81–87 of 87 posts
Looking at the terms & conditions, any algorithms that the users create become the intellectual property of Quantblocks. Is this just a tool to help users or is it a tool for the company to source the best algorithms?
If you find Quantblocks interesting, you should also look at Quantopian. (www.quantopian.com) We're geared a bit more towards programmers. Rather than use blocks, our members develop their algorithms in Python. We have an in-browser IDE with a lot of smart auto-completion. A few of our nifty features: * free access to 10 years of by-minute historical data for all US stocks * the writer of the algorithm owns the algor…
Additionally, the choices you've made for inclusion could be more diverse. Where is SPY, SQQQ, GLD, etc?
If you find Quantblocks interesting, you should also look at Quantopian. (www.quantopian.com) We're geared a bit more towards programmers. Rather than use blocks, our members develop their algorithms in Python. We have an in-browser IDE with a lot of smart auto-completion. A few of our nifty features: * free access to 10 years of by-minute historical data for all US stocks * the writer of the algorithm owns the algor…
Do you guys have historical data for equity options?
However, we are actually more excited about adding non-market data, because we want to bring more talent to 'algorithmic investment'. We hope our community can create algorithms that make buy/sell decisions based on more than just liquidity - fundamentals, reported data, qualitative news and research content. In other words, automating more of fundamental analysis and investment.
It is really too bad folks keep pushing technical trading platforms to the public. The promise of quick money to be made in a sea of billions of dollars might seem innocuous, but it's (a) bad for the market and (b) bad for society. It's bad for the market because collectively, the buying and selling of shares based on anything other than company fundamentals (earnings, cash flow, projected growth, etc) distorts the p…
I work at Quantopian, and our goal is to make it possible for more people to explore algorithmic investing. I agree the social utility of from increasing liquidity from current levels is at best diminishing returns, but algorithms could bring the same drop in costs and increase in quality for money management that it brought to trading. That's a benefit to individuals, pension funds, charitable endowments, and anyone else that has to save and plan for the future. Financial professions couldn't have a worse rap these days, much of it deserved, but there are real social problems that require financial solutions. People need to save for retirement, plan for the kids' college tuition, and take on mortgages.
I think it is really good for society to have smart people work on investment management. Especially if they are automating, collaborating, and discussing their work openly - the opposite of today's Wall Street. I like that QuantBlock did something original, and I love that they are striving for really broad access.
We think the key to advancing algorithmic investment is to create more access so smart hackers can tinker with investment strategies. Those folks should be able to explore and test ideas/algos without spending a few years building a backtester, or a few years' of salary on data. That's why our backtester is free to use at quantopian.com, and why the source code will be released at PyData NYC (http://blog.quantopian.com/pydatanyc-here-we-come/).
I wrote more about where we want Quantopian to go, and where I think finance needs to go on our blog: http://blog.quantopian.com/quantopian-manifesto/
If you find Quantblocks interesting, you should also look at Quantopian. (www.quantopian.com) We're geared a bit more towards programmers. Rather than use blocks, our members develop their algorithms in Python. We have an in-browser IDE with a lot of smart auto-completion. A few of our nifty features: * free access to 10 years of by-minute historical data for all US stocks * the writer of the algorithm owns the algor…
Great work Dan, it is totally what I would be looking for when backtesting and strategy development. Do you mind sharing what js framework you used on the client side?