{"payload":{"feedbackUrl":"https://github.com/orgs/community/discussions/53140","repo":{"id":60466577,"defaultBranch":"master","name":"stockstats","ownerLogin":"jealous","currentUserCanPush":false,"isFork":false,"isEmpty":false,"createdAt":"2016-06-05T15:21:22.000Z","ownerAvatar":"https://avatars.githubusercontent.com/u/1789979?v=4","public":true,"private":false,"isOrgOwned":false},"refInfo":{"name":"","listCacheKey":"v0:1690700791.0","currentOid":""},"activityList":{"items":[{"before":"9cb82d7b3c48432a2d5628590013751551ea94c4","after":"8b76182772630b95588f29bd0ae72092795a43c6","ref":"refs/heads/master","pushedAt":"2024-01-05T18:00:58.000Z","pushType":"pr_merge","commitsCount":1,"pusher":{"login":"jealous","name":"Cedric Zhuang","path":"/jealous","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/1789979?s=80&v=4"},"commit":{"message":"Numerical comparison implemented (#184)\n\n* Compare implemented\r\n\r\n* Update stockstats.py\r\n\r\n* Formatting improved\r\n\r\n* Update stockstats.py","shortMessageHtmlLink":"Numerical comparison implemented (#184)"}},{"before":"73d830afcfe6520eab1baa0d92375d93e8f6232b","after":null,"ref":"refs/heads/bugfix/zScoreFirst","pushedAt":"2023-07-30T07:06:03.000Z","pushType":"branch_deletion","commitsCount":0,"pusher":{"login":"jealous","name":"Cedric Zhuang","path":"/jealous","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/1789979?s=80&v=4"}},{"before":"37ae9c131ec0182652412f19f0b8920fae8927ea","after":"9cb82d7b3c48432a2d5628590013751551ea94c4","ref":"refs/heads/master","pushedAt":"2023-07-30T07:05:58.000Z","pushType":"pr_merge","commitsCount":1,"pusher":{"login":"jealous","name":"Cedric Zhuang","path":"/jealous","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/1789979?s=80&v=4"},"commit":{"message":"[GH-175] z-score based kdj is invalid. 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These trailing\r\nstop lines are composed of a fast and a slow moving Average True Range (ATR).\r\nThese ATR lines are smoothed making this indicator less susceptible to short\r\nterm volatility.\r\n\r\nhttps://www.tradingview.com/script/0vn4HZ7O-Quantitative-Qualitative-Estimation-QQE/\r\n\r\nImplementation reference:\r\nhttps://github.com/twopirllc/pandas-ta/blob/main/pandas_ta/momentum/qqe.py\r\n\r\nExample:\r\n* `df['qqe']` retrieves the QQE with RSI window 14, MA window 5.\r\n* `df['qqel']` retrieves the QQE long\r\n* `df['qqes']` retrieves the QQE short\r\n* `df['qqe_10,4']` retrieves the QQE with RSI window 10, MA window 4\r\n* `df['qqel_10,4']` retrieves the QQE long with customized windows.\r\n Initialized by retrieving `df['qqe_10,4']`\r\n* `df['qqes_10,4']` retrieves the QQE short with customized windows\r\n Initialized by retrieving `df['qqe_10,4']`\r\n\r\nThe period of short, long EMA and signal line can be tuned with\r\n`set_dft_window('qqe', (rsi, rsi_ma))`. 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These trailing\nstop lines are composed of a fast and a slow moving Average True Range (ATR).\nThese ATR lines are smoothed making this indicator less susceptible to short\nterm volatility.\n\nhttps://www.tradingview.com/script/0vn4HZ7O-Quantitative-Qualitative-Estimation-QQE/\n\nImplementation reference:\nhttps://github.com/twopirllc/pandas-ta/blob/main/pandas_ta/momentum/qqe.py\n\nExample:\n* `df['qqe']` retrieves the QQE with RSI window 14, MA window 5.\n* `df['qqel']` retrieves the QQE long\n* `df['qqes']` retrieves the QQE short\n* `df['qqe_10,4']` retrieves the QQE with RSI window 10, MA window 4\n* `df['qqel_10,4']` retrieves the QQE long with customized windows.\n Initialized by retrieving `df['qqe_10,4']`\n* `df['qqes_10,4']` retrieves the QQE short with customized windows\n Initialized by retrieving `df['qqe_10,4']`\n\nThe period of short, long EMA and signal line can be tuned with\n`set_dft_window('qqe', (rsi, rsi_ma))`. 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These trailing\nstop lines are composed of a fast and a slow moving Average True Range (ATR).\nThese ATR lines are smoothed making this indicator less susceptible to short\nterm volatility.\n\nhttps://www.tradingview.com/script/0vn4HZ7O-Quantitative-Qualitative-Estimation-QQE/\n\nImplementation reference:\nhttps://github.com/twopirllc/pandas-ta/blob/main/pandas_ta/momentum/qqe.py\n\nExample:\n* `df['qqe']` retrieves the QQE with RSI window 14, MA window 5.\n* `df['qqel']` retrieves the QQE long\n* `df['qqes']` retrieves the QQE short\n* `df['qqe_10,4']` retrieves the QQE with RSI window 10, MA window 4\n* `df['qqel_10,4']` retrieves the QQE long with customized windows.\n Initialized by retrieving `df['qqe_10,4']`\n* `df['qqes_10,4']` retrieves the QQE short with customized windows\n Initialized by retrieving `df['qqe_10,4']`\n\nThe period of short, long EMA and signal line can be tuned with\n`set_dft_window('qqe', (rsi, rsi_ma))`. 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These trailing\nstop lines are composed of a fast and a slow moving Average True Range (ATR).\nThese ATR lines are smoothed making this indicator less susceptible to short\nterm volatility.\n\nhttps://www.tradingview.com/script/0vn4HZ7O-Quantitative-Qualitative-Estimation-QQE/\n\nImplementation reference:\nhttps://github.com/twopirllc/pandas-ta/blob/main/pandas_ta/momentum/qqe.py\n\nExample:\n* `df['qqe']` retrieves the QQE with RSI window 14, MA window 5.\n* `df['qqel']` retrieves the QQE long\n* `df['qqes']` retrieves the QQE short\n* `df['qqe_10,4']` retrieves the QQE with RSI window 10, MA window 4\n* `df['qqel_10,4']` retrieves the QQE long with customized windows.\n Initialized by retrieving `df['qqe_10,4']`\n* `df['qqes_10,4']` retrieves the QQE short with customized windows\n Initialized by retrieving `df['qqe_10,4']`\n\nThe period of short, long EMA and signal line can be tuned with\n`set_dft_window('qqe', (rsi, rsi_ma))`. 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These trailing\nstop lines are composed of a fast and a slow moving Average True Range (ATR).\nThese ATR lines are smoothed making this indicator less susceptible to short\nterm volatility.\n\nImplementation reference:\nhttps://github.com/twopirllc/pandas-ta/blob/main/pandas_ta/momentum/qqe.py\n\nExample:\n* `df['qqe']` retrieves the QQE with RSI window 14, MA window 5.\n* `df['qqel']` retrieves the QQE long\n* `df['qqes']` retrieves the QQE short\n* `df['qqe_10,4']` retrieves the QQE with RSI window 10, MA window 4\n* `df['qqel_10,4']` retrieves the QQE long with customized windows.\n Initialized by retrieving `df['qqe_10,4']`\n* `df['qqes_10,4']` retrieves the QQE short with customized windows\n Initialized by retrieving `df['qqe_10,4']`\n\nThe period of short, long EMA and signal line can be tuned with\n`set_dft_window('qqe', (rsi, rsi_ma))`. 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These trailing\nstop lines are composed of a fast and a slow moving Average True Range (ATR).\nThese ATR lines are smoothed making this indicator less susceptible to short\nterm volatility.\n\nImplementation reference:\nhttps://github.com/twopirllc/pandas-ta/blob/main/pandas_ta/momentum/qqe.py\n\nExample:\n* `df['qqe']` retrieves the QQE with RSI window 14, MA window 5.\n* `df['qqel']` retrieves the QQE long\n* `df['qqes']` retrieves the QQE short\n* `df['qqe_10,4']` retrieves the QQE with RSI window 10, MA window 4\n* `df['qqel_10,4']` retrieves the QQE long with customized windows.\n Initialized by retrieving `df['qqe_10,4']`\n* `df['qqes_10,4']` retrieves the QQE short with customized windows\n Initialized by retrieving `df['qqe_10,4']`\n\nThe period of short, long EMA and signal line can be tuned with\n`set_dft_window('qqe', (rsi, rsi_ma))`. 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larger moving average.\n\nhttps://school.stockcharts.com/doku.php?id=technical_indicators:percentage_volume_oscillator_pvo\n\nFormular:\n\n* Percentage Volume Oscillator (PVO):\n ((12-day EMA of Volume - 26-day EMA of Volume)/26-day EMA of Volume) x 100\n* Signal Line: 9-day EMA of PVO\n* PVO Histogram: PVO - Signal Line","shortMessageHtmlLink":"[GH-171] Add support for PVO"}},{"before":null,"after":"ccb635e52b93af232a9e70818605933f70580252","ref":"refs/heads/feature/pvo","pushedAt":"2023-07-10T12:55:47.000Z","pushType":"branch_creation","commitsCount":0,"pusher":{"login":"jealous","name":"Cedric Zhuang","path":"/jealous","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/1789979?s=80&v=4"},"commit":{"message":"[GH-171] Add support for PVO\n\nThe Percentage Volume Oscillator (PVO) is a momentum oscillator for volume.\nThe PVO measures the difference between two volume-based moving averages as\na percentage of the larger moving 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with window 10.","shortMessageHtmlLink":"[GH-167] Add Pretty Good Oscillator Support (#168)"}},{"before":null,"after":"ba9d805346ac18978a6500aaba161284d8010885","ref":"refs/heads/feature/pgo","pushedAt":"2023-07-08T15:07:47.000Z","pushType":"branch_creation","commitsCount":0,"pusher":{"login":"jealous","name":"Cedric Zhuang","path":"/jealous","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/1789979?s=80&v=4"},"commit":{"message":"[GH-167] Add Pretty Good Oscillator Support\n\nThe Pretty Good Oscillator indicator by Mark Johnson measures the\ndistance of the current close from its N-day simple moving average,\nexpressed in terms of an average true range over a similar period.\n\nhttps://library.tradingtechnologies.com/trade/chrt-ti-pretty-good-oscillator.html\n\nFormular:\n* PGO = (Close - SMA) / (EMA of TR)\n\nExample:\n* `df['pgo']` retrieves the PGO with default window 14.\n* `df['pgo_10']` retrieves the PGO with window 10.","shortMessageHtmlLink":"[GH-167] Add Pretty Good Oscillator Support"}},{"before":"cc97f7437517bc09a7d19a59c854fd75c911c9fd","after":null,"ref":"refs/heads/feature/kst","pushedAt":"2023-07-08T14:49:24.000Z","pushType":"branch_deletion","commitsCount":0,"pusher":{"login":"jealous","name":"Cedric Zhuang","path":"/jealous","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/1789979?s=80&v=4"}},{"before":"febcde6624a5143e817238aef6f0e40e6679b35a","after":"31d5d46dde5cebd0d0f662993f3bf8b6de602e8a","ref":"refs/heads/master","pushedAt":"2023-07-08T14:49:21.000Z","pushType":"pr_merge","commitsCount":1,"pusher":{"login":"jealous","name":"Cedric Zhuang","path":"/jealous","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/1789979?s=80&v=4"},"commit":{"message":"[GH-165] Add Know Sure Thing support (#166)\n\nThe Know Sure Thing (KST) is a momentum oscillator developed by\r\nMartin Pring to make rate-of-change readings easier for traders\r\nto interpret.\r\n\r\nhttps://www.investopedia.com/terms/k/know-sure-thing-kst.asp\r\n\r\nFormular:\r\n* KST=(RCMA1×1)+(RCMA2×2) + (RCMA3×3)+(RCMA4×4)\r\n\r\nWhere:\r\n* RCMA1=10-period SMA of 10-period ROC\r\n* RCMA2=10-period SMA of 15-period ROC\r\n* RCMA3=10-period SMA of 20-period ROC\r\n* RCMA4=15-period SMA of 30-period ROC","shortMessageHtmlLink":"[GH-165] Add Know Sure Thing support (#166)"}},{"before":"9521c798f787e56b7208910d853d0bc3bc1b4884","after":"cc97f7437517bc09a7d19a59c854fd75c911c9fd","ref":"refs/heads/feature/kst","pushedAt":"2023-07-08T14:46:55.000Z","pushType":"force_push","commitsCount":0,"pusher":{"login":"jealous","name":"Cedric Zhuang","path":"/jealous","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/1789979?s=80&v=4"},"commit":{"message":"[GH-165] Add Know Sure Thing support\n\nThe Know Sure Thing (KST) is a momentum oscillator developed by\nMartin Pring to make rate-of-change readings easier for traders\nto interpret.\n\nhttps://www.investopedia.com/terms/k/know-sure-thing-kst.asp\n\nFormular:\n* KST=(RCMA1×1)+(RCMA2×2) + (RCMA3×3)+(RCMA4×4)\n\nWhere:\n* RCMA1=10-period SMA of 10-period ROC\n* RCMA2=10-period SMA of 15-period ROC\n* RCMA3=10-period SMA of 20-period ROC\n* RCMA4=15-period SMA of 30-period ROC","shortMessageHtmlLink":"[GH-165] Add Know Sure Thing support"}},{"before":null,"after":"9521c798f787e56b7208910d853d0bc3bc1b4884","ref":"refs/heads/feature/kst","pushedAt":"2023-07-08T14:45:17.000Z","pushType":"branch_creation","commitsCount":0,"pusher":{"login":"jealous","name":"Cedric Zhuang","path":"/jealous","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/1789979?s=80&v=4"},"commit":{"message":"[GH-165] Add Know Sure Thing support\n\nThe Know Sure Thing (KST) is a momentum oscillator developed by\nMartin Pring to make rate-of-change readings easier for traders\nto interpret.\n\nhttps://www.investopedia.com/terms/k/know-sure-thing-kst.asp\n\nFormular:\n* KST=(RCMA1×1)+(RCMA2×2) + (RCMA3×3)+(RCMA4×4)\n\nWhere:\n* RCMA1=10-period SMA of 10-period ROC\n* RCMA2=10-period SMA of 15-period ROC\n* RCMA3=10-period SMA of 20-period ROC\n* RCMA4=15-period SMA of 30-period ROC","shortMessageHtmlLink":"[GH-165] Add Know Sure Thing support"}},{"before":"de5d84af947e04736803cb98ef8b019b0d17d31f","after":null,"ref":"refs/heads/feature/inertia","pushedAt":"2023-07-07T15:15:26.000Z","pushType":"branch_deletion","commitsCount":0,"pusher":{"login":"jealous","name":"Cedric Zhuang","path":"/jealous","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/1789979?s=80&v=4"}},{"before":"e486d156e27d75f351d1286d5ab2e0639dce38fd","after":"febcde6624a5143e817238aef6f0e40e6679b35a","ref":"refs/heads/master","pushedAt":"2023-07-07T15:15:22.000Z","pushType":"pr_merge","commitsCount":1,"pusher":{"login":"jealous","name":"Cedric Zhuang","path":"/jealous","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/1789979?s=80&v=4"},"commit":{"message":"[GH-163] Add Inertia Indicator (#164)\n\nIn financial markets, the concept of inertia was given by Donald Dorsey\r\nin the 1995 issue of Technical Analysis of Stocks and Commodities\r\nthrough the Inertia Indicator. The Inertia Indicator is moment-based\r\nand is an extension of Dorsey’s Relative Volatility Index (RVI).\r\n\r\nFormular:\r\n* inertia = n periods linear regression of RVGI\r\n\r\nExamples:\r\n* `df['inertia']` retrieves the inertia of 20 periods linear regression of 14 periods RVGI\r\n* `df['inertia_10']` retrieves the inertia of 10 periods linear regression of 14 periods RVGI","shortMessageHtmlLink":"[GH-163] Add Inertia Indicator (#164)"}},{"before":null,"after":"de5d84af947e04736803cb98ef8b019b0d17d31f","ref":"refs/heads/feature/inertia","pushedAt":"2023-07-07T15:13:32.000Z","pushType":"branch_creation","commitsCount":0,"pusher":{"login":"jealous","name":"Cedric Zhuang","path":"/jealous","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/1789979?s=80&v=4"},"commit":{"message":"[GH-163] Add Inertia Indicator\n\nIn financial markets, the concept of inertia was given by Donald Dorsey\nin the 1995 issue of Technical Analysis of Stocks and Commodities\nthrough the Inertia Indicator. The Inertia Indicator is moment-based\nand is an extension of Dorsey’s Relative Volatility Index (RVI).\n\nFormular:\n* inertia = n periods linear regression of RVGI\n\nExamples:\n* `df['inertia']` retrieves the inertia of 20 periods linear regression of 14 periods RVGI\n* `df['inertia_10']` retrieves the inertia of 10 periods linear regression of 14 periods RVGI","shortMessageHtmlLink":"[GH-163] Add Inertia Indicator"}}],"hasNextPage":true,"hasPreviousPage":false,"activityType":"all","actor":null,"timePeriod":"all","sort":"DESC","perPage":30,"cursor":"djE6ks8AAAAD2Mq20gA","startCursor":null,"endCursor":null}},"title":"Activity · jealous/stockstats"}