{"id":45511,"date":"2026-06-22T22:28:19","date_gmt":"2026-06-23T03:28:19","guid":{"rendered":"https:\/\/library-staging.tradingtechnologies.com\/doc\/keltner-channel-kc-2\/"},"modified":"2026-06-22T22:28:20","modified_gmt":"2026-06-23T03:28:20","slug":"keltner-channel-kc-2","status":"publish","type":"doc","link":"https:\/\/library-staging.tradingtechnologies.com\/ja\/keltner-channel-kc-2\/","title":{"rendered":"\u30b1\u30eb\u30c8\u30ca\u30fc \u30c1\u30e3\u30cd\u30eb (KC)"},"content":{"rendered":"<p class=\"BodyOther\">\u30b1\u30eb\u30c8\u30ca\u30fc \u30c1\u30e3\u30cd\u30eb (Keltner Channel) \u306f\u30011960\u5e74\u306b Chester W. Keltner \u306e\u8457\u66f8 \u300cHow To Make Money in Commodities\u300d (\u5546\u54c1\u5148\u7269\u3067\u5132\u3051\u308b\u65b9\u6cd5) \u306b\u3066\u7d39\u4ecb\u3055\u308c\u307e\u3057\u305f\u3002\u307e\u305f\u30da\u30ea\u30fc\uff65\u30ab\u30a6\u30d5\u30de\u30f3 (Perry Kaufman) \u306e\u8457\u66f8\u300cThe New Commodity Trading Systems and Methods\u300d (\u30cb\u30e5\u30fc \u30c8\u30ec\u30fc\u30c7\u30a3\u30f3\u30b0 \u30b7\u30b9\u30c6\u30e0 \u30a2\u30f3\u30c9 \u30e1\u30bd\u30c3\u30c9) \u3067\u3082\u89e3\u8aac\u3055\u308c\u3066\u3044\u307e\u3059\u3002\u30b1\u30eb\u30c8\u30ca\u30fc \u30c1\u30e3\u30cd\u30eb\u306f\u3001\u5358\u7d14\u79fb\u52d5\u5e73\u5747 (\u901a\u5e38\u3001\u9ad8\u30fb\u5b89\u30fb\u7d42\u5024\u306e\u5e73\u5747\u5024\u306e\u79fb\u52d5\u5e73\u5747) \u3068 \u3001\u3053\u306e\u79fb\u52d5\u5e73\u5747\u7dda\u306e\u4e0a\u4e0b\u306b\u63cf\u753b\u3055\u308c\u305f\u30d0\u30f3\u30c9\u306e\u30013\u672c\u306e\u7dda\u3067\u69cb\u6210\u3055\u308c\u3066\u3044\u307e\u3059\u3002\u30d0\u30f3\u30c9\u5e45\u306f <a href=\"chrt-ti-average-true-range.html\">\u30a2\u30d9\u30ec\u30fc\u30b8 \u30c8\u30a5\u30eb\u30fc \u30ec\u30f3\u30b8<\/a> \u306b\u4efb\u610f\u306e\u4e57\u6570\u3092\u9069\u7528\u3057\u305f\u3082\u306e\u3067\u3001\u3053\u306e\u7d50\u679c\u3092\u4e2d\u592e\u306e\u79fb\u52d5\u5e73\u5747\u7dda\u306b\u3001\u8db3\u3057\u5f15\u304d\u3057\u3066\u63cf\u7dda\u3057\u307e\u3059\u3002<\/p>\n<p>\u4fa1\u683c\u304c\u30c1\u30e3\u30cd\u30eb\u7dda\u3092\u8d8a\u3048\u308b\u3068\u3001\u5e02\u5834\u306e\u65b9\u5411\u306b\u57fa\u3065\u3044\u3066\u3001\u3042\u308b\u7a2e\u306e\u5909\u5316\u304c\u767a\u751f\u3057\u3066\u3044\u308b\u3053\u3068\u3092\u793a\u3057\u307e\u3059\u3002<\/p>\n<ul>\n<li>\u4e0d\u6d3b\u767a\u306a\u5e02\u5834\u3067\u306f\u3001\u30d0\u30f3\u30c9\u3092\u8d85\u904e\u3059\u308b\u3068\u3001\u904e\u5270\u58f2\u308a\u306e\u5e02\u6cc1\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/li>\n<li>\u9ad8\u9a30\u5e02\u6cc1\u3067\u306f\u3001\u4e0a\u90e8\u306e\u5883\u754c\u7dda\u3092\u8d8a\u3048\u308b\u3068\u30d6\u30ec\u30a4\u30af\u30a2\u30a6\u30c8\u306e\u53ef\u80fd\u6027\u3092\u793a\u3057\u307e\u3059\u3002<\/li>\n<li>\u4e0b\u964d\u5e02\u5834\u3067\u306f\u3001\u4e0b\u90e8\u306e\u5883\u754c\u7dda\u3092\u8d8a\u3048\u308b\u3068\u3001\u3042\u308b\u7a2e\u306e\u5e02\u5834\u306e\u5f31\u307f\u3092\u793a\u3057\u307e\u3059\u3002<\/li>\n<li>\n<\/ul>\n<p><!--\n\n\n<p>Keltner Channels are very similar to <a href=\"chrt-ti-bollinger-bands.html\">Bollinger Bands<\/a> but determine width based on Average True Range instead of standard deviation. This presents a smoother channel because the latter is more volatile. Many consider this a positive because it creates a more constant width. The standard formula for Keltner uses an exponential average, which is faster than a simple average, although both indicators are able to substitute any average type.<\/p>\n\n\n\n\n\n<p>Channels and bands are designed to contain most trading. Therefore, moves above or below the channel lines suggest a change is happening. In flat markets, touches of the bands can indicate overbought and oversold condition. If prices move above the upper band it may be a breakout signal. In rising market, it is not uncommon to see prices spend time above the bands but in this case it is a sign of strength. Conversely, in a --> \u4e0b\u964d\u5e02\u5834\u3067\u306f\u3001\u30d0\u30f3\u30c9\u306e\u4e0b\u306e\u8a71\u6642\u9593\u306f\u5f31\u307f\u306e\u30b5\u30a4\u30f3\u3067\u3059\u3002<\/p>\n<p><img decoding=\"async\" class=\"img-responsive\" src=\"https:\/\/library-staging.tradingtechnologies.com\/wp-content\/uploads\/2026\/06\/keltner-channel-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\/keltner-channel-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><strong>Shift<\/strong> (\u30b7\u30d5\u30c8): \u30d0\u30f3\u30c9\u3092\u63cf\u753b\u3059\u308b\u79fb\u52d5\u5e73\u5747\u3088\u308a\u4e0a\u3068\u4e0b\u306e\u30a2\u30d9\u30ec\u30fc\u30b8 \u30c8\u30a5\u30eb\u30fc \u30ec\u30f3\u30b8\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>Channel Fill<\/strong> (\u30c1\u30e3\u30cd\u30eb \u30d5\u30a3\u30eb): \u4e0a\u90e8\u30d0\u30f3\u30c9\u3068\u4e0b\u90e8\u30d0\u30f3\u30c9\u9593\u306e\u90e8\u5206\u3092\u7db2\u639b\u3051\u8868\u793a\u3059\u308b\u304b\u3069\u3046\u304b\u3092\u6c7a\u5b9a\u3057\u307e\u3059\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<p><a name=\"Formula\"><\/a><\/p>\n<h2 class=\"Blurb\">\u6570\u5f0f<\/h2>\n<p class=\"BodyOther\">[\u4e2d\u592e\u7dda = MA_{n};of frac{(\u9ad8\u5024 + \u5b89\u5024 + \u7d42\u5024)}{3}]<\/p>\n<p class=\"BodyOther\">[\u4e0a\u90e8\u30d0\u30f3\u30c9 = \u4e2d\u592e\u7dda + ( y * ATR)]<\/p>\n<p class=\"BodyOther\">[\u4e0b\u90e8\u30d0\u30f3\u30c9 = \u4e2d\u592e\u7dda &#8211; ( y * ATR)]<\/p>\n<p class=\"BodyChapterLevel\">\u5834\u6240:<\/p>\n<p>[MA_{n} = User;defined;moving;average;of;n-periods] [y = Shift = factor;applied;to;the;ATR] [ATR = Average;True;Range;of;n-period] <!--\n<a name=\"Example\"><\/a>\n        \n\n<h5 class=\"Blurb\">Example<\/h5>\n\n\n\n\n<p class=\"BodyOther\">\n          <img decoding=\"async\" src=\"Content\/Technical_Indicator_Definitions165.jpg\">\n            \n          <\/img>\n        <\/p>\n\n--><\/p>\n","protected":false},"excerpt":{"rendered":"<p class=\"BodyOther\">\u30b1\u30eb\u30c8\u30ca\u30fc \u30c1\u30e3\u30cd\u30eb (Keltner Channel) \u306f\u30011960\u5e74\u306b Chester W. Keltner \u306e\u8457\u66f8 \u300cHow To Make Money in Commodities\u300d (\u5546\u54c1\u5148\u7269\u3067\u5132\u3051\u308b\u65b9\u6cd5) \u306b\u3066\u7d39\u4ecb\u3055\u308c\u307e\u3057\u305f\u3002\u307e\u305f\u30da\u30ea\u30fc\uff65\u30ab\u30a6\u30d5\u30de\u30f3 (Perry Kaufman) \u306e\u8457\u66f8\u300cThe New Commodity Trading Systems and Methods\u300d (\u30cb\u30e5\u30fc \u30c8\u30ec\u30fc\u30c7\u30a3\u30f3\u30b0 \u30b7\u30b9\u30c6\u30e0 \u30a2\u30f3\u30c9 \u30e1\u30bd\u30c3\u30c9) \u3067\u3082\u89e3\u8aac\u3055\u308c\u3066\u3044\u307e\u3059\u3002\u30b1\u30eb\u30c8\u30ca\u30fc \u30c1\u30e3\u30cd\u30eb\u306f\u3001\u5358\u7d14\u79fb\u52d5\u5e73\u5747 (\u901a\u5e38\u3001\u9ad8\u30fb\u5b89\u30fb\u7d42\u5024\u306e\u5e73\u5747\u5024\u306e\u79fb\u52d5\u5e73\u5747) \u3068 \u3001\u3053\u306e\u79fb\u52d5\u5e73\u5747\u7dda\u306e\u4e0a\u4e0b\u306b\u63cf\u753b\u3055\u308c\u305f\u30d0\u30f3\u30c9\u306e\u30013\u672c\u306e\u7dda\u3067\u69cb\u6210\u3055\u308c\u3066\u3044\u307e\u3059\u3002\u30d0\u30f3\u30c9\u5e45\u306f <a href=\"chrt-ti-average-true-range.html\">\u30a2\u30d9\u30ec\u30fc\u30b8 \u30c8\u30a5\u30eb\u30fc \u30ec\u30f3\u30b8<\/a> \u306b\u4efb\u610f\u306e\u4e57\u6570\u3092\u9069\u7528\u3057\u305f\u3082\u306e\u3067\u3001\u3053\u306e\u7d50\u679c\u3092\u4e2d\u592e\u306e\u79fb\u52d5\u5e73\u5747\u7dda\u306b\u3001\u8db3\u3057\u5f15\u304d\u3057\u3066\u63cf\u7dda\u3057\u307e\u3059\u3002<\/p>\n<p>\u4fa1\u683c\u304c\u30c1\u30e3\u30cd\u30eb\u7dda\u3092\u8d8a\u3048\u308b\u3068\u3001\u5e02\u5834\u306e\u65b9\u5411\u306b\u57fa\u3065\u3044\u3066\u3001\u3042\u308b\u7a2e\u306e\u5909\u5316\u304c\u767a\u751f\u3057\u3066\u3044\u308b\u3053\u3068\u3092\u793a\u3057\u307e\u3059\u3002<\/p>\n<ul>\n<li>\u4e0d\u6d3b\u767a\u306a\u5e02\u5834\u3067\u306f\u3001\u30d0\u30f3\u30c9\u3092\u8d85\u904e\u3059\u308b\u3068\u3001\u904e\u5270\u58f2\u308a\u306e\u5e02\u6cc1\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/li>\n<li>\u9ad8\u9a30\u5e02\u6cc1\u3067\u306f\u3001\u4e0a\u90e8\u306e\u5883\u754c\u7dda\u3092\u8d8a\u3048\u308b\u3068\u30d6\u30ec\u30a4\u30af\u30a2\u30a6\u30c8\u306e\u53ef\u80fd\u6027\u3092\u793a\u3057\u307e\u3059\u3002<\/li>\n<li>\u4e0b\u964d\u5e02\u5834\u3067\u306f\u3001\u4e0b\u90e8\u306e\u5883\u754c\u7dda\u3092\u8d8a\u3048\u308b\u3068\u3001\u3042\u308b\u7a2e\u306e\u5e02\u5834\u306e\u5f31\u307f\u3092\u793a\u3057\u307e\u3059\u3002<\/li>\n<li>\n<\/ul>\n<p><!--\n\n\n\n\n<p>Keltner Channels are very similar to <a href=\"chrt-ti-bollinger-bands.html\">Bollinger Bands<\/a> but determine width based on Average True Range instead of standard deviation. This presents a smoother channel because the latter is more volatile. Many consider this a positive because it creates a more constant width. The standard formula for Keltner uses an exponential average, which is faster than a simple average, although both indicators are able to substitute any average type.<\/p>\n\n\n\n\n\n\n\n\n\n<p>Channels and bands are designed to contain most trading. Therefore, moves above or below the channel lines suggest a change is happening. In flat markets, touches of the bands can indicate overbought and oversold condition. If prices move above the upper band it may be a breakout signal. In rising market, it is not uncommon to see prices spend time above the bands but in this case it is a sign of strength. Conversely, in a --> \u4e0b\u964d\u5e02\u5834\u3067\u306f\u3001\u30d0\u30f3\u30c9\u306e\u4e0b\u306e\u8a71\u6642\u9593\u306f\u5f31\u307f\u306e\u30b5\u30a4\u30f3\u3067\u3059\u3002<\/p>\n<p><img decoding=\"async\" class=\"img-responsive\" src=\"https:\/\/library-staging.tradingtechnologies.com\/wp-content\/uploads\/2026\/06\/keltner-channel-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\/keltner-channel-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><strong>Shift<\/strong> (\u30b7\u30d5\u30c8): \u30d0\u30f3\u30c9\u3092\u63cf\u753b\u3059\u308b\u79fb\u52d5\u5e73\u5747\u3088\u308a\u4e0a\u3068\u4e0b\u306e\u30a2\u30d9\u30ec\u30fc\u30b8 \u30c8\u30a5\u30eb\u30fc \u30ec\u30f3\u30b8\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>Channel Fill<\/strong> (\u30c1\u30e3\u30cd\u30eb \u30d5\u30a3\u30eb): \u4e0a\u90e8\u30d0\u30f3\u30c9\u3068\u4e0b\u90e8\u30d0\u30f3\u30c9\u9593\u306e\u90e8\u5206\u3092\u7db2\u639b\u3051\u8868\u793a\u3059\u308b\u304b\u3069\u3046\u304b\u3092\u6c7a\u5b9a\u3057\u307e\u3059\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<p><a name=\"Formula\"><\/a><\/p>\n<h2 class=\"Blurb\">\u6570\u5f0f<\/h2>\n<p class=\"BodyOther\">[\u4e2d\u592e\u7dda = MA_{n};of frac{(\u9ad8\u5024 + \u5b89\u5024 + \u7d42\u5024)}{3}]<\/p>\n<p class=\"BodyOther\">[\u4e0a\u90e8\u30d0\u30f3\u30c9 = \u4e2d\u592e\u7dda + ( y * ATR)]<\/p>\n<p class=\"BodyOther\">[\u4e0b\u90e8\u30d0\u30f3\u30c9 = \u4e2d\u592e\u7dda &#8211; ( y * ATR)]<\/p>\n<p class=\"BodyChapterLevel\">\u5834\u6240:<\/p>\n<p>[MA_{n} = User;defined;moving;average;of;n-periods] [y = Shift = factor;applied;to;the;ATR] [ATR = Average;True;Range;of;n-period] <!--\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=\"BodyOther\">\n          <img decoding=\"async\" src=\"Content\/Technical_Indicator_Definitions165.jpg\">\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-45511","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\/45511","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\/45511\/revisions"}],"wp:attachment":[{"href":"https:\/\/library-staging.tradingtechnologies.com\/ja\/wp-json\/wp\/v2\/media?parent=45511"}],"wp:term":[{"taxonomy":"docs-category","embeddable":true,"href":"https:\/\/library-staging.tradingtechnologies.com\/ja\/wp-json\/wp\/v2\/docs-category?post=45511"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}