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- 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);
- }
- /*
- * 最大回撤
- *
- *
- */
- defg maxDrawdown(navs) {
- return max(1 - navs \ cummax(navs));
- }
- /*
- * 取主基准和BFI的历史月收益率
- *
- * @param benchmarks <TABLE>: entity-benchmark 的对应关系表
- * @param end_day <DATE>: 收益的截止日期
- *
- * @return <TABLE>: benchmark_id, end_date, ret
- *
- */
- def get_benchmark_return(benchmarks, end_day) {
- s_index_ids = '';
- s_factor_ids = '';
- if(benchmarks.isVoid() || benchmarks.size() == 0) { return null; }
- // 前缀为 IN 的 benchmark id
- t_index_id = SELECT DISTINCT benchmark_id FROM benchmarks WHERE benchmark_id LIKE 'IN%';
- s_index_ids = iif(isVoid(t_index_id), "", "'" + t_index_id.benchmark_id.concat("','") + "'");
- // 前缀为 FA 的 benchmark id
- t_factor_id = SELECT DISTINCT benchmark_id FROM benchmarks WHERE benchmark_id LIKE 'FA%';
- s_factor_ids = iif(isVoid(t_factor_id), "", "'" + t_factor_id.benchmark_id.concat("','") + "'");
- // 目前指数的月度业绩存在 fund_performance 表
- t_bmk = SELECT fund_id AS benchmark_id, temporalParse(end_date, 'yyyy-MM') AS end_date, ret FROM get_monthly_ret('IX', s_index_ids, 1990.01.01, end_day, true);
- // 而因子的月度业绩存在 cm_factor_performance 表
- INSERT INTO t_bmk SELECT factor_id, temporalParse(end_date, 'yyyy-MM') AS end_date, ret FROM get_monthly_ret('FA', s_factor_ids, 1990.01.01, end_day, true);
- return t_bmk;
- }
- /*
- * 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: max drawdowns are the same with SWAGGER, but are off with SQL
- * TODO: var, cvar, calmar are off; std dev, skewness, kurtosis are slightly off
- * TODO: since inception date
- *
- *
- */
- 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 \ nav.cummax()) 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,
- maxDrawdown(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 live with lots of records having winrate but no tracking error and info ratio
- *
- * 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,
- cumcount(iif(exc_ret >= 0, 1, null)) \ cnt AS winrate,
- exc_ret.cumstd() AS track_error,
- iif(exc_ret.cumstd() == 0, null, exc_ret.cumavg() \ exc_ret.cumstd()) 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,
- cumcount(iif(exc_ret >= 0, 1, null)) \ cnt AS winrate,
- exc_ret.cumstd() AS track_error,
- iif(exc_ret.cumstd() == 0, null, exc_ret.cumavg() \ exc_ret.cumstd()) 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,
- mcount(iif(exc_ret >= 0, 1, null), win) \ cnt AS winrate,
- mstd(exc_ret, win) AS track_error,
- iif(mstd(exc_ret, win) == 0, null, mavg(exc_ret, win) \ mstd(exc_ret, win)) AS info
- FROM t0
- CONTEXT BY entity_id, benchmark_id
- ORDER BY entity_id, end_date, benchmark_id;
- }
- return t;
- }
- /*
- * 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, ret.cumbeta(ret_bmk) 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, ret.cumbeta(ret_bmk) 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, ret.mbeta(ret_bmk, win) 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+t.ret).cumprod() AS upside_ret, (1+bmk.ret).cumprod() AS bmk_upside_ret, bmk.end_date.cumcount() AS bmk_upside_cnt, bm.benchmark_id
- 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 >= 0
- CONTEXT BY t.entity_id, bm.benchmark_id;
-
- t2 = SELECT t.entity_id, t.end_date,
- (1+t.ret).cumprod() AS downside_ret, (1+bmk.ret).cumprod() AS bmk_downside_ret, bmk.end_date.cumcount() AS bmk_downside_cnt, bm.benchmark_id
- 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 < 0
- CONTEXT BY t.entity_id, bm.benchmark_id;
- } else if(trailing_month == 'ytd') {
- t1 = SELECT t.entity_id, t.end_date,
- (1+t.ret).cumprod() AS upside_ret, (1+bmk.ret).cumprod() AS bmk_upside_ret, bmk.end_date.cumcount() AS bmk_upside_cnt, bm.benchmark_id
- 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 >= 0
- CONTEXT BY t.entity_id, bm.benchmark_id, t.end_date.year();
-
- t2 = SELECT t.entity_id, t.end_date,
- (1+t.ret).cumprod() AS downside_ret, (1+bmk.ret).cumprod() AS bmk_downside_ret, bmk.end_date.cumcount() AS bmk_downside_cnt, bm.benchmark_id
- 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 < 0
- 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+t.ret).mprod(win) AS upside_ret, (1+bmk.ret).mprod(win) AS bmk_upside_ret, bmk.end_date.mcount(win) AS bmk_upside_cnt, bm.benchmark_id
- 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 >= 0
- CONTEXT BY t.entity_id, bm.benchmark_id;
-
- t2 = SELECT t.entity_id, t.end_date,
- (1+t.ret).mprod(win) AS downside_ret, (1+bmk.ret).mprod(win) AS bmk_downside_ret, bmk.end_date.mcount(win) AS bmk_downside_cnt,bm.benchmark_id
- 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 < 0
- CONTEXT BY t.entity_id, bm.benchmark_id;
- }
- t = (SELECT * FROM (
- SELECT iif(isNull(t1.entity_id), t2.entity_id, t1.entity_id) AS entity_id,
- iif(isNull(t1.end_date), t2.end_date, t1.end_date) AS end_date,
- iif(isNull(t1.benchmark_id), t2.benchmark_id, t1.benchmark_id) AS 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,
- t2.downside_ret.pow(1 \ t2.bmk_downside_cnt)-1 AS downside_capture_ret,
- (t2.downside_ret.pow(1 \ t2.bmk_downside_cnt)-1)/(t2.bmk_downside_ret.pow(1 \ t2.bmk_downside_cnt)-1) AS downside_capture_ratio
- FROM t1 FULL JOIN t2 ON t1.entity_id = t2.entity_id AND t1.benchmark_id = t2.benchmark_id AND t1.end_date = t2.end_date)
- ORDER BY entity_id, benchmark_id, end_date).ffill();
- 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$INT;
- jensen = SELECT t.entity_id, t.end_date, t.ret.mavg(win) - rfr.ret.mavg(win) - beta.beta * (bmk.ret.mavg(win) - rfr.ret.mavg(win)) AS jensen, beta.benchmark_id
- FROM ret t
- INNER JOIN beta beta ON t.entity_id = beta.entity_id AND t.end_date = beta.end_date
- INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND beta.benchmark_id = bmk.benchmark_id
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE t.ret > -1
- CONTEXT BY t.entity_id, beta.benchmark_id;
- }
- return jensen;
- }
- /*
- * Modigliani Modigliani Measure (M2)
- * NOTE: M2 = sharpe * std(benchmark) + risk_free_rate
- * NOTE: Java version is noncompliant-GIPS annulized number
- */
- def cal_m2(ret, benchmarks, bmk_ret, risk_free, trailing_month) {
- if(trailing_month == 'incep') {
-
- m2 = SELECT t.entity_id, t.end_date, (t.ret - rfr.ret).cumavg() / t.ret.cumstd() * bmk.ret.cumstd() + rfr.ret.cumavg() AS m2, bm.benchmark_id
- FROM ret t
- INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
- INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE t.ret > -1
- CONTEXT BY t.entity_id, bm.benchmark_id;
- } else if(trailing_month == 'ytd') {
- m2 = SELECT t.entity_id, t.end_date, (t.ret - rfr.ret).cumavg() / t.ret.cumstd() * bmk.ret.cumstd() + rfr.ret.cumavg() AS m2, bm.benchmark_id
- FROM ret t
- INNER JOIN benchmarks bm ON t.entity_id = bm.entity_id AND t.end_date = bm.end_date
- INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id
- INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
- WHERE t.ret > -1
- CONTEXT BY t.entity_id, bm.benchmark_id, t.end_date.year();
- } else {
- win = trailing_month$INT;
- m2 = SELECT t.entity_id, t.end_date, (t.ret - rfr.ret).mavg(win) / t.ret.mstd(win) * bmk.ret.mstd(win) + rfr.ret.mavg(win) 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) {
- // 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) {
- // 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_trailing2(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_indicators2(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate) {
-
- return cal_trailing2(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_indicators2(entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate) {
- return cal_trailing2(cal_indicators_with_benchmark, entity_info, benchmarks, end_day, tb_ret, bmk_ret, risk_free_rate);
- }
- /*
- * Calculate fund indicators for one date
- *
- * @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-6M', 'PBI-1Y', 'PBI-2Y', 'PBI-3Y', 'PBI-4Y', 'PBI-5Y', 'PBI-10Y', 'MS-3Y', 'MS-5Y', 'MS-10Y']
- *
- * TODO: primary_benchmark_id seems not be used as benchmark, when it is FA00000VNB
- *
- * 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;
- start_month = 1990.01M;
- fund_info = get_fund_info(fund_ids);
-
- if(fund_info.isVoid() || fund_info.size() == 0) { return null };
-
- fund_info.rename!('fund_id', 'entity_id');
- 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('FD', fund_ids, very_old_date, end_day, true);
- tb_ret.rename!(['fund_id'], ['entity_id']);
- }
- // 取基金和基准的对照表
- primary_benchmark = SELECT fund_id AS entity_id, end_date, iif(benchmark_id.isNull(), 'IN00000008', benchmark_id) AS benchmark_id
- FROM get_fund_primary_benchmark(fund_ids, start_month.temporalFormat('yyyy-MM'), end_day.month().temporalFormat('yyyy-MM')) ;
- // 取所有出现的基准月收益
- bmk_ret = get_benchmark_return(primary_benchmark, end_day);
- risk_free_rate = SELECT fund_id, temporalParse(end_date, 'yyyy-MM') AS end_date, ret FROM get_risk_free_rate(very_old_date, end_day);
- // 标准的指标
- t0 = cal_trailing_indicators2(fund_info, primary_benchmark, end_day, tb_ret, bmk_ret, risk_free_rate);
- // Morningstar 指标
- //t1 = cal_trailing_ms_indicators(fund_info, tb_ret, end_day, risk_free_rate);
- // PBI stands for "Primary Benchmark Index", MS stands for "MorningStar"
- v_table_name = ['PBI-INCEP', 'PBI-YTD', 'PBI-6M', 'PBI-1Y', 'PBI-2Y', 'PBI-3Y', 'PBI-4Y', 'PBI-5Y', 'PBI-10Y'/*, 'MS-3Y', 'MS-5Y', 'MS-10Y'*/];
- return dict(v_table_name, t0);
- // return dict(v_table_name, t0 <- t1[5] <- t1[7] <- t1[8]);
-
- }
- /*
- * Calculate fund BFI indicators for one date
- *
- * @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-6M', 'BFI-1Y', 'BFI-2Y', 'BFI-3Y', 'BFI-4Y', 'BFI-5Y', 'BFI-10Y']
- *
- * TODO: primary_benchmark_id seems not be used as benchmark, when it is FA00000VNB
- * TODO: intergrate with cal_fund_indicators
- *
- * 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;
- start_month = 1990.01M;
- fund_info = get_fund_info(fund_ids);
-
- if(fund_info.isVoid() || fund_info.size() == 0) { return null };
-
- fund_info.rename!('fund_id', 'entity_id');
- 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('FD', fund_ids, very_old_date, end_day, true);
- tb_ret.rename!(['fund_id'], ['entity_id']);
- }
- // 取基金和基准的对照表
- 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(fund_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);
- risk_free_rate = SELECT fund_id, temporalParse(end_date, 'yyyy-MM') AS end_date, ret FROM get_risk_free_rate(very_old_date, end_day);
- t0 = cal_trailing_bfi_indicators2(fund_info, bfi_benchmark, end_day, tb_ret, bmk_ret, risk_free_rate);
- // BFI stands for "Best Fit Index"
- v_table_name = ['BFI-INCEP', 'BFI-YTD', 'BFI-6M', 'BFI-1Y', 'BFI-2Y', 'BFI-3Y', 'BFI-4Y', 'BFI-5Y', 'BFI-10Y'];
-
- return dict(v_table_name, t0);
- }
- /*
- * Calculate portfolio indicators for one date
- *
- * @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;
- 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;
-
- // 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']);
- }
- // 沪深300做基准,同SQL保持一致
- primary_benchmark = SELECT entity_id, 'IN00000008' AS benchmark_id FROM portfolio_info;
- // 取所有出现的基准月收益
- bmk_ret = get_benchmark_return(primary_benchmark, end_day);
- risk_free_rate = SELECT fund_id, temporalParse(end_date, 'yyyy-MM') AS end_date, ret FROM get_risk_free_rate(very_old_date, end_day);
- t0 = cal_trailing_indicators2(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 portfolio bfi indicators for one date
- *
- * @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;
-
- // 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']);
- }
- // 取组合和基准的对照表
- bfi_benchmark = SELECT portfolio_id AS entity_id, 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);
- risk_free_rate = SELECT fund_id, temporalParse(end_date, 'yyyy-MM') AS end_date, ret FROM get_risk_free_rate(very_old_date, end_day);
- t0 = cal_trailing_bfi_indicators(portfolio_info, bfi_benchmark, tb_ret, end_day, 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);
- }
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