indicatorCalculator.dos 56 KB

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  1. module fundit::indicatorCalculator
  2. use fundit::dataPuller
  3. use fundit::returnCalculator
  4. use fundit::navCalculator
  5. /*
  6. * Annulized multiple
  7. */
  8. def get_annulization_multiple(freq) {
  9. ret = 1;
  10. if (freq == 'd') {
  11. ret = 252; // We have differences here between Java and DolphinDB, Java uses 365.25 days
  12. } else if (freq == 'w') {
  13. ret = 52;
  14. } else if (freq == 'm') {
  15. ret = 12;
  16. } else if (freq == 'q') {
  17. ret = 4;
  18. } else if (freq == 's') {
  19. ret = 2;
  20. } else if (freq == 'a') {
  21. ret = 1;
  22. }
  23. return ret;
  24. }
  25. /*
  26. * 将VaR包裹一层,使之成为系统认可的聚集函数
  27. * @param returns <DOUBLE VECTOR>: 非空收益率
  28. * @param method <STRING>: 'normal', 'logNormal', 'historical', 'monteCarlo'
  29. * @param confidenceLevel <DOUBLE>: 置信水平,取值区间(0, 1)
  30. *
  31. */
  32. defg aggVaR(returns, method, confidenceLevel) {
  33. return returns.VaR(method, confidenceLevel);
  34. }
  35. /*
  36. * 将CVaR包裹一层,使之成为系统认可的聚集函数
  37. * @param returns <DOUBLE VECTOR>: 非空收益率
  38. * @param method <STRING>: 'normal', 'logNormal', 'historical', 'monteCarlo'
  39. * @param confidenceLevel <DOUBLE>: 置信水平,取值区间(0, 1)
  40. *
  41. */
  42. defg aggCVaR(returns, method, confidenceLevel) {
  43. return returns.CVaR(method, confidenceLevel);
  44. }
  45. /*
  46. * 回撤
  47. *
  48. *
  49. */
  50. defg maxDrawdown(navs) {
  51. return max(1 - navs \ cummax(navs));
  52. }
  53. /*
  54. * 取主基准和BFI的历史月收益率
  55. *
  56. * @param benchmarks <TABLE>: entity-benchmark 的对应关系表
  57. * @param end_day <DATE>: 收益的截止日期
  58. *
  59. * @return <TABLE>: benchmark_id, end_date, ret
  60. *
  61. */
  62. def get_benchmark_return(benchmarks, end_day) {
  63. s_index_ids = '';
  64. s_factor_ids = '';
  65. if(benchmarks.isVoid() || benchmarks.size() == 0) { return null; }
  66. // 前缀为 IN 的 benchmark id
  67. t_index_id = SELECT DISTINCT benchmark_id FROM benchmarks WHERE benchmark_id LIKE 'IN%';
  68. s_index_ids = iif(isVoid(t_index_id), "", "'" + t_index_id.benchmark_id.concat("','") + "'");
  69. // 前缀为 FA 的 benchmark id
  70. t_factor_id = SELECT DISTINCT benchmark_id FROM benchmarks WHERE benchmark_id LIKE 'FA%';
  71. s_factor_ids = iif(isVoid(t_factor_id), "", "'" + t_factor_id.benchmark_id.concat("','") + "'");
  72. // 目前指数的月度业绩存在 fund_performance 表
  73. t_bmk = SELECT fund_id AS benchmark_id, temporalParse(end_date, 'yyyy-MM') AS end_date, ret FROM get_monthly_ret('IX', s_index_ids, 1990.01.01, end_day, true);
  74. // 而因子的月度业绩存在 cm_factor_performance 表
  75. INSERT INTO t_bmk SELECT factor_id, temporalParse(end_date, 'yyyy-MM') AS end_date, ret FROM get_monthly_ret('FA', s_factor_ids, 1990.01.01, end_day, true);
  76. return t_bmk;
  77. }
  78. /*
  79. * Trailing Monthly Return, Standard Deviation, Skewness, Kurtosis, Max Drawdown, VaR, CVaR, Calmar Ratio
  80. *
  81. * @param entity_info <TABLE>: xxx_information表,NEED COLUMNS entity_id, inception_date
  82. * @param ret <TABLE>: 收益表,需要有 entity_id, price_dat, end_date, nav
  83. * @param trailing_month <STRING>: trailing X month or ytd, incep
  84. *
  85. * NOTE: standard deviation of Java version is noncompliant-GIPS annulized number
  86. *
  87. * Create: 20240904 Joey
  88. * TODO: SQL is wrong for max drawdowns
  89. * TODO: var, cvar, calmar are off; std dev, skewness, kurtosis are slightly off
  90. * TODO: SQL is missing for portfolio since inception date return
  91. * TODO: Java calculates max drawdown even there is no nav
  92. * TODO: Java ytd worst month could be wrong (i.e. portfolio 166002, 2024-03)
  93. *
  94. */
  95. def cal_basic_performance(entity_info, ret, trailing_month) {
  96. // accumulate 版的 skewness, kurtosis, var, cvar 似乎都不对劲,只好找个笨办法来实现
  97. if(trailing_month == 'incep') {
  98. // 需要至少6个数才计算标准差、峰度、偏度
  99. t0 = SELECT price_date.max() AS price_date,
  100. prod(1+ret)-1 AS trailing_ret,
  101. prod(1+ret)-1 AS trailing_ret_a,
  102. iif(count(entity_id) > 5, std(ret), null) AS std_dev,
  103. iif(count(entity_id) > 5, skew(ret, false), null) AS skewness,
  104. iif(count(entity_id) > 5, kurtosis(ret, false), null)-3 AS kurtosis,
  105. min(ret) AS wrst_month
  106. FROM ret
  107. WHERE ret > -1
  108. GROUP BY entity_id
  109. CGROUP BY end_date
  110. ORDER BY end_date;
  111. // 年化收益(给后面计算Calmar用)
  112. UPDATE t0
  113. SET trailing_ret_a = (1+trailing_ret).pow(12\(t0.end_date - ei.inception_date.month()))-1
  114. FROM ej(t0, entity_info ei, 'entity_id')
  115. WHERE t0.end_date > ei.inception_date.month() + 12;
  116. // 不会用上面的办法算最大回撤, VaR, CVaR
  117. t_var = SELECT entity_id, end_date, ret,
  118. cummax(1 - nav \ cummax(nav)) AS drawdown,
  119. - cumpercentile(ret, 5, 'linear') AS var
  120. FROM ret WHERE ret > -1
  121. CONTEXT BY entity_id;
  122. t_cvar = SELECT entity_id, end_date, drawdown, var,
  123. - cumavg(iif(ret <= -var, ret, null)) AS cvar
  124. FROM t_var
  125. CONTEXT BY entity_id;
  126. t1 = SELECT t0.*, t_cvar.drawdown, t_cvar.var, t_cvar.cvar
  127. FROM t0 LEFT JOIN t_cvar ON t0.entity_id = t_cvar.entity_id AND t0.end_date = t_cvar.end_date
  128. ORDER BY t0.entity_id, t0.end_date;
  129. } else if(trailing_month == 'ytd') {
  130. t1 = SELECT entity_id, end_date, price_date.cummax() AS price_date,
  131. cumprod(1+ret)-1 AS trailing_ret,
  132. cumprod(1+ret)-1 AS trailing_ret_a, // no need annulization for ytd
  133. iif(cumcount(entity_id) > 5, cumstd(ret), null) AS std_dev,
  134. iif(cumcount(entity_id) > 5, tmoving(skew{, false}, end_date, ret, 12), null) AS skewness,
  135. iif(cumcount(entity_id) > 5, tmoving(kurtosis{, false}, end_date, ret, 12)-3, null) AS kurtosis,
  136. cummin(ret) AS wrst_month,
  137. cummax(1 - nav \ cummax(nav)) AS drawdown
  138. FROM ret WHERE ret > -1
  139. CONTEXT BY entity_id, end_date.year()
  140. ORDER BY entity_id, end_date;
  141. // trailing x month
  142. } else {
  143. win = trailing_month$INT;
  144. t1 = SELECT entity_id, end_date, price_date.mmax(win) AS price_date,
  145. mprod(1+ret, win)-1 AS trailing_ret,
  146. iif(trailing_month > 12,
  147. mprod(1+ret, win).pow(12\win)-1,
  148. mprod(1+ret, win)-1) AS trailing_ret_a,
  149. mstd(ret, win) AS std_dev,
  150. mskew(ret, win, false) AS skewness,
  151. mkurtosis(ret, win, false) - 3 AS kurtosis,
  152. mmin(ret, win) AS wrst_month,
  153. moving(maxDrawdown, nav, win) AS drawdown,
  154. moving(aggVaR{, 'historical', 0.95}, ret, win) AS var,
  155. moving(aggCVaR{, 'historical', 0.95}, ret, win) AS cvar
  156. FROM ret WHERE ret > -1
  157. CONTEXT BY entity_id
  158. ORDER BY entity_id, end_date;
  159. }
  160. t1.addColumn('calmar', DOUBLE);
  161. UPDATE t1 SET calmar = iif(drawdown == 0, null, trailing_ret_a\drawdown);
  162. return t1;
  163. }
  164. /*
  165. * Lower Partial Moment
  166. * NOTE: risk free rate is used as Minimal Accepted Rate (MAR) here
  167. *
  168. */
  169. def cal_LPM(ret, risk_free, trailing_month) {
  170. t = SELECT *, cumcount(entity_id) AS cnt FROM ret WHERE ret > -1 CONTEXT BY entity_id;
  171. if(trailing_month == 'incep') {
  172. lpm = SELECT entity_id, end_date,
  173. iif(cumcount(end_date) > 5, (cumsum (iif(rfr.ret > t.ret, rfr.ret - t.ret, 0)) \ cumcount(end_date)).pow(1\1), null) AS lpm1,
  174. iif(cumcount(end_date) > 5, (cumsum2 (iif(rfr.ret > t.ret, rfr.ret - t.ret, 0)) \ cumcount(end_date)).pow(1\2), null) AS lpm2,
  175. iif(cumcount(end_date) > 5, (cumsum3 (iif(rfr.ret > t.ret, rfr.ret - t.ret, 0)) \ cumcount(end_date)).pow(1\3), null) AS lpm3
  176. FROM t
  177. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  178. CONTEXT BY entity_id
  179. ORDER BY entity_id, end_date;
  180. } else if(trailing_month == 'ytd') {
  181. lpm = SELECT entity_id, end_date,
  182. iif(cumcount(end_date) > 5, (cumsum (iif(rfr.ret > t.ret, rfr.ret - t.ret, 0)) \ cumcount(end_date)).pow(1\1), null) AS lpm1,
  183. iif(cumcount(end_date) > 5, (cumsum2 (iif(rfr.ret > t.ret, rfr.ret - t.ret, 0)) \ cumcount(end_date)).pow(1\2), null) AS lpm2,
  184. iif(cumcount(end_date) > 5, (cumsum3 (iif(rfr.ret > t.ret, rfr.ret - t.ret, 0)) \ cumcount(end_date)).pow(1\3), null) AS lpm3
  185. FROM t
  186. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  187. CONTEXT BY entity_id, end_date.year()
  188. ORDER BY entity_id, end_date;
  189. } else {
  190. win = trailing_month$INT;
  191. lpm = SELECT t.entity_id, t.end_date,
  192. (msum (iif(rfr.ret > t.ret, rfr.ret - t.ret, 0), win) \ mcount(end_date, win)).pow(1\1) AS lpm1,
  193. (msum2(iif(rfr.ret > t.ret, rfr.ret - t.ret, 0), win) \ mcount(end_date, win)).pow(1\2) AS lpm2,
  194. (moving(sum3, iif(rfr.ret > t.ret, rfr.ret - t.ret, 0), win) \ mcount(end_date, win)).pow(1\3) AS lpm3
  195. FROM t
  196. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  197. CONTEXT BY t.entity_id
  198. ORDER BY entity_id, end_date;
  199. }
  200. return lpm;
  201. }
  202. /*
  203. * Downside Devision, Omega Ratio, Sortino Ratio, Kappa Ratio
  204. *
  205. * TODO: Java version of Downside Deviation (LPM2) uses cnt-1 as denominator to calculate mean excess return, which might be wrong
  206. * Java version of Omega could be wrong because Java uses annualized returns and cnt-1
  207. * Java'version of Kappa could be very wrong
  208. *
  209. */
  210. def cal_omega_sortino_kappa(ret, risk_free, trailing_month) {
  211. lpm = cal_LPM(ret, risk_free, trailing_month);
  212. if(trailing_month == 'incep') {
  213. tb = SELECT t.entity_id, t.end_date,
  214. l.lpm2 AS ds_dev,
  215. (t.ret - rfr.ret ).cumavg() \ l.lpm1 + 1 AS omega,
  216. (t.ret - rfr.ret ).cumavg() \ l.lpm2 AS sortino,
  217. (t.ret - rfr.ret ).cumavg() \ l.lpm3 AS kappa
  218. FROM ret t
  219. INNER JOIN lpm l ON t.entity_id = l.entity_id AND t.end_date = l.end_date
  220. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  221. WHERE t.ret > -1
  222. CONTEXT BY t.entity_id;
  223. } else if(trailing_month == 'ytd') {
  224. tb = SELECT t.entity_id, t.end_date,
  225. l.lpm2 AS ds_dev,
  226. (t.ret - rfr.ret ).cumavg() \ l.lpm1 + 1 AS omega,
  227. (t.ret - rfr.ret ).cumavg() \ l.lpm2 AS sortino,
  228. (t.ret - rfr.ret ).cumavg() \ l.lpm3 AS kappa
  229. FROM ret t
  230. INNER JOIN lpm l ON t.entity_id = l.entity_id AND t.end_date = l.end_date
  231. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  232. WHERE t.ret > -1
  233. CONTEXT BY t.entity_id, t.end_date.year();
  234. } else {
  235. win = trailing_month$INT;
  236. tb = SELECT t.entity_id, t.end_date,
  237. l.lpm2 AS ds_dev,
  238. (t.ret - rfr.ret ).mavg(win) \ l.lpm1 + 1 AS omega,
  239. (t.ret - rfr.ret ).mavg(win) \ l.lpm2 AS sortino,
  240. (t.ret - rfr.ret ).mavg(win) \ l.lpm3 AS kappa
  241. FROM ret t
  242. INNER JOIN lpm l ON t.entity_id = l.entity_id AND t.end_date = l.end_date
  243. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  244. WHERE t.ret > -1
  245. CONTEXT BY t.entity_id;
  246. }
  247. return tb;
  248. }
  249. /*
  250. * Winning Ratio, Tracking Error, Information Ratio
  251. *
  252. * NOTE: mcount is very unique in mFun, because it doesn't support minPeriods(BUG?), while others default minPeriods = window.
  253. * As a result, we have to delete records having winrate but no tracking error and info ratio for the sake of consisence
  254. *
  255. * TODO: Win Rate incept is off, because Java incorrectly takes all end_date as denominator even when benchmark has no price
  256. * Information Ratio is way off!
  257. * Not sure how to describe a giant number("inf"), for now 999 is used
  258. */
  259. def cal_benchmark_tracking(ret, benchmarks, bmk_ret, trailing_month) {
  260. if(trailing_month == 'incep') {
  261. t0 = SELECT t.entity_id, t.end_date, t.price_date,
  262. t.ret, bmk.ret AS ret_bmk,
  263. t.entity_id.cumcount() AS cnt,
  264. t.ret - bmk.ret AS exc_ret, bm.benchmark_id
  265. FROM ret t
  266. INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
  267. INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id
  268. WHERE t.ret > -1
  269. AND bmk.ret > -1
  270. CONTEXT BY t.entity_id, bm.benchmark_id;
  271. t = SELECT entity_id, end_date, benchmark_id,
  272. iif(cnt > 5, cumcount(iif(exc_ret >= 0, 1, null)) \ cnt, null) AS winrate,
  273. iif(cnt > 5, exc_ret.cumstd(), null) AS track_error,
  274. iif(cnt > 5, iif(exc_ret.cumstd() == 0, null, exc_ret.cumavg() \ exc_ret.cumstd()), 5) AS info
  275. FROM t0
  276. CONTEXT BY entity_id, benchmark_id
  277. ORDER BY entity_id, end_date, benchmark_id;
  278. } else if(trailing_month == 'ytd') {
  279. t0 = SELECT t.entity_id, t.end_date, t.price_date,
  280. t.ret, bmk.ret AS ret_bmk,
  281. t.entity_id.cumcount() AS cnt, t.ret - bmk.ret AS exc_ret, bm.benchmark_id
  282. FROM ret t
  283. INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
  284. INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id
  285. WHERE t.ret > -1
  286. AND bmk.ret > -1
  287. CONTEXT BY t.entity_id, bm.benchmark_id, t.end_date.year();
  288. t = SELECT entity_id, end_date, benchmark_id,
  289. iif(cnt > 5, cumcount(iif(exc_ret >= 0, 1, null)) \ cnt, null) AS winrate,
  290. iif(cnt > 5, exc_ret.cumstd(), null) AS track_error,
  291. iif(cnt > 5, iif(exc_ret.cumstd() == 0, null, exc_ret.cumavg() \ exc_ret.cumstd()), null) AS info
  292. FROM t0
  293. CONTEXT BY entity_id, benchmark_id, end_date.year()
  294. ORDER BY entity_id, end_date, benchmark_id;
  295. } else {
  296. win = trailing_month$INT;
  297. t0 = SELECT t.entity_id, t.end_date, t.price_date,
  298. t.ret, bmk.ret AS ret_bmk,
  299. t.entity_id.mcount(win) AS cnt,
  300. t.ret - bmk.ret AS exc_ret, bm.benchmark_id
  301. FROM ret t
  302. INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
  303. INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id
  304. WHERE t.ret > -1
  305. AND bmk.ret > -1
  306. CONTEXT BY t.entity_id, bm.benchmark_id;
  307. t = SELECT entity_id, end_date, benchmark_id,
  308. iif(cnt > 5, mcount(iif(exc_ret >= 0, 1, null), win) \ cnt, null) AS winrate,
  309. iif(cnt > 5, mstd(exc_ret, win), null) AS track_error,
  310. iif(cnt > 5, iif(mstd(exc_ret, win) == 0, null, mavg(exc_ret, win) \ mstd(exc_ret, win)), null) AS info
  311. FROM t0
  312. CONTEXT BY entity_id, benchmark_id
  313. ORDER BY entity_id, end_date, benchmark_id;
  314. }
  315. return t; //SELECT * FROM t WHERE track_error IS NOT NULL;
  316. }
  317. /*
  318. * Alpha & Beta
  319. * NOTE: alpha of Java version is wrong because it doesn't use risk free rate
  320. */
  321. def cal_alpha_beta(ret, benchmarks, bmk_ret, risk_free, trailing_month) {
  322. t = SELECT t.entity_id, t.end_date, t.ret, bm.benchmark_id, bmk.ret AS ret_bmk
  323. FROM ret t
  324. INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
  325. INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id
  326. WHERE t.ret > -1
  327. AND bmk.ret > -1;
  328. if(trailing_month == 'incep') {
  329. beta = SELECT entity_id, end_date, benchmark_id,
  330. iif(cumcount(end_date) > 5, ret.cumbeta(ret_bmk), null) AS beta
  331. FROM t CONTEXT BY entity_id, benchmark_id;
  332. alpha = SELECT t.entity_id, t.end_date, t.benchmark_id, beta.beta AS beta,
  333. (t.ret - rfr.ret).cumavg() - beta.beta * (t.ret_bmk - rfr.ret).cumavg() AS alpha
  334. FROM t
  335. INNER JOIN beta beta ON t.entity_id = beta.entity_id AND t.benchmark_id = beta.benchmark_id AND t.end_date = beta.end_date
  336. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  337. CONTEXT BY t.entity_id, t.benchmark_id
  338. ORDER BY t.entity_id, t.end_date, t.benchmark_id;
  339. } else if(trailing_month == 'ytd') {
  340. beta = SELECT entity_id, end_date, benchmark_id,
  341. iif(cumcount(end_date) > 5, ret.cumbeta(ret_bmk), null) AS beta
  342. FROM t CONTEXT BY entity_id, benchmark_id, end_date.year();
  343. alpha = SELECT t.entity_id, t.end_date, t.benchmark_id, beta.beta AS beta,
  344. (t.ret - rfr.ret).cumavg() - beta.beta * (t.ret_bmk - rfr.ret).cumavg() AS alpha
  345. FROM t
  346. INNER JOIN beta beta ON t.entity_id = beta.entity_id AND t.benchmark_id = beta.benchmark_id AND t.end_date = beta.end_date
  347. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  348. CONTEXT BY t.entity_id, t.benchmark_id, t.end_date.year()
  349. ORDER BY t.entity_id, t.end_date, t.benchmark_id;
  350. } else {
  351. win = trailing_month$INT;
  352. beta = SELECT entity_id, end_date, benchmark_id,
  353. iif(mcount(end_date, win) > 5, ret.mbeta(ret_bmk, win), null) AS beta
  354. FROM t CONTEXT BY entity_id, benchmark_id;
  355. alpha = SELECT t.entity_id, t.end_date, t.benchmark_id, beta.beta AS beta,
  356. (t.ret - rfr.ret).mavg(win) - beta.beta * (t.ret_bmk - rfr.ret).mavg(win) AS alpha
  357. FROM t
  358. INNER JOIN beta beta ON t.entity_id = beta.entity_id AND t.benchmark_id = beta.benchmark_id AND t.end_date = beta.end_date
  359. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  360. CONTEXT BY t.entity_id, t.benchmark_id
  361. ORDER BY t.entity_id, t.end_date, t.benchmark_id;
  362. }
  363. return alpha;
  364. }
  365. /*
  366. * Upside/Down Capture Return/Ratio
  367. *
  368. * TODO: trailing x month values are way off!
  369. *
  370. */
  371. def cal_capture_ratio(ret, benchmarks, bmk_ret, trailing_month) {
  372. if(trailing_month == 'incep') {
  373. t1 = SELECT t.entity_id, t.end_date,
  374. (1+t.ret).cumprod() AS upside_ret, (1+bmk.ret).cumprod() AS bmk_upside_ret, bmk.end_date.cumcount() AS bmk_upside_cnt, bm.benchmark_id
  375. FROM ret t
  376. INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
  377. INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id AND t.end_date = bmk.end_date
  378. WHERE t.ret > -1
  379. AND bmk.ret >= 0
  380. CONTEXT BY t.entity_id, bm.benchmark_id;
  381. t2 = SELECT t.entity_id, t.end_date,
  382. (1+t.ret).cumprod() AS downside_ret, (1+bmk.ret).cumprod() AS bmk_downside_ret, bmk.end_date.cumcount() AS bmk_downside_cnt, bm.benchmark_id
  383. FROM ret t
  384. INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
  385. INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id AND t.end_date = bmk.end_date
  386. WHERE t.ret > -1
  387. AND bmk.ret < 0
  388. CONTEXT BY t.entity_id, bm.benchmark_id;
  389. } else if(trailing_month == 'ytd') {
  390. t1 = SELECT t.entity_id, t.end_date,
  391. (1+t.ret).cumprod() AS upside_ret, (1+bmk.ret).cumprod() AS bmk_upside_ret, bmk.end_date.cumcount() AS bmk_upside_cnt, bm.benchmark_id
  392. FROM ret t
  393. INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
  394. INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id AND t.end_date = bmk.end_date
  395. WHERE t.ret > -1
  396. AND bmk.ret >= 0
  397. CONTEXT BY t.entity_id, bm.benchmark_id, t.end_date.year();
  398. t2 = SELECT t.entity_id, t.end_date,
  399. (1+t.ret).cumprod() AS downside_ret, (1+bmk.ret).cumprod() AS bmk_downside_ret, bmk.end_date.cumcount() AS bmk_downside_cnt, bm.benchmark_id
  400. FROM ret t
  401. INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
  402. INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id AND t.end_date = bmk.end_date
  403. WHERE t.ret > -1
  404. AND bmk.ret < 0
  405. CONTEXT BY t.entity_id, bm.benchmark_id, t.end_date.year();
  406. } else {
  407. win = trailing_month$INT;
  408. t1 = SELECT t.entity_id, t.end_date,
  409. (1+t.ret).mprod(win) AS upside_ret, (1+bmk.ret).mprod(win) AS bmk_upside_ret, bmk.end_date.mcount(win) AS bmk_upside_cnt, bm.benchmark_id
  410. FROM ret t
  411. INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
  412. INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id AND t.end_date = bmk.end_date
  413. WHERE t.ret > -1
  414. AND bmk.ret >= 0
  415. CONTEXT BY t.entity_id, bm.benchmark_id;
  416. t2 = SELECT t.entity_id, t.end_date,
  417. (1+t.ret).mprod(win) AS downside_ret, (1+bmk.ret).mprod(win) AS bmk_downside_ret, bmk.end_date.mcount(win) AS bmk_downside_cnt,bm.benchmark_id
  418. FROM ret t
  419. INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
  420. INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id AND t.end_date = bmk.end_date
  421. WHERE t.ret > -1
  422. AND bmk.ret < 0
  423. CONTEXT BY t.entity_id, bm.benchmark_id;
  424. }
  425. t = (SELECT * FROM (
  426. SELECT iif(isNull(t1.entity_id), t2.entity_id, t1.entity_id) AS entity_id,
  427. iif(isNull(t1.end_date), t2.end_date, t1.end_date) AS end_date,
  428. iif(isNull(t1.benchmark_id), t2.benchmark_id, t1.benchmark_id) AS benchmark_id,
  429. t1.upside_ret.pow(1 \ t1.bmk_upside_cnt)-1 AS upside_capture_ret,
  430. (t1.upside_ret.pow(1 \ t1.bmk_upside_cnt)-1)/(t1.bmk_upside_ret.pow(1 \ t1.bmk_upside_cnt)-1) AS upside_capture_ratio,
  431. t2.downside_ret.pow(1 \ t2.bmk_downside_cnt)-1 AS downside_capture_ret,
  432. (t2.downside_ret.pow(1 \ t2.bmk_downside_cnt)-1)/(t2.bmk_downside_ret.pow(1 \ t2.bmk_downside_cnt)-1) AS downside_capture_ratio
  433. FROM t1 FULL JOIN t2 ON t1.entity_id = t2.entity_id AND t1.benchmark_id = t2.benchmark_id AND t1.end_date = t2.end_date)
  434. ORDER BY entity_id, benchmark_id, end_date).ffill();
  435. return t;
  436. }
  437. /*
  438. * Sharpe Ratio
  439. * NOTE: Java version is noncompliant-GIPS annulized number
  440. */
  441. def cal_sharpe(ret, std_dev, risk_free, trailing_month) {
  442. if(trailing_month == 'incep') {
  443. sharpe = SELECT t.entity_id, t.end_date, (t.ret - rfr.ret).cumavg() / std.std_dev AS sharpe
  444. FROM ret t
  445. INNER JOIN std_dev std ON t.entity_id = std.entity_id AND t.end_date = std.end_date
  446. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  447. WHERE std.std_dev <> 0 AND t.ret > -1
  448. CONTEXT BY t.entity_id;
  449. } else if(trailing_month == 'ytd') {
  450. sharpe = SELECT t.entity_id, t.end_date, (t.ret - rfr.ret).cumavg() / std.std_dev AS sharpe
  451. FROM ret t
  452. INNER JOIN std_dev std ON t.entity_id = std.entity_id AND t.end_date = std.end_date
  453. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  454. WHERE std.std_dev <> 0 AND t.ret > -1
  455. CONTEXT BY t.entity_id, t.end_date.year();
  456. } else {
  457. win = trailing_month$INT;
  458. sharpe = SELECT t.entity_id, t.end_date, (t.ret - rfr.ret).mavg(win) / std.std_dev AS sharpe
  459. FROM ret t
  460. INNER JOIN std_dev std ON t.entity_id = std.entity_id AND t.end_date = std.end_date
  461. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  462. WHERE std.std_dev <> 0 AND t.ret > -1
  463. CONTEXT BY t.entity_id;
  464. }
  465. return sharpe;
  466. }
  467. /*
  468. * Treynor Ratio = annulized excess return / beta
  469. *
  470. * TODO: ytd is off because Java uses non-GIPS rule to annulize return
  471. */
  472. def cal_treynor(ret, risk_free, beta, trailing_month) {
  473. if(trailing_month == 'incep') {
  474. t = SELECT *, cumcount(entity_id) AS cnt
  475. FROM ret t
  476. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  477. WHERE t.ret > -1
  478. AND rfr.ret > -1
  479. CONTEXT BY t.entity_id;
  480. treynor = SELECT t.entity_id, t.end_date, beta.benchmark_id,
  481. ((1 + t.ret).cumprod().pow(12\iif(t.cnt<12, 12, t.cnt)) - (1 + t.rfr_ret).cumprod().pow(12\iif(t.cnt<12, 12, t.cnt))) / beta.beta AS treynor
  482. FROM t
  483. INNER JOIN beta AS beta ON t.entity_id = beta.entity_id AND t.end_date = beta.end_date
  484. CONTEXT BY t.entity_id, beta.benchmark_id;
  485. } else if(trailing_month == 'ytd') {
  486. t = SELECT *, cumcount(entity_id) AS cnt
  487. FROM ret t
  488. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  489. WHERE t.ret > -1
  490. AND rfr.ret > -1
  491. CONTEXT BY t.entity_id, t.end_date.year();
  492. treynor = SELECT t.entity_id, t.end_date, beta.benchmark_id,
  493. ((1 + t.ret).cumprod().pow(12\iif(t.cnt<12, 12, t.cnt)) - (1 + t.rfr_ret).cumprod().pow(12\iif(t.cnt<12, 12, t.cnt))) / beta.beta AS treynor
  494. FROM t
  495. INNER JOIN beta AS beta ON t.entity_id = beta.entity_id AND t.end_date = beta.end_date
  496. CONTEXT BY t.entity_id, beta.benchmark_id, t.end_date.year();
  497. } else {
  498. win = trailing_month$INT;
  499. t = SELECT *, mcount(entity_id, win) AS cnt
  500. FROM ret t
  501. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  502. WHERE t.ret > -1
  503. AND rfr.ret > -1
  504. CONTEXT BY t.entity_id;
  505. treynor = SELECT t.entity_id, t.end_date, beta.benchmark_id,
  506. ((1 + t.ret).mprod(win).pow(12\iif(t.cnt<12, 12, t.cnt)) - (1 + t.rfr_ret).mprod(win).pow(12\iif(t.cnt<12, 12, t.cnt))) / beta.beta AS treynor
  507. FROM t
  508. INNER JOIN beta AS beta ON t.entity_id = beta.entity_id AND t.end_date = beta.end_date
  509. CONTEXT BY t.entity_id, beta.benchmark_id;
  510. }
  511. return treynor;
  512. }
  513. /*
  514. * Jensen's Alpha
  515. * TODO: the result is slightly off
  516. */
  517. def cal_jensen(ret, bmk_ret, risk_free, beta, trailing_month) {
  518. if(trailing_month == 'incep') {
  519. jensen = SELECT t.entity_id, t.end_date, t.ret.cumavg() - rfr.ret.cumavg() - beta.beta * (bmk.ret.cumavg() - rfr.ret.cumavg()) AS jensen, beta.benchmark_id
  520. FROM ret t
  521. INNER JOIN beta beta ON t.entity_id = beta.entity_id AND t.end_date = beta.end_date
  522. INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND beta.benchmark_id = bmk.benchmark_id
  523. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  524. WHERE t.ret > -1
  525. CONTEXT BY t.entity_id, beta.benchmark_id;
  526. } else if(trailing_month == 'ytd') {
  527. jensen = SELECT t.entity_id, t.end_date, t.ret.cumavg() - rfr.ret.cumavg() - beta.beta * (bmk.ret.cumavg() - rfr.ret.cumavg()) AS jensen, beta.benchmark_id
  528. FROM ret t
  529. INNER JOIN beta beta ON t.entity_id = beta.entity_id AND t.end_date = beta.end_date
  530. INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND beta.benchmark_id = bmk.benchmark_id
  531. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  532. WHERE t.ret > -1
  533. CONTEXT BY t.entity_id, beta.benchmark_id, t.end_date.year();
  534. } else {
  535. win = trailing_month$INT;
  536. jensen = SELECT t.entity_id, t.end_date, t.ret.mavg(win) - rfr.ret.mavg(win) - beta.beta * (bmk.ret.mavg(win) - rfr.ret.mavg(win)) AS jensen, beta.benchmark_id
  537. FROM ret t
  538. INNER JOIN beta beta ON t.entity_id = beta.entity_id AND t.end_date = beta.end_date
  539. INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND beta.benchmark_id = bmk.benchmark_id
  540. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  541. WHERE t.ret > -1
  542. CONTEXT BY t.entity_id, beta.benchmark_id;
  543. }
  544. return jensen;
  545. }
  546. /*
  547. * Modigliani Modigliani Measure (M2)
  548. * NOTE: M2 = sharpe * std(benchmark) + risk_free_rate
  549. * NOTE: Java version is noncompliant-GIPS annulized number
  550. */
  551. def cal_m2(ret, benchmarks, bmk_ret, risk_free, trailing_month) {
  552. if(trailing_month == 'incep') {
  553. m2 = SELECT t.entity_id, t.end_date, (t.ret - rfr.ret).cumavg() / t.ret.cumstd() * bmk.ret.cumstd() + rfr.ret.cumavg() AS m2, bm.benchmark_id
  554. FROM ret t
  555. INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
  556. INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id
  557. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  558. WHERE t.ret > -1
  559. CONTEXT BY t.entity_id, bm.benchmark_id;
  560. } else if(trailing_month == 'ytd') {
  561. m2 = SELECT t.entity_id, t.end_date, (t.ret - rfr.ret).cumavg() / t.ret.cumstd() * bmk.ret.cumstd() + rfr.ret.cumavg() AS m2, bm.benchmark_id
  562. FROM ret t
  563. INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
  564. INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id
  565. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  566. WHERE t.ret > -1
  567. CONTEXT BY t.entity_id, bm.benchmark_id, t.end_date.year();
  568. } else {
  569. win = trailing_month$INT;
  570. m2 = SELECT t.entity_id, t.end_date, (t.ret - rfr.ret).mavg(win) / t.ret.mstd(win) * bmk.ret.mstd(win) + rfr.ret.mavg(win) AS m2, bm.benchmark_id
  571. FROM ret t
  572. INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
  573. INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id
  574. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  575. WHERE t.ret > -1
  576. CONTEXT BY t.entity_id, bm.benchmark_id;
  577. }
  578. return m2;
  579. }
  580. /*
  581. * Morningstar Return, Morningstar Risk-Adjusted Return
  582. *
  583. * TODO: Tax and loads are NOT taken care of
  584. * TODO: Assume Chinese methodology using 3, 5, 10 as number of traling years
  585. * TODO: need verify with reliable results
  586. *
  587. * NOTE: Morningstar methodology requires monthly return for calculation, so that "12" is hard-coded here
  588. *
  589. *
  590. */
  591. def cal_ms_return(ret, risk_free, trailing_month) {
  592. win = trailing_month$INT;
  593. r = SELECT t.entity_id, t.end_date,
  594. ((1 + t.ret)\(1 + rfr.ret)).mprod(win).pow(12\(t.end_date.mmax(win) - t.end_date.mmin(win)))-1 AS ms_ret_a,
  595. (1 + t.ret).pow(-2).mavg(win).pow(-12/2)-1 AS ms_rar_a
  596. FROM ret t
  597. INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
  598. WHERE t.ret > -1
  599. CONTEXT BY t.entity_id;
  600. return r;
  601. }
  602. /*
  603. * 有效主体-基准对应表
  604. *
  605. * @param benchmarks <TABLE>: entity-benchmark 的对应关系表 NEED COLUMNS: entity_id, end_date, benchmark_id
  606. * @param end_day <DATE>:
  607. * @param trailing_month <STRING>:
  608. * @param isEffectiveOnly <BOOL>: false时与Java相同; true:多了个限制条件:如果区间内有效基准数少于1/2,不做计算
  609. * 比如过去12个月中某BFI只出现2次,小于需要的6次,此BFI不参与 trailing 1 year 计算
  610. *
  611. */
  612. def get_effective_benchmarks(benchmarks, end_day, trailing_month, isEffectiveOnly) {
  613. min_pct = 0.5;
  614. if(isEffectiveOnly) {
  615. t_dates = SELECT DISTINCT entity_id, end_date FROM benchmarks WHERE end_date <= end_day.month();
  616. if(trailing_month == 'incep') {
  617. t = SELECT entity_id, end_date, end_date.cumcount() AS cnt FROM t_dates CONTEXT BY entity_id;
  618. bmk = SELECT bmk.* FROM benchmarks bmk
  619. INNER JOIN t ON bmk.entity_id = t.entity_id AND bmk.end_date = t.end_date
  620. CONTEXT BY bmk.entity_id, bmk.benchmark_id
  621. HAVING bmk.end_date.cumcount() >= t.cnt * min_pct;
  622. } else if(trailing_month == 'ytd') {
  623. t = SELECT entity_id, end_date, end_date.cumcount() AS cnt FROM t_dates CONTEXT BY entity_id, end_date.year();
  624. bmk = SELECT bmk.* FROM benchmarks bmk
  625. INNER JOIN t ON bmk.entity_id = t.entity_id AND bmk.end_date = t.end_date
  626. CONTEXT BY entity_id, benchmark_id, end_date.year()
  627. HAVING bmk.end_date.cumcount() >= t.cnt * min_pct;
  628. } else {
  629. win = trailing_month$INT;
  630. t = SELECT entity_id, end_date, end_date.mcount(win) AS cnt FROM t_dates CONTEXT BY entity_id;
  631. bmk = SELECT bmk.* FROM benchmarks bmk
  632. INNER JOIN t ON bmk.entity_id = t.entity_id AND bmk.end_date = t.end_date
  633. CONTEXT BY entity_id, benchmark_id
  634. HAVING bmk.end_date.mcount(win) >= t.cnt * min_pct;
  635. }
  636. } else {
  637. bmk = SELECT * FROM benchmarks WHERE end_date <= end_day.month();
  638. }
  639. return bmk;
  640. }
  641. /*
  642. * Calculation for monthly indicators which need benchmark
  643. *
  644. * @param entity_info <TABLE>: xxx_information表,NEED COLUMNS entity_id, inception_date
  645. * @param benchmark_mapping <TABLE>: entity-benchmark mapping table, NEED COLUMNS entity_id, end_date, benchmark_id
  646. * @param end_day <DATE>;
  647. * @param tb_ret <TABLE>: 收益表,NEED COLUMNS entity_id, price_dat, end_date, nav
  648. * @param index_ret <TABLE>: historical benchmark return table, NEED COLUMNS fund_id, end_date, ret
  649. * @param risk_free <TABLE>: historical risk free rate table, NEED COLUMNS fund_id, end_date, ret
  650. * @param month <INT>: trailing x month
  651. *
  652. * @return: indicators table
  653. *
  654. *
  655. * Create 20240904 模仿Java & python代码在Dolphin中实现,具体计算逻辑可能会有不同 Joey
  656. * TODO: some datapoints require more data, we need a way to disable calculation for them
  657. *
  658. */
  659. def cal_indicators_with_benchmark(entity_info, benchmark_mapping, end_day, tb_ret, index_ret, risk_free, month) {
  660. if(entity_info.isVoid() || entity_info.size() == 0 || benchmark_mapping.isVoid() || benchmark_mapping.size() == 0 ) return null;
  661. if(tb_ret.isVoid() || tb_ret.size() == 0 || index_ret.isVoid() || index_ret.size() == 0 || risk_free.isVoid() || risk_free.size() == 0 ) return null;
  662. // sorting for correct first() and last() value
  663. ret = SELECT * FROM tb_ret WHERE ret > -1 AND end_date <= end_day.month() ORDER BY entity_id, price_date;
  664. // get the effective benchmarks
  665. benchmarks = get_effective_benchmarks(benchmark_mapping, end_day, month, true);
  666. if(ret.isVoid() || ret.size() == 0 || benchmarks.isVoid() || benchmarks.size() == 0) return null;
  667. // alpha, beta
  668. alpha_beta = cal_alpha_beta(ret, benchmarks, index_ret, risk_free, month);
  669. // 胜率、跟踪误差、信息比率
  670. bmk_tracking = cal_benchmark_tracking(ret, benchmarks, index_ret, month);
  671. // 特雷诺
  672. treynor = cal_treynor(ret, risk_free, alpha_beta, month);
  673. // 詹森指数
  674. jensen = cal_jensen(ret, index_ret, risk_free, alpha_beta, month);
  675. // M2
  676. m2 = cal_m2(ret, benchmarks, index_ret, risk_free, month);
  677. // 上下行捕获率、收益
  678. capture_r = cal_capture_ratio(ret, benchmarks, index_ret, month);
  679. r = SELECT * FROM bmk_tracking a1
  680. LEFT JOIN alpha_beta ON a1.entity_id = alpha_beta.entity_id AND a1.benchmark_id = alpha_beta.benchmark_id AND a1.end_date = alpha_beta.end_date
  681. LEFT JOIN treynor ON a1.entity_id = treynor.entity_id AND a1.benchmark_id = treynor.benchmark_id AND a1.end_date = treynor.end_date
  682. LEFT JOIN jensen ON a1.entity_id = jensen.entity_id AND a1.benchmark_id = jensen.benchmark_id AND a1.end_date = jensen.end_date
  683. LEFT JOIN m2 ON a1.entity_id = m2.entity_id AND a1.benchmark_id = m2.benchmark_id AND a1.end_date = m2.end_date
  684. LEFT JOIN capture_r ON a1.entity_id = capture_r.entity_id AND a1.benchmark_id = capture_r.benchmark_id AND a1.end_date = capture_r.end_date;
  685. // 年化各数据点
  686. // GIPS RULE: NO annulization for data less than 1 year
  687. plainAnnu = get_annulization_multiple('m');
  688. sqrtAnnu = sqrt(get_annulization_multiple('m'));
  689. r.addColumn(['alpha_a', 'jensen_a', 'track_error_a', 'info_a', 'm2_a'],
  690. [DOUBLE, DOUBLE, DOUBLE, DOUBLE, DOUBLE]);
  691. UPDATE r
  692. SET alpha_a = alpha * iif(end_date - inception_date.month() > 12, plainAnnu, 1),
  693. jensen_a = jensen * iif(end_date - inception_date.month() > 12, plainAnnu, 1),
  694. track_error_a = track_error * iif(end_date - inception_date.month() > 12, sqrtAnnu, 1),
  695. info_a = info * iif(end_date - inception_date.month() > 12, sqrtAnnu, 1),
  696. m2_a = m2 * iif(end_date - inception_date.month() > 12, plainAnnu, 1)
  697. FROM ej(r, entity_info, 'entity_id');
  698. return r;
  699. }
  700. /*
  701. * Monthly standard indicator calculation
  702. *
  703. * @param entity_info <TABLE>:
  704. * @param benchmarks <TABLE>: entity-benchmark mapping table
  705. * @param end_day <DATE>:
  706. * @param tb_ret <TABLE>: 收益表,NEED COLUMNS entity_id, price_dat, end_date, nav
  707. * @param benchmark_ret <TABLE>: historical benchmark return table, NEED COLUMNS fund_id, end_date, ret
  708. * @param risk_free <TABLE>: historical risk free rate table, NEED COLUMNS fund_id, end_date, ret
  709. * @param month <STRING>:
  710. *
  711. * @return: indicators table
  712. *
  713. *
  714. * Create 20240904 模仿Java & python代码在Dolphin中实现,具体计算逻辑可能会有不同 Joey
  715. *
  716. */
  717. def cal_indicators(entity_info, benchmarks, end_day, tb_ret, benchmark_ret, risk_free, month) {
  718. if(entity_info.isVoid() || entity_info.size() == 0 || benchmarks.isVoid() || benchmarks.size() == 0 ) return null;
  719. if(tb_ret.isVoid() || tb_ret.size() == 0 || benchmark_ret.isVoid() || benchmark_ret.size() == 0 || risk_free.isVoid() || risk_free.size() == 0 ) return null;
  720. // sorting for correct first() and last() value
  721. ret = SELECT * FROM tb_ret WHERE end_date <= end_day.month() ORDER BY entity_id, price_date;
  722. // 收益、标准差、偏度、峰度、最大回撤、VaR, CVaR、卡玛比率
  723. rtn = cal_basic_performance(entity_info, ret, month);
  724. // 夏普
  725. sharpe = cal_sharpe(ret, rtn, risk_free, month);
  726. // 整合后的下行标准差、欧米伽、索提诺、卡帕
  727. lpms = cal_omega_sortino_kappa(ret, risk_free, month);
  728. // 需要基准的指标们
  729. indicator_with_benchmark = cal_indicators_with_benchmark(entity_info, benchmarks, end_day, ret, benchmark_ret, risk_free, month);
  730. r = SELECT * FROM rtn a1
  731. LEFT JOIN sharpe ON a1.entity_id = sharpe.entity_id AND a1.end_date = sharpe.end_date
  732. LEFT JOIN lpms ON a1.entity_id = lpms.entity_id AND a1.end_date = lpms.end_date
  733. LEFT JOIN indicator_with_benchmark bmk ON a1.entity_id = bmk.entity_id AND a1.end_date = bmk.end_date;
  734. // 晨星收益和风险
  735. if(month$STRING in ['36', '60', '120']) {
  736. ms = cal_ms_return(ret, risk_free, month);
  737. r = SELECT * FROM r LEFT JOIN ms ON r.entity_id = ms.entity_id AND r.end_date = ms.end_date;
  738. }
  739. // 年化各数据点
  740. // GIPS RULE: NO annulization for data less than 1 year
  741. plainAnnu = get_annulization_multiple('m');
  742. sqrtAnnu = sqrt(get_annulization_multiple('m'));
  743. r.addColumn(['std_dev_a', 'ds_dev_a', 'sharpe_a', 'sortino_a'],
  744. [DOUBLE, DOUBLE, DOUBLE, DOUBLE]);
  745. UPDATE r
  746. SET std_dev_a = std_dev * iif(end_date - inception_date.month() > 12, sqrtAnnu, 1),
  747. ds_dev_a = ds_dev * iif(end_date - inception_date.month() > 12, sqrtAnnu, 1),
  748. sharpe_a = sharpe * iif(end_date - inception_date.month() > 12, sqrtAnnu, 1),
  749. sortino_a = sortino * iif(end_date - inception_date.month() > 12, sqrtAnnu, 1)
  750. FROM ej(r, entity_info, 'entity_id');
  751. return r;
  752. }
  753. /*
  754. * Calculate trailing 6m, ytd, 1y, 2y, 3y, 4y, 5y, 10y and since inception datapoints
  755. *
  756. * @param: func <FUNCTION>: the calculation function
  757. * @param: entity_info <TABLE>: basic information of entity, NEED COLUMNS entity_id, inception_date
  758. * @param benchmarks <TABLE>: entity-benchmark mapping table
  759. * @param: end_day <DATE>: 计算截止日期
  760. * @param: ret <TABLE>: 收益表,NEED COLUMNS entity_id, price_dat, end_date, nav
  761. * @param bmk_ret <TABLE>: historical benchmark return table, NEED COLUMNS fund_id, end_date, ret
  762. * @param risk_free <TABLE>: historical risk free rate table, NEED COLUMNS fund_id, end_date, ret
  763. * @param periods <BOOL VECTOR>: 是否计算的区间向量,分别对应 incep, ytd, 6m, 1y, 2y, 3y, 4y, 5y, 10y
  764. *
  765. *
  766. */
  767. def cal_trailing(func, entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate) {
  768. r_incep = null;
  769. r_ytd = null;
  770. r_6m = null;
  771. r_1y = null;
  772. r_2y = null;
  773. r_3y = null;
  774. r_4y = null;
  775. r_5y = null;
  776. r_10y = null;
  777. // incep
  778. r_incep = func(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate, 'incep');
  779. // ytd
  780. r_ytd = func(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate, 'ytd');
  781. // 6m
  782. r_6m = func(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate, '6');
  783. // 1y
  784. r_1y = func(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate, '12');
  785. // 2y
  786. r_2y = func(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate, '24');
  787. // 3y
  788. r_3y = func(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate, '36');
  789. // 4y
  790. r_4y = func(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate, '48');
  791. // 5y
  792. r_5y = func(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate, '60');
  793. // 10y
  794. r_10y = func(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate, '120');
  795. return r_incep, r_ytd, r_6m, r_1y, r_2y, r_3y, r_4y, r_5y, r_10y;
  796. }
  797. /*
  798. * Calculate trailing ytd, 6m, 1y, 2y, 3y, 4y, 5y, 10y and since inception standard indicators
  799. *
  800. * @param: entity_info <TABLE>: basic information of entity, NEED COLUMNS entity_id, inception_date
  801. * @param benchmarks <TABLE>: entity-benchmark mapping table
  802. * @param: ret <TABLE>: 收益表,NEED COLUMNS entity_id, price_dat, end_date, nav
  803. * @param: end_day <DATE>: 计算截止日期
  804. * @param bmk_ret <TABLE>: historical benchmark return table, NEED COLUMNS fund_id, end_date, ret
  805. * @param risk_free <TABLE>: historical risk free rate table, NEED COLUMNS fund_id, end_date, ret
  806. *
  807. */
  808. def cal_trailing_indicators(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate) {
  809. return cal_trailing(cal_indicators, entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate);
  810. }
  811. /*
  812. * Calculate trailing 6m, ytd, 1y, 2y, 3y, 4y, 5y, 10y and since inception bfi indicators
  813. *
  814. * @param: entity_info <TABLE>: basic information of entity, NEED COLUMNS entity_id, inception_date
  815. * @param benchmarks <TABLE>: entity-benchmark mapping table
  816. * @param: ret <TABLE>: 收益表,NEED COLUMNS entity_id, price_dat, end_date, nav
  817. * @param: end_day <DATE>: 计算截止日期
  818. * @param bmk_ret <TABLE>: historical benchmark return table, NEED COLUMNS fund_id, end_date, ret
  819. * @param risk_free <TABLE>: historical risk free rate table, NEED COLUMNS fund_id, end_date, ret
  820. *
  821. *
  822. */
  823. def cal_trailing_bfi_indicators(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate) {
  824. return cal_trailing(cal_indicators_with_benchmark, entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate);
  825. }
  826. /*
  827. * Calculate historcial fund trailing indicators
  828. *
  829. * @param entity_type <STRING>: MF, HF
  830. * @param fund_ids <STRING>: 逗号和单引号分隔的fund_id
  831. * @param end_day <DATE>: 要计算的日期
  832. * @param isFromNav <BOOL>: 用净值实时计算还是从表中取月收益
  833. * @param isFromSQL <BOOL>: TODO: 从MySQL还是本地DolphinDB取净值/收益数据
  834. *
  835. * @return <DICT TABLE>: ['PBI-INCEP', 'PBI-YTD', 'PBI-6M', 'PBI-1Y', 'PBI-2Y', 'PBI-3Y', 'PBI-4Y', 'PBI-5Y', 'PBI-10Y', 'MS-3Y', 'MS-5Y', 'MS-10Y']
  836. *
  837. * TODO: primary_benchmark_id seems not be used as benchmark, when it is FA00000VNB
  838. *
  839. * Example: cal_fund_indicators('HF', "'HF000004KN','HF000103EU','HF00018WXG'", 2024.06.28, true);
  840. *
  841. */
  842. def cal_fund_indicators(entity_type, fund_ids, end_day, isFromNav) {
  843. very_old_date = 1990.01.01;
  844. start_month = 1990.01M;
  845. fund_info = get_fund_info(fund_ids);
  846. if(fund_info.isVoid() || fund_info.size() == 0) { return null };
  847. fund_info.rename!('fund_id', 'entity_id');
  848. if(isFromNav == true) {
  849. // 从净值开始计算收益
  850. tb_ret = SELECT * FROM cal_fund_monthly_returns(entity_type, fund_ids, true) WHERE price_date <= end_day;
  851. tb_ret.rename!(['fund_id', 'cumulative_nav'], ['entity_id', 'nav']);
  852. } else {
  853. // 从fund_performance表里读月收益
  854. tb_ret = get_monthly_ret('FD', fund_ids, very_old_date, end_day, true);
  855. tb_ret.rename!(['fund_id'], ['entity_id']);
  856. v_end_date = tb_ret.end_date.temporalParse('yyyy-MM');
  857. tb_ret.replaceColumn!('end_date', v_end_date);
  858. }
  859. if(tb_ret.isVoid() || tb_ret.size() == 0) { return null; }
  860. // 取基金和基准的对照表
  861. primary_benchmark = SELECT fund_id AS entity_id, end_date, iif(benchmark_id.isNull(), 'IN00000008', benchmark_id) AS benchmark_id
  862. FROM get_fund_primary_benchmark(fund_ids, start_month.temporalFormat('yyyy-MM'), end_day.month().temporalFormat('yyyy-MM')) ;
  863. // 取所有出现的基准月收益
  864. bmk_ret = get_benchmark_return(primary_benchmark, end_day);
  865. if(bmk_ret.isVoid() || bmk_ret.size() == 0) { return null; }
  866. risk_free_rate = SELECT fund_id, temporalParse(end_date, 'yyyy-MM') AS end_date, ret FROM get_risk_free_rate(very_old_date, end_day);
  867. if(risk_free_rate.isVoid() || risk_free_rate.size() == 0) { return null; }
  868. // 标准的指标
  869. t0 = cal_trailing_indicators(fund_info, primary_benchmark, end_day, tb_ret, bmk_ret, risk_free_rate);
  870. // Morningstar 指标
  871. //t1 = cal_trailing_ms_indicators(fund_info, tb_ret, end_day, risk_free_rate);
  872. // PBI stands for "Primary Benchmark Index", MS stands for "MorningStar"
  873. v_table_name = ['PBI-INCEP', 'PBI-YTD', 'PBI-6M', 'PBI-1Y', 'PBI-2Y', 'PBI-3Y', 'PBI-4Y', 'PBI-5Y', 'PBI-10Y'/*, 'MS-3Y', 'MS-5Y', 'MS-10Y'*/];
  874. return dict(v_table_name, t0);
  875. // return dict(v_table_name, t0 <- t1[5] <- t1[7] <- t1[8]);
  876. }
  877. /*
  878. * Calculate historcial fund trailing BFI indicators
  879. *
  880. * @param entity_type <STRING>: MF, HF
  881. * @param fund_ids <STRING>: 逗号和单引号分隔的fund_id
  882. * @param end_day <DATE>: 要计算的日期
  883. * @param isFromNav <BOOL>: 用净值实时计算还是从表中取月收益
  884. * @param isFromSQL <BOOL>: TODO: 从MySQL还是本地DolphinDB取净值/收益数据
  885. *
  886. * @return <DICT TABLE>: ['BFI-INCEP', 'BFI-YTD', 'BFI-6M', 'BFI-1Y', 'BFI-2Y', 'BFI-3Y', 'BFI-4Y', 'BFI-5Y', 'BFI-10Y']
  887. *
  888. * TODO: primary_benchmark_id seems not be used as benchmark, when it is FA00000VNB
  889. * TODO: intergrate with cal_fund_indicators
  890. *
  891. * Example: cal_fund_bfi_indicators('MF', "'MF00003PW2', 'MF00003PW1', 'MF00003PXO'", 2024.08.31, true);
  892. *
  893. */
  894. def cal_fund_bfi_indicators(entity_type, fund_ids, end_day, isFromNav) {
  895. very_old_date = 1990.01.01;
  896. start_month = 1990.01M;
  897. fund_info = get_fund_info(fund_ids);
  898. if(fund_info.isVoid() || fund_info.size() == 0) { return null };
  899. fund_info.rename!('fund_id', 'entity_id');
  900. if(isFromNav == true) {
  901. // 从净值开始计算收益
  902. tb_ret = SELECT * FROM cal_fund_monthly_returns(entity_type, fund_ids, true) WHERE price_date <= end_day;
  903. tb_ret.rename!(['fund_id', 'cumulative_nav'], ['entity_id', 'nav']);
  904. } else {
  905. // 从fund_performance表里读月收益
  906. tb_ret = get_monthly_ret('FD', fund_ids, very_old_date, end_day, true);
  907. tb_ret.rename!(['fund_id'], ['entity_id']);
  908. v_end_date = tb_ret.end_date.temporalParse('yyyy-MM');
  909. tb_ret.replaceColumn!('end_date', v_end_date);
  910. }
  911. if(tb_ret.isVoid() || tb_ret.size() == 0) { return null; }
  912. // 取基金和基准的对照表
  913. bfi_benchmark = SELECT fund_id AS entity_id, end_date.temporalParse('yyyy-MM') AS end_date, factor_id AS benchmark_id
  914. FROM get_fund_bfi_factors(fund_ids, start_month.temporalFormat('yyyy-MM'), end_day.temporalFormat('yyyy-MM'));
  915. if(bfi_benchmark.isVoid() || bfi_benchmark.size() == 0) { return null; }
  916. bmk_ret = get_benchmark_return(bfi_benchmark, end_day);
  917. risk_free_rate = SELECT fund_id, temporalParse(end_date, 'yyyy-MM') AS end_date, ret FROM get_risk_free_rate(very_old_date, end_day);
  918. if(risk_free_rate.isVoid() || risk_free_rate.size() == 0) { return null; }
  919. t0 = cal_trailing_bfi_indicators(fund_info, bfi_benchmark, end_day, tb_ret, bmk_ret, risk_free_rate);
  920. // BFI stands for "Best Fit Index"
  921. v_table_name = ['BFI-INCEP', 'BFI-YTD', 'BFI-6M', 'BFI-1Y', 'BFI-2Y', 'BFI-3Y', 'BFI-4Y', 'BFI-5Y', 'BFI-10Y'];
  922. return dict(v_table_name, t0);
  923. }
  924. /*
  925. * Calculate historcial portfolio trailing indicators
  926. *
  927. * @param portfolio_ids <STRING>: comma-delimited portfolio ids
  928. * @param end_day <DATE>: the date
  929. * @param cal_method <INT>: calculate based on cumulative nav (1) or nav (2)
  930. * @param isFromNav <BOOL>: calculate returns from NAV on-the-fly (true) or get from monthly return table (false)
  931. *
  932. * Example: cal_portfolio_indicators('166002,166114', 2024.08.31, 1, true);
  933. *
  934. */
  935. def cal_portfolio_indicators(portfolio_ids, end_day, cal_method, isFromNav) {
  936. very_old_date = 1990.01.01;
  937. start_month = very_old_date.month();
  938. portfolio_info = get_portfolio_info(portfolio_ids);
  939. if(portfolio_info.isVoid() || portfolio_info.size() == 0) { return null };
  940. portfolio_info.rename!('portfolio_id', 'entity_id');
  941. if(isFromNav == true) {
  942. // 从净值开始计算收益
  943. tb_raw_ret = SELECT * FROM cal_portfolio_nav(portfolio_ids, very_old_date, cal_method) WHERE price_date <= end_day;
  944. if(tb_raw_ret.isVoid() || tb_raw_ret.size() == 0) return null;
  945. // funky thing is you can't use "AS" for the grouping columns?
  946. tb_ret = SELECT portfolio_id, price_date.month(), price_date.last() AS price_date, (1+ret).prod()-1 AS ret, nav.last() AS nav
  947. FROM tb_raw_ret
  948. WHERE price_date <= end_day
  949. GROUP BY portfolio_id, price_date.month();
  950. tb_ret.rename!(['portfolio_id', 'month_price_date'], ['entity_id', 'end_date']);
  951. } else {
  952. // 从pf_portfolio_performance表里读月收益
  953. tb_ret = get_monthly_ret('PF', portfolio_ids, very_old_date, end_day, true);
  954. tb_ret.rename!(['portfolio_id'], ['entity_id']);
  955. v_end_date = tb_ret.end_date.temporalParse('yyyy-MM');
  956. tb_ret.replaceColumn!('end_date', v_end_date);
  957. }
  958. if(tb_ret.isVoid() || tb_ret.size() == 0) return null;
  959. // 沪深300做基准,同SQL保持一致
  960. t_dates = table(start_month..end_day.month() AS end_date);
  961. primary_benchmark = SELECT ei.entity_id, dt.end_date, 'IN00000008' AS benchmark_id
  962. FROM portfolio_info ei JOIN t_dates dt
  963. WHERE dt.end_date >= ei.inception_date.month();
  964. if(primary_benchmark.isVoid() || primary_benchmark.size() == 0) { return null; }
  965. // 取所有出现的基准月收益
  966. bmk_ret = get_benchmark_return(primary_benchmark, end_day);
  967. if(bmk_ret.isVoid() || bmk_ret.size() == 0) { return null; }
  968. risk_free_rate = SELECT fund_id, temporalParse(end_date, 'yyyy-MM') AS end_date, ret FROM get_risk_free_rate(very_old_date, end_day);
  969. if(risk_free_rate.isVoid() || risk_free_rate.size() == 0) { return null; }
  970. t0 = cal_trailing_indicators(portfolio_info, primary_benchmark, end_day, tb_ret, bmk_ret, risk_free_rate);
  971. v_table_name = ['PBI-INCEP', 'PBI-YTD', 'PBI-6M', 'PBI-1Y', 'PBI-2Y', 'PBI-3Y', 'PBI-4Y', 'PBI-5Y', 'PBI-10Y'];
  972. return dict(v_table_name, t0);
  973. }
  974. /*
  975. * Calculate historcial portfolio trailing BFI indicators
  976. *
  977. * @param portfolio_ids <STRING>: comma-delimited portfolio ids
  978. * @param end_day <DATE>: the date
  979. * @param cal_method <INT>: calculate based on cumulative nav (1) or nav (2)
  980. * @param isFromNav <BOOL>: calculate returns from NAV on-the-fly (true) or get from monthly return table (false)
  981. *
  982. * TODO: intergrate with cal_portfolio_indicators
  983. *
  984. * Example: cal_portfolio_bfi_indicators('166002,166114', 2024.08.31, 1, true);
  985. *
  986. */
  987. def cal_portfolio_bfi_indicators(portfolio_ids, end_day, cal_method, isFromNav) {
  988. very_old_date = 1990.01.01;
  989. start_month = 1990.01M;
  990. portfolio_info = get_portfolio_info(portfolio_ids);
  991. if(portfolio_info.isVoid() || portfolio_info.size() == 0) { return null };
  992. portfolio_info.rename!('portfolio_id', 'entity_id');
  993. if(isFromNav == true) {
  994. // 从净值开始计算收益
  995. tb_raw_ret = SELECT * FROM cal_portfolio_nav(portfolio_ids, very_old_date, cal_method) WHERE price_date <= end_day;
  996. if(tb_raw_ret.isVoid() || tb_raw_ret.size() == 0) return null;
  997. // funky thing is you can't use "AS" for the grouping columns?
  998. tb_ret = SELECT portfolio_id, price_date.month(), price_date.last() AS price_date, (1+ret).prod()-1 AS ret, nav.last() AS nav
  999. FROM tb_raw_ret
  1000. WHERE price_date <= end_day
  1001. GROUP BY portfolio_id, price_date.month();
  1002. tb_ret.rename!(['portfolio_id', 'month_price_date'], ['entity_id', 'end_date']);
  1003. } else {
  1004. // 从pf_portfolio_performance表里读月收益
  1005. tb_ret = get_monthly_ret('PF', portfolio_ids, very_old_date, end_day, true);
  1006. tb_ret.rename!(['portfolio_id'], ['entity_id']);
  1007. v_end_date = tb_ret.end_date.temporalParse('yyyy-MM');
  1008. tb_ret.replaceColumn!('end_date', v_end_date);
  1009. }
  1010. if(tb_ret.isVoid() || tb_ret.size() == 0) return null;
  1011. // 取组合和基准的对照表
  1012. bfi_benchmark = SELECT portfolio_id AS entity_id, end_date.temporalParse('yyyy-MM') AS end_date, factor_id AS benchmark_id
  1013. FROM get_portfolio_bfi_factors(portfolio_ids, start_month.temporalFormat('yyyy-MM'), end_day.temporalFormat('yyyy-MM'));
  1014. if(bfi_benchmark.isVoid() || bfi_benchmark.size() == 0) { return null; }
  1015. bmk_ret = get_benchmark_return(bfi_benchmark, end_day);
  1016. if(bmk_ret.isVoid() || bmk_ret.size() == 0) { return null; }
  1017. risk_free_rate = SELECT fund_id, temporalParse(end_date, 'yyyy-MM') AS end_date, ret FROM get_risk_free_rate(very_old_date, end_day);
  1018. if(risk_free_rate.isVoid() || risk_free_rate.size() == 0) { return null; }
  1019. t0 = cal_trailing_bfi_indicators(portfolio_info, bfi_benchmark, end_day, tb_ret, bmk_ret, risk_free_rate);
  1020. v_table_name = ['PBI-INCEP', 'PBI-YTD', 'PBI-6M', 'PBI-1Y', 'PBI-2Y', 'PBI-3Y', 'PBI-4Y', 'PBI-5Y', 'PBI-10Y'];
  1021. return dict(v_table_name, t0);
  1022. }