init

analyzer/StockPriceDirectionAnalyzer.py

@@ -1,7 +1,239 @@
+import os
+import sqlite3
+import pandas as pd
+
 class StockPriceDirectionAnalyzer:
 
-    def __init__(self):
+    stock_info = None
+
+    def __init__(self, stockFileName):
+        self.stock_info = {}
+        self.stockFileName = stockFileName
         return
 
+    def open(self):
+        self.conn = sqlite3.connect(self.stockFileName)
+        self.cursor = self.conn.cursor()
+
+    def close(self):
+        self.cursor.close()
+        self.conn.close()
+        return
+
+    def get_all_stock_code(self):
+        self.open()
+
+
+        sql = "SELECT distinct code FROM stock"
+        self.cursor.execute(sql)
+        rows = self.cursor.fetchall()
+
+        sql = "SELECT distinct code, name FROM stock"
+        self.cursor.execute(sql)
+        rows = self.cursor.fetchall()
+        for row in rows:
+            self.stock_info[row[0]] = row[1]
+
+        self.close()
+        return [row[0] for row in rows]
+
+    def load(self, master_code, limit_count=2000):
+        self.open()
+        sql = "SELECT ymd, close FROM stock where CODE=? order by ymd"
+        self.cursor.execute(sql, (master_code, ))
+        master_data = self.cursor.fetchall()
+        self.close()
+        master_data = master_data[-limit_count:]
+
+        return master_data
+
+    def getClosePrice(self, stock_codes, first_day, limit_count=2000):
+        data = {}
+        self.open()
+
+
+        # 신용잔고 누적
+        sql = "SELECT ymd, dep2_1 FROM meta_3 where ymd>=? order by ymd"
+        self.cursor.execute(sql, (first_day, ))
+        rows = self.cursor.fetchall()
+        if len(rows) >=limit_count:
+            #data['dep2_1'] = [(rows[i][0], rows[i][1]-rows[i-1][1]) for i in range(1, len(rows))]
+            data['dep2_1'] = [(rows[i][0], rows[i][1]) for i in range(len(rows))]
+            data['dep2_1_diff'] = [(rows[i][0], rows[i][1] - rows[i - 1][1]) for i in range(1, len(rows))]
+            self.stock_info['dep2_1'] = '신용잔고 누적'
+            self.stock_info['dep2_1_diff'] = '신용잔고 누적 차이'
+
+
+        # 투자자별 매매 동향
+        sql = "SELECT ymd, pri, fori, ins, ins0, ins1, ins2, ins3, ins4, ins5, cor FROM meta_2 where ymd>=? order by ymd"
+        self.cursor.execute(sql, (first_day,))
+        rows = self.cursor.fetchall()
+        if len(rows) >= limit_count:
+            data['pri'] = [(rows[i][0], rows[i][1]) for i in range(len(rows))]
+            data['fori'] = [(rows[i][0], rows[i][2]) for i in range(len(rows))]
+            data['ins'] = [(rows[i][0], rows[i][3]) for i in range(len(rows))]
+            data['ins0'] = [(rows[i][0], rows[i][4]) for i in range(len(rows))]
+            data['ins1'] = [(rows[i][0], rows[i][5]) for i in range(len(rows))]
+            data['ins2'] = [(rows[i][0], rows[i][6]) for i in range(len(rows))]
+            data['ins3'] = [(rows[i][0], rows[i][7]) for i in range(len(rows))]
+            data['ins4'] = [(rows[i][0], rows[i][8]) for i in range(len(rows))]
+            data['ins5'] = [(rows[i][0], rows[i][9]) for i in range(len(rows))]
+            data['cor'] = [(rows[i][0], rows[i][10]) for i in range(len(rows))]
+            self.stock_info['pri'] = '개인'
+            self.stock_info['fori'] = '외국인'
+            self.stock_info['ins'] = '기관합'
+            self.stock_info['ins0'] = '금융투자'
+            self.stock_info['ins1'] = '보험'
+            self.stock_info['ins2'] = '투신 (사모)'
+            self.stock_info['ins3'] = '은행'
+            self.stock_info['ins4'] = '기타금융기관'
+            self.stock_info['ins5'] = '연기금 등'
+            self.stock_info['cor'] = '기타법인'
+
+
+        # 환율
+        sql = "SELECT distinct code FROM meta_1"
+        self.cursor.execute(sql)
+        rows = self.cursor.fetchall()
+        exchange_codes = [row[0] for row in rows]
+
+        for exchange_code in exchange_codes:
+            sql = "SELECT ymd, price FROM meta_1 where code=? and ymd>=? order by ymd"
+            self.cursor.execute(sql, (exchange_code, first_day, ))
+            rows = self.cursor.fetchall()
+            if len(rows) >= limit_count:
+                data[exchange_code] = rows
+                self.stock_info[exchange_code] = exchange_code
+
+
+        # 원자재
+        sql = "SELECT distinct code FROM meta_5"
+        self.cursor.execute(sql)
+        rows = self.cursor.fetchall()
+        meterial_codes = [row[0] for row in rows]
+
+        for meterial_code in meterial_codes:
+            sql = "SELECT ymd, close FROM meta_5 where code=? and ymd>=? order by ymd"
+            self.cursor.execute(sql, (meterial_code, first_day, ))
+            rows = self.cursor.fetchall()
+            if len(rows) >= limit_count:
+                data[meterial_code] = rows
+                self.stock_info[meterial_code] = meterial_code
+
+        # 종목 종가
+        for stock_code in stock_codes:
+            sql = "SELECT ymd, close FROM stock where CODE=? and ymd>=? order by ymd"
+            self.cursor.execute(sql, (stock_code, first_day, ))
+            rows = self.cursor.fetchall()
+            if len(rows) >=limit_count:
+                data[stock_code] = rows
+
+
+
+
+        self.close()
+        return data
+
+    def debug(self, master_data, data):
+        master_days = [item[0] for item in master_data]
+
+        trimedData = {}
+        for i, stock_code in enumerate(data):
+            stock_data = data[stock_code]
+            stock_days = [item[0] for item in stock_data]
+
+            if len(master_days) < len(stock_days):
+                diff = set(stock_days) - set(master_days)
+            else:
+                diff = set(master_days) - set(stock_days)
+
+            tmp = []
+            for item in stock_data:
+                if item[0] not in diff:
+                    tmp.append((item[0], item[1]))
+            if len(tmp) == len(master_data):
+                trimedData[stock_code] = tmp
+
+        return trimedData
+
+    def trim(self, master_data, data):
+        master_days = [item[0] for item in master_data]
+
+        trimedData = {}
+        for i, stock_code in enumerate(data):
+            stock_data = data[stock_code]
+            stock_days = [item[0] for item in stock_data]
+
+            intersection = set(stock_days) & set(master_days)
+
+            tmp = []
+            for item in stock_data:
+                if item[0] in intersection:
+                    tmp.append((item[0], item[1]))
+            trimedData[stock_code] = tmp
+
+        return trimedData
+
+    def analyzeCorRelation(self, master_data, trimedData):
+        corr_scores = {}
+
+        master_days = [item[0] for item in master_data]
+        master_set = {}
+        for item in master_data:
+            master_set[item[0]] = item[1]
+
+
+        for stock_code in trimedData:
+            stock_data = trimedData[stock_code]
+
+            stock_days = [item[0] for item in stock_data]
+            stock_set = {}
+            for item in stock_data:
+                stock_set[item[0]] = item[1]
+
+            intersection = sorted(list(set(stock_days) & set(master_days)))
+            master_list = []
+            stock_list = []
+            for day in intersection:
+                master_list.append(master_set[day])
+                stock_list.append(stock_set[day])
+
+            lst = [master_list[3:], stock_list[:-3]]
+            df = pd.DataFrame(lst).T
+            corr = df.corr(method='pearson')
+
+            corr_scores[stock_code + "_" + self.stock_info[stock_code]] = corr.at[0, 1]
+
+        return corr_scores
+
+    def analyze(self, master_code, limit_count=1501):
+        stock_codes = self.get_all_stock_code()
+
+        master_data = self.load(master_code, limit_count)
+        first_day = master_data[0][0]
+
+        data = self.getClosePrice(stock_codes, first_day, limit_count)
+
+        #debugData = self.debug(master_data, data)
+        trimedData = self.trim(master_data, data)
+
+        corr_scores = self.analyzeCorRelation(master_data, trimedData)
+        return corr_scores
+
+
 if __name__ == "__main__":
-    stockPriceDirectionAnalyzer = StockPriceDirectionAnalyzer()
+    PROJECT_HOME = "."
+
+    RESOURCE_PATH = os.path.join(PROJECT_HOME, 'resources')
+    stockFileName = os.path.join(RESOURCE_PATH, 'stock.db')
+
+    stockPriceDirectionAnalyzer = StockPriceDirectionAnalyzer(stockFileName)
+    corr_scores = stockPriceDirectionAnalyzer.analyze(master_code='252670')
+    corr_scores_list = sorted(corr_scores.items(), key=lambda item: item[1], reverse=True)
+    for item in corr_scores_list:
+        print("%s %4.3f" % (item[0], item[1]))
+
+
+    print('done...')
+
+