支持一次计算完整历史月度指标

modules/indicatorCalculator.dos

@@ -3,6 +3,7 @@ module fundit::indicatorCalculator
 use fundit::dataPuller
 use fundit::returnCalculator
 use fundit::navCalculator
+
 /*
  *  Annulized multiple
  */
@@ -61,33 +62,35 @@ def get_benchmark_return(benchmarks, end_day) {
 	return t_bmk;
 }
 /*
- *     Trailing Return, Standard Deviation, Skewness, Kurtosis, Max Drawdown, VaR, CVaR
+ *     Trailing Return, Standard Deviation, Skewness, Kurtosis, Max Drawdown, VaR, CVaR, Calmar Ratio
  *     @param ret: 收益表，需要有 entity_id, price_dat, end_date, nav 
  *     @param freq: 数据频率，d, w, m, q, s, a
  *     
+ *     TODO: max drowdown is off!
  *     NOTE: standard deviation of Java version is noncompliant-GIPS annulized number
  *     
  *     Create:  20240904                                                                     Joey
  *                       TODO: var and cvar are silightly off compared with Java version
+ *                             calmar is offCalmar
  *     
  */
 def cal_basic_performance(ret, freq) {
 
-    t = SELECT entity_id, max(end_date) AS end_date, max(price_date) AS price_date, min(price_date) AS min_date,
-               //(nav.last() \ nav.first() - 1).round(6) AS trailing_ret,
+/*  OLD version that can only calculate the latest numbers (group-by version)
+
+    t = SELECT entity_id, end_date.max() AS end_date, max(price_date) AS price_date, min(price_date) AS min_date,
                ((1+ret).prod()-1).round(6) AS trailing_ret,
                iif(price_date.max().month()-price_date.min().month()>12,
-                   //(nav.last() \ nav.first()).pow(365 \(max(price_date) - min(price_date)))-1, 
-                   //(nav.last() \ nav.first() - 1)).round(6) AS trailing_ret_a,
-                   ((1+ret).prod()-1) * sqrt(get_annulization_multiple(freq)),
+                   ((1+ret).prod()).pow(get_annulization_multiple('m')\(end_date.max()-end_date.min()))-1,
                    ((1+ret).prod()-1)).round(6) AS trailing_ret_a,
                ret.std() AS std_dev,
                ret.skew(false) AS skewness,
                ret.kurtosis(false) - 3 AS kurtosis,
-               ret.min() AS wrst_month,
+               ret.min() AS wrst_month
                max( 1 - nav \ nav.cummax() ) AS drawdown
         FROM ret
         GROUP BY entity_id;
+        
 
     // var & cvar require return NOT NULL
     // NOTE: DolphinDB supports 4 different ways: normal, logNormal, historical, monteCarlo. we use historical
@@ -100,6 +103,43 @@ def cal_basic_performance(ret, freq) {
 
     return (SELECT * FROM t LEFT JOIN t1 ON t.entity_id = t1.entity_id AND t.end_date = t1.end_date AND t.price_date = t1.price_date);
 
+*/
+
+   t = SELECT max(price_date) AS price_date, min(price_date) AS min_date,
+              ((1+ret).prod()-1).round(6) AS trailing_ret,
+              iif(price_date.max().month()-price_date.min().month()>12,
+                  ((1+ret).prod()).pow(get_annulization_multiple('m')\(end_date.max()-end_date.min()))-1,
+                  ((1+ret).prod()-1)).round(6) AS trailing_ret_a,
+              ret.std() AS std_dev,
+              ret.skew(false) AS skewness,
+              ret.kurtosis(false) - 3 AS kurtosis,
+              ret.min() AS wrst_month
+        FROM ret
+        GROUP BY entity_id
+        CGROUP BY end_date
+        ORDER BY end_date;
+
+    // because neither VaR and CVaR in context-by (cumXXX version) are NOT supported by DolphinDB , nor they are supported in cgroup-by
+    // we have to implement them using more basic ways:
+    t1 = SELECT entity_id, end_date, ret,
+                cummax( 1 - nav \ nav.cummax() ) AS drawdown, // same story: cummax is not supported by cgroup-by, so it is moved here
+                -ret.cumpercentile(5, 'linear') AS var
+         FROM ret
+         CONTEXT BY entity_id;
+
+    // CVaR = mean of all returns below VaR
+    t_cvar = SELECT DISTINCT entity_id, end_date, drawdown, var, cvar 
+             FROM (
+                 SELECT t1.entity_id, t1.end_date, t1.drawdown, t1.var, -avg(t2.ret) AS cvar
+                 FROM t1
+                 INNER JOIN t1 AS t2 ON t1.entity_id = t2.entity_id 
+                 WHERE t2.end_date <= t1.end_date
+                   AND t2.ret < -t1.var
+                 CONTEXT BY t1.entity_id, t1.end_date );
+
+    return (SELECT *, iif(t_cvar.drawdown == 0, null, t.trailing_ret_a\t_cvar.drawdown) AS calmar
+            FROM t LEFT JOIN t_cvar ON t.entity_id = t_cvar.entity_id AND t.end_date = t_cvar.end_date ORDER BY entity_id, end_date);
+
 }
 
 
@@ -112,14 +152,13 @@ def cal_LPM(ret, risk_free) {
     
     t = SELECT *, count(entity_id) AS cnt FROM ret WHERE ret > -1 CONTEXT BY entity_id;
 
-    lpm = SELECT t.entity_id, max(t.end_date) AS end_date,
-                 (sum (rfr.ret - t.ret) \ (t.cnt[0])).pow(1\1) AS lpm1, 
-                 (sum2(rfr.ret - t.ret) \ (t.cnt[0])).pow(1\2) AS lpm2, 
-                 (sum3(rfr.ret - t.ret) \ (t.cnt[0])).pow(1\3) AS lpm3
+    lpm = SELECT t.entity_id, t.end_date,
+                 (cumsum (iif(rfr.ret > t.ret, rfr.ret - t.ret, 0)) \ (t.cnt[0])).pow(1\1) AS lpm1, 
+                 (cumsum2(iif(rfr.ret > t.ret, rfr.ret - t.ret, 0)) \ (t.cnt[0])).pow(1\2) AS lpm2, 
+                 (cumsum3(iif(rfr.ret > t.ret, rfr.ret - t.ret, 0)) \ (t.cnt[0])).pow(1\3) AS lpm3
           FROM t 
           INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
-          WHERE t.ret < rfr.ret
-          GROUP BY t.entity_id;
+          CONTEXT BY t.entity_id;
 
     return lpm;
 }
@@ -136,15 +175,15 @@ def cal_omega_sortino_kappa(ret, risk_free) {
 
     lpm = cal_LPM(ret, risk_free);
 
-    tb = SELECT t.entity_id, 
-                l.lpm2[0] AS ds_dev,
-                (t.ret - rfr.ret ).mean() \ l.lpm1[0] + 1 AS omega,
-                (t.ret - rfr.ret ).mean() \ l.lpm2[0] AS sortino,
-                (t.ret - rfr.ret ).mean() \ l.lpm3[0] AS kappa
+    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
+              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
-              GROUP BY t.entity_id;
+              CONTEXT BY t.entity_id;
 
     return tb;
 }
@@ -158,43 +197,49 @@ def cal_alpha_beta(ret, benchmarks, bmk_ret, risk_free) {
 
     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
+        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;
 
-    beta = SELECT entity_id, benchmark_id, ret.beta(ret_bmk) AS beta FROM t GROUP BY entity_id, benchmark_id;
+    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.benchmark_id, beta.beta[0] AS beta, (t.ret - rfr.ret).mean() - beta.beta[0] * (t.ret_bmk - rfr.ret).mean() AS alpha
+    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
+            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
-            GROUP BY t.entity_id, t.benchmark_id;
+            CONTEXT BY t.entity_id, t.benchmark_id
+            ORDER BY t.entity_id, t.end_date, t.benchmark_id;
 
     return alpha;
 }
 
 /*
  *    Winning Ratio, Tracking Error, Information Ratio
+ *   
+ *    DO WE FOUND A BIG BUG OF JAVA IMPLEMENTATION, WHICH ASSUMES FACTORS OF CURRENT MONTH ARE SAME AS HISTORICAL ONES!
+ *    
  *    TODO: 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) {
 
      t0 = SELECT t.entity_id, t.end_date, t.price_date,
-                 t.ret, bmk.ret AS ret_bmk, count(t.entity_id) AS cnt, (t.ret - bmk.ret) AS exc_ret, bm.benchmark_id
+                 t.ret, bmk.ret AS ret_bmk, cumcount(t.entity_id) 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
+          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.max() AS end_date, price_date.max() AS price_date, price_date.min() AS min_date, benchmark_id,
-                exc_ret.bucketCount(0:999, 1) \ cnt[0] AS winrate,
-                exc_ret.std() AS track_error, 
-                iif(exc_ret.std() == 0, null, exc_ret.mean() / exc_ret.std()) AS info
-         FROM t0 GROUP BY entity_id, benchmark_id;
+     t = SELECT entity_id, end_date.cummax() AS end_date, price_date.cummax() AS price_date, price_date.cummin() AS min_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;
 
      return t;
 }
@@ -205,29 +250,32 @@ def cal_benchmark_tracking(ret, benchmarks, bmk_ret) {
  */
 def cal_capture_ratio(ret, benchmarks, bmk_ret) {
 
-    t1 = SELECT t.entity_id, (1+t.ret).prod() AS upside_ret, (1+bmk.ret).prod() AS bmk_upside_ret, bmk.end_date.count() AS bmk_upside_cnt, bm.benchmark_id
+    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
-         INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id
+         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
-         GROUP BY t.entity_id, bm.benchmark_id;
+         CONTEXT BY t.entity_id, bm.benchmark_id;
 
-    t2 = SELECT t.entity_id, (1+t.ret).prod() AS downside_ret, (1+bmk.ret).prod() AS bmk_downside_ret, bmk.end_date.count() AS bmk_downside_cnt, 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
-         INNER JOIN bmk_ret bmk ON t.end_date = bmk.end_date AND bm.benchmark_id = bmk.benchmark_id
+         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
-         GROUP BY t.entity_id, bm.benchmark_id;
-
-    t = SELECT iif(isNull(t1.entity_id), t2.entity_id, t1.entity_id) AS entity_id,
-               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;
+         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;
 }
@@ -238,12 +286,12 @@ def cal_capture_ratio(ret, benchmarks, bmk_ret) {
  */
 def cal_sharpe(ret, std_dev, risk_free) {
 
-    sharpe = SELECT t.entity_id, (t.ret - rfr.ret).mean() / std.std_dev[0] AS sharpe
+    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
+             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] <> 0
-             GROUP BY t.entity_id;
+             WHERE std.std_dev <> 0
+             CONTEXT BY t.entity_id;
 
     return sharpe;
 }
@@ -253,18 +301,19 @@ def cal_sharpe(ret, std_dev, risk_free) {
  */
 def cal_treynor(ret, risk_free, beta) {
 
-    t = SELECT *, count(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 = 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, beta.benchmark_id,
-                    ((1 + t.ret).prod().pow(12\iif(t.cnt[0]<12, 12, t.cnt[0])) - (1 + t.rfr_ret).prod().pow(12\iif(t.cnt[0]<12, 12, t.cnt[0]))) / beta.beta[0] AS treynor
+    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
-              GROUP BY t.entity_id, beta.benchmark_id;
+              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;
 }
@@ -275,27 +324,14 @@ def cal_treynor(ret, risk_free, beta) {
  */
 def cal_jensen(ret, bmk_ret, risk_free, beta) {
 
-    jensen = SELECT t.entity_id, t.ret.mean() - rfr.ret.mean() - beta.beta[0] * (bmk.ret.mean() - rfr.ret.mean()) AS jensen, beta.benchmark_id
+    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
+             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
-             GROUP BY t.entity_id, beta.benchmark_id;
-               
-    return jensen;
-}
-
-/*
- *    Calmar Ratio
- *    TODO: the result is off
- *
- */
-def cal_calmar(ret_a){
+             CONTEXT BY t.entity_id, beta.benchmark_id;
 
-    calmar = SELECT entity_id, trailing_ret_a \ drawdown AS calmar
-             FROM ret_a;
-
-    return calmar;
+    return jensen;
 }
 
 /*
@@ -305,12 +341,12 @@ def cal_calmar(ret_a){
  */
 def cal_m2(ret, benchmarks, bmk_ret, risk_free) {
 
-    m2 = SELECT t.entity_id, (t.ret - rfr.ret).mean() / t.ret.std() * bmk.ret.std() + rfr.ret.mean() AS m2, bm.benchmark_id
+    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
+         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
-         GROUP BY t.entity_id, bm.benchmark_id;
+         CONTEXT BY t.entity_id, bm.benchmark_id;
 
     return m2;
 }
@@ -320,6 +356,7 @@ def cal_m2(ret, benchmarks, bmk_ret, risk_free) {
  *    
  *    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
  * 
@@ -327,12 +364,12 @@ def cal_m2(ret, benchmarks, bmk_ret, risk_free) {
  */
 def cal_ms_return(ret, risk_free) {
 
-    r = SELECT t.entity_id, t.end_date.max() AS end_date, t.price_date.max() AS price_date, t.price_date.min() AS min_date,
-               ((1 + t.ret)\(1 + rfr.ret)).prod().pow(12\(t.end_date.max() - t.end_date.min()))-1 AS ms_ret_a,
-               (1 + t.ret).pow(-2).mean().pow(-12/2)-1 AS ms_rar_a
+    r = SELECT t.entity_id, t.end_date, t.price_date.cummax() AS price_date, t.price_date.cummin() AS min_date,
+               ((1 + t.ret)\(1 + rfr.ret)).cumprod().pow(12\(t.end_date.cummax() - t.end_date.cummin()))-1 AS ms_ret_a,
+               (1 + t.ret).pow(-2).cumavg().pow(-12/2)-1 AS ms_rar_a
         FROM ret t
         INNER JOIN risk_free rfr ON t.end_date = rfr.end_date
-        GROUP BY t.entity_id;
+        CONTEXT BY t.entity_id;
 
     return r;
 }
@@ -375,11 +412,11 @@ def cal_indicators_with_benchmark(mutable ret, benchmarks, index_ret, risk_free)
     capture_r = cal_capture_ratio(ret, benchmarks, index_ret);
 
     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
-                 LEFT JOIN treynor ON a1.entity_id = treynor.entity_id AND a1.benchmark_id = treynor.benchmark_id
-                 LEFT JOIN jensen ON a1.entity_id = jensen.entity_id AND a1.benchmark_id = jensen.benchmark_id
-                 LEFT JOIN m2 ON a1.entity_id = m2.entity_id AND a1.benchmark_id = m2.benchmark_id
-                 LEFT JOIN capture_r ON a1.entity_id = capture_r.entity_id AND a1.benchmark_id = capture_r.benchmark_id;
+                 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
@@ -396,7 +433,7 @@ def cal_indicators_with_benchmark(mutable ret, benchmarks, index_ret, risk_free)
           info_a = info * iif(price_date.month() - min_date.month() >= 11, sqrtAnnu, 1),
           m2_a = m2 * iif(price_date.month() - min_date.month() >= 11, plainAnnu, 1);
     
-    return r.dropColumns!(['end_date', 'price_date', 'min_date']);
+    return r.dropColumns!(['price_date', 'min_date']);
 }
 
 /*
@@ -418,15 +455,12 @@ def cal_indicators(mutable ret, benchmarks, benchmark_ret, risk_free) {
     // sorting for correct first() and last() value
     ret.sortBy!(['entity_id', 'price_date'], [1, 1]);
 
-    // 收益、标准差、偏度、峰度、最大回撤、VaR, CVaR
+    // 收益、标准差、偏度、峰度、最大回撤、VaR, CVaR、卡玛比率
     rtn = cal_basic_performance(ret, 'm');
 
     // 夏普
     sharpe = cal_sharpe(ret, rtn, risk_free);
 
-    // 卡玛比率
-    calmar = cal_calmar(rtn);
-
     // 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);
 
@@ -434,10 +468,9 @@ def cal_indicators(mutable ret, benchmarks, benchmark_ret, risk_free) {
     indicator_with_benchmark = cal_indicators_with_benchmark(ret, benchmarks, benchmark_ret, risk_free);
 
     r = SELECT * FROM rtn a1
-                 LEFT JOIN sharpe ON a1.entity_id = sharpe.entity_id
-                 LEFT JOIN calmar ON a1.entity_id = calmar.entity_id
-                 LEFT JOIN lpms ON a1.entity_id = lpms.entity_id
-                 LEFT JOIN indicator_with_benchmark ON a1.entity_id = indicator_with_benchmark.entity_id;
+                 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;
 
     // 年化各数据点
     // GIPS RULE: NO annulization for data less than 1 year
@@ -650,6 +683,8 @@ 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 };
@@ -667,7 +702,8 @@ def cal_fund_indicators(entity_type, fund_ids, end_day, isFromNav) {
     }
 
     // 取基金和基准的对照表
-    primary_benchmark = SELECT entity_id, iif(benchmark_id.isNull(), 'IN00000008', benchmark_id) AS benchmark_id FROM fund_info;
+    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);
@@ -707,6 +743,8 @@ 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 };
@@ -724,7 +762,8 @@ def cal_fund_bfi_indicators(entity_type, fund_ids, end_day, isFromNav) {
     }
 
     // 取基金和基准的对照表
-    bfi_benchmark = SELECT fund_id AS entity_id, factor_id AS benchmark_id FROM get_fund_bfi_factors(fund_ids, end_day.temporalFormat('yyyy-MM'));
+    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; }
 
@@ -812,6 +851,8 @@ 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 };
@@ -836,7 +877,8 @@ def cal_portfolio_bfi_indicators(portfolio_ids, end_day, cal_method, isFromNav)
     }
 
     // 取组合和基准的对照表
-    bfi_benchmark = SELECT portfolio_id AS entity_id, factor_id AS benchmark_id FROM get_portfolio_bfi_factors(portfolio_ids, end_day.temporalFormat('yyyy-MM'));
+    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; }