOM_{1})]<\/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 class=\"BodyOther\">\u30ea\u30c1\u30e3\u30fc\u30c9\u30fbW\u30fb\u30a2\u30fc\u30e0\u30ba\u30fbJr (Richard W. Arms, Jr.) \u304c\u8003\u6848\u3057\u305f \u30a4\u30fc\u30ba \u30aa\u30d6 \u30e0\u30fc\u30d6\u30e1\u30f3\u30c8 (EOM\u3001Ease of Movement) \u6307\u6a19\u306f\u3001\u4fa1\u683c\u306e\u5909\u5316\u3068\u51fa\u6765\u9ad8\u3092\u95a2\u9023\u4ed8\u3051\u307e\u3059\u3002\u3053\u308c\u306f\u30c8\u30ec\u30f3\u30c9\u306e\u529b\u3092\u8a55\u4fa1\u3059\u308b\u969b\u306b\u7279\u306b\u4fbf\u5229\u3067\u3059\u3002\u6b63\u306e\u9ad8\u5024\u306f\u4fa1\u683c\u304c\u4f4e\u51fa\u6765\u9ad8\u3067\u5897\u52a0\u3057\u3064\u3064\u3042\u308b\u306e\u3092\u793a\u3057\u3001\u5f37\u3044\u8ca0\u306e\u5024\u306f\u4fa1\u683c\u304c\u4f4e\u51fa\u6765\u9ad8\u3067\u843d\u3061\u3064\u3064\u3042\u308b\u3053\u3068\u3092\u793a\u3057\u307e\u3059\u3002<\/p>\n<p><img decoding=\"async\" class=\"img-responsive\" src=\"https:\/\/library-staging.tradingtechnologies.com\/wp-content\/uploads\/2026\/06\/ease-of-movement-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\/ease-of-movement-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>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><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<p><a name=\"Formula\"><\/a><\/p>\n<h2 class=\"Blurb\">\u6570\u5f0f<\/h2>\n<p class=\"BodyOther\">\u4ee5\u4e0b\u306e4\u3064\u306e\u8a08\u7b97\u306f\u3001\u30a4\u30fc\u30ba \u30aa\u30d6 \u30e0\u30fc\u30d6\u30e1\u30f3\u30c8\u6307\u6a19\u306b\u5fc5\u8981\u3067\u3059\u3002<\/p>\n<p class=\"BodyChapterLevel\">[Distance;Moved = DM = left(frac{High_{current} &#8211; Low_{current}}{2}right) &#8211; left(frac{High_{previous} &#8211; Low_{previous}}{2}right) ]<\/p>\n<p class=\"BodyChapterLevel\">[Box Ratio = BR = left(frac{frac{Volume_{current}}{1,000,000,000}}{High_{current} &#8211; Low_{current}}right) ]<\/p>\n<p class=\"BodyOther\">1\u671f\u9593\u306e EOM \u3092\u8a08\u7b97:<\/p>\n<p class=\"BodyOther\">[EOM_{1} = frac{DM}{BR}]<\/p>\n<p class=\"BodyChapterLevel\">\u79fb\u52d5\u5e73\u5747\u3092\u8a08\u7b97\u3057\u307e\u3059\u3002\u3053\u3053\u3067\u30e6\u30fc\u30b6\u30fc\u306f\u591a\u69d8\u306a\u79fb\u52d5\u5e73\u5747\u30bf\u30a4\u30d7\u304b\u3089\u9078\u629e\u3067\u304d\u307e\u3059\u3002<\/p>\n<p class=\"BodyChapterLevel\">[EOM_{n-period MA} = MA(EOM_{1})]<\/p>\n<p><!--\n<a name=\"Example\"><\/a>\n        \n\n\n\n<h5 class=\"Blurb\">Example<\/h5>\n\n\n\n\n\n\n\n\n<p class=\"\">\n          <img decoding=\"async\" src=\"\">\n           \n          <\/img>\n        <\/p>\n\n\n\n--><\/p>\n","protected":false},"author":2,"template":"","meta":{"_acf_changed":false,"footnotes":""},"docs-category":[375],"class_list":["post-45466","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\/45466","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\/45466\/revisions"}],"wp:attachment":[{"href":"https:\/\/library-staging.tradingtechnologies.com\/ja\/wp-json\/wp\/v2\/media?parent=45466"}],"wp:term":[{"taxonomy":"docs-category","embeddable":true,"href":"https:\/\/library-staging.tradingtechnologies.com\/ja\/wp-json\/wp\/v2\/docs-category?post=45466"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}