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Updated test file

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Gourav Kumar 2022-06-06 08:17:12 +05:30
parent c713e3283b
commit 569f20709b
1 changed files with 14 additions and 18 deletions
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testing.ipynb
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@ -485,7 +485,7 @@
"source": [
"import random\n",
"import math\n",
"import fincal as fc\n",
"import pyfacts as pft\n",
"from typing import List\n",
"import datetime\n",
"from dateutil.relativedelta import relativedelta"
@ -536,7 +536,7 @@
"\n",
"\n",
"def sample_data_generator(\n",
" frequency: fc.Frequency,\n",
" frequency: pft.Frequency,\n",
" num: int = 1000,\n",
" skip_weekends: bool = False,\n",
" mu: float = 0.1,\n",
@ -571,11 +571,11 @@
" start_date = datetime.datetime(2017, 1, 1)\n",
" timedelta_dict = {\n",
" frequency.freq_type: int(\n",
" frequency.value * num * (7 / 5 if frequency == fc.AllFrequencies.D and skip_weekends else 1)\n",
" frequency.value * num * (7 / 5 if frequency == pft.AllFrequencies.D and skip_weekends else 1)\n",
" )\n",
" }\n",
" end_date = start_date + relativedelta(**timedelta_dict)\n",
" dates = fc.create_date_series(start_date, end_date, frequency.symbol, skip_weekends=skip_weekends, eomonth=eomonth)\n",
" dates = pft.create_date_series(start_date, end_date, frequency.symbol, skip_weekends=skip_weekends, eomonth=eomonth)\n",
" values = create_prices(1000, mu, sigma, num)\n",
" ts = list(zip(dates, values))\n",
" return ts\n"
@ -583,40 +583,36 @@
},
{
"cell_type": "code",
"execution_count": 12,
"execution_count": 6,
"id": "c85b5dd9-9a88-4608-ac58-1a141295f63f",
"metadata": {},
"outputs": [],
"source": [
"data = sample_data_generator(num=261, frequency=fc.AllFrequencies.W)\n",
"ts = fc.TimeSeries(data, \"W\")"
"market_data = sample_data_generator(num=3600, frequency=pft.AllFrequencies.D)\n",
"mts = pft.TimeSeries(market_data, \"D\")\n",
"stock_data = sample_data_generator(num=3600, frequency=pft.AllFrequencies.D, mu=0.12, sigma=0.05)\n",
"sts = pft.TimeSeries(stock_data, 'D')"
]
},
{
"cell_type": "code",
"execution_count": 13,
"execution_count": 8,
"id": "0488a4d0-bca1-4341-9fae-1fd254adc0dc",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"TimeSeries([(datetime.datetime(2017, 1, 1, 0, 0), 1003.03),\n",
"\t (datetime.datetime(2017, 1, 8, 0, 0), 1002.71),\n",
"\t (datetime.datetime(2017, 1, 15, 0, 0), 1008.77)\n",
"\t ...\n",
"\t (datetime.datetime(2021, 12, 12, 0, 0), 1107.21),\n",
"\t (datetime.datetime(2021, 12, 19, 0, 0), 1106.66),\n",
"\t (datetime.datetime(2021, 12, 26, 0, 0), 1104.32)], frequency='W')"
"1.020217253491451"
]
},
"execution_count": 13,
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ts"
"pft.beta(sts, mts)"
]
},
{
@ -708,7 +704,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.2"
"version": "3.10.4"
}
},
"nbformat": 4,