HN Academy

I took computational investing on coursera, which seems to have some overlap with the contents of the book. Course involves building and back testing stock trading strategies in python.

https://www.coursera.org/course/compinvesting1

⬐ dnesteruk

That course isn't really well done. There are much better quant courses out there on Coursera.

⬐ leoplct

Do you have get some profit using these strategies?

⬐ myth_drannon

no, because the prof that teaches this course still didn't make any money using these strategies, otherwise he would be on his yacht in French Riviera

⬐ throwaway13qf85

Is that the Georgia Tech/Tucker Balch course?

I'm amazed that GT let him teach that course. It's full of errors, omissions and bad habits. I vaguely followed along, and the most noticeable thing was how much the students complained about the low quality of the course.

The only result of someone implementing the advice in that course is that they'd lose a lot of money quite quickly.

I'm doing Computational Investing from gatech on coursera now, https://www.coursera.org/course/compinvesting1.

I do enjoy the course because I wanted to learn more about finance, although they could improve a lot on their presentation skills and material preparation. I hope they will take a lesson or two from their coursera feedback for the benefit of their online students.

⬐ gohwell

Good class, I can't stand the first 15 second music intro.

renting machines really close to multiple exchanges and keeping them running would be cost prohibitive for most individual investor.

I'm currently taking https://www.coursera.org/course/compinvesting1, it's quite basic but the next course, 'Computational Investing 2' will go through Machine Learning for investing (scheduled for January I think).

Hope this helps.

Cool - which course is she taking? This is the Computational Investing course. Buried very deep in a forum is a post by the tutor saying that you should know programming and how to use the command line - unfortunately it's too well hidden.

The main struggle has actually been with people on OSX Lion getting the libraries installed.

https://www.coursera.org/course/compinvesting1

⬐ marklit

She's doing the 'Learn to Program: The Fundamentals' course run by U of T. I'm glad she did as it's forcing me to use Python 3 :)

⬐ Rossimac

On the introduction page of this course it states, "This course is intended for folks who have a strong programming background, but who are new to finance and investing."

Hardly well-hidden.

⬐ aidos

I stand corrected. Maybe there should be a test to weed people out early then. Dunno - there are a few too many people on the forums who don't know the 'cd' command.

I was referring to this little quiz [1] which I thought should be posted directly in the description to scare people off.

[1] http://wiki.quantsoftware.org/index.php?title=Compinvesti-pr...

⬐ Rossimac

Definitely a bit more computationally intensive than I would have imagined it to be. That's a bit of a challenge even for some with a CS degree!

Cheers for pointing this course out, though. It's right up my street.

⬐ aidos

Great! Very interesting stuff (as it's all new to me).

Not a problem. You are going to want to tackle your fundamentals first.

This includes things like linear algebra and basic matrix operations, statistical inference (correlation, p tests, sampling,probability,..), and then start working your way up the tree for algorithms.

The order in [1] is a good order and will get you familiar with the fundamentals in a fairly easy way. Use [1] for the overviews of different topics as well. Note that [1] isn't a good in depth practice though.

It's a fairly hand holding introduction to machine learning in general. After you get the brief overview down, start looking in to different problems that might interest you.

Depending on how you learn, since you know R, put some things in to practice with R. It has fantastic support for most learning algorithms as direct libraries.

Other than that, depending on what you're interested in (finance, so I'm assuming forecasting?) start looking in to domain specific problems that you're comfortable with.

One thing I've seen people do is use kaggle [2] for the "Knowledge" competitions. Those are essentially tutorials with test datasets.

Since you're in finance, you maybe interested in the signal processing based math that goes in to guessing when something happens within a certain time period.

See [3] for finance specific and [4] for the more general engineering math.

I hope that helps. Independent study is largely based on how you learn and just leveraging resources available coupled with practice in subjects you find interesting to maintain motivation.

Now keep in mind everyone is different. Some like the courses and homework approach, others just like experimenting on something they're interested in to accomplish concrete goals.

[1] https://class.coursera.org/ml/lecture/preview

[2] http://www.kaggle.com/competitions

[3] https://www.coursera.org/course/compinvesting1

[4] https://www.coursera.org/course/scientificcomp

⬐ gedrap

The reason for sharing is that I've noticed many people asking about quant trading and etc recently. Hopefully it will be useful.

This could be an interesting course for people wanting to know more about 'computational investing' and the algorithms behind stock (market) analysis and trading: https://www.coursera.org/course/compinvesting1. Not specially targeted at HFT, but interesting basic background information nevertheless.

An interesting course on using software algorithms for stock analysis and trading can be found at Coursera: https://www.coursera.org/course/compinvesting1

That course also uses Python as programming language in the examples. Short description from that URL: "Find out how modern electronic markets work, why stock prices change in the ways they do, and how computation can help our understanding of them. Build algorithms and visualizations to inform investing practice."

There is a coursera course called "Computational Investing, Part I" that I am taking that aims to build a market trading simulator to test a trading model. It just started so it's not too late to join.

https://www.coursera.org/course/compinvesting1