コード例 #1
0
def get_contract_list_4year_range(**kwargs):

    now = datetime.datetime.utcnow()
    start_year = kwargs['start_year']
    end_year = kwargs['end_year']

    if 'tickerhead_list' in kwargs.keys():
        tickerhead_list = kwargs['tickerhead_list']
    else:
        tickerhead_list = cmi.cme_futures_tickerhead_list

    futures_contract_months = cmi.futures_contract_months
    contract_name_dict = cmi.contract_name
    ticker_class_dict = cmi.ticker_class
    year_list = range(start_year,end_year)
    ticker_list = []
    for i in tickerhead_list:
        contract_months = futures_contract_months[i]
        for j in contract_months:
            for k in year_list:
                ticker = i+j+str(k)
                ticker_list.append((ticker,i,k,cmi.letter_month_string.find(j)+1,exp.get_futures_expiration(ticker),
                                'futures',contract_name_dict[i],ticker_class_dict[i],'USD',now,now))

    return ticker_list
コード例 #2
0
def get_contract_list_4year_range(**kwargs):

    now = datetime.datetime.utcnow()
    start_year = kwargs["start_year"]
    end_year = kwargs["end_year"]

    if "tickerhead_list" in kwargs.keys():
        tickerhead_list = kwargs["tickerhead_list"]
    else:
        tickerhead_list = cmi.cme_futures_tickerhead_list

    futures_contract_months = cmi.futures_contract_months
    contract_name_dict = cmi.contract_name
    ticker_class_dict = cmi.ticker_class
    year_list = range(start_year, end_year)
    ticker_list = []
    for i in tickerhead_list:
        contract_months = futures_contract_months[i]
        for j in contract_months:
            for k in year_list:
                ticker = i + j + str(k)
                ticker_list.append(
                    (
                        ticker,
                        i,
                        k,
                        cmi.letter_month_string.find(j) + 1,
                        exp.get_futures_expiration(ticker),
                        "futures",
                        contract_name_dict[i],
                        ticker_class_dict[i],
                        "USD",
                        now,
                        now,
                    )
                )

    return ticker_list
コード例 #3
0
def get_simple_rate(**kwargs):

    as_of_date = kwargs['as_of_date']
    date_to = kwargs['date_to']

    if 'date_from' in kwargs.keys():
        date_from = kwargs['date_from']
    else:
        date_from = as_of_date

    if 'ticker_head' in kwargs.keys():
        ticker_head = kwargs['ticker_head']
    else:
        ticker_head = 'ED'

    ta_output_dir = dn.get_dated_directory_extension(folder_date=as_of_date,
                                                     ext='ta')

    file_name = ta_output_dir + '/' + ticker_head + '_interest_curve.pkl'

    #print('as_of_date: ' + str(as_of_date) + ', date_to: ' + str(date_to))

    if os.path.isfile(file_name):
        price_frame = pd.read_pickle(file_name)

    if (not os.path.isfile(file_name)) or price_frame.empty:
        price_frame = gfp.get_futures_price_preloaded(ticker_head=ticker_head,
                                                      settle_date=as_of_date)
        price_frame = price_frame[price_frame['close_price'].notnull()]

        price_frame.sort_values('tr_dte', ascending=True, inplace=True)
        price_frame['exp_date'] = [
            exp.get_futures_expiration(x) for x in price_frame['ticker']
        ]
        price_frame['implied_rate'] = 100 - price_frame['close_price']
        price_frame.to_pickle(file_name)

    if price_frame.empty:
        return {
            'rate_output':
            np.NaN,
            'price_frame':
            pd.DataFrame(
                columns=['ticker', 'cal_dte', 'exp_date', 'implied_rate'])
        }

    datetime_to = cu.convert_doubledate_2datetime(date_to)
    datetime_from = cu.convert_doubledate_2datetime(date_from)

    price_frame_first = price_frame[price_frame['exp_date'] <= datetime_from]
    price_frame_middle = price_frame[(price_frame['exp_date'] > datetime_from)
                                     & (price_frame['exp_date'] < datetime_to)]

    if price_frame_middle.empty:
        if not price_frame_first.empty:
            rate_output = price_frame_first['implied_rate'].iloc[-1] / 100
        else:
            rate_output = price_frame['implied_rate'].iloc[0] / 100
        return {
            'rate_output':
            rate_output,
            'price_frame':
            price_frame[['ticker', 'cal_dte', 'exp_date', 'implied_rate']]
        }

    if price_frame_first.empty:
        first_rate = price_frame_middle['implied_rate'].iloc[0]
        first_period = (
            price_frame_middle['exp_date'].iloc[0].to_pydatetime() -
            datetime_from).days
    else:
        first_rate = price_frame_first['implied_rate'].iloc[-1]
        first_period = (
            price_frame_middle['exp_date'].iloc[0].to_pydatetime() -
            datetime_from).days

    last_rate = price_frame_middle['implied_rate'].iloc[-1]
    last_period = (
        datetime_to -
        price_frame_middle['exp_date'].iloc[-1].to_pydatetime()).days

    middle_discount = [
        1 + (price_frame_middle['implied_rate'].iloc[x] *
             (price_frame_middle['cal_dte'].iloc[x + 1] -
              price_frame_middle['cal_dte'].iloc[x]) / 36500)
        for x in range(len(price_frame_middle.index) - 1)
    ]

    total_discount = np.prod(
        np.array(middle_discount)) * (1 +
                                      (first_rate * first_period / 36500)) * (
                                          1 +
                                          (last_rate * last_period / 36500))

    total_period = (
        price_frame_middle['cal_dte'].iloc[-1] -
        price_frame_middle['cal_dte'].iloc[0]) + first_period + last_period

    rate_output = (total_discount - 1) * 365 / total_period

    return {
        'rate_output':
        rate_output,
        'price_frame':
        price_frame[['ticker', 'cal_dte', 'exp_date', 'implied_rate']]
    }
コード例 #4
0
def get_simple_rate(**kwargs):

    as_of_date = kwargs["as_of_date"]
    date_to = kwargs["date_to"]

    if "date_from" in kwargs.keys():
        date_from = kwargs["date_from"]
    else:
        date_from = as_of_date

    if "ticker_head" in kwargs.keys():
        ticker_head = kwargs["ticker_head"]
    else:
        ticker_head = "ED"

    ta_output_dir = dn.get_dated_directory_extension(folder_date=as_of_date, ext="ta")

    file_name = ta_output_dir + "/" + ticker_head + "_interest_curve.pkl"

    # print('as_of_date: ' + str(as_of_date) + ', date_to: ' + str(date_to))

    if os.path.isfile(file_name):
        price_frame = pd.read_pickle(file_name)

    if (not os.path.isfile(file_name)) or price_frame.empty:
        price_frame = gfp.get_futures_price_preloaded(ticker_head=ticker_head, settle_date=as_of_date)
        price_frame = price_frame[price_frame["close_price"].notnull()]

        price_frame.sort("tr_dte", ascending=True, inplace=True)
        price_frame["exp_date"] = [exp.get_futures_expiration(x) for x in price_frame["ticker"]]
        price_frame["implied_rate"] = 100 - price_frame["close_price"]
        price_frame.to_pickle(file_name)

    if price_frame.empty:
        return {
            "rate_output": np.NaN,
            "price_frame": pd.DataFrame(columns=["ticker", "cal_dte", "exp_date", "implied_rate"]),
        }

    datetime_to = cu.convert_doubledate_2datetime(date_to)
    datetime_from = cu.convert_doubledate_2datetime(date_from)

    price_frame_first = price_frame[price_frame["exp_date"] <= datetime_from]
    price_frame_middle = price_frame[
        (price_frame["exp_date"] > datetime_from) & (price_frame["exp_date"] < datetime_to)
    ]

    if price_frame_middle.empty:
        if not price_frame_first.empty:
            rate_output = price_frame_first["implied_rate"].iloc[-1] / 100
        else:
            rate_output = price_frame["implied_rate"].iloc[0] / 100
        return {
            "rate_output": rate_output,
            "price_frame": price_frame[["ticker", "cal_dte", "exp_date", "implied_rate"]],
        }

    if price_frame_first.empty:
        first_rate = price_frame_middle["implied_rate"].iloc[0]
        first_period = (price_frame_middle["exp_date"].iloc[0].to_datetime() - datetime_from).days
    else:
        first_rate = price_frame_first["implied_rate"].iloc[-1]
        first_period = (price_frame_middle["exp_date"].iloc[0].to_datetime() - datetime_from).days

    last_rate = price_frame_middle["implied_rate"].iloc[-1]
    last_period = (datetime_to - price_frame_middle["exp_date"].iloc[-1].to_datetime()).days

    middle_discount = [
        1
        + (
            price_frame_middle["implied_rate"].iloc[x]
            * (price_frame_middle["cal_dte"].iloc[x + 1] - price_frame_middle["cal_dte"].iloc[x])
            / 36500
        )
        for x in range(len(price_frame_middle.index) - 1)
    ]

    total_discount = (
        np.prod(np.array(middle_discount))
        * (1 + (first_rate * first_period / 36500))
        * (1 + (last_rate * last_period / 36500))
    )

    total_period = (
        (price_frame_middle["cal_dte"].iloc[-1] - price_frame_middle["cal_dte"].iloc[0]) + first_period + last_period
    )

    rate_output = (total_discount - 1) * 365 / total_period

    return {"rate_output": rate_output, "price_frame": price_frame[["ticker", "cal_dte", "exp_date", "implied_rate"]]}
コード例 #5
0
                          ('SIJ2016', pd.datetime(2016, 3, 28)),
                          ('SIK2016', pd.datetime(2016, 4, 26)),
                          ('SIM2016', pd.datetime(2016, 5, 25)),
                          ('SIN2016', pd.datetime(2016, 6, 27)),
                          ('SIQ2016', pd.datetime(2016, 7, 26)),
                          ('SIU2016', pd.datetime(2016, 8, 25)),
                          ('SIZ2016', pd.datetime(2016, 11, 22)),
                          ('SIN2017', pd.datetime(2017, 6, 27)),
                          ('SIZ2017', pd.datetime(2017, 11, 27)),
                          ('SIN2018', pd.datetime(2018, 6, 26)),
                          ('SIZ2018', pd.datetime(2018, 11, 27)),
                          ('SIN2019', pd.datetime(2019, 6, 25)),
                          ('SIZ2019', pd.datetime(2019, 11, 25)),
                          ('SIN2020', pd.datetime(2020, 6, 25)),
                          ('SIZ2020', pd.datetime(2020, 11, 24)))


success_indx = [exp.get_futures_expiration(expiration_test[i][0]) == expiration_test[i][1] for i in range(len(expiration_test))]
#success_indx = [exp.get_options_expiration(option_expiration_test[i][0]) == option_expiration_test[i][1] for i in range(len(option_expiration_test))]
failed = [expiration_test[i] for i in range(len(expiration_test)) if not success_indx[i]]
#failed = [option_expiration_test[i] for i in range(len(option_expiration_test)) if not success_indx[i]]

if not failed:
    print('TEST PASSED!')
else:
    print('TEST FAILED:')
    for i in failed:
        print(i)