def enrich(raw_prices):
en_prices = []
for i, price in enumerate(raw_prices[0: -1]):
#get the past 30 day's daily change
past30_changes = [float(p["currentValue"]) - float(p["previousClosePrice"]) for p in raw_prices[i + 1: i + 30]]
day_change = float(price["currentValue"]) - float(price["previousClosePrice"])
z30 = calculator.calZscore(past30_changes, day_change)
past90_changes = [float(p["currentValue"]) - float(p["previousClosePrice"]) for p in raw_prices[i + 1: i + 90]]
z90 = calculator.calZscore(past90_changes, day_change)
en_message = {}
en_message["postDate"] = price["date"][0:10]
en_message["zscore30"] = round(z30, 4)
en_message["zscore90"] = round(z90, 4)
en_message["derivedFrom"] = {"derivedIds": [price["embersId"]]}
en_message["type"] = price["type"]
en_message["currentValue"] = price["currentValue"]
en_message["name"] = price["name"]
en_message["previousCloseValue"] = price["previousClosePrice"]
en_message["oneDayChange"] = round(day_change, 4)
en_message["changePercent"] = round(day_change / price["currentValue"], 4)
en_message["embersId"] = hashlib.sha1(str(en_message)).hexdigest()
en_prices.append(en_message)
return en_prices
def getZscore(t_domain, cur_date, stock_index, cur_diff, duration):
scores = []
sql = "select oneDayChange from t_enriched_bloomberg_prices where postDate<'{}' and name = '{}' order by postDate desc".format(cur_date, stock_index)
rows = t_domain.select(sql, max_items=duration)
for row in rows:
scores.append(float(row['oneDayChange']))
zscore = calculator.calZscore(scores, cur_diff)
return zscore
def getZscore(conn,cur_date,currency_index,cur_diff,duration):
t_domain = get_domain(conn,"t_enriched_bloomberg_prices")
scores = []
sql = "select oneDayChange from t_enriched_bloomberg_prices where post_date<'{}' and name = '{}' order by post_date desc".format(cur_date,currency_index)
rows = t_domain.select(sql,max_items=duration)
for row in rows:
scores.append(row["oneDayChange"])
zscore = calculator.calZscore(scores, cur_diff)
return zscore
def getZscore(conn,cur_date,stock_index,cur_diff,duration):
cur = conn.cursor()
scores = []
sql = "select one_day_change from t_enriched_bloomberg_prices where post_date<? and name = ? order by post_date desc limit ?"
cur.execute(sql,(cur_date,stock_index,duration))
rows = cur.fetchall()
for row in rows:
scores.append(row[0])
zscore = calculator.calZscore(scores, cur_diff)
return zscore
