1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556575859606162636465666768697071727374757677787980818283848586878889909192939495969798991001011021031041051061071081091101111121131141151161171181191201211221231241251261271281291301311321331341351361371381391401411421431441451461471481491501511521531541551561571581591601611621631641651661671681691701711721731741751761771781791801811821831841851861871881891901911921931941951961971981992002012022032042052062072082092102112122132142152162172182192202212222232242252262272282292302312322332342352362372382392402412422432442452462472482492502512522532542552562572582592602612622632642652662672682692702712722732742752762772782792802812822832842852862872882892902912922932942952962972982993003013023033043053063073083093103113123133143153163173183193203213223233243253263273283293303313323333343353363373383393403413423433443453463473483493503513523533543553563573583593603613623633643653663673683693703713723733743753763773783793803813823833843853863873883893903913923933943953963973983994004014024034044054064074084094104114124134144154164174184194204214224234244254264274284294304314324334344354364374384394404414424434444454464474484494504514524534544554564574584594604614624634644654664674684694704714724734744754764774784794804814824834844854864874884894904914924934944954964974984995005015025035045055065075085095105115125135145155165175185195205215225235245255265275285295305315325335345355365375385395405415425435445455465475485495505515525535545555565575585595605615625635645655665675685695705715725735745755765775785795805815825835845855865875885895905915925935945955965975985996006016026036046056066076086096106116126136146156166176186196206216226236246256266276286296306316326336346356366376386396406416426436446456466476486496506516526536546556566576586596606616626636646656666676686696706716726736746756766776786796806816826836846856866876886896906916926936946956966976986997007017027037047057067077087097107117127137147157167177187197207217227237247257267277287297307317327337347357367377387397407417427437447457467477487497507517527537547557567577587597607617627637647657667677687697707717727737747757767777787797807817827837847857867877887897907917927937947957967977987998008018028038048058068078088098108118128138148158168178188198208218228238248258268278288298308318328338348358368378388398408418428438448458468478488498508518528538548558568578588598608618628638648658668678688698708718728738748758768778788798808818828838848858868878888898908918928938948958968978988999009019029039049059069079089099109119129139149159169179189199209219229239249259269279289299309319329339349359369379389399409419429439449459469479489499509519529539549559569579589599609619629639649659669679689699709719729739749759769779789799809819829839849859869879889899909919929939949959969979989991000100110021003100410051006100710081009101010111012101310141015101610171018101910201021102210231024102510261027102810291030103110321033103410351036103710381039104010411042104310441045104610471048104910501051105210531054105510561057105810591060106110621063106410651066106710681069107010711072107310741075107610771078107910801081108210831084108510861087108810891090109110921093109410951096109710981099110011011102110311041105110611071108110911101111111211131114111511161117111811191120112111221123112411251126112711281129113011311132113311341135113611371138113911401141114211431144114511461147114811491150115111521153115411551156115711581159116011611162116311641165116611671168116911701171117211731174117511761177117811791180118111821183118411851186118711881189119011911192119311941195119611971198119912001201120212031204120512061207120812091210121112121213121412151216121712181219122012211222122312241225122612271228122912301231123212331234123512361237123812391240124112421243124412451246124712481249125012511252125312541255125612571258125912601261126212631264126512661267126812691270127112721273127412751276127712781279128012811282128312841285128612871288128912901291129212931294129512961297129812991300130113021303130413051306130713081309131013111312131313141315131613171318131913201321132213231324132513261327132813291330133113321333133413351336133713381339134013411342134313441345134613471348134913501351135213531354135513561357135813591360136113621363136413651366136713681369137013711372137313741375137613771378137913801381 |
- module fundit::indicatorCalculator
- use fundit::sqlUtilities
- use fundit::operationDataPuller
- use fundit::performanceDataPuller
- use fundit::ms_dataPuller
- use fundit::returnCalculator
- use fundit::navCalculator
- /*
- * 将VaR包裹一层,使之成为系统认可的聚集函数
- * @param returns <DOUBLE VECTOR>: 非空收益率
- * @param method <STRING>: 'normal', 'logNormal', 'historical', 'monteCarlo'
- * @param confidenceLevel <DOUBLE>: 置信水平,取值区间(0, 1)
- *
- */
- defg aggVaR(returns, method, confidenceLevel) {
- if(returns.form() != 1) return null;
-
- return returns.VaR(method, confidenceLevel);
- }
- /*
- * 将CVaR包裹一层,使之成为系统认可的聚集函数
- * @param returns <DOUBLE VECTOR>: 非空收益率
- * @param method <STRING>: 'normal', 'logNormal', 'historical', 'monteCarlo'
- * @param confidenceLevel <DOUBLE>: 置信水平,取值区间(0, 1)
- *
- */
- defg aggCVaR(returns, method, confidenceLevel) {
- if(returns.form() != 1) return null;
- return returns.CVaR(method, confidenceLevel);
- }
- /*
- * 最大回撤
- *
- *
- */
- defg maxDrawdown(navs) {
- return max(1 - navs \ cummax(navs));
- }
- /*
- * 几何平均值
- *
- */
- defg geometricMean(x){
-
- return x.log().avg().exp()
- }
- /*
- * Trailing Monthly Return, Standard Deviation, Skewness, Kurtosis, Max Drawdown, VaR, CVaR, Calmar Ratio
- *
- * @param entity_info <TABLE>: xxx_information表,NEED COLUMNS entity_id, inception_date
- * @param ret <TABLE>: 收益表,需要有 entity_id, price_dat, end_date, nav
- * @param trailing_month <STRING>: trailing X month or ytd, incep
- *
- * NOTE: standard deviation of Java version is noncompliant-GIPS annulized number
- *
- * Create: 20240904 Joey
- * TODO: SQL is wrong for max drawdowns
- * TODO: var, cvar, calmar are off; std dev, skewness, kurtosis are slightly off
- * TODO: SQL is missing for portfolio since inception date return
- * TODO: Java calculates max drawdown even there is no nav
- * TODO: Java ytd worst month could be wrong (i.e. portfolio 166002, 2024-03)
- * TODO: arith_mean & gerom_mean ARE NOT TESTED
- *
- */
- def cal_basic_performance(entity_info, ret, trailing_month) {
- // accumulate 版的 skewness, kurtosis, var, cvar 似乎都不对劲,只好找个笨办法来实现
- if(trailing_month == 'incep') {
- // 需要至少6个数才计算标准差、峰度、偏度
- t0 = SELECT price_date.max() AS price_date, nav, ret,
- ret.mean() AS arith_mean, (1+ret).prod().pow(1\count(entity_id))-1 AS geom_mean,
- iif(count(entity_id) > 5, std(ret), null) AS std_dev,
- iif(count(entity_id) > 5, skew(ret, false), null) AS skewness,
- iif(count(entity_id) > 5, kurtosis(ret, false), null)-3 AS kurtosis,
- min(ret) AS wrst_month
- FROM ret
- WHERE ret > -1
- GROUP BY entity_id
- CGROUP BY end_date
- ORDER BY entity_id, end_date;
- // 年化收益(给后面计算Calmar用)
- t0.addColumn(['trailing_ret', 'trailing_ret_a'], [DOUBLE, DOUBLE]);
- // MySQL 有bug导致首月ret_1m为空,所以用 prod(1+ret)-1算的有时不对
- UPDATE t0
- SET trailing_ret = nav\ini_value - 1,
- trailing_ret_a = iif(t0.end_date - ei.inception_date.month() > 12, (nav\ini_value).pow(12\(t0.end_date - ei.inception_date.month())) - 1, nav\ini_value - 1)
- FROM ej(t0, entity_info ei, 'entity_id');
-
- // 不会用上面的办法算最大回撤, VaR, CVaR
- t_var = SELECT entity_id, end_date, ret,
- cummax(1 - nav \ cummax(nav)) AS drawdown,
- - cumpercentile(ret, 5, 'linear') AS var
- FROM ret WHERE ret > -1
- CONTEXT BY entity_id;
- t_cvar = SELECT entity_id, end_date, drawdown, var,
- - cumavg(iif(ret <= -var, ret, null)) AS cvar
- FROM t_var
- CONTEXT BY entity_id;
- t1 = SELECT t0.*, t_cvar.drawdown, t_cvar.var, t_cvar.cvar
- FROM t0 LEFT JOIN t_cvar ON t0.entity_id = t_cvar.entity_id AND t0.end_date = t_cvar.end_date
- ORDER BY t0.entity_id, t0.end_date;
-
- } else if(trailing_month == 'ytd') {
- t1 = SELECT entity_id, end_date, price_date.cummax() AS price_date, nav, ret,
- ret.cumavg() AS arith_mean, (1+ret).cumprod().pow(1\cumcount(entity_id))-1 AS geom_mean,
- cumprod(1+ret)-1 AS trailing_ret,
- cumprod(1+ret)-1 AS trailing_ret_a, // no need annulization for ytd
- iif(cumcount(entity_id) > 5, cumstd(ret), null) AS std_dev,
- iif(cumcount(entity_id) > 5, tmoving(skew{, false}, end_date, ret, 12), null) AS skewness,
- iif(cumcount(entity_id) > 5, tmoving(kurtosis{, false}, end_date, ret, 12)-3, null) AS kurtosis,
- cummin(ret) AS wrst_month,
- cummax(1 - nav \ cummax(nav)) AS drawdown
- FROM ret WHERE ret > -1
- CONTEXT BY entity_id, end_date.year()
- ORDER BY entity_id, end_date;
- // trailing x month
- } else {
- // 先转成STRING,避免单字符被认为是CHAR而导致转整型出错的结果
- win = trailing_month$STRING$INT;
- t1 = SELECT entity_id, end_date, price_date.mmax(win) AS price_date, nav, ret,
- ret.mavg(win) AS arith_mean, (1+ret).mprod(win).pow(1\mcount(entity_id, win))-1 AS geom_mean,
- mprod(1+ret, win)-1 AS trailing_ret,
- iif(win > 12,
- mprod(1+ret, win).pow(12\win)-1,
- mprod(1+ret, win)-1) AS trailing_ret_a,
- mstd(ret, win) AS std_dev,
- mskew(ret, win, false) AS skewness,
- mkurtosis(ret, win, false) - 3 AS kurtosis,
- mmin(ret, win) AS wrst_month,
- moving(maxDrawdown, nav, win) AS drawdown,
- moving(aggVaR{, 'historical', 0.95}, ret, win) AS var,
- moving(aggCVaR{, 'historical', 0.95}, ret, win) AS cvar
- FROM ret WHERE ret > -1
- CONTEXT BY entity_id
- ORDER BY entity_id, end_date;
- }
- t1.addColumn('calmar', DOUBLE);
- UPDATE t1 SET calmar = iif(drawdown == 0, null, trailing_ret_a\drawdown);
- return t1;
- }
- /*
- * Lower Partial Moment
- * NOTE: risk free rate is used as Minimal Accepted Rate (MAR) here
- *
- */
- def cal_LPM(ret, risk_free, trailing_month) {
- t = SELECT *, cumcount(entity_id) AS cnt FROM ret WHERE ret > -1 CONTEXT BY entity_id;
- if(trailing_month == 'incep') {
- lpm = SELECT entity_id, end_date,
- 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,
- 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,
- 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
- FROM t
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- CONTEXT BY entity_id
- ORDER BY entity_id, end_date;
-
- } else if(trailing_month == 'ytd') {
- lpm = SELECT entity_id, end_date,
- 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,
- 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,
- 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
- FROM t
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- CONTEXT BY entity_id, end_date.year()
- ORDER BY entity_id, end_date;
- } else {
- win = trailing_month$STRING$INT;
- lpm = SELECT t.entity_id, t.end_date,
- (msum (iif(rfr.ret > t.ret, rfr.ret - t.ret, 0), win) \ mcount(end_date, win)).pow(1\1) AS lpm1,
- (msum2(iif(rfr.ret > t.ret, rfr.ret - t.ret, 0), win) \ mcount(end_date, win)).pow(1\2) AS lpm2,
- (moving(sum3, iif(rfr.ret > t.ret, rfr.ret - t.ret, 0), win) \ mcount(end_date, win)).pow(1\3) AS lpm3
- FROM t
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- CONTEXT BY t.entity_id
- ORDER BY entity_id, end_date;
- }
-
- return lpm;
- }
- /*
- * Downside Devision, Omega Ratio, Sortino Ratio, Kappa Ratio
- *
- * TODO: Java version of Downside Deviation (LPM2) uses cnt-1 as denominator to calculate mean excess return, which might be wrong
- * Java version of Omega could be wrong because Java uses annualized returns and cnt-1
- * Java'version of Kappa could be very wrong
- *
- */
- def cal_omega_sortino_kappa(ret, risk_free, trailing_month) {
- lpm = cal_LPM(ret, risk_free, trailing_month);
- if(trailing_month == 'incep') {
- tb = SELECT t.entity_id, t.end_date,
- l.lpm2 AS ds_dev,
- iif(l.lpm1.round(4) == 0, NULL, (t.ret - rfr.ret ).cumavg() \ l.lpm1 + 1) AS omega,
- iif(l.lpm2.round(4) == 0, NULL, (t.ret - rfr.ret ).cumavg() \ l.lpm2) AS sortino,
- iif(l.lpm3.round(4) == 0, NULL, (t.ret - rfr.ret ).cumavg() \ l.lpm3) AS kappa
- FROM ret t
- INNER JOIN lpm l ON t.entity_id = l.entity_id AND t.end_date = l.end_date
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE t.ret > -1
- CONTEXT BY t.entity_id;
- } else if(trailing_month == 'ytd') {
- tb = SELECT t.entity_id, t.end_date,
- l.lpm2 AS ds_dev,
- iif(l.lpm1.round(4) == 0, NULL, (t.ret - rfr.ret ).cumavg() \ l.lpm1 + 1) AS omega,
- iif(l.lpm2.round(4) == 0, NULL, (t.ret - rfr.ret ).cumavg() \ l.lpm2) AS sortino,
- iif(l.lpm3.round(4) == 0, NULL, (t.ret - rfr.ret ).cumavg() \ l.lpm3) AS kappa
- FROM ret t
- INNER JOIN lpm l ON t.entity_id = l.entity_id AND t.end_date = l.end_date
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE t.ret > -1
- CONTEXT BY t.entity_id, t.end_date.year();
- } else {
- win = trailing_month$STRING$INT;
-
- tb = SELECT t.entity_id, t.end_date,
- l.lpm2 AS ds_dev,
- iif(l.lpm1.round(4) == 0, NULL, (t.ret - rfr.ret ).mavg(win) \ l.lpm1 + 1) AS omega,
- iif(l.lpm2.round(4) == 0, NULL, (t.ret - rfr.ret ).mavg(win) \ l.lpm2) AS sortino,
- iif(l.lpm3.round(4) == 0, NULL, (t.ret - rfr.ret ).mavg(win) \ l.lpm3) AS kappa
- FROM ret t
- INNER JOIN lpm l ON t.entity_id = l.entity_id AND t.end_date = l.end_date
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE t.ret > -1
- CONTEXT BY t.entity_id;
- }
- return tb;
- }
- /*
- * Winning Ratio, Tracking Error, Information Ratio
- *
- * NOTE: mcount is very unique in mFun, because it doesn't support minPeriods(BUG?), while others default minPeriods = window.
- * As a result, we have to delete records having winrate but no tracking error and info ratio for the sake of consisence
- *
- * TODO: Win Rate incept is off, because Java incorrectly takes all end_date as denominator even when benchmark has no price
- * Information Ratio is way off!
- * Not sure how to describe a giant number("inf"), for now 999 is used
- */
- def cal_benchmark_tracking(ret, benchmarks, bmk_ret, trailing_month) {
- if(trailing_month == 'incep') {
- t0 = SELECT t.entity_id, t.end_date, t.price_date,
- t.ret, bmk.ret AS ret_bmk,
- t.entity_id.cumcount() AS cnt,
- t.ret - bmk.ret AS exc_ret, bm.benchmark_id
- FROM ret t
- INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
- INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id
- WHERE t.ret > -1
- AND bmk.ret > -1
- CONTEXT BY t.entity_id, bm.benchmark_id;
- t = SELECT entity_id, end_date, benchmark_id,
- iif(cnt > 5, cumcount(iif(exc_ret >= 0, 1, null)) \ cnt, null) AS winrate,
- iif(cnt > 5, exc_ret.cumstd(), null) AS track_error,
- iif(cnt > 5, iif(exc_ret.cumstd() == 0, null, exc_ret.cumavg() \ exc_ret.cumstd()), 5) AS info
- FROM t0
- CONTEXT BY entity_id, benchmark_id
- ORDER BY entity_id, end_date, benchmark_id;
- } else if(trailing_month == 'ytd') {
- t0 = SELECT t.entity_id, t.end_date, t.price_date,
- t.ret, bmk.ret AS ret_bmk,
- t.entity_id.cumcount() AS cnt, t.ret - bmk.ret AS exc_ret, bm.benchmark_id
- FROM ret t
- INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
- INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id
- WHERE t.ret > -1
- AND bmk.ret > -1
- CONTEXT BY t.entity_id, bm.benchmark_id, t.end_date.year();
- t = SELECT entity_id, end_date, benchmark_id,
- iif(cnt > 5, cumcount(iif(exc_ret >= 0, 1, null)) \ cnt, null) AS winrate,
- iif(cnt > 5, exc_ret.cumstd(), null) AS track_error,
- iif(cnt > 5, iif(exc_ret.cumstd() == 0, null, exc_ret.cumavg() \ exc_ret.cumstd()), null) AS info
- FROM t0
- CONTEXT BY entity_id, benchmark_id, end_date.year()
- ORDER BY entity_id, end_date, benchmark_id;
- } else {
- win = trailing_month$STRING$INT;
- t0 = SELECT t.entity_id, t.end_date, t.price_date,
- t.ret, bmk.ret AS ret_bmk,
- t.entity_id.mcount(win) AS cnt,
- t.ret - bmk.ret AS exc_ret, bm.benchmark_id
- FROM ret t
- INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
- INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id
- WHERE t.ret > -1
- AND bmk.ret > -1
- CONTEXT BY t.entity_id, bm.benchmark_id;
- t = SELECT entity_id, end_date, benchmark_id,
- iif(cnt > 5, mcount(iif(exc_ret >= 0, 1, null), win) \ cnt, null) AS winrate,
- iif(cnt > 5, mstd(exc_ret, win), null) AS track_error,
- iif(cnt > 5, iif(mstd(exc_ret, win) == 0, null, mavg(exc_ret, win) \ mstd(exc_ret, win)), null) AS info
- FROM t0
- CONTEXT BY entity_id, benchmark_id
- ORDER BY entity_id, end_date, benchmark_id;
- }
- return t; //SELECT * FROM t WHERE track_error IS NOT NULL;
- }
- /*
- * Alpha & Beta
- * NOTE: alpha of Java version is wrong because it doesn't use risk free rate
- */
- def cal_alpha_beta(ret, benchmarks, bmk_ret, risk_free, trailing_month) {
- t = SELECT t.entity_id, t.end_date, t.ret, bm.benchmark_id, bmk.ret AS ret_bmk
- FROM ret t
- INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
- INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id
- WHERE t.ret > -1
- AND bmk.ret > -1;
- if(trailing_month == 'incep') {
- beta = SELECT entity_id, end_date, benchmark_id,
- iif(cumcount(end_date) > 5, ret.cumbeta(ret_bmk), null) AS beta
- FROM t CONTEXT BY entity_id, benchmark_id;
- alpha = SELECT t.entity_id, t.end_date, t.benchmark_id, beta.beta AS beta,
- (t.ret - rfr.ret).cumavg() - beta.beta * (t.ret_bmk - rfr.ret).cumavg() AS alpha
- FROM t
- 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
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- CONTEXT BY t.entity_id, t.benchmark_id
- ORDER BY t.entity_id, t.end_date, t.benchmark_id;
- } else if(trailing_month == 'ytd') {
- beta = SELECT entity_id, end_date, benchmark_id,
- iif(cumcount(end_date) > 5, ret.cumbeta(ret_bmk), null) AS beta
- FROM t CONTEXT BY entity_id, benchmark_id, end_date.year();
- alpha = SELECT t.entity_id, t.end_date, t.benchmark_id, beta.beta AS beta,
- (t.ret - rfr.ret).cumavg() - beta.beta * (t.ret_bmk - rfr.ret).cumavg() AS alpha
- FROM t
- 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
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- CONTEXT BY t.entity_id, t.benchmark_id, t.end_date.year()
- ORDER BY t.entity_id, t.end_date, t.benchmark_id;
- } else {
- win = trailing_month$STRING$INT;
- beta = SELECT entity_id, end_date, benchmark_id,
- iif(mcount(end_date, win) > 5, ret.mbeta(ret_bmk, win), null) AS beta
- FROM t CONTEXT BY entity_id, benchmark_id;
- alpha = SELECT t.entity_id, t.end_date, t.benchmark_id, beta.beta AS beta,
- (t.ret - rfr.ret).mavg(win) - beta.beta * (t.ret_bmk - rfr.ret).mavg(win) AS alpha
- FROM t
- 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
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- CONTEXT BY t.entity_id, t.benchmark_id
- ORDER BY t.entity_id, t.end_date, t.benchmark_id;
- }
- return alpha;
- }
- /*
- * Upside/Down Capture Return/Ratio
- *
- * TODO: trailing x month values are way off!
- *
- */
- def cal_capture_ratio(ret, benchmarks, bmk_ret, trailing_month) {
- if(trailing_month == 'incep') {
- t1 = SELECT t.entity_id, t.end_date,
- (1 + iif(bmk.ret >= 0, t.ret, 0)).cumprod() AS upside_ret,
- (1 + iif(bmk.ret >= 0, bmk.ret, 0)).cumprod() AS bmk_upside_ret,
- cumcount(iif(bmk.ret >= 0, 1, null)) AS bmk_upside_cnt,
- (1 + iif(bmk.ret < 0, t.ret, 0)).cumprod() AS downside_ret,
- (1 + iif(bmk.ret < 0, bmk.ret, 0)).cumprod() AS bmk_downside_ret,
- cumcount(iif(bmk.ret < 0, 1, null)) AS bmk_downside_cnt,
- bm.benchmark_id
- FROM ret t
- INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
- 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
- WHERE t.ret > -1
- AND bmk.ret > -1
- CONTEXT BY t.entity_id, bm.benchmark_id;
- } else if(trailing_month == 'ytd') {
- t1 = SELECT t.entity_id, t.end_date,
- (1 + iif(bmk.ret >= 0, t.ret, 0)).cumprod() AS upside_ret,
- (1 + iif(bmk.ret >= 0, bmk.ret, 0)).cumprod() AS bmk_upside_ret,
- cumcount(iif(bmk.ret >= 0, 1, null)) AS bmk_upside_cnt,
- (1 + iif(bmk.ret < 0, t.ret, 0)).cumprod() AS downside_ret,
- (1 + iif(bmk.ret < 0, bmk.ret, 0)).cumprod() AS bmk_downside_ret,
- cumcount(iif(bmk.ret < 0, 1, null)) AS bmk_downside_cnt,
- bm.benchmark_id
- FROM ret t
- INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
- 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
- WHERE t.ret > -1
- AND bmk.ret > -1
- CONTEXT BY t.entity_id, bm.benchmark_id, t.end_date.year();
- } else {
- win = trailing_month$STRING$INT;
- t1 = SELECT t.entity_id, t.end_date,
- (1 + iif(bmk.ret >= 0, t.ret, 0)).mprod(win) AS upside_ret,
- (1 + iif(bmk.ret >= 0, bmk.ret, 0)).mprod(win) AS bmk_upside_ret,
- mcount(iif(bmk.ret >= 0, 1, null), win) AS bmk_upside_cnt,
- (1 + iif(bmk.ret < 0, t.ret, 0)).mprod(win) AS downside_ret,
- (1 + iif(bmk.ret < 0, bmk.ret, 0)).mprod(win) AS bmk_downside_ret,
- mcount(iif(bmk.ret < 0, 1, null), win) AS bmk_downside_cnt,
- bm.benchmark_id
- FROM ret t
- INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
- 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
- WHERE t.ret > -1
- AND bmk.ret > -1
- CONTEXT BY t.entity_id, bm.benchmark_id;
- }
- t = SELECT entity_id, end_date, benchmark_id,
- iif(t1.bmk_upside_cnt == 0, NULL, t1.upside_ret.pow(1 \ t1.bmk_upside_cnt)-1) AS upside_capture_ret,
- iif(t1.bmk_upside_cnt == 0, NULL, (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,
- iif(t1.bmk_downside_cnt == 0, NULL, t1.downside_ret.pow(1 \ t1.bmk_downside_cnt)-1) AS downside_capture_ret,
- iif(t1.bmk_downside_cnt == 0, NULL, (t1.downside_ret.pow(1 \ t1.bmk_downside_cnt)-1)/(t1.bmk_downside_ret.pow(1 \ t1.bmk_downside_cnt)-1)) AS downside_capture_ratio
- FROM t1
- ORDER BY entity_id, benchmark_id, end_date;
- return t;
- }
- /*
- * Sharpe Ratio
- * NOTE: Java version is noncompliant-GIPS annulized number
- */
- def cal_sharpe(ret, std_dev, risk_free, trailing_month) {
- if(trailing_month == 'incep') {
- sharpe = SELECT t.entity_id, t.end_date, (t.ret - rfr.ret).cumavg() \ std.std_dev AS sharpe
- FROM ret t
- INNER JOIN std_dev std ON t.entity_id = std.entity_id AND t.end_date = std.end_date
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE std.std_dev.round(4) <> 0 AND t.ret > -1
- CONTEXT BY t.entity_id;
-
- } else if(trailing_month == 'ytd') {
- sharpe = SELECT t.entity_id, t.end_date, (t.ret - rfr.ret).cumavg() \ std.std_dev AS sharpe
- FROM ret t
- INNER JOIN std_dev std ON t.entity_id = std.entity_id AND t.end_date = std.end_date
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE std.std_dev.round(4) <> 0 AND t.ret > -1
- CONTEXT BY t.entity_id, t.end_date.year();
- } else {
- win = trailing_month$STRING$INT;
- sharpe = SELECT t.entity_id, t.end_date, (t.ret - rfr.ret).mavg(win) \ std.std_dev AS sharpe
- FROM ret t
- INNER JOIN std_dev std ON t.entity_id = std.entity_id AND t.end_date = std.end_date
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE std.std_dev.round(4) <> 0 AND t.ret > -1
- CONTEXT BY t.entity_id;
- }
- return sharpe;
- }
- /*
- * Treynor Ratio = annulized excess return / beta
- *
- * TODO: ytd is off because Java uses non-GIPS rule to annulize return
- */
- def cal_treynor(ret, risk_free, beta, trailing_month) {
- if(trailing_month == 'incep') {
- t = SELECT *, cumcount(entity_id) AS cnt
- FROM ret t
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE t.ret > -1
- AND rfr.ret > -1
- CONTEXT BY t.entity_id;
-
- treynor = SELECT t.entity_id, t.end_date, beta.benchmark_id,
- iif(beta.beta.round(4) == 0, NULL,
- ((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
- FROM t
- INNER JOIN beta AS beta ON t.entity_id = beta.entity_id AND t.end_date = beta.end_date
- CONTEXT BY t.entity_id, beta.benchmark_id;
- } else if(trailing_month == 'ytd') {
- t = SELECT *, cumcount(entity_id) AS cnt
- FROM ret t
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE t.ret > -1
- AND rfr.ret > -1
- CONTEXT BY t.entity_id, t.end_date.year();
-
- treynor = SELECT t.entity_id, t.end_date, beta.benchmark_id,
- iif(beta.beta.round(4) == 0, NULL,
- ((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
- FROM t
- INNER JOIN beta AS beta ON t.entity_id = beta.entity_id AND t.end_date = beta.end_date
- CONTEXT BY t.entity_id, beta.benchmark_id, t.end_date.year();
- } else {
- win = trailing_month$STRING$INT;
- t = SELECT *, mcount(entity_id, win) AS cnt
- FROM ret t
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE t.ret > -1
- AND rfr.ret > -1
- CONTEXT BY t.entity_id;
-
- treynor = SELECT t.entity_id, t.end_date, beta.benchmark_id,
- iif(beta.beta.round(4) == 0, NULL,
- ((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
- FROM t
- INNER JOIN beta AS beta ON t.entity_id = beta.entity_id AND t.end_date = beta.end_date
- CONTEXT BY t.entity_id, beta.benchmark_id;
- }
- return treynor;
- }
- /*
- * Jensen's Alpha
- * TODO: the result is slightly off
- */
- def cal_jensen(ret, bmk_ret, risk_free, beta, trailing_month) {
- if(trailing_month == 'incep') {
-
- 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
- FROM ret t
- INNER JOIN beta beta ON t.entity_id = beta.entity_id AND t.end_date = beta.end_date
- INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND beta.benchmark_id = bmk.benchmark_id
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE t.ret > -1
- CONTEXT BY t.entity_id, beta.benchmark_id;
- } else if(trailing_month == 'ytd') {
- 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
- FROM ret t
- INNER JOIN beta beta ON t.entity_id = beta.entity_id AND t.end_date = beta.end_date
- INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND beta.benchmark_id = bmk.benchmark_id
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE t.ret > -1
- CONTEXT BY t.entity_id, beta.benchmark_id, t.end_date.year();
- } else {
- win = trailing_month$STRING$INT;
- 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
- FROM ret t
- INNER JOIN beta beta ON t.entity_id = beta.entity_id AND t.end_date = beta.end_date
- INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND beta.benchmark_id = bmk.benchmark_id
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE t.ret > -1
- CONTEXT BY t.entity_id, beta.benchmark_id;
- }
- return jensen;
- }
- /*
- * Modigliani Modigliani Measure (M2)
- * NOTE: M2 = sharpe * std(benchmark) + risk_free_rate
- * NOTE: Java version is noncompliant-GIPS annulized number
- */
- def cal_m2(ret, benchmarks, bmk_ret, risk_free, trailing_month) {
- if(trailing_month == 'incep') {
-
- m2 = SELECT t.entity_id, t.end_date,
- iif(t.entity_id.cumcount() > 5,
- iif(t.ret.cumstd().round(4) == 0, NULL, (t.ret - rfr.ret).cumavg() \ t.ret.cumstd() * bmk.ret.cumstd() + rfr.ret.cumavg()),
- NULL) AS m2, bm.benchmark_id
- FROM ret t
- INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
- INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE t.ret > -1
- CONTEXT BY t.entity_id, bm.benchmark_id;
- } else if(trailing_month == 'ytd') {
- m2 = SELECT t.entity_id, t.end_date,
- iif(t.entity_id.cumcount() > 5,
- iif(t.ret.cumstd().round(4) == 0, NULL, (t.ret - rfr.ret).cumavg() \ t.ret.cumstd() * bmk.ret.cumstd() + rfr.ret.cumavg()),
- NULL) AS m2, bm.benchmark_id
- FROM ret t
- INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
- INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE t.ret > -1
- CONTEXT BY t.entity_id, bm.benchmark_id, t.end_date.year();
- } else {
- win = trailing_month$STRING$INT;
- m2 = SELECT t.entity_id, t.end_date,
- iif(t.entity_id.mcount(win) > 5,
- iif(t.ret.mstd(win) == 0, NULL, (t.ret - rfr.ret).mavg(win) \ t.ret.mstd(win) * bmk.ret.mstd(win) + rfr.ret.mavg(win)),
- NULL) AS m2, bm.benchmark_id
- FROM ret t
- INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
- INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE t.ret > -1
- CONTEXT BY t.entity_id, bm.benchmark_id;
- }
- return m2;
- }
- /*
- * Morningstar Return, Morningstar Risk-Adjusted Return
- *
- * TODO: Tax and loads are NOT taken care of
- * TODO: Assume Chinese methodology using 3, 5, 10 as number of traling years
- * TODO: need verify with reliable results
- *
- * NOTE: Morningstar methodology requires monthly return for calculation, so that "12" is hard-coded here
- *
- *
- */
- def cal_ms_return(ret, risk_free, trailing_month) {
- win = trailing_month$STRING$INT;
- r = SELECT t.entity_id, t.end_date,
- iif(t.end_date.mmax(win) == t.end_date.mmin(win), NULL,
- ((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,
- (1 + t.ret).pow(-2).mavg(win).pow(-12/2)-1 AS ms_rar_a
- FROM ret t
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE t.ret > -1
- CONTEXT BY t.entity_id;
- return r;
- }
- /*
- * 有效主体-基准对应表
- *
- * @param benchmarks <TABLE>: entity-benchmark 的对应关系表 NEED COLUMNS: entity_id, end_date, benchmark_id
- * @param end_day <DATE>:
- * @param trailing_month <STRING>:
- * @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
- * 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
- *
- */
- def get_effective_benchmarks(benchmarks, end_day, trailing_month, isEffectiveOnly) {
- min_pct = 0.5;
- if(isEffectiveOnly) {
- t_dates = SELECT DISTINCT entity_id, end_date FROM benchmarks WHERE end_date <= end_day.month();
- if(trailing_month == 'incep') {
- t = SELECT entity_id, end_date, end_date.cumcount() AS cnt FROM t_dates CONTEXT BY entity_id;
-
- bmk = SELECT bmk.* FROM benchmarks bmk
- INNER JOIN t ON bmk.entity_id = t.entity_id AND bmk.end_date = t.end_date
- CONTEXT BY bmk.entity_id, bmk.benchmark_id
- HAVING bmk.end_date.cumcount() >= t.cnt * min_pct;
- } else if(trailing_month == 'ytd') {
- t = SELECT entity_id, end_date, end_date.cumcount() AS cnt FROM t_dates CONTEXT BY entity_id, end_date.year();
-
- bmk = SELECT bmk.* FROM benchmarks bmk
- INNER JOIN t ON bmk.entity_id = t.entity_id AND bmk.end_date = t.end_date
- CONTEXT BY entity_id, benchmark_id, end_date.year()
- HAVING bmk.end_date.cumcount() >= t.cnt * min_pct;
- } else {
- win = trailing_month$STRING$INT;
- t = SELECT entity_id, end_date, end_date.mcount(win) AS cnt FROM t_dates CONTEXT BY entity_id;
-
- bmk = SELECT bmk.* FROM benchmarks bmk
- INNER JOIN t ON bmk.entity_id = t.entity_id AND bmk.end_date = t.end_date
- CONTEXT BY entity_id, benchmark_id
- HAVING bmk.end_date.mcount(win) >= t.cnt * min_pct;
- }
- } else {
- bmk = SELECT * FROM benchmarks WHERE end_date <= end_day.month();
- }
- return bmk;
- }
- /*
- * Calculation for monthly indicators which need benchmark
- *
- * @param entity_info <TABLE>: xxx_information表,NEED COLUMNS entity_id, inception_date
- * @param benchmark_mapping <TABLE>: entity-benchmark mapping table, NEED COLUMNS entity_id, end_date, benchmark_id
- * @param end_day <DATE>;
- * @param tb_ret <TABLE>: 收益表,NEED COLUMNS entity_id, price_dat, end_date, nav
- * @param index_ret <TABLE>: historical benchmark return table, NEED COLUMNS fund_id, end_date, ret
- * @param risk_free <TABLE>: historical risk free rate table, NEED COLUMNS fund_id, end_date, ret
- * @param month <INT>: trailing x month
- *
- * @return: indicators table
- *
- *
- * 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
- * TODO: some datapoints require more data, we need a way to disable calculation for them
- *
- */
- def cal_indicators_with_benchmark(entity_info, benchmark_mapping, end_day, tb_ret, index_ret, risk_free, month) {
- if(entity_info.isVoid() || entity_info.size() == 0 || benchmark_mapping.isVoid() || benchmark_mapping.size() == 0 ) return null;
- if(tb_ret.isVoid() || tb_ret.size() == 0 || index_ret.isVoid() || index_ret.size() == 0 || risk_free.isVoid() || risk_free.size() == 0 ) return null;
- // sorting for correct first() and last() value
- ret = SELECT * FROM tb_ret WHERE ret > -1 AND end_date <= end_day.month() ORDER BY entity_id, price_date;
- // get the effective benchmarks
- benchmarks = get_effective_benchmarks(benchmark_mapping, end_day, month, true);
- if(ret.isVoid() || ret.size() == 0 || benchmarks.isVoid() || benchmarks.size() == 0) return null;
- // alpha, beta
- alpha_beta = cal_alpha_beta(ret, benchmarks, index_ret, risk_free, month);
- // 胜率、跟踪误差、信息比率
- bmk_tracking = cal_benchmark_tracking(ret, benchmarks, index_ret, month);
- // 特雷诺
- treynor = cal_treynor(ret, risk_free, alpha_beta, month);
- // 詹森指数
- jensen = cal_jensen(ret, index_ret, risk_free, alpha_beta, month);
- // M2
- m2 = cal_m2(ret, benchmarks, index_ret, risk_free, month);
- // 上下行捕获率、收益
- capture_r = cal_capture_ratio(ret, benchmarks, index_ret, month);
- r = SELECT * FROM bmk_tracking a1
- 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
- LEFT JOIN treynor ON a1.entity_id = treynor.entity_id AND a1.benchmark_id = treynor.benchmark_id AND a1.end_date = treynor.end_date
- LEFT JOIN jensen ON a1.entity_id = jensen.entity_id AND a1.benchmark_id = jensen.benchmark_id AND a1.end_date = jensen.end_date
- LEFT JOIN m2 ON a1.entity_id = m2.entity_id AND a1.benchmark_id = m2.benchmark_id AND a1.end_date = m2.end_date
- 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;
- // 年化各数据点
- // GIPS RULE: NO annulization for data less than 1 year
- plainAnnu = get_annulization_multiple('m');
- sqrtAnnu = sqrt(get_annulization_multiple('m'));
- r.addColumn(['alpha_a', 'jensen_a', 'track_error_a', 'info_a', 'm2_a'],
- [DOUBLE, DOUBLE, DOUBLE, DOUBLE, DOUBLE]);
- UPDATE r
- SET alpha_a = alpha * iif(end_date - inception_date.month() > 12, plainAnnu, 1),
- jensen_a = jensen * iif(end_date - inception_date.month() > 12, plainAnnu, 1),
- track_error_a = track_error * iif(end_date - inception_date.month() > 12, sqrtAnnu, 1),
- info_a = info * iif(end_date - inception_date.month() > 12, sqrtAnnu, 1),
- m2_a = m2 * iif(end_date - inception_date.month() > 12, plainAnnu, 1)
- FROM ej(r, entity_info, 'entity_id');
-
- return r;
- }
- /*
- * Monthly standard indicator calculation
- *
- * @param entity_info <TABLE>:
- * @param benchmarks <TABLE>: entity-benchmark mapping table
- * @param end_day <DATE>:
- * @param tb_ret <TABLE>: 收益表,NEED COLUMNS entity_id, price_dat, end_date, nav
- * @param benchmark_ret <TABLE>: historical benchmark return table, NEED COLUMNS fund_id, end_date, ret
- * @param risk_free <TABLE>: historical risk free rate table, NEED COLUMNS fund_id, end_date, ret
- * @param month <STRING>:
- *
- * @return: indicators table
- *
- *
- * 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
- *
- */
- def cal_indicators(entity_info, benchmarks, end_day, tb_ret, benchmark_ret, risk_free, month) {
- if(entity_info.isVoid() || entity_info.size() == 0 || benchmarks.isVoid() || benchmarks.size() == 0 ) return null;
- if(tb_ret.isVoid() || tb_ret.size() == 0 || benchmark_ret.isVoid() || benchmark_ret.size() == 0 || risk_free.isVoid() || risk_free.size() == 0 ) return null;
- // sorting for correct first() and last() value
- ret = SELECT * FROM tb_ret WHERE end_date <= end_day.month() ORDER BY entity_id, price_date;
- // 收益、标准差、偏度、峰度、最大回撤、VaR, CVaR、卡玛比率
- rtn = cal_basic_performance(entity_info, ret, month);
- // 夏普
- sharpe = cal_sharpe(ret, rtn, risk_free, month);
- // 整合后的下行标准差、欧米伽、索提诺、卡帕
- lpms = cal_omega_sortino_kappa(ret, risk_free, month);
- // 需要基准的指标们
- indicator_with_benchmark = cal_indicators_with_benchmark(entity_info, benchmarks, end_day, ret, benchmark_ret, risk_free, month);
- r = SELECT * FROM rtn a1
- LEFT JOIN sharpe ON a1.entity_id = sharpe.entity_id AND a1.end_date = sharpe.end_date
- LEFT JOIN lpms ON a1.entity_id = lpms.entity_id AND a1.end_date = lpms.end_date
- LEFT JOIN indicator_with_benchmark bmk ON a1.entity_id = bmk.entity_id AND a1.end_date = bmk.end_date;
- // 晨星收益和风险
- if(month$STRING in ['36', '60', '120']) {
- ms = cal_ms_return(ret, risk_free, month);
- r = SELECT * FROM r LEFT JOIN ms ON r.entity_id = ms.entity_id AND r.end_date = ms.end_date;
- }
- // 年化各数据点
- // GIPS RULE: NO annulization for data less than 1 year
- plainAnnu = get_annulization_multiple('m');
- sqrtAnnu = sqrt(get_annulization_multiple('m'));
- r.addColumn(['std_dev_a', 'ds_dev_a', 'sharpe_a', 'sortino_a'],
- [DOUBLE, DOUBLE, DOUBLE, DOUBLE]);
- UPDATE r
- SET std_dev_a = std_dev * iif(end_date - inception_date.month() > 12, sqrtAnnu, 1),
- ds_dev_a = ds_dev * iif(end_date - inception_date.month() > 12, sqrtAnnu, 1),
- sharpe_a = sharpe * iif(end_date - inception_date.month() > 12, sqrtAnnu, 1),
- sortino_a = sortino * iif(end_date - inception_date.month() > 12, sqrtAnnu, 1)
- FROM ej(r, entity_info, 'entity_id');
-
- return r;
- }
- /*
- * Calculate trailing 3m, 6m, ytd, 1y, 2y, 3y, 4y, 5y, 10y and since inception datapoints
- *
- * @param: func <FUNCTION>: the calculation function
- * @param: entity_info <TABLE>: basic information of entity, NEED COLUMNS entity_id, inception_date
- * @param benchmarks <TABLE>: entity-benchmark mapping table
- * @param: end_day <DATE>: 计算截止日期
- * @param: ret <TABLE>: 收益表,NEED COLUMNS entity_id, price_dat, end_date, nav
- * @param bmk_ret <TABLE>: historical benchmark return table, NEED COLUMNS fund_id, end_date, ret
- * @param risk_free <TABLE>: historical risk free rate table, NEED COLUMNS fund_id, end_date, ret
- *
- *
- */
- def cal_trailing(func, entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate ) {
- r_incep = null;
- r_ytd = null;
- r_3m = null;
- r_6m = null;
- r_1y = null;
- r_2y = null;
- r_3y = null;
- r_4y = null;
- r_5y = null;
- r_10y = null;
- // incep
- r_incep = func(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate, 'incep');
- // ytd
- r_ytd = func(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate, 'ytd');
- // 3m 只需要支持收益计算
- r_3m = cal_basic_performance(entity_info, tb_ret, '3');
- // 6m
- r_6m = func(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate, '6');
- // 1y
- r_1y = func(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate, '12');
- // 2y
- r_2y = func(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate, '24');
- // 3y
- r_3y = func(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate, '36');
- // 4y
- r_4y = func(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate, '48');
- // 5y
- r_5y = func(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate, '60');
- // 10y
- r_10y = func(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate, '120');
- return r_incep, r_ytd, r_3m, r_6m, r_1y, r_2y, r_3y, r_4y, r_5y, r_10y;
- }
- /*
- * Calculate trailing ytd, 3m, 6m, 1y, 2y, 3y, 4y, 5y, 10y and since inception standard indicators
- *
- * @param: entity_info <TABLE>: basic information of entity, NEED COLUMNS entity_id, inception_date
- * @param benchmarks <TABLE>: entity-benchmark mapping table
- * @param: ret <TABLE>: 收益表,NEED COLUMNS entity_id, price_dat, end_date, nav
- * @param: end_day <DATE>: 计算截止日期
- * @param bmk_ret <TABLE>: historical benchmark return table, NEED COLUMNS fund_id, end_date, ret
- * @param risk_free <TABLE>: historical risk free rate table, NEED COLUMNS fund_id, end_date, ret
- *
- */
- def cal_trailing_indicators(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate) {
-
- return cal_trailing(cal_indicators, entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate);
- }
- /*
- * Calculate trailing ytd, 3m, 6m, 1y, 2y, 3y, 4y, 5y, 10y and since inception bfi indicators
- *
- * @param: entity_info <TABLE>: basic information of entity, NEED COLUMNS entity_id, inception_date
- * @param benchmarks <TABLE>: entity-benchmark mapping table
- * @param: ret <TABLE>: 收益表,NEED COLUMNS entity_id, price_dat, end_date, nav
- * @param: end_day <DATE>: 计算截止日期
- * @param bmk_ret <TABLE>: historical benchmark return table, NEED COLUMNS fund_id, end_date, ret
- * @param risk_free <TABLE>: historical risk free rate table, NEED COLUMNS fund_id, end_date, ret
- *
- * NOTE: 3m 的所有指标没有意义
- *
- *
- */
- def cal_trailing_bfi_indicators(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate) {
- return cal_trailing(cal_indicators_with_benchmark, entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate);
- }
- /*
- * 通用月度指标计算
- *
- * @param entity_type <STRING>:
- * @param indicator_type <STRING>: PBI, BFI
- * @param monthly_returns <TABLE>: NEED COLUMN: entity_id, end_date, price_date, nav, ret
- *
- * @return <DICT TABLE>: ['PBI-INCEP', 'PBI-YTD', 'PBI-3M', 'PBI-6M', 'PBI-1Y', 'PBI-2Y', 'PBI-3Y', 'PBI-4Y', 'PBI-5Y', 'PBI-10Y']
- *
- */
- def cal_monthly_indicators(entity_type, indicator_type, monthly_returns) {
- if(find(['MF', 'HF', 'PF', 'MI', 'FI'], entity_type) < 0) return null;
- if(monthly_returns.isVoid() || monthly_returns.size() < 1) return null;
- oldest_date = EXEC price_date.min() FROM monthly_returns;
- v_entity_ids = EXEC DISTINCT entity_id FROM monthly_returns;
-
- entity_info = get_entity_info(entity_type, v_entity_ids);
-
- if(entity_info.isVoid() || entity_info.size() == 0) { return null };
-
- end_day = today();
- // 取基金和基准的对照表
- if(indicator_type == 'BFI') {
- benchmark = SELECT entity_id, end_date.temporalParse('yyyy-MM') AS end_date, factor_id AS benchmark_id
- FROM get_entity_bfi_factors(entity_type, v_entity_ids, oldest_date.month(), end_day.month());
- } else {
- // 主基准, 对应 xxx_info 中的 primary_benchmark_id
- benchmark = SELECT entity_id, end_date, iif(benchmark_id.isNull(), 'IN00000008', benchmark_id) AS benchmark_id
- FROM get_entity_primary_benchmark(entity_type, v_entity_ids, oldest_date.temporalFormat('yyyy-MM'), end_day.temporalFormat('yyyy-MM')) ;
-
- }
- // 取所有出现的基准月收益
- bmk_ret = get_benchmark_return(benchmark, end_day);
- if(bmk_ret.isVoid() || bmk_ret.size() == 0) { return null; }
- // TODO: risk free指数月收益存在fund_performance表,所以先将就用 fund_id 表示。之后统一改为更准确的名字
- risk_free_rate = SELECT entity_id AS fund_id, temporalParse(end_date, 'yyyy-MM') AS end_date, ret FROM get_risk_free_rate(oldest_date, end_day);
- if(risk_free_rate.isVoid() || risk_free_rate.size() == 0) { return null; }
- // 指标计算
- if(indicator_type == 'BFI') {
- t0 = cal_trailing_bfi_indicators(entity_info, benchmark, end_day, monthly_returns, bmk_ret, risk_free_rate);
- v_table_name = ['BFI-INCEP', 'BFI-YTD', 'BFI-3M', 'BFI-6M', 'BFI-1Y', 'BFI-2Y', 'BFI-3Y', 'BFI-4Y', 'BFI-5Y', 'BFI-10Y'];
- } else {
- t0 = cal_trailing_indicators(entity_info, benchmark, end_day, monthly_returns, bmk_ret, risk_free_rate);
- v_table_name = ['PBI-INCEP', 'PBI-YTD', 'PBI-3M', 'PBI-6M', 'PBI-1Y', 'PBI-2Y', 'PBI-3Y', 'PBI-4Y', 'PBI-5Y', 'PBI-10Y'];
- }
- return dict(v_table_name, t0);
-
- }
- /*
- * Calculate historcial fund trailing indicators
- *
- * @param entity_type <STRING>: MF, HF
- * @param fund_ids <STRING>: 逗号和单引号分隔的fund_id
- * @param end_day <DATE>: 要计算的日期
- * @param isFromNav <BOOL>: 用净值实时计算还是从表中取月收益
- * @param isFromSQL <BOOL>: TODO: 从MySQL还是本地DolphinDB取净值/收益数据
- *
- * @return <DICT TABLE>: ['PBI-INCEP', 'PBI-YTD', 'PBI-3M', 'PBI-6M', 'PBI-1Y', 'PBI-2Y', 'PBI-3Y', 'PBI-4Y', 'PBI-5Y', 'PBI-10Y', 'MS-3Y', 'MS-5Y', 'MS-10Y']
- *
- *
- * Example: cal_fund_indicators('HF', "'HF000004KN','HF000103EU','HF00018WXG'", 2024.06.28, true);
- *
- */
- def cal_fund_indicators(entity_type, fund_ids, end_day, isFromNav) {
- very_old_date = 1990.01.01;
- if(isFromNav == true) {
- // 从净值开始计算收益
- tb_ret = SELECT * FROM cal_fund_monthly_returns(entity_type, fund_ids, true) WHERE price_date <= end_day;
- tb_ret.rename!(['fund_id', 'cumulative_nav'], ['entity_id', 'nav']);
- } else {
- // 从fund_performance表里读月收益
- tb_ret = get_monthly_ret(entity_type, fund_ids, very_old_date, end_day, true);
-
- v_end_date = tb_ret.end_date.temporalParse('yyyy-MM');
- tb_ret.replaceColumn!('end_date', v_end_date);
- }
- if(tb_ret.isVoid() || tb_ret.size() == 0) { return null; }
- // 标准的指标
- d = cal_monthly_indicators(entity_type, 'PBI', tb_ret);
- return d;
- }
- /*
- * Calculate historcial fund trailing BFI indicators
- *
- * @param entity_type <STRING>: MF, HF
- * @param fund_ids <STRING>: 逗号和单引号分隔的fund_id
- * @param end_day <DATE>: 要计算的日期
- * @param isFromNav <BOOL>: 用净值实时计算还是从表中取月收益
- * @param isFromSQL <BOOL>: TODO: 从MySQL还是本地DolphinDB取净值/收益数据
- *
- * @return <DICT TABLE>: ['BFI-INCEP', 'BFI-YTD', 'BFI-3M', 'BFI-6M', 'BFI-1Y', 'BFI-2Y', 'BFI-3Y', 'BFI-4Y', 'BFI-5Y', 'BFI-10Y']
- *
- *
- * Example: cal_fund_bfi_indicators('MF', "'MF00003PW2', 'MF00003PW1', 'MF00003PXO'", 2024.08.31, true);
- *
- */
- def cal_fund_bfi_indicators(entity_type, fund_ids, end_day, isFromNav) {
- very_old_date = 1990.01.01;
- if(isFromNav == true) {
- // 从净值开始计算收益
- tb_ret = SELECT * FROM cal_fund_monthly_returns(entity_type, fund_ids, true) WHERE price_date <= end_day;
- tb_ret.rename!(['fund_id', 'cumulative_nav'], ['entity_id', 'nav']);
- } else {
- // 从fund_performance表里读月收益
- tb_ret = get_monthly_ret(entity_type, fund_ids, very_old_date, end_day, true);
- tb_ret.rename!(['fund_id'], ['entity_id']);
-
- v_end_date = tb_ret.end_date.temporalParse('yyyy-MM');
- tb_ret.replaceColumn!('end_date', v_end_date);
- }
- if(tb_ret.isVoid() || tb_ret.size() == 0) { return null; }
- // BFI指标
- d = cal_monthly_indicators(entity_type, 'BFI', tb_ret);
- return d;
- }
- /*
- * Calculate historcial portfolio trailing indicators
- *
- * @param portfolio_ids <STRING>: comma-delimited portfolio ids
- * @param end_day <DATE>: the date
- * @param cal_method <INT>: calculate based on cumulative nav (1) or nav (2)
- * @param isFromNav <BOOL>: calculate returns from NAV on-the-fly (true) or get from monthly return table (false)
- *
- * Example: cal_portfolio_indicators('166002,166114', 2024.08.31, 1, true);
- *
-
- def cal_portfolio_indicators(portfolio_ids, end_day, cal_method, isFromNav) {
- very_old_date = 1990.01.01;
- start_month = very_old_date.month();
- portfolio_info = get_portfolio_info(portfolio_ids);
- if(portfolio_info.isVoid() || portfolio_info.size() == 0) { return null };
-
- portfolio_info.rename!('portfolio_id', 'entity_id');
- if(isFromNav == true) {
- // 从净值开始计算收益
- tb_raw_ret = SELECT * FROM cal_portfolio_nav(portfolio_ids, very_old_date, cal_method) WHERE price_date <= end_day;
- if(tb_raw_ret.isVoid() || tb_raw_ret.size() == 0) return null;
- // funky thing is you can't use "AS" for the grouping columns?
- tb_ret = SELECT portfolio_id, price_date.month(), price_date.last() AS price_date, (1+ret).prod()-1 AS ret, nav.last() AS nav
- FROM tb_raw_ret
- WHERE price_date <= end_day
- GROUP BY portfolio_id, price_date.month();
- tb_ret.rename!(['portfolio_id', 'month_price_date'], ['entity_id', 'end_date']);
- } else {
- // 从pf_portfolio_performance表里读月收益
- tb_ret = get_monthly_ret('PF', portfolio_ids, very_old_date, end_day, true);
- tb_ret.rename!(['portfolio_id'], ['entity_id']);
- v_end_date = tb_ret.end_date.temporalParse('yyyy-MM');
- tb_ret.replaceColumn!('end_date', v_end_date);
- }
- if(tb_ret.isVoid() || tb_ret.size() == 0) return null;
- // 混合因子做基准,同SQL保持一致
- t_dates = table(start_month..end_day.month() AS end_date);
- primary_benchmark = SELECT ei.entity_id, dt.end_date, 'FA00000VNB' AS benchmark_id
- FROM portfolio_info ei JOIN t_dates dt
- WHERE dt.end_date >= ei.inception_date.month();
- if(primary_benchmark.isVoid() || primary_benchmark.size() == 0) { return null; }
- // 取所有出现的基准月收益
- bmk_ret = get_benchmark_return(primary_benchmark, end_day);
- if(bmk_ret.isVoid() || bmk_ret.size() == 0) { return null; }
- // TODO: risk free指数月收益存在fund_performance表,所以先将就用 fund_id 表示。之后统一改为更准确的名字
- risk_free_rate = SELECT entity_id AS fund_id, temporalParse(end_date, 'yyyy-MM') AS end_date, ret FROM get_risk_free_rate(very_old_date, end_day);
- if(risk_free_rate.isVoid() || risk_free_rate.size() == 0) { return null; }
- t0 = cal_trailing_indicators(portfolio_info, primary_benchmark, end_day, tb_ret, bmk_ret, risk_free_rate);
- v_table_name = ['PBI-INCEP', 'PBI-YTD', 'PBI-6M', 'PBI-1Y', 'PBI-2Y', 'PBI-3Y', 'PBI-4Y', 'PBI-5Y', 'PBI-10Y'];
-
- return dict(v_table_name, t0);
- }
- * Calculate historcial portfolio trailing BFI indicators
- *
- * @param portfolio_ids <STRING>: comma-delimited portfolio ids
- * @param end_day <DATE>: the date
- * @param cal_method <INT>: calculate based on cumulative nav (1) or nav (2)
- * @param isFromNav <BOOL>: calculate returns from NAV on-the-fly (true) or get from monthly return table (false)
- *
- * TODO: intergrate with cal_portfolio_indicators
- *
- * Example: cal_portfolio_bfi_indicators('166002,166114', 2024.08.31, 1, true);
- *
-
- def cal_portfolio_bfi_indicators(portfolio_ids, end_day, cal_method, isFromNav) {
- very_old_date = 1990.01.01;
- start_month = 1990.01M;
- portfolio_info = get_portfolio_info(portfolio_ids);
- if(portfolio_info.isVoid() || portfolio_info.size() == 0) { return null };
-
- portfolio_info.rename!('portfolio_id', 'entity_id');
- if(isFromNav == true) {
- // 从净值开始计算收益
- tb_raw_ret = SELECT * FROM cal_portfolio_nav(portfolio_ids, very_old_date, cal_method) WHERE price_date <= end_day;
- if(tb_raw_ret.isVoid() || tb_raw_ret.size() == 0) return null;
-
- // funky thing is you can't use "AS" for the grouping columns?
- tb_ret = SELECT portfolio_id, price_date.month(), price_date.last() AS price_date, (1+ret).prod()-1 AS ret, nav.last() AS nav
- FROM tb_raw_ret
- WHERE price_date <= end_day
- GROUP BY portfolio_id, price_date.month();
- tb_ret.rename!(['portfolio_id', 'month_price_date'], ['entity_id', 'end_date']);
- } else {
- // 从pf_portfolio_performance表里读月收益
- tb_ret = get_monthly_ret('PF', portfolio_ids, very_old_date, end_day, true);
- tb_ret.rename!(['portfolio_id'], ['entity_id']);
- v_end_date = tb_ret.end_date.temporalParse('yyyy-MM');
- tb_ret.replaceColumn!('end_date', v_end_date);
- }
- if(tb_ret.isVoid() || tb_ret.size() == 0) return null;
- // 取组合和基准的对照表
- bfi_benchmark = SELECT portfolio_id AS entity_id, end_date.temporalParse('yyyy-MM') AS end_date, factor_id AS benchmark_id
- FROM get_portfolio_bfi_factors(portfolio_ids, start_month.temporalFormat('yyyy-MM'), end_day.temporalFormat('yyyy-MM'));
- if(bfi_benchmark.isVoid() || bfi_benchmark.size() == 0) { return null; }
- bmk_ret = get_benchmark_return(bfi_benchmark, end_day);
- if(bmk_ret.isVoid() || bmk_ret.size() == 0) { return null; }
- // TODO: risk free指数月收益存在fund_performance表,所以先将就用 fund_id 表示。之后统一改为更准确的名字
- risk_free_rate = SELECT entity_id AS fund_id, temporalParse(end_date, 'yyyy-MM') AS end_date, ret FROM get_risk_free_rate(very_old_date, end_day);
- if(risk_free_rate.isVoid() || risk_free_rate.size() == 0) { return null; }
-
- t0 = cal_trailing_bfi_indicators(portfolio_info, bfi_benchmark, end_day, tb_ret, bmk_ret, risk_free_rate);
- v_table_name = ['PBI-INCEP', 'PBI-YTD', 'PBI-6M', 'PBI-1Y', 'PBI-2Y', 'PBI-3Y', 'PBI-4Y', 'PBI-5Y', 'PBI-10Y'];
-
- return dict(v_table_name, t0);
- }
- */
- /*
- * 【Morningstar Integration】通用月度指标计算
- *
- * @param entity_type <STRING>:
- * @param indicator_type <STRING>: PBI, BFI
- * @param monthly_returns <TABLE>: NEED COLUMN: entity_id, end_date, price_date, nav, ret
- *
- * @return <DICT TABLE>: ['PBI-INCEP', 'PBI-YTD', 'PBI-3M', 'PBI-6M', 'PBI-1Y', 'PBI-2Y', 'PBI-3Y', 'PBI-4Y', 'PBI-5Y', 'PBI-10Y']
- *
- */
- def ms_cal_monthly_indicators(entity_type, indicator_type, monthly_returns) {
- if(find(['MF', 'HF', 'PF'], entity_type) < 0) return null;
- if(monthly_returns.isVoid() || monthly_returns.size() < 1) return null;
- oldest_date = EXEC price_date.min() FROM monthly_returns;
- v_entity_ids = (SELECT DISTINCT entity_id FROM monthly_returns).entity_id;
-
- entity_info = get_entity_info(entity_type, v_entity_ids);
-
- if(entity_info.isVoid() || entity_info.size() == 0) { return null };
-
- end_day = today();
- // 取基金和基准的对照表
- if(indicator_type == 'BFI') {
- benchmark = SELECT entity_id, end_date.temporalParse('yyyy-MM') AS end_date, factor_id AS benchmark_id
- FROM get_entity_bfi_factors(entity_type, v_entity_ids, oldest_date.month(), end_day.month());
- } else if(indicator_type == 'CAI') {
- benchmark = SELECT fund_id AS entity_id, end_date.temporalParse('yyyy-MM') AS end_date, factor_id AS benchmark_id
- FROM ms_get_fund_category_average(v_entity_ids, oldest_date.temporalFormat('yyyy-MM'), end_day.temporalFormat('yyyy-MM'));
- } else {
- // 主基准, 对应 xxx_info 中的 primary_benchmark_id
- benchmark = SELECT entity_id, end_date, iif(benchmark_id.isNull(), 'IN00000008', benchmark_id) AS benchmark_id
- FROM ms_get_entity_primary_benchmark(entity_type, v_entity_ids, oldest_date.temporalFormat('yyyy-MM'), end_day.temporalFormat('yyyy-MM')) ;
-
- }
- // 取所有出现的基准月收益
- bmk_ret = get_benchmark_return(benchmark, end_day);
- if(bmk_ret.isVoid() || bmk_ret.size() == 0) { return null; }
- // TODO: risk free指数月收益存在fund_performance表,所以先将就用 fund_id 表示。之后统一改为更准确的名字
- risk_free_rate = SELECT entity_id AS fund_id, temporalParse(end_date, 'yyyy-MM') AS end_date, ret FROM ms_get_risk_free_rate(oldest_date, end_day);
- if(risk_free_rate.isVoid() || risk_free_rate.size() == 0) { return null; }
- // 指标计算
- if(indicator_type == 'BFI') {
- t0 = cal_trailing_bfi_indicators(entity_info, benchmark, end_day, monthly_returns, bmk_ret, risk_free_rate);
- v_table_name = ['BFI-INCEP', 'BFI-YTD', 'BFI-3M', 'BFI-6M', 'BFI-1Y', 'BFI-2Y', 'BFI-3Y', 'BFI-4Y', 'BFI-5Y', 'BFI-10Y'];
- } else if(indicator_type == 'CAI') {
- t0 = cal_trailing_bfi_indicators(entity_info, benchmark, end_day, monthly_returns, bmk_ret, risk_free_rate);
- v_table_name = ['CAI-INCEP', 'CAI-YTD', 'CAI-3M', 'CAI-6M', 'CAI-1Y', 'CAI-2Y', 'CAI-3Y', 'CAI-4Y', 'CAI-5Y', 'CAI-10Y'];
-
- } else {
- t0 = cal_trailing_indicators(entity_info, benchmark, end_day, monthly_returns, bmk_ret, risk_free_rate);
- v_table_name = ['PBI-INCEP', 'PBI-YTD', 'PBI-3M', 'PBI-6M', 'PBI-1Y', 'PBI-2Y', 'PBI-3Y', 'PBI-4Y', 'PBI-5Y', 'PBI-10Y'];
- }
- return dict(v_table_name, t0);
-
- }
|