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Python For Finance: Algorithmic Trading

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Re: Python For Finance: Algorithmic Trading

#11
post #5

Earlier quoted context omitted.

Have you done this? If so it would be great to get your perspective

Yes, I am doing it as a side project and I am looking to retire in a few years and live off that...

I'll third this comment. Some more details on what you trade, where you trade, how long you've been doing it, performance metrics, etc... would be fascinating.

Re: Python For Finance: Algorithmic Trading

#12
post #5

Earlier quoted context omitted.

Yes, I am doing it as a side project and I am looking to retire in a few years and live off that...

I'll third this comment. Some more details on what you trade, where you trade, how long you've been doing it, performance metrics, etc... would be fascinating.

As you can see I am paranoid, because the more people trading the same strategy, the less effective it becomes, not to mention, if someone knows your trading strategy it can trade against you... it’s a zero sum game after all...

All that said, here are the 2 most important advises I wish someone told me when I started years ago:

Have an iron clad risk management strategy for your portfolio, e.g. if you are willing to risk 1% of your capital on any given day and tomorrow happens to be the Black Monday and all stock go down 50% you still have to be sure you’ll loose only 1% if you have to sell everything... This is where the back data comes into play – the goal is to back test not how much money you are going to make, but how much money you are going to loose in the worst case scenario if you have to liquidate everything and move to all cash. If you have this working 100%, you just need a trading strategy with a minimal edge and you’ll make money in the long run in the market and the compounding effect will really make you a rich person (rich person to me is someone who makes more money then he spends, WITHOUT working more than 1 hour a day)

And the second advice is never ever trust and buy a trading strategy from someone, the fact he is selling or "teaching" a trading strategy means it is not working and he is trying to make some money by scamming people and selling the dream, all those trading educators cannot make money trading and that’s why they are coming with up with those fake trading courses... just check this website to see the magnitude of this scam and how people are loosing their life savings... I just don’t know why FBI, SEC and the government is not doing something to stop those guys...

https://www.tradingschools.org/

Good luck and as I said before, just treat is as a hobby at first and spend the time testing and you’ll find something that is working for you...

EDIT: some spelling errors fixed.

Re: Python For Finance: Algorithmic Trading

#13
Personally, I struggle to see the competitive advantage Quantopian brings. They use retail brokerage platforms to facilitate trading, which rules out anything close to HFT. Then, they are tied to any financial data vendor (Morningstar in this case) to not offer too much visibility on the underlying data. As others have mentioned, this makes it tough to validate aspects like adjusted vs. as reported earnings, how delistings are handled, etc. From my experience, getting/making sure the data is accurate is a ton of work, even if it is from good sources and you can see all the actual data. The moment an investor/trader on the platform gets traction is the moment they want Compustat data, exchange data, Bloomberg for fixed income, and will trade through Instinet/Flextrade, etc. The moment the platform is successful is the moment Morningstar could pull the rug out from them. If someone has better understanding or knowledge on Quantopian in particular, I'd be interested to hear why.

Re: Python For Finance: Algorithmic Trading

#14

Personally, I struggle to see the competitive advantage Quantopian brings. They use retail brokerage platforms to facilitate trading, which rules out anything close to HFT. Then, they are tied to any financial data vendor (Morningstar in this case) to not offer too much visibility on the underlying data. As others have mentioned, this makes it tough to validate aspects like adjusted vs. as reported earnings, how deli…

My understanding is that Quantopian has no interest in being a platform for HFT. It's there to democratize trading strategies and test them in a sound way. They do a lot to have a good backtesting platform and clean the data that is available in the platform. If I wanted to automate a strategy, I'd have to figure out the Robinhood API and basically recreate what they have. Instead, I can use their platform, their backtests, their free data, and build strategies that efficiently lose money.

I think the other goal being that if you create a profitable strategy, you can enter it into competitions, trade with other people's money, and make a profit. I think the platform is a value add, I have an account and use the research notebooks. Some day when I more spare time I'll make some trading algorithms.

Re: Python For Finance: Algorithmic Trading

#15
post #2

It is a great article, but why on earth someone will use a service like Quantopian or similar service? They are your competitor and who will prevent a disgruntle employee or a hacker to steel your successful trading strategy? Just buy some data from eBay, you can get 20 years of historical stock market data for less than $100 and you can test any trading strategy or idea imaginable, including trend following, buy and…

Not everyone can build their own backtesting tool. I played around with quantopian for a little while and did some live trading with quantopian + robinhood and I never would have been able to do that without quantopian

Re: Python For Finance: Algorithmic Trading

#16
post #14

Personally, I struggle to see the competitive advantage Quantopian brings. They use retail brokerage platforms to facilitate trading, which rules out anything close to HFT. Then, they are tied to any financial data vendor (Morningstar in this case) to not offer too much visibility on the underlying data. As others have mentioned, this makes it tough to validate aspects like adjusted vs. as reported earnings, how deli…

My understanding is that Quantopian has no interest in being a platform for HFT. It's there to democratize trading strategies and test them in a sound way. They do a lot to have a good backtesting platform and clean the data that is available in the platform. If I wanted to automate a strategy, I'd have to figure out the Robinhood API and basically recreate what they have. Instead, I can use their platform, their bac…

The main problem with Quantopian is that the data missing especially for delisted stocks, here are some examples you can test yourself: AA, CWH, NIHD, PANL, HTZ, DSL - I have a whole list I found very fast, just imagine what other mistakes could be there... And the other problem is that they are my competitor, so I would never give them my trading strategy or ideas I am testing at the moment...

Re: Python For Finance: Algorithmic Trading

#18
post #15
post #2

It is a great article, but why on earth someone will use a service like Quantopian or similar service? They are your competitor and who will prevent a disgruntle employee or a hacker to steel your successful trading strategy? Just buy some data from eBay, you can get 20 years of historical stock market data for less than $100 and you can test any trading strategy or idea imaginable, including trend following, buy and…

Not everyone can build their own backtesting tool. I played around with quantopian for a little while and did some live trading with quantopian + robinhood and I never would have been able to do that without quantopian

I am not a developer, but using my brokers API, examples and python, it took me few months to build a very robust and automatic trading system... I did learn python by back testing my trading ideas... To use Quantopian you still have to learn python, so I am not sure where is the benefit, considering all the problems mentioned here...

Re: Python For Finance: Algorithmic Trading

#19
I went to the Quantopian conference for their basic training on algorithmic trading. This blog post was pretty much what they covered, intro to pandas and a simple strategy. There is a lot of educational material on their site too (which is what you ended up getting in the paid training).

My biggest thing with the Python for Finance books - I know Python, I want to learn finance. All these books are the inverse of that, for people who know finance and want to learn Python. There is a good site for quantitative economics [1] that has tutorials in Python and Julia. I would love a mathematics of finance book that had the examples in Python.

1. https://lectures.quantecon.org/py/

Re: Python For Finance: Algorithmic Trading

#20
post #16
post #14

Earlier quoted context omitted.

My understanding is that Quantopian has no interest in being a platform for HFT. It's there to democratize trading strategies and test them in a sound way. They do a lot to have a good backtesting platform and clean the data that is available in the platform. If I wanted to automate a strategy, I'd have to figure out the Robinhood API and basically recreate what they have. Instead, I can use their platform, their bac…

The main problem with Quantopian is that the data missing especially for delisted stocks, here are some examples you can test yourself: AA, CWH, NIHD, PANL, HTZ, DSL - I have a whole list I found very fast, just imagine what other mistakes could be there... And the other problem is that they are my competitor, so I would never give them my trading strategy or ideas I am testing at the moment...

The trading strategy stuff has been brought up before. They say when evaluating algorithms they only look at the alpha, beta, etc. and not the algorithm itself. While the system can see what you're running, I think they work pretty hard to let your code be yours. I'm definitely not very advanced in algorithmic trading, so I see how there could be some data issues that I wouldn't come across.
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