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Python For Finance: Algorithmic Trading

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Re: Python For Finance: Algorithmic Trading

#61

Post by vageli »

etep wrote: post #48
lowpro wrote: post #45

The main issue I found in algo and financial aspects of programming is that the market is a zero sum game, and my intro knowledge of finance and algorithms, even when I know python, are no match for MIT PHD Quants who does it full time. There's no real way to compete with that, and therefore I would lose money, even if the data showed it might be successful in the future, firms and full time workers on algo trading w…

If the market is a zero sum game, then for every winning trade, there must be a losing trade. Obviously some teams must be winning consistently, which implies that some are losing consistently. This says that the consistent losers go out of business. So who are the winners going to trade with? By contradiction, it is not zero sum.

> Obviously some teams must be winning consistently, which implies that some are losing consistently.

That does not necessarily follow; markets are not static and players are free to enter and leave.

Re: Python For Finance: Algorithmic Trading

#62

Post by 21 »

nickthemagicman wrote: post #25

How is algorithmic trading not equivalent to astrology? Nothing can be predicted because there's way too many confounding factors.

So how do you explain this:

When filing for its IPO in March 2014, it was disclosed that during five years Virtu Financial made profit 1,277 out of 1,278 days, losing money just one day.

Re: Python For Finance: Algorithmic Trading

#63

Post by SirLJ »

dsacco wrote: post #53
SirLJ wrote: post #10

Earlier quoted context omitted.

My experience is unfortunately different, I found the data for some delisted stocks like HTZ missing which will massively screw the past results due to the survivorship bias...

Can you please prove this or stop saying it? Quantopian's data is from Nanex and is free of survivorship bias, as I mentioned to you in another comment.

Yes I can prove it, go and request historical data for symbols like AA, HTZ and you'll see yourself

Re: Python For Finance: Algorithmic Trading

#64

Post by etep »

vageli wrote: post #61
etep wrote: post #48

Earlier quoted context omitted.

If the market is a zero sum game, then for every winning trade, there must be a losing trade. Obviously some teams must be winning consistently, which implies that some are losing consistently. This says that the consistent losers go out of business. So who are the winners going to trade with? By contradiction, it is not zero sum.

> Obviously some teams must be winning consistently, which implies that some are losing consistently. That does not necessarily follow; markets are not static and players are free to enter and leave.

People like to say the market is a zero sum game, but I have always been suspicious of this truism.

Its fair to say that participants can leave the market, but in practice that isn't what we see. In practice there are firms doing this trading, and they are staying in business, and obviously making money.

Are they fleecing the little guy then? This explanation falls flat for me, i.e. for the amount of money they seem to be making, it would take a lot of small time participants losing everything every day. Most people I know aren't even active traders.

So why is it an accepted truism that the market is zero sum?

Re: Python For Finance: Algorithmic Trading

#65

Post by dsacco »

SirLJ wrote: post #55
dsacco wrote: post #44

Earlier quoted context omitted.

This is false. Quantopian sources their historical and real time data from Nanex, and the data is explicitly free of survivorship bias (i.e. they maintain data for delisted equities). I don't know what you verified, but it directly contradicts my own experience and the FAQ: https://www.quantopian.com/faq#data-sources To your second point, as another commenter said Quantopian doesn't see your algorithm unless you give…

Please go back and check and you'll se the data is missing for the symbols stated above, and I am sur for many more based on my limited test... everyone can see I am right by trying to request the data, nothing false about that...

> everyone can see I am right by trying to request the data, nothing false about that...

Oh, they can? Well that's funny, because I just went onto Quantopian and checked for myself.

http://imgur.com/a/VwMUJ

http://imgur.com/a/VV68C

Gee, would you look at that...they are there.

This took me all of five minutes. Do you have anything else I can easily disprove while I'm at it?

Re: Python For Finance: Algorithmic Trading

#66

Post by SirLJ »

dsacco wrote: post #40
Blackstone4 wrote: post #3

Earlier quoted context omitted.

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

This commenter comes into every single thread about trading and talks about buying data from ebay, then consistently demonstrates that he doesn't know the first thing about due diligence on financial data. Each time I try to ask him about his data quality or methodology at even a high level, he responds by accusing me of wanting to steal his work or stop the democratization of data. I'm going to reiterate this right…

Unless you are day trading you don't need such a granular data format, so please stop saying you need to spend thousands and thousands of dollars to be able to back test a trading strategy

Re: Python For Finance: Algorithmic Trading

#67

Post by sidlls »

etep wrote: post #64
vageli wrote: post #61

Earlier quoted context omitted.

> Obviously some teams must be winning consistently, which implies that some are losing consistently. That does not necessarily follow; markets are not static and players are free to enter and leave.

People like to say the market is a zero sum game, but I have always been suspicious of this truism. Its fair to say that participants can leave the market, but in practice that isn't what we see. In practice there are firms doing this trading, and they are staying in business, and obviously making money. Are they fleecing the little guy then? This explanation falls flat for me, i.e. for the amount of money they seem…

>Are they fleecing the little guy then?

Yes, more or less (although that's just one way they make money, and probably not the most lucrative) And fortunately for them there are plenty of "little guys" ready to enter the market on a regular basis.

Re: Python For Finance: Algorithmic Trading

#68

Post by dsacco »

SirLJ wrote: post #60
dsacco wrote: post #56

Earlier quoted context omitted.

First of all, you're criticizing QuantConnect's data when you claim to get your data from ebay. Second, yes you absolutely can verify QuantConnect's data. You can use it as much as you want within the context of their platform, you just can't download the data en masse from their platform and use it on your own. But if you have tick data (equities) or minute data (options) yourself, you can certainly verify it (which…

Unfortunately you cannot display QC tic data to be able to very it against you broker for example. As I said before if you have a good and cheap source, please share it with everyone...

> good and cheap source

Pick one. You don't get both. I'm happy to share where you can get real data from.

https://www.tickdata.com

https://datashop.cboe.com

http://www.nanex.net/nxcore.html

https://quantquote.com

No affiliation with any of these.

Re: Python For Finance: Algorithmic Trading

#69

Post by SirLJ »

dsacco wrote: post #65
SirLJ wrote: post #55

Earlier quoted context omitted.

Please go back and check and you'll se the data is missing for the symbols stated above, and I am sur for many more based on my limited test... everyone can see I am right by trying to request the data, nothing false about that...

> everyone can see I am right by trying to request the data, nothing false about that... Oh, they can? Well that's funny, because I just went onto Quantopian and checked for myself. http://imgur.com/a/VwMUJ http://imgur.com/a/VV68C Gee, would you look at that...they are there. This took me all of five minutes. Do you have anything else I can easily disprove while I'm at it?

The problem is the data is missing for specific dates... I just can imagine what else is missing or it is wrong...

Re: Python For Finance: Algorithmic Trading

#70

Post by etep »

sidlls wrote: post #67
etep wrote: post #64

Earlier quoted context omitted.

People like to say the market is a zero sum game, but I have always been suspicious of this truism. Its fair to say that participants can leave the market, but in practice that isn't what we see. In practice there are firms doing this trading, and they are staying in business, and obviously making money. Are they fleecing the little guy then? This explanation falls flat for me, i.e. for the amount of money they seem…

>Are they fleecing the little guy then? Yes, more or less (although that's just one way they make money, and probably not the most lucrative) And fortunately for them there are plenty of "little guys" ready to enter the market on a regular basis.

My point exactly, not the most lucrative. So what remains is the implicit assertion they are fleecing the big time guys. And somehow the big time guys remain in business... so what's going on?
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