python-batch/fsi_montecarlo/OLD/pubsub_bq.tpl.py (99 lines of code) (raw):

#!/usr/bin/env python3 # Copyright 2023 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """ Run MC simulation for VaR portfolio risk """ import avro.schema import io import google.auth import numpy import time import yfinance as yf from absl import app from absl import flags from avro.io import DatumWriter, BinaryEncoder, BinaryDecoder, DatumReader from datetime import datetime from datetime import timedelta from google.cloud import pubsub_v1, bigquery from google.cloud.pubsub import SchemaServiceClient PROJECT_ID = '${project_id}' INCOMING_TOPIC_ID = '${topic_name}' INCOMING_TOPIC_SCHEMA = '${schema_name}' DATASET_ID = '${dataset_name}' TABLE_ID = '${table_name}' FLAGS = flags.FLAGS flags.DEFINE_string("ticker", 'GOOG', "Nasdaq Stock Ticker to run, default GOOG") flags.DEFINE_string("start_date", '2022-01-01' , "Start data for data query, default 2022-01-01") flags.DEFINE_integer("calendar_days", 365 , "How many calendar days to include in the calculation") flags.DEFINE_integer("epoch_time", f'{int(time.time())}' , "Epoch time, number of seconds since January 1st, 1970 at 00:00:00 UTC.") flags.DEFINE_integer("iterations", 100 , "Number of iterations to run.") flags.DEFINE_boolean("print_raw", False, "Dump raw data.") class VaRSimulator: def __init__(self): pass def get_data(self): self.get_historical_data_yahoo() def get_historical_data_yahoo(self): # get historical market data: https://pypi.org/project/yfinance/ self.raw_data = yf.Ticker(self.ticker).history(start=self.start_date, end=self.end_date ) self.data = self.raw_data.Close def print_raw(self): print(self.get_stats()) print(type(self.raw_data)) print(self.raw_data) def get_stats(self): close = self.data self.first = close[0] self.last = close[-1] self.trading_days = len(close) self.cagr = (self.last / self.first) ** (365.0/self.calendar_days) -1.0 self.volatility = self.data.pct_change().std() return(self.first, self.last, self.trading_days, self.cagr, self.volatility) def run_simulation(self): returns = numpy.random.normal(self.cagr/self.trading_days, self.volatility, self.trading_days) + 1 returns = numpy.insert(returns,0,1.0) self.simulation_results = self.last * returns.cumprod() return(self.simulation_results) def create_object(self): self.object = { "ticker": self.ticker, "epoch_time": self.epoch_time, "iteration": self.iteration, "start_date": self.start_date, "end_date": self.end_date, "simulation_results": list(map(lambda x: {"price":x}, self.simulation_results)) } return(self.object) class PubsubToBiquery: def __init__(self): the_time = int(time.time()) self.project_id = PROJECT_ID self.publisher_client = pubsub_v1.PublisherClient() self.topic_path = self.publisher_client.topic_path(self.project_id, INCOMING_TOPIC_ID) self.schema_client = SchemaServiceClient() self.schema_path = self.schema_client.schema_path(self.project_id, INCOMING_TOPIC_SCHEMA) pubsub_schema = self.schema_client.get_schema(request={"name": self.schema_path}) avro_schema = avro.schema.parse(pubsub_schema.definition) self.writer = DatumWriter(avro_schema) def publish_record(self,record): byte_stream = io.BytesIO() encoder = BinaryEncoder(byte_stream) self.writer.write(record, encoder) data = byte_stream.getvalue() byte_stream.flush() future = self.publisher_client.publish(self.topic_path, data) if(FLAGS.print_raw): print(f"Published message ID: {future.result()}") def main(argv): vr = VaRSimulator() pbbq = PubsubToBiquery() vr.ticker =FLAGS.ticker vr.start_date =FLAGS.start_date vr.end_date =f'{(datetime.strptime(FLAGS.start_date,"%Y-%m-%d") + timedelta(days = FLAGS.calendar_days)).date()}' vr.calendar_days = FLAGS.calendar_days vr.epoch_time = FLAGS.epoch_time vr.iteration = 1 vr.get_data() vr.get_stats() for i in range(FLAGS.iterations): vr.iteration = i vr.run_simulation() pbbq.publish_record(vr.create_object()) if(FLAGS.print_raw): vr.print_raw() if __name__ == "__main__": """ This is executed when run from the command line """ app.run(main)