building quant database and risk modeling / transaction cost analysis
Does anyone have experience setting up a quant database? What is the most optimal way to structure the tables?
Also are there any good references for transaction cost analysis and risk modeling? Want to start with mainly equities and options.
Thanks for any advice from experienced voices.
Bloomberg terminal
bloomberg terminal is terrible for historical data
It really depends on what you're trying to do ( what type of queries you'll run) and how big the data sets are. You could use a relational database - or one of those nosql ones.
i'm trying to build a securities database. But also interested in being able to query 13f filings.
If it’s timeseries, you should use a columnar database like Cassandra.
it's best to use a vendor for 13f filings (you don't want to download all that stuff yourself and then parse it) and have your securities records easily matchable with the vendor's securities. You'll probably be OK with a relational database structure.
I have the data for 13f filings already so don't plan on scraping it. Have you built a securities database before? I'm mainly looking for the best way to structure the relationships.
It's hard to make suggestions without knowing your requirements, your tech stack, and your skills/experience. With that said, here are some pointers:
https://github.com/alpacahq/marketstore</a">MarketStore -- DataFrame Server for Financial Timeseries Data
https://github.com/timescale/timescaledb</a">TimescaleDB -- Open-source database designed to make SQL scalable for time-series data
https://github.com/man-group/arctic</a">Arctic -- TimeSeries and Tick store
https://github.com/influxdata/influxdb</a">InfluxDB -- Scalable datastore for metrics, events, and real-time analytics
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