"Pair-trading VXX and XIV based on the StockTwits sentiments of the SPY at market open. The backtest did really well from 2011 to 2014 with 1700-1800% return in 3 years; and flat between 2014 to present-time... would love to see what people come up to reduce the drawdown's and improve the performance from 2014-2016".
The reason I share my algorithms is trading is one of the hardest ways to make easy money. Making money due to slippage, regime change and overfitting bias is difficult, a poor investment (most hedge funds don't beat index funds) but sharing and learning about statistics, machine-learning and big data is a better investment in self.
Also philosophically, most strategies have limited shelf-life, so it is better to learn how to fish than to hold onto the fish you've got.
Hi, a shameless plug: I went to the Quantopian (the company that is behind Zipline and essentially uses Zipline as the core backend to their cloud platform) algo-trading hackathon two weekends ago and came up with this algo:
Pair-trading VXX and XIV based on the StockTwits sentiments of the SPY at market open. The backtest did really well from 2011 to 2014 with 1700-1800% return in 3 years; and flat between 2014 to present-time,
I'd really love it if people can improve upon the algo and see what people when they clone the algo and come up with ways to mitigate the drawdown's and improve the performance!
http://changefol.io is a site that I use to set up micro-donations that's based off my daily spending, e.g., donate $0.05 for every $1 I spend at the gas pump to Sierra Club; $0.10 for every $1 I spend at the grocery store to WWF (World Wild Life Fund).
Uhh, I really hate INTJ personalities, most are so uptight centered on being judgmental. The "worker bee" personality that I see at IT/software places.
INFP ftw, feeling up and perceiving people over thinking and judging people!
As an INTP, I hear ya, INFP! But those $@!%#& hyperliteral nit-picky TLDR-craving conclusion-jumping downvote-happy INTJs have a clear plurality here.
We're going to need a ?N?P coalition — INFP, INTP, ENFP, ENTP — to retain a little space for some poetic truth and beauty on HN.
There are barely enough ?S?? here to be worth courting. They're probably out dancing and drinking themselves to death during prime HN submission/comment hours, anyway. But just in case any S are reading this, all I have to say to you is: herd immunity and antibiotic resistance are real things! Use some protection! (Ah, damn, that was a little J of me. Sometimes I put on a J or E mask, but it's just for laughs, honest.)
All joking aside, definitionally feelers are going to place higher weight on their personal feelings, which makes discussing technical subjects difficult, because they're less willing to evaluate different things on their merits alone.
Hahaha I hate them too (INTP here), unfortunately lots of people I interact with are INTJ, which is why I like to be alone, I think, well maybe that's not the only reason.
You are right that for a individual investor focused on the long term, a algo-order probably wouldn't make a difference in comparison to a market order with your E-Trade/Schwab account (most likely, your order-flow won't go directly to the market anyways; it is either crossed internally, or re-routed to a broker/dealer that's paying retail brokers for the order flow such as Timberhill).
However, I respectfully disagree that humans are better at making trading decisions than computers. The world of algo trading can be divided into two sides, a) high frequency traders, who through fast cancel-and-replace limit orders and colo with the market centers, try to act as virtual market-makers (or scalpers, depending on your perspective), b) buy-side institutional fund managers who want to complete their orders, without HFT predators and negative market pressure. Large block orders are spliced into small lots (i.e., VWAP) and sent to the market using intentional limit price over time to hide the movement of a huge buy or sell order on the market.
Human beings might be better than machines at picking single stocks for long term investing (although most people are probably still better off investing in an ETF). But that's not how sell-side traders make money in the first place. Guys like GS/MS/Timberhill make money by having the unfair advantage of faster execution speed, more capital and specialized trading algo's against the small retail investors.
What is your impression of them as a pernicious/positive force? Are they essentially market making?
Open for debate. Depends on what you mean as a pernicious/positive force. Good for retail investors, institutional investors, stability of the market, or the sell-side? All of these are conflicting sides. It is generally SEC's mission to protect the small individual investors' fair access to the market, while trying to walk the fine line of not disrupting the big institutional investors/sell-side brokers' way of doing business (and their political lobbying groups).
Pro HFT argument: HFT are virtual market makers that through the use of technology and arbitraging through multiple ECNs, are decreasing the bid/ask spread of the traditional market makers and providing more liquidity to the market. They serve as stabilizing force during irrational exuberances.
Con HFT argument: HFT are bad predators who through technology, jump ahead of institutional investors' block orders and in term pass on higher priced liquidity to retail investors that no one needs. They don't serve as stabilizing force, as they stop trading as soon as they stop making money and in fact may fan the fire by employing high frequency short selling in a flash crash.
"Yes it takes practice to become a good singer, but any number of hours of practicing poor technique won't do much good."
Yes, this is true and oft-repeated mantra on YC News. But it begs the question, how does one practice the "proper" technique (I mean after all, doesn't everyone want to follow the correct form of shooting hoops/strumming a guitar chord, but most people don't have a dedicated shooting coach/guitar teacher to watch their every move or they do know the right technique by heart in theory but can't carry it out in practice for various reasons).
The best protip I've received in learning an instrument (and actually doing anything) is when you are stuck at a particular exercise, move onto the next hardest exercise anyways. When you stumble upon the simplest guitar lick on the first page of a guitar book,you might say "are you crazy? I can't even play the first exercise." But if you play the next hardest lick and stumble upon it for a couple of days, then try to play a third lick even harder than the second lick for a couple of days, and then go back to the very first lick. You might find that you can now play it pretty well, or suck much less than before.
Yes, practicing is all about hard work and all that, but it is also about momentum and keeping things fresh and new. If it's not fun, you are doing something wrong.
One of the most important parts of learning vocal technique is learning what feels right and what doesn't. Good teachers will often work on this with students by asking how the student thought something went ("Was that better or worse than last time? What was better about it?") before offering their own feedback. This isn't easy, but it's critical.
When I'm practicing, sometimes I'm just doing something wrong. If I can't fix it or I can't even figure out what it is, but I know it doesn't feel right, sometimes I just stop that practice session. That's when I know I'll be practicing improper technique. I'll try again next time and remember to ask my teacher about it in my next lesson.
There's a great, short book on how to practice while making "good" mistakes. It's called "The Perfect Wrong Note." I've been found it helpful while teaching myself to pick the banjo.
Yea, write a simple Python/Perl script that interfaces with TOR and force-reset your exit nodes each time you send out a new request and randomize the time interval. There are plenty of TOR exit nodes in the world to swing the vote your way.
It's not too difficult to detect and ban votes from exit nodes. It could even be done after the fact (and still be mostly effective) if it appeared that an attack took place.
I think your analysis is correct despite of all the self-congratulations that goes on here on Hacker News.
A couple caveats though; I think your definition of technology is too narrow, Web 2.0 is only one segment. The smartest people have moved on from IT which has already matured, and are working on green tech and genetic therapy where supposedly the next break through will come.
Also, even in software since money seems to be the biggest concern to you, consumer-centric software isn't where the money is made - it's just what appeals to be the most sexy to the young & naive. High frequency trading, e-discovery, medical informatics, Sarbones-Oxley compliance modules - there are tons of enterprise software companies in those fields make revenue more than most of the Web 2.0 startup's you listed.
Finally, I don't think what motivates programmers aren't necessarily the same that motivates a business-person. The best way I can describe this is by the musician and A&R example; there are some musician's who want to make it big and appeal to as many people as they can (i.e., Linkin Park), there are those complementary record labels who can help popular musicians by handling the business side and tailor their records to the focus groups. But there are also those musician's who care more about pushing than envelope than selling records, and if they are successful, like the early black blues & jazz musician's in the 40's and 30's, their influence will get heard in the 60's and 70's (ripped off by white musicians). Most people in IT operates on this sliding scale between craftsmen and A&R as well.
In the context of this article, I'd call Yodlee a library, not a platform. He wants to add data to Mint like application developers add data to Facebook. Mint doesn't do anything like that with Yodlee.
I'll share my algorithm here:
https://www.quantopian.com/posts/xiv-slash-vxx-pair-trade-1
"Pair-trading VXX and XIV based on the StockTwits sentiments of the SPY at market open. The backtest did really well from 2011 to 2014 with 1700-1800% return in 3 years; and flat between 2014 to present-time... would love to see what people come up to reduce the drawdown's and improve the performance from 2014-2016".
The reason I share my algorithms is trading is one of the hardest ways to make easy money. Making money due to slippage, regime change and overfitting bias is difficult, a poor investment (most hedge funds don't beat index funds) but sharing and learning about statistics, machine-learning and big data is a better investment in self.
Also philosophically, most strategies have limited shelf-life, so it is better to learn how to fish than to hold onto the fish you've got.