コード例 #1
0
import pandas as pd

# KOSPI code list
kospi = get_code_list_by_market(market=2)
kospi.to_excel("KOSPI.xlsx")

# KOSDAQ code list
kosdaq = get_code_list_by_market(market=3)
kosdaq.to_excel("KOSDAQ.xlsx")

# KOSPI+KOSDAQ
df = pd.concat([kospi, kosdaq])
#print(df.head())

# k
k = srim_reader.get_5years_earning_rate()

data = []
index = 0
for acode in df.index:
    name = df.loc[acode, "nm"]
    disparity, *others = srim.get_disparity(acode, k, w=0.7)
    roe = others[5]
    data.append({'code': acode, 'name': name, 'disparity': disparity, 'roe': roe})
    time.sleep(3)
    print(index, "/", len(df.index))
    if index == 20:
        break
    index += 1

# filtering the company (ROE > k)
コード例 #2
0
ファイル: __init__.py プロジェクト: umzzi/pystocklib
    :param code:
    :param k:
    :param w:
    :return:
    """
    est_price, shares, value, net_worth, roe, excess_earning, price1, price2 = estimate_price(code, k, w)
    cur_price = reader.get_current_price(code)

    try:
        disparity = (cur_price / est_price) * 100
        disparity20 = (cur_price / price2) * 100
    except:
        disparity = None
        disparity20 = None
    return disparity, cur_price, est_price, shares, value, net_worth, roe, excess_earning, price1, price2, disparity20


if __name__ == "__main__":
    k = reader.get_5years_earning_rate()

    #price_w = estimate_price("005930")
    #price_w_10 = estimate_price("005930", w=0.9)
    #price_w_20 = estimate_price("005930", w=0.8)
    #k = reader.get_5years_earning_rate()
    #print(get_disparity("005930", k, w=0.3))

    print(estimate_price("023460", k))



コード例 #3
0
ファイル: testGetShares.py プロジェクト: umzzi/pystocklib
# print("pegr:",pegr)
# print(epsavg)

price = ""
if price is not None and bool(price):
    print(int(float(price)))

# cf = pd.read_html(hh_reader.get_html_fnguide(code, gb=4))
# print(cf)

print(sys.argv[1])
print(sys.argv[2])
print(sys.argv[3])

# eps2 = [3479.0, 2088.0, 2643.0, 3364.0]
eps2 = [5421.0, 6024.0, 3166.0, 4067.0]
eps2 = [5931.0, 6325.0, 6812.0, 7416.0]

eps_incr_percent, eps_geo_avg, eps_incre_level = hh_reader.calculate_eps(eps2)
print(srim_calculator.calculate_pegr(eps_geo_avg, 1.0))
print(eps_incr_percent)
print(eps_geo_avg)

k = get_5years_earning_rate()
print(k)

# KOSPI code list
kospi = get_code_list_by_market(market=2)
kospi.to_excel("KOSPI3.xlsx")