rankingCalculator.dos 27 KB

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  1. module fundit::rankingCalculator
  2. use fundit::sqlUtilities
  3. use fundit::dataPuller
  4. use fundit::dataSaver
  5. /*
  6. * 汇集所有参与排名的指标信息
  7. *
  8. */
  9. def get_indicator_info() {
  10. ids = [1,
  11. 2, 6, 9, 10, 11, 12, 21, 50, 52, 59,
  12. 14, 15, 16, 17, 18, 19, 40, 58,
  13. 37, 38, 41, 42, 43, 44, 45, 46, 47, 48, 49,
  14. 33, 34, 35, 36,
  15. 66, 53, 54, 55, 56, 57
  16. ];
  17. names = ['ret',
  18. 'maxdrawdown', 'kurtosis', 'skewness', 'stddev', 'alpha', 'beta', 'downsidedev', 'maxdrawdown_months', 'maxdrawdown_recoverymonths', 'winrate',
  19. 'kapparatio', 'treynorratio', 'jensen', 'omegaratio', 'sharperatio', 'sortinoratio_MAR', 'calmarratio', 'sortinoratio',
  20. 'per_con', 'info_ratio', 'var', 'cvar', 'smddvar', 'smddcvar', 'smdd_lpm1', 'smdd_lpm2', 'smdd_downside_dev', 'tracking_error', 'm2',
  21. 'upsidecapture_ret', 'downsidecapture_ret', 'upsidecapture_ratio', 'downsidecapture_ratio',
  22. 'stability', 'jc_stddev', 'gzstyle_stddev', 'gzstrategy_stddev', 'zz_stddev', 'zx_stddev'
  23. ];
  24. is_ASCs = [false,
  25. true, true, false, true, false, false, true, true, true, false,
  26. false, false, false, false, false, false, false, false,
  27. false, false, true, true, true, true, true, true, true, true, false,
  28. false, false, false, true,
  29. true, true, true, true, true, true
  30. ];
  31. return table(names AS name, ids AS id, is_ASCs AS is_ASC);
  32. }
  33. /*
  34. * 自定义百分位计算
  35. *
  36. */
  37. defg perRank(x, is_ASC) {
  38. return (100 * x.rank(ascending=is_ASC, percent=true)).round(0);
  39. }
  40. /*
  41. * 动态生成用于排序的SQL脚本
  42. *
  43. * @param data_table <TABLE>: 指标横表
  44. * @param indicator_table <TABLE>: 指标表,有 id, name, is_ASC 字段
  45. *
  46. * TODO: portfolio, cf, manager, company,
  47. * TODO: bfi & category
  48. *
  49. */
  50. def gen_ranking_sql(data_table, indicator_table) {
  51. ranking = create_entity_indicator_ranking();
  52. ranking_num = create_entity_indicator_ranking_num();
  53. for(indicator in indicator_table) {
  54. // 与 MySQL 不同,这里统一把近4年和成立以来的排名去掉
  55. if(indicator.id == 1)
  56. v_trailing = ['1m', '3m', '6m', '1y', '2y', '3y', '5y', '10y', 'ytd'];
  57. else {
  58. v_trailing = ['6m', '1y', '2y', '3y', '5y', '10y', 'ytd'];
  59. v_missing_trailing = ['1m', '3m'];
  60. }
  61. // 绝对排名和百分位排名
  62. t_ranking = sql(select = (sqlCol(['entity_id', 'end_date', 'category_id']), <indicator.id as indicator_id>,
  63. sqlCol(indicator.name + '_' + v_trailing,, 'indicator_' + v_trailing),
  64. sqlCol(indicator.name + '_' + v_trailing, rank{, indicator.is_ASC}, 'absrank_' + v_trailing),
  65. sqlCol(indicator.name + '_' + v_trailing, perRank{, indicator.is_ASC}, 'perrank_' + v_trailing)
  66. ),
  67. from = data_table,
  68. where = < category_id IS NOT NULL>,
  69. groupBy = sqlCol(['category_id', 'end_date']),
  70. groupFlag = 0 ).eval(); // context by
  71. // 为了满足表结构的要求, 非收益的指标要补上1m和3m的字段,虽然都是NULL
  72. if(indicator.id != 1) {
  73. v_tmp_col = ['indicator_' + v_missing_trailing, 'absrank_' + v_missing_trailing, 'perrank_' + v_missing_trailing].flatten();
  74. v_tmp_type = [take(DOUBLE, v_missing_trailing.size()), take(INT, v_missing_trailing.size()), take(INT, v_missing_trailing.size())].flatten();
  75. t_ranking.addColumn(v_tmp_col, v_tmp_type);
  76. }
  77. t_ranking.reorderColumns!(ranking.colNames());
  78. ranking.tableInsert(t_ranking);
  79. // 平均值、集合数量、各分位的阈值
  80. t_ranking_num = sql(select =(sqlCol(['end_date', 'category_id']),
  81. sqlCol('raise_type', mean, 'raise_type'), <indicator.id as indicator_id>,
  82. sqlCol(indicator.name + '_' + v_trailing, mean, 'avg_' + v_trailing),
  83. sqlCol(indicator.name + '_' + v_trailing, count, 'avg_' + v_trailing + '_cnt'),
  84. sqlCol(indicator.name + '_' + v_trailing, percentile{, iif(indicator.is_ASC, 5, 95)}, 'perrank_percent_5_' + v_trailing),
  85. sqlCol(indicator.name + '_' + v_trailing, percentile{, iif(indicator.is_ASC, 10, 90)}, 'perrank_percent_10_' + v_trailing),
  86. sqlCol(indicator.name + '_' + v_trailing, percentile{, iif(indicator.is_ASC, 25, 75)}, 'perrank_percent_25_' + v_trailing),
  87. sqlCol(indicator.name + '_' + v_trailing, percentile{, iif(indicator.is_ASC, 50, 50)}, 'perrank_percent_50_' + v_trailing),
  88. sqlCol(indicator.name + '_' + v_trailing, percentile{, iif(indicator.is_ASC, 75, 25)}, 'perrank_percent_75_' + v_trailing),
  89. sqlCol(indicator.name + '_' + v_trailing, percentile{, iif(indicator.is_ASC, 90, 10)}, 'perrank_percent_90_' + v_trailing),
  90. sqlCol(indicator.name + '_' + v_trailing, percentile{, iif(indicator.is_ASC, 95, 5)}, 'perrank_percent_95_' + v_trailing),
  91. sqlCol(indicator.name + '_' + v_trailing, iif(indicator.is_ASC, min, max), 'best_' + v_trailing),
  92. sqlCol(indicator.name + '_' + v_trailing, iif(indicator.is_ASC, max, min), 'worst_' + v_trailing)
  93. ),
  94. from = data_table,
  95. where = < category_id IS NOT NULL>,
  96. groupBy = sqlCol(['category_id', 'end_date']),
  97. groupFlag = 1).eval(); // group by
  98. // 为了满足表结构的要求, 非收益的指标要补上1m和3m的字段,虽然都是NULL
  99. if(indicator.id != 1) {
  100. v_tmp_col = ['avg_' + v_missing_trailing, 'avg_' + v_missing_trailing + '_cnt', 'perrank_percent_5_' + v_missing_trailing,
  101. 'perrank_percent_10_' + v_missing_trailing, 'perrank_percent_25_' + v_missing_trailing,
  102. 'perrank_percent_50_' + v_missing_trailing, 'perrank_percent_75_' + v_missing_trailing,
  103. 'perrank_percent_90_' + v_missing_trailing, 'perrank_percent_95_' + v_missing_trailing,
  104. 'best_' + v_missing_trailing, 'worst_' + v_missing_trailing
  105. ].flatten();
  106. v_tmp_type = [take(DOUBLE, v_missing_trailing.size()), take(INT, v_missing_trailing.size()), take(DOUBLE, v_missing_trailing.size()),
  107. take(DOUBLE, v_missing_trailing.size()), take(DOUBLE, v_missing_trailing.size()),
  108. take(DOUBLE, v_missing_trailing.size()), take(DOUBLE, v_missing_trailing.size()),
  109. take(DOUBLE, v_missing_trailing.size()), take(DOUBLE, v_missing_trailing.size()),
  110. take(DOUBLE, v_missing_trailing.size()),take(DOUBLE, v_missing_trailing.size())
  111. ].flatten();
  112. t_ranking_num.addColumn(v_tmp_col, v_tmp_type);
  113. }
  114. t_ranking_num.reorderColumns!(ranking_num.colNames());
  115. ranking_num.tableInsert(t_ranking_num);
  116. }
  117. return ranking, ranking_num;
  118. }
  119. /*
  120. * 运行排名SQL脚本
  121. *
  122. *
  123. */
  124. def run_ranking_sql(cal_type, mutable data_table, indicator_table) {
  125. // data_table = t
  126. // v_tables = v_ranking_tables
  127. // cal_type = 'strategy'
  128. ret = array(ANY, 0);
  129. if(cal_type == 'bfi') {
  130. UPDATE data_table SET category_id = factor_id;
  131. v_ranking = gen_ranking_sql(data_table, indicator_table);
  132. ret.append!(v_ranking[0]); // ranking table
  133. ret.append!(v_ranking[1]); // ranking_num table
  134. } else {
  135. // 策略排名
  136. UPDATE data_table SET category_id = strategy$STRING;
  137. v_ranking = gen_ranking_sql(data_table, indicator_table);
  138. ret.append!(v_ranking[0]); // ranking table
  139. ret.append!(v_ranking[1]); // ranking_num table
  140. // 子策略排名
  141. UPDATE data_table SET category_id = substrategy$STRING;
  142. v_ranking = gen_ranking_sql(data_table, indicator_table);
  143. ret.append!(v_ranking[0]); // ranking table
  144. ret.append!(v_ranking[1]); // ranking_num table
  145. }
  146. return ret;
  147. }
  148. /*
  149. * 通用指标排名计算
  150. *
  151. * @param cal_type <STRING>: strategy, bfi
  152. *
  153. */
  154. def cal_indicator_ranking(cal_type, entity_type, entity_info, end_date, isFromMySQL) {
  155. // 当前只对基金做排名, 其它类型参考基金排名做相对排名
  156. if(!(entity_type in ['MF', 'HF'])) return null;
  157. // return
  158. table_desc = get_performance_table_description(entity_type);
  159. tb_data_return = get_monthly_indicator_data(table_desc.table_name[0], end_date, isFromMySQL);
  160. // risk
  161. table_desc = get_risk_stats_table_description(entity_type);
  162. tb_data_risk_stats = get_monthly_indicator_data(table_desc.table_name[0], end_date, isFromMySQL);
  163. // risk adjusted return
  164. table_desc = get_riskadjret_stats_table_description(entity_type);
  165. tb_data_riskadjret_stats = get_monthly_indicator_data(table_desc.table_name[0], end_date, isFromMySQL);
  166. // others
  167. table_desc = get_indicator_table_description(entity_type);
  168. tb_data_indicator_stats = get_monthly_indicator_data(table_desc.table_name[0], end_date, isFromMySQL);
  169. tb_data = SELECT *
  170. FROM tb_data_return d1
  171. LEFT JOIN tb_data_indicator_stats d2 ON d1.fund_id = d2.fund_id AND d1.end_date = d2.end_date
  172. LEFT JOIN tb_data_risk_stats d3 ON d1.fund_id = d3.fund_id AND d1.end_date = d3.end_date
  173. LEFT JOIN tb_data_riskadjret_stats d4 ON d1.fund_id = d4.fund_id AND d1.end_date = d4.end_date;
  174. if(cal_type == 'bfi') {
  175. // bfi (as benchmark) indicator
  176. table_desc = get_bfi_indicator_table_description(entity_type);
  177. tb_data_bfi_indicator = get_monthly_indicator_data(table_desc.table_name[0], end_date, isFromMySQL);
  178. // 去掉被移到 fund_ty_bfi_bm_indicator 表中的重复字段
  179. v_dups = [38, 48, 11, 12, 59, 16];
  180. v_dup_col = EXEC name + suffix
  181. FROM cj(get_indicator_info(), table(['_6m', '_1y', '_2y', '_3y', '_5y', '_10y', '_ytd'] AS suffix))
  182. WHERE id IN v_dups;
  183. tb_data.dropColumns!(v_dup_col);
  184. tb_data = SELECT * FROM tb_data d1
  185. LEFT JOIN tb_data_bfi_indicator d2 ON d1.fund_id = d2.fund_id AND d1.end_date = d2.end_date;
  186. v_indicator_id = [1, // 对应 fund_performance, 取消39(年化收益) 因为没有意义
  187. 41, 42, 49, // 对应 fund_indicator, 取消37 (per_con), 43, 44, 45, 46, 47 (smdd模型) 因为dolphin 未计算
  188. 2, 6, 9, 10, 21, // 对应 fund_risk_stats, 取消50, 52 因为 dolphin 未计算
  189. 14, 15, 17, 18, 40, 58, // 对应 fund_riskadjret_stats 取消19 (MAR Sortino ratio) 因为 dolphin 未计算
  190. 11, 12, 16, 33, 34, 35, 36, 38, 48, 59 // 对应 fund_ty_bfi_bm_indicator
  191. ]; // 取消 pf_fund_factor_stability 66 (stabiliy) 因为 dolphin 未计算
  192. // 取消 fund_rbsa_style 53, 54, 55, 56, 57(风格稳定性) 因为 dolphin 未计算
  193. } else {
  194. // upside/downside capture
  195. table_desc = get_capture_style_table_description(entity_type);
  196. tb_data_capture_stats = get_monthly_indicator_data(table_desc.table_name[0], end_date, isFromMySQL);
  197. tb_data = SELECT * FROM tb_data d1
  198. LEFT JOIN tb_data_capture_stats d2 ON d1.fund_id = d2.fund_id AND d1.end_date = d2.end_date;
  199. v_indicator_id = [1, // 对应 fund_performance, 取消39(年化收益) 因为没有意义
  200. 38, 41, 42, 48, 49, // 对应 fund_indicator, 取消37 (per_con), 43, 44, 45, 46, 47 (smdd模型) 因为dolphin 未计算
  201. 2, 6, 9, 10, 11, 12, 21, 59, // 对应 fund_risk_stats, 取消50, 52 因为 dolphin 未计算
  202. 14, 15, 16, 17, 18, 40, 58, // 对应 fund_riskadjret_stats 取消19 (MAR Sortino ratio) 因为 dolphin 未计算
  203. 33, 34, 35, 36 // 对应 fund_style_stats
  204. ];
  205. }
  206. sec_id_col = table_desc.sec_id_col[0];
  207. tb_data.rename!(sec_id_col, 'entity_id');
  208. t = SELECT *
  209. FROM entity_info en
  210. INNER JOIN tb_data d ON en.entity_id = d.entity_id
  211. WHERE en.strategy IS NOT NULL;
  212. indicator_table = SELECT * FROM get_indicator_info() WHERE id IN v_indicator_id;
  213. v_ranking_tables = run_ranking_sql(cal_type, t, indicator_table);
  214. return v_ranking_tables;
  215. }
  216. /*
  217. * 将源指标表横表变竖表,以方便排名计算
  218. *
  219. *
  220. */
  221. def transform_data_for_ranking(entity_type, data_table, ranking_by, indicator_info) {
  222. // 只有收益需要1m, 3m
  223. if(indicator_info.size() == 1 && indicator_info[0].id == 1 )
  224. v_trailing = ['1m', '3m', '6m', '1y', '2y', '3y', '5y', '10y', 'ytd'];
  225. else
  226. v_trailing = ['6m', '1y', '2y', '3y', '5y', '10y', 'ytd'];
  227. // 只有 portfolio_id 是整型,其它的都是字符串
  228. is_id_integer = false;
  229. if(entity_type == 'PF') is_id_integer = true;
  230. if(ranking_by == 'strategy')
  231. tb_ranking = create_entity_indicator_ranking(is_id_integer).rename!(ranking_by, 'category_id');
  232. else if(ranking_by == 'substrategy')
  233. tb_ranking = create_entity_indicator_substrategy_ranking(is_id_integer).rename!(ranking_by, 'category_id');
  234. else if(ranking_by == 'factor_id')
  235. tb_ranking = NULL;
  236. for(indicator in indicator_info) {
  237. t = sql(select = (sqlCol(['entity_id', 'end_date', 'category_id']), <indicator.id as indicator_id>,
  238. sqlCol(indicator.name + '_' + v_trailing,, 'indicator_' + v_trailing)
  239. ),
  240. from = data_table
  241. ).eval();
  242. if(indicator_info.size() > 1 || indicator_info[0].id <> 1 )
  243. {
  244. t.join!(table(take(double(NULL), t.size()) AS indicator_1m,
  245. take(double(NULL), t.size()) AS indicator_3m) );
  246. }
  247. t.join!(table( take(int(NULL), t.size()) AS absrank_1m,
  248. take(int(NULL), t.size()) AS perrank_1m,
  249. take(int(NULL), t.size()) AS absrank_3m,
  250. take(int(NULL), t.size()) AS perrank_3m,
  251. take(int(NULL), t.size()) AS absrank_6m,
  252. take(int(NULL), t.size()) AS perrank_6m,
  253. take(int(NULL), t.size()) AS absrank_1y,
  254. take(int(NULL), t.size()) AS perrank_1y,
  255. take(int(NULL), t.size()) AS absrank_2y,
  256. take(int(NULL), t.size()) AS perrank_2y,
  257. take(int(NULL), t.size()) AS absrank_3y,
  258. take(int(NULL), t.size()) AS perrank_3y,
  259. take(int(NULL), t.size()) AS absrank_5y,
  260. take(int(NULL), t.size()) AS perrank_5y,
  261. take(int(NULL), t.size()) AS absrank_10y,
  262. take(int(NULL), t.size()) AS perrank_10y,
  263. take(int(NULL), t.size()) AS absrank_ytd,
  264. take(int(NULL), t.size()) AS perrank_ytd )
  265. );
  266. INSERT INTO tb_ranking
  267. SELECT * FROM (sql(select = sqlCol(tb_ranking.colNames()),
  268. from = t).eval());
  269. }
  270. return tb_ranking;
  271. }
  272. /*
  273. * 将源风险指标表横表变竖表,以方便排名计算
  274. *
  275. *
  276. */
  277. def transform_return_for_ranking (entity_type, entity_info, end_date, ranking_by, isFromMySQL=true) {
  278. table_desc = get_performance_table_description(entity_type);
  279. tb_data = get_monthly_indicator_data(table_desc.table_name[0], end_date, isFromMySQL);
  280. sec_id_col = table_desc.sec_id_col[0];
  281. tb_data.rename!(sec_id_col, 'entity_id');
  282. data_table = SELECT * FROM entity_info en
  283. INNER JOIN tb_data d ON en.entity_id = d.entity_id
  284. WHERE en.strategy IS NOT NULL
  285. data_table.dropColumns!('id');
  286. data_table.rename!(ranking_by, 'category_id');
  287. // 目前SQL排名的指标还包含39:年化收益,与收益没有什么差别所以被取消
  288. v_indicator_name = ['ret'];
  289. v_indicator_id = [1];
  290. v_is_ASC = [false];
  291. t_indicator = table(v_indicator_name AS name, v_indicator_id AS id, v_is_ASC AS is_ASC);
  292. tb_ranking = transform_data_for_ranking(entity_type, data_table, ranking_by, t_indicator).rename!('category_id', ranking_by);
  293. return tb_ranking;
  294. }
  295. /*
  296. * 将源风险指标表横表变竖表,以方便排名计算
  297. *
  298. *
  299. */
  300. def transform_risk_stats_for_ranking (entity_type, entity_info, end_date, ranking_by, isFromMySQL=true) {
  301. table_desc = get_risk_stats_table_description(entity_type);
  302. tb_data = get_monthly_indicator_data(table_desc.table_name[0], end_date, isFromMySQL);
  303. sec_id_col = table_desc.sec_id_col[0];
  304. tb_data.rename!(sec_id_col, 'entity_id');
  305. data_table = SELECT * FROM entity_info en
  306. INNER JOIN tb_data d ON en.entity_id = d.entity_id
  307. WHERE en.strategy IS NOT NULL
  308. data_table.dropColumns!('id');
  309. data_table.rename!(ranking_by, 'category_id');
  310. // 目前SQL排名的指标
  311. v_indicator_name = ['maxdrawdown', 'kurtosis', 'skewness', 'stddev', 'alpha', 'beta', 'downsidedev', 'maxdrawdown_months', 'maxdrawdown_recoverymonths', 'winrate'];
  312. v_indicator_id = [2, 6, 9, 10, 11, 12, 21, 50, 52, 59];
  313. v_is_ASC = [true, true, false, true, false, false, true, true, true, false];
  314. t_indicator = table(v_indicator_name AS name, v_indicator_id AS id, v_is_ASC AS is_ASC);
  315. tb_ranking = transform_data_for_ranking(entity_type, data_table, ranking_by, t_indicator).rename!('category_id', ranking_by);
  316. return tb_ranking;
  317. }
  318. /*
  319. * 将源风险调整指标表横表变竖表,以方便排名计算
  320. *
  321. *
  322. */
  323. def transform_risk_adj_ret_stats_for_ranking (entity_type, entity_info, end_date, ranking_by, isFromMySQL=true) {
  324. table_desc = get_riskadjret_stats_table_description(entity_type);
  325. tb_data = get_monthly_indicator_data(table_desc.table_name[0], end_date, isFromMySQL);
  326. sec_id_col = table_desc.sec_id_col[0];
  327. tb_data.rename!(sec_id_col, 'entity_id');
  328. data_table = SELECT * FROM entity_info en
  329. INNER JOIN tb_data d ON en.entity_id = d.entity_id
  330. WHERE en.strategy IS NOT NULL
  331. data_table.dropColumns!('id');
  332. data_table.rename!(ranking_by, 'category_id');
  333. // 目前SQL排名的指标
  334. v_indicator_name = ['kapparatio', 'treynorratio', 'jensen', 'omegaratio', 'sharperatio', 'sortinoratio_MAR', 'calmarratio', 'sortinoratio'];
  335. v_indicator_id = [14, 15, 16, 17, 18, 19, 40, 58];
  336. v_is_ASC = [false, false, false, false, false, false, false, false];
  337. t_indicator = table(v_indicator_name AS name, v_indicator_id AS id, v_is_ASC AS is_ASC);
  338. tb_ranking = transform_data_for_ranking(entity_type, data_table, ranking_by, t_indicator).rename!('category_id', ranking_by);
  339. return tb_ranking;
  340. }
  341. /*
  342. * 将源杂项风险指标表横表变竖表,以方便排名计算
  343. *
  344. *
  345. */
  346. def transform_other_indicator_for_ranking (entity_type, entity_info, end_date, ranking_by, isFromMySQL=true) {
  347. table_desc = get_indicator_table_description(entity_type);
  348. tb_data = get_monthly_indicator_data(table_desc.table_name[0], end_date, isFromMySQL);
  349. sec_id_col = table_desc.sec_id_col[0];
  350. tb_data.rename!(sec_id_col, 'entity_id');
  351. data_table = SELECT * FROM entity_info en
  352. INNER JOIN tb_data d ON en.entity_id = d.entity_id
  353. WHERE en.strategy IS NOT NULL
  354. data_table.dropColumns!('id');
  355. data_table.rename!(ranking_by, 'category_id');
  356. // 目前SQL排名的指标
  357. v_indicator_name = ['per_con', 'info_ratio', 'var', 'cvar', 'smddvar', 'smddcvar', 'smdd_lpm1', 'smdd_lpm2', 'smdd_downside_dev', 'tracking_error', 'm2'];
  358. v_indicator_id = [37, 38, 41, 42, 43, 44, 45, 46, 47, 48, 49];
  359. v_is_ASC = [false, false, true, true, true, true, true, true, true, true, false];
  360. t_indicator = table(v_indicator_name AS name, v_indicator_id AS id, v_is_ASC AS is_ASC);
  361. tb_ranking = transform_data_for_ranking(entity_type, data_table, ranking_by, t_indicator).rename!('category_id', ranking_by);
  362. return tb_ranking;
  363. }
  364. /*
  365. * 将源杂项风险指标表横表变竖表,以方便排名计算
  366. *
  367. *
  368. */
  369. def transform_capture_style_for_ranking (entity_type, entity_info, end_date, ranking_by, isFromMySQL=true) {
  370. table_desc = get_capture_style_table_description(entity_type);
  371. tb_data = get_monthly_indicator_data(table_desc.table_name[0], end_date, isFromMySQL);
  372. sec_id_col = table_desc.sec_id_col[0];
  373. tb_data.rename!(sec_id_col, 'entity_id');
  374. data_table = SELECT * FROM entity_info en
  375. INNER JOIN tb_data d ON en.entity_id = d.entity_id
  376. WHERE en.strategy IS NOT NULL
  377. data_table.dropColumns!('id');
  378. data_table.rename!(ranking_by, 'category_id');
  379. // 目前SQL排名的指标
  380. v_indicator_name = ['upsidecapture_ret', 'downsidecapture_ret', 'upsidecapture_ratio', 'downsidecapture_ratio'];
  381. v_indicator_id = [33, 34, 35, 36];
  382. v_is_ASC = [false, false, false, true];
  383. t_indicator = table(v_indicator_name AS name, v_indicator_id AS id, v_is_ASC AS is_ASC);
  384. tb_ranking = transform_data_for_ranking(entity_type, data_table, ranking_by, t_indicator).rename!('category_id', ranking_by);
  385. return tb_ranking;
  386. }
  387. /*
  388. *
  389. * 参考某指定类排名,计算相对排名
  390. *
  391. * @param benchmark_ranking <TABLE>: 被参考的排名表,如公募混合基金
  392. * @param entity_ranking <TABLE>: 被计算的指标表,排名被填充在原表中
  393. * @param isFromMySQL <BOOL>
  394. *
  395. *
  396. * Example: cal_relative_ranking(get_fund_indicator_ranking(NULL, 2024.09M, 102, true),
  397. * transform_risk_stats_for_ranking('PF', get_entity_info('PF', NULL), 2024.09M, true),
  398. * true);
  399. */
  400. def cal_relative_ranking(benchmark_ranking, mutable entity_ranking, isFromMySQL=true) {
  401. v_trailing = ['1m', '3m', '6m', '1y', '2y', '3y', '5y', '10y', 'ytd'];
  402. for(tr in v_trailing) {
  403. indicator_val_col = 'indicator_' + tr;
  404. // 乘上100,000 是为了满足 window join 的字段必须是INT或DURATION
  405. tb_tmp = sql(select = (sqlCol(['entity_id', 'end_date', 'category_id', 'indicator_id']),
  406. sqlColAlias(makeCall(round, binaryExpr(sqlCol(indicator_val_col), 1000000, *), 0), indicator_val_col + '_int')),
  407. from = entity_ranking,
  408. where = < _$indicator_val_col is not null >,
  409. orderBy = sqlCol(['end_date', 'category_id', 'indicator_id', indicator_val_col])
  410. ).eval();
  411. tb_tmp2 = sql(select = (sqlCol(['end_date', 'category_id', 'indicator_id']),
  412. sqlColAlias(makeCall(round, binaryExpr(sqlCol(indicator_val_col), 1000000, *), 0), indicator_val_col + '_int'),
  413. sqlCol('absrank_' + tr), sqlCol('perrank_' + tr)
  414. ),
  415. from = benchmark_ranking,
  416. where = < _$indicator_val_col is not null >,
  417. orderBy = sqlCol(['end_date', 'category_id', 'indicator_id', indicator_val_col])
  418. ).eval();
  419. absrank_col = 'absrank_' + tr;
  420. perrank_col = 'perrank_' + tr;
  421. // 用 pwj 来找最接近的排名
  422. tb_tmp_ranking = sql(select = (sqlCol(['entity_id', 'end_date', 'category_id', 'indicator_id']),
  423. sqlCol(indicator_val_col + '_int'),
  424. sqlCol(['absrank_max', 'perrank_max'])),
  425. from = pwj(tb_tmp, tb_tmp2,
  426. window = 0:1,
  427. aggs = [<max(_$absrank_col) as 'absrank_max'>, <max(_$perrank_col) as 'perrank_max'>],
  428. matchingCols = ['end_date', 'category_id', 'indicator_id', indicator_val_col + '_int'])
  429. ).eval();
  430. // 计算的结果填入排名表
  431. sqlUpdate(table = entity_ranking,
  432. updates = [<absrank_max as _$absrank_col>, <perrank_max as _$perrank_col>],
  433. from = <ej(entity_ranking, tb_tmp_ranking, ['entity_id', 'end_date', 'category_id','indicator_id'])>
  434. ).eval();
  435. }
  436. }
  437. /*
  438. * 排名数据入库
  439. *
  440. * @param cal_type
  441. * @param ranking_tables <VECTOR>: 当 cal_type = 'strategy' 时包含4个数据表的向量,分别是一级策略排名,一级策略排名阈值,二级策略排名,二级策略排名阈值
  442. * cal_type = 'bfi' 时包含2个数据表的向量,分别是bfi策略排名,bfi策略排名阈值
  443. */
  444. def save_ranking_tables(cal_type, ranking_tables) {
  445. //cal_type = 'bfi'
  446. //ranking_tables=v_ranking_tables
  447. if(ranking_tables.isVoid()) return;
  448. entity_id_col = 'fund_id';
  449. if(cal_type == 'bfi') {
  450. source_table = 'raw_db.pf_fund_bfi_bm_indicator_ranking';
  451. target_table = 'raw_db.pf_fund_bfi_bm_indicator_ranking';
  452. category_id_col = 'factor_id';
  453. } else {
  454. source_table = 'raw_db.pf_fund_indicator_ranking';
  455. target_table = 'raw_db.pf_fund_indicator_ranking';
  456. category_id_col = 'strategy';
  457. }
  458. t = ranking_tables[0];
  459. save_and_sync(t.rename!(['entity_id', 'category_id'], [entity_id_col, category_id_col]), source_table, target_table);
  460. t = ranking_tables[1];
  461. save_and_sync(t.rename!('category_id', category_id_col), source_table + '_num', target_table + '_num');
  462. if(cal_type == 'strategy') {
  463. source_table = source_table.strReplace('_ranking', '_substrategy_ranking');
  464. target_table = target_table.strReplace('_ranking', '_substrategy_ranking');
  465. category_id_col = 'substrategy';
  466. t = ranking_tables[2];
  467. save_and_sync(t.rename!(['entity_id', 'category_id'], [entity_id_col, category_id_col]), source_table, target_table);
  468. t = ranking_tables[3];
  469. save_and_sync(t.rename!('category_id', category_id_col), source_table + '_num', target_table + '_num');
  470. }
  471. }
  472. /*
  473. * 参考排名数据入库
  474. *
  475. * @param ranking_tables <TABLE>:
  476. */
  477. def save_relative_ranking_table(entity_type, ranking_table, ranking_by) {
  478. if(ranking_table.isVoid()) return;
  479. source_table = '';
  480. target_table = '';
  481. if(entity_type == 'PF') {
  482. entity_id_col = 'portfolio_id';
  483. if(ranking_by == 'strategy') {
  484. source_table = 'raw_db.pf_portfolio_indicator_ranking';
  485. target_table = 'raw_db.pf_portfolio_indicator_ranking';
  486. } else if(ranking_by == 'substrategy') {
  487. source_table = 'raw_db.pf_portfolio_indicator_substrategy_ranking';
  488. target_table = 'raw_db.pf_portfolio_indicator_substrategy_ranking';
  489. } else if(ranking_by == 'factor_id') {
  490. source_table = 'raw_db.pf_portfolio_bfi_bm_indicator_ranking';
  491. target_table = 'raw_db.pf_portfolio_bfi_bm_indicator_ranking';
  492. }
  493. } else if(entity_type == 'CF') {
  494. entity_id_col = 'fund_id';
  495. source_table = 'raw_db.pf_cus_fund_indicator_ranking';
  496. target_table = 'raw_db.pf_cus_fund_indicator_ranking'
  497. }
  498. save_and_sync(ranking_table, source_table, target_table);
  499. }