12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596061626364656667686970717273747576777879808182838485868788899091929394959697989910010110210310410510610710810911011111211311411511611711811912012112212312412512612712812913013113213313413513613713813914014114214314414514614714814915015115215315415515615715815916016116216316416516616716816917017117217317417517617717817918018118218318418518618718818919019119219319419519619719819920020120220320420520620720820921021121221321421521621721821922022122222322422522622722822923023123223323423523623723823924024124224324424524624724824925025125225325425525625725825926026126226326426526626726826927027127227327427527627727827928028128228328428528628728828929029129229329429529629729829930030130230330430530630730830931031131231331431531631731831932032132232332432532632732832933033133233333433533633733833934034134234334434534634734834935035135235335435535635735835936036136236336436536636736836937037137237337437537637737837938038138238338438538638738838939039139239339439539639739839940040140240340440540640740840941041141241341441541641741841942042142242342442542642742842943043143243343443543643743843944044144244344444544644744844945045145245345445545645745845946046146246346446546646746846947047147247347447547647747847948048148248348448548648748848949049149249349449549649749849950050150250350450550650750850951051151251351451551651751851952052152252352452552652752852953053153253353453553653753853954054154254354454554654754854955055155255355455555655755855956056156256356456556656756856957057157257357457557657757857958058158258358458558658758858959059159259359459559659759859960060160260360460560660760860961061161261361461561661761861962062162262362462562662762862963063163263363463563663763863964064164264364464564664764864965065165265365465565665765865966066166266366466566666766866967067167267367467567667767867968068168268368468568668768868969069169269369469569669769869970070170270370470570670770870971071171271371471571671771871972072172272372472572672772872973073173273373473573673773873974074174274374474574674774874975075175275375475575675775875976076176276376476576676776876977077177277377477577677777877978078178278378478578678778878979079179279379479579679779879980080180280380480580680780880981081181281381481581681781881982082182282382482582682782882983083183283383483583683783883984084184284384484584684784884985085185285385485585685785885986086186286386486586686786886987087187287387487587687787887988088188288388488588688788888989089189289389489589689789889990090190290390490590690790890991091191291391491591691791891992092192292392492592692792892993093193293393493593693793893994094194294394494594694794894995095195295395495595695795895996096196296396496596696796896997097197297397497597697797897998098198298398498598698798898999099199299399499599699799899910001001100210031004100510061007100810091010101110121013101410151016101710181019102010211022102310241025102610271028102910301031103210331034103510361037103810391040104110421043104410451046104710481049105010511052105310541055105610571058105910601061106210631064106510661067106810691070107110721073107410751076107710781079108010811082108310841085108610871088108910901091109210931094109510961097109810991100110111021103110411051106110711081109111011111112111311141115111611171118111911201121112211231124112511261127112811291130113111321133113411351136113711381139114011411142114311441145114611471148114911501151115211531154115511561157115811591160116111621163116411651166116711681169117011711172117311741175117611771178117911801181118211831184118511861187118811891190119111921193119411951196119711981199120012011202120312041205120612071208120912101211121212131214121512161217121812191220122112221223122412251226122712281229123012311232123312341235123612371238123912401241124212431244124512461247124812491250125112521253125412551256125712581259126012611262126312641265126612671268126912701271127212731274127512761277127812791280128112821283128412851286128712881289 |
- module fundit::indicatorCalculator
- use fundit::dataPuller
- use fundit::returnCalculator
- use fundit::navCalculator
- /*
- * Annulized multiple
- */
- def get_annulization_multiple(freq) {
- ret = 1;
-
- if (freq == 'd') {
- ret = 252; // We have differences here between Java and DolphinDB, Java uses 365.25 days
- } else if (freq == 'w') {
- ret = 52;
- } else if (freq == 'm') {
- ret = 12;
- } else if (freq == 'q') {
- ret = 4;
- } else if (freq == 's') {
- ret = 2;
- } else if (freq == 'a') {
- ret = 1;
- }
-
- return ret;
- }
- /*
- * 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) {
- 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) {
- return returns.CVaR(method, confidenceLevel);
- }
- /*
- * 回撤
- *
- *
- */
- defg maxDrawdown(navs) {
- return max(1 - navs \ cummax(navs));
- }
- /*
- * 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)
- *
- */
- 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,
- prod(1+ret)-1 AS trailing_ret,
- prod(1+ret)-1 AS trailing_ret_a,
- 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 end_date;
- // 年化收益(给后面计算Calmar用)
- UPDATE t0
- SET trailing_ret_a = (1+trailing_ret).pow(12\(t0.end_date - ei.inception_date.month()))-1
- FROM ej(t0, entity_info ei, 'entity_id')
- WHERE t0.end_date > ei.inception_date.month() + 12;
-
- // 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,
- 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 {
-
- win = trailing_month$INT;
-
- t1 = SELECT entity_id, end_date, price_date.mmax(win) AS price_date,
- mprod(1+ret, win)-1 AS trailing_ret,
- iif(trailing_month > 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$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,
- (t.ret - rfr.ret ).cumavg() \ l.lpm1 + 1 AS omega,
- (t.ret - rfr.ret ).cumavg() \ l.lpm2 AS sortino,
- (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,
- (t.ret - rfr.ret ).cumavg() \ l.lpm1 + 1 AS omega,
- (t.ret - rfr.ret ).cumavg() \ l.lpm2 AS sortino,
- (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$INT;
-
- tb = SELECT t.entity_id, t.end_date,
- l.lpm2 AS ds_dev,
- (t.ret - rfr.ret ).mavg(win) \ l.lpm1 + 1 AS omega,
- (t.ret - rfr.ret ).mavg(win) \ l.lpm2 AS sortino,
- (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$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$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$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,
- t1.upside_ret.pow(1 \ t1.bmk_upside_cnt)-1 AS upside_capture_ret,
- (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,
- t1.downside_ret.pow(1 \ t1.bmk_downside_cnt)-1 AS downside_capture_ret,
- (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 <> 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 <> 0 AND t.ret > -1
- CONTEXT BY t.entity_id, t.end_date.year();
- } else {
- win = trailing_month$INT;
- sharpe = SELECT t.entity_id, t.end_date, (t.ret - rfr.ret).mavg(win) / std.std_dev AS sharpe
- FROM ret t
- INNER JOIN std_dev std ON t.entity_id = std.entity_id AND t.end_date = std.end_date
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE std.std_dev <> 0 AND t.ret > -1
- CONTEXT BY t.entity_id;
- }
- return sharpe;
- }
- /*
- * Treynor Ratio = annulized excess return / beta
- *
- * TODO: ytd is off because Java uses non-GIPS rule to annulize return
- */
- def cal_treynor(ret, risk_free, beta, trailing_month) {
- if(trailing_month == 'incep') {
- t = SELECT *, cumcount(entity_id) AS cnt
- FROM ret t
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE t.ret > -1
- AND rfr.ret > -1
- CONTEXT BY t.entity_id;
-
- treynor = SELECT t.entity_id, t.end_date, beta.benchmark_id,
- ((1 + t.ret).cumprod().pow(12\iif(t.cnt<12, 12, t.cnt)) - (1 + t.rfr_ret).cumprod().pow(12\iif(t.cnt<12, 12, t.cnt))) / beta.beta AS treynor
- FROM t
- INNER JOIN beta AS beta ON t.entity_id = beta.entity_id AND t.end_date = beta.end_date
- CONTEXT BY t.entity_id, beta.benchmark_id;
- } else if(trailing_month == 'ytd') {
- t = SELECT *, cumcount(entity_id) AS cnt
- FROM ret t
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE t.ret > -1
- AND rfr.ret > -1
- CONTEXT BY t.entity_id, t.end_date.year();
-
- treynor = SELECT t.entity_id, t.end_date, beta.benchmark_id,
- ((1 + t.ret).cumprod().pow(12\iif(t.cnt<12, 12, t.cnt)) - (1 + t.rfr_ret).cumprod().pow(12\iif(t.cnt<12, 12, t.cnt))) / beta.beta AS treynor
- FROM t
- INNER JOIN beta AS beta ON t.entity_id = beta.entity_id AND t.end_date = beta.end_date
- CONTEXT BY t.entity_id, beta.benchmark_id, t.end_date.year();
- } else {
- win = trailing_month$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,
- ((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$INT;
- jensen = SELECT t.entity_id, t.end_date, t.ret.mavg(win) - rfr.ret.mavg(win) - beta.beta * (bmk.ret.mavg(win) - rfr.ret.mavg(win)) AS jensen, beta.benchmark_id
- FROM ret t
- INNER JOIN beta beta ON t.entity_id = beta.entity_id AND t.end_date = beta.end_date
- INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND beta.benchmark_id = bmk.benchmark_id
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE t.ret > -1
- CONTEXT BY t.entity_id, beta.benchmark_id;
- }
- return jensen;
- }
- /*
- * Modigliani Modigliani Measure (M2)
- * NOTE: M2 = sharpe * std(benchmark) + risk_free_rate
- * NOTE: Java version is noncompliant-GIPS annulized number
- */
- def cal_m2(ret, benchmarks, bmk_ret, risk_free, trailing_month) {
- if(trailing_month == 'incep') {
-
- m2 = SELECT t.entity_id, t.end_date,
- iif(t.entity_id.cumcount() > 5, (t.ret - rfr.ret).cumavg() / t.ret.cumstd() * bmk.ret.cumstd() + rfr.ret.cumavg(), null) AS m2, bm.benchmark_id
- FROM ret t
- INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
- INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE t.ret > -1
- CONTEXT BY t.entity_id, bm.benchmark_id;
- } else if(trailing_month == 'ytd') {
- m2 = SELECT t.entity_id, t.end_date,
- iif(t.entity_id.cumcount() > 5, (t.ret - rfr.ret).cumavg() / t.ret.cumstd() * bmk.ret.cumstd() + rfr.ret.cumavg(), null) AS m2, bm.benchmark_id
- FROM ret t
- INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
- INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE t.ret > -1
- CONTEXT BY t.entity_id, bm.benchmark_id, t.end_date.year();
- } else {
- win = trailing_month$INT;
- m2 = SELECT t.entity_id, t.end_date,
- iif(t.entity_id.mcount(win) > 5, (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$INT;
- r = SELECT t.entity_id, t.end_date,
- ((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$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 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
- * @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
- *
- *
- */
- def cal_trailing(func, entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate) {
- r_incep = null;
- r_ytd = 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');
- // 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_6m, r_1y, r_2y, r_3y, r_4y, r_5y, r_10y;
- }
- /*
- * Calculate trailing ytd, 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 6m, ytd, 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
- *
- *
- */
- 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-6M', 'PBI-1Y', 'PBI-2Y', 'PBI-3Y', 'PBI-4Y', 'PBI-5Y', 'PBI-10Y', 'MS-3Y', 'MS-5Y', 'MS-10Y']
- *
- */
- def 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 fund_id AS entity_id, end_date.temporalParse('yyyy-MM') AS end_date, factor_id AS benchmark_id
- FROM get_fund_bfi_factors(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 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-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-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 fund_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-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(fund_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(fund_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(fund_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(fund_type, 'PBI', tb_ret);
- return d;
- }
- /*
- * Calculate historcial fund trailing BFI indicators
- *
- * @param fund_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-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(fund_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(fund_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(fund_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(fund_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);
- }
|