Databases in Trading

I'm looking to apply for a job and it seems they require a lot of Excel and Access work. The Excel part is clear, but I'm not sure about Access.

How is Microsoft Access or other database software used in S&T, especially in commodity trading?

9 Comments
 
CanDoI'm looking to apply for a job and it seems they require a lot of Excel and Access work. The Excel part is clear, but I'm not sure about Access.

How is Microsoft Access or other database software used in S&T, especially in commodity trading?

no idea...but interested to hear as well.

I know it can be used as a powerful contact manager, but not sure what else it's usually used for...

 
Best Response

Not sure why people are saying it would be useless.. Contrary to the above, I think it's not very impactful for contact management -- anyone can come up with a workable solution for maintaining contacts.

Databases are useful in almost any business which, unsurprisingly, deals with data. Trading is highly data intensive, also unsurprisingly. A couple examples where you might use a database in trading are:

-- Maintaining information such as parameters for a large set of products. -- Storing your trades and other useful information associated with said trades. This would be especially useful when you want to look back at the trades and filter/process them in various ways to try to learn about what you're doing well/poorly. Using a database allows you to query stuff on the fly when you think of different ways to examine your own data. -- Various operational stuff like maintaining positions, account information, etc. You want to be able to query these in an interactive way if you want to be able to aggregate your positions in different ways on the fly, which can be useful for evaluating the risk of your portfolio.

Let's try to make uninformed claims less often..

 
juked07Not sure why people are saying it would be useless.. Contrary to the above, I think it's not very impactful for contact management -- anyone can come up with a workable solution for maintaining contacts.

Databases are useful in almost any business which, unsurprisingly, deals with data. Trading is highly data intensive, also unsurprisingly. A couple examples where you might use a database in trading are:

-- Maintaining information such as parameters for a large set of products. -- Storing your trades and other useful information associated with said trades. This would be especially useful when you want to look back at the trades and filter/process them in various ways to try to learn about what you're doing well/poorly. Using a database allows you to query stuff on the fly when you think of different ways to examine your own data. -- Various operational stuff like maintaining positions, account information, etc. You want to be able to query these in an interactive way if you want to be able to aggregate your positions in different ways on the fly, which can be useful for evaluating the risk of your portfolio.

Let's try to make uninformed claims less often..

But at the same time, I doubt Access is what would be used in terms of database management on any trading desk. I've only spent large amounts of time at my desk and haven't seen others, but I know for us we do not use MS Access but rather have loads of proprietary software we use for all of our database stuff. It's significantly more robust and very specialized for our needs, which is how I feel most desks would be set up.

 

Front, Mid, or back-office? Being able to use databases is a great skill and one we look for. Not a fan of MS Access it is really a last case tool. Understanding how data structures work and SQL would be the best bet.

As a commodity desk we mainly use databases to build analytics to look at trends and project future patterns. We have a series of data updates that run overnight and input tons of info, such as daily weather/supply and demand #s/current prices/current future strip and so. Then we have models which use this data in a proper format. For instance I could pull 10 years of weather data for certain areas in the US and compare to pricing data, then compare to where the S/D of that commodity was and so on.

 

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