Update .gitignore and add files.

stockapp/shell/stat.sql

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+
+-- 统计 year_diff = 10000 的所有记录中， win_rate 在不同区间的分布情况，给出每个区间的 行数，以及占整体的比例
+WITH filtered_data AS (
+    SELECT win_rate
+    FROM hs300_5years_yield_stats_2410
+    WHERE year_diff = 10000
+)
+SELECT 
+    CASE 
+        WHEN win_rate >= 0.99995 THEN '100%'
+        WHEN win_rate >= 0.9 AND win_rate < 0.99995 THEN '90%～100%'
+        WHEN win_rate >= 0.5 AND win_rate < 0.9 THEN '50% ~ 90%'
+        WHEN win_rate >= 0.2 AND win_rate < 0.5 THEN '20% ~ 50%'
+        ELSE '20% 以下'
+    END AS win_rate_range,
+    ROUND(COUNT(*) / (SELECT COUNT(*) FROM filtered_data) * 100, 2) AS percentage,
+    COUNT(*) AS count
+FROM filtered_data
+GROUP BY win_rate_range
+ORDER BY 
+    CASE win_rate_range
+        WHEN '100%' THEN 1
+        WHEN '90%～100%' THEN 2
+        WHEN '50% ~ 90%' THEN 3
+        WHEN '20% ~ 50%' THEN 4
+        ELSE 5
+    END;
+;
+
+-- annual_median_yield_rate 代表了投资的年化回报率的中位数，我们想要统计在 year_diff = 10000 的所有记录中，中位数的分布情况。
+-- 首先把所有记录按照中位数降序排列，然后把所有记录的条数分成10等份，我们要输出的是 每一个等份下面，中位数的区间，以及等份的记录条数。
+WITH ranked_data AS (
+    SELECT 
+        annual_median_yield_rate,
+        NTILE(10) OVER (ORDER BY annual_median_yield_rate DESC) AS tile_rank
+    FROM sp500_5years_yield_stats_2410
+    WHERE year_diff = 10000
+)
+SELECT 
+    MAX(annual_median_yield_rate) AS max_yield_rate,
+    MIN(annual_median_yield_rate) AS min_yield_rate,
+    COUNT(*) AS record_count
+FROM ranked_data
+GROUP BY tile_rank
+ORDER BY tile_rank;
+
+-- max_deficit_days 是买入即亏损的最大时长。我们统计在 year_diff = 10000 的所有记录中，按照之前定义的胜率分布下，每一个胜率分布区间内，max_deficit_days 的最大值，最小值，和平均值。
+WITH filtered_data AS (
+    SELECT win_rate, max_deficit_days
+    FROM sp500_5years_yield_stats_2410
+    WHERE year_diff = 10000
+)
+SELECT 
+    CASE 
+        WHEN win_rate >= 0.99995 THEN '100%'
+        WHEN win_rate >= 0.9 AND win_rate < 0.99995 THEN '90%～100%'
+        WHEN win_rate >= 0.5 AND win_rate < 0.9 THEN '50% ~ 90%'
+        WHEN win_rate >= 0.2 AND win_rate < 0.5 THEN '20% ~ 50%'
+        ELSE '20% 以下'
+    END AS win_rate_range,
+    MAX(max_deficit_days) AS max_deficit,
+    MIN(max_deficit_days) AS min_deficit,
+    ROUND(AVG(max_deficit_days), 2) AS avg_deficit
+FROM filtered_data
+GROUP BY win_rate_range
+ORDER BY 
+    CASE win_rate_range
+        WHEN '100%' THEN 1
+        WHEN '90%～100%' THEN 2
+        WHEN '50% ~ 90%' THEN 3
+        WHEN '20% ~ 50%' THEN 4
+        ELSE 5
+    END;
+
+
+-- 提取  year_diff = 10000 的所有记录中，win_rate >= 0.99995 的所有记录的 code, name, max_yield_rate, median_yield_rate, annual_max_yield_rate, annual_median_yield_rate, max_deficit_days
+SELECT 
+    code, 
+    name, 
+    max_yield_rate, 
+    median_yield_rate, 
+    annual_max_yield_rate, 
+    annual_median_yield_rate, 
+    max_deficit_days
+FROM hs300_5years_yield_stats_2410
+WHERE year_diff = 10000
+  AND win_rate >= 0.99995;
+
+
+-- 对每个不同的 code，统计不同 year_diff （year_diff != 10000）下的最大 annual_median_yield_rate 对应的 year_diff ，我们就得到了 code , 最优 year_diff 的结果；然后对 year_diff 进行分组统计对应的行数，以及占总行数的比例。
+WITH best_year_diff_per_code AS (
+    SELECT code, 
+           year_diff,
+           annual_median_yield_rate,
+           RANK() OVER (PARTITION BY code ORDER BY annual_median_yield_rate DESC) AS rank_by_yield
+    FROM sp500_5years_yield_stats_2410
+    WHERE year_diff != 10000
+)
+SELECT 
+    year_diff,
+    ROUND(COUNT(*) / (SELECT COUNT(*) FROM best_year_diff_per_code WHERE rank_by_yield = 1) * 100, 2) AS percentage,
+    COUNT(*) AS record_count
+FROM best_year_diff_per_code
+WHERE rank_by_yield = 1
+GROUP BY year_diff
+ORDER BY year_diff;
+
+
+
+-- 对每个不同的 code，统计不同 year_diff （year_diff != 10000）下的最大 annual_median_yield_rate 对应的 year_diff ，我们就得到了 code , 最优 year_diff 的结果；输出这个结果。
+WITH best_year_diff_per_code AS (
+    SELECT 
+        code,
+        year_diff,
+        annual_median_yield_rate,
+        RANK() OVER (PARTITION BY code ORDER BY annual_median_yield_rate DESC) AS rank_by_yield
+    FROM sp500_5years_yield_stats_2410
+    WHERE year_diff != 10000
+)
+SELECT 
+    code, 
+    year_diff AS best_year_diff, 
+    annual_median_yield_rate AS max_annual_median_yield_rate
+FROM best_year_diff_per_code
+WHERE rank_by_yield = 1
+ORDER BY code;