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Python For Finance: Algorithmic Trading

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Re: Python For Finance: Algorithmic Trading

#101

Post by zootam »

SirLJ wrote: post #47
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…

Sorry, but this is like saying those CalTech PHD in Computers Science are the best, so no point for me to go into that field... This is like everything in life, not easy, but if you work on it it'll pay out in the end

>but if you work on it it'll pay out in the end

unless its one of the many things in your life that don't

Re: Python For Finance: Algorithmic Trading

#102

Post by osrec »

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…

Why do you say it's a zero sum game? If I've learnt anything from my time in finance, it's that the market is definitely not zero sum. The prices you see represent sentiment, not a hard valuation, and someone isn't necessarily losing when you gain. If you really think about it, even entire economies aren't really zero sum as our method of valuation is intrinsically subjective!

Re: Python For Finance: Algorithmic Trading

#104

Post by wtvanhest »

lz400 wrote: post #92
wtvanhest wrote: post #41

Earlier quoted context omitted.

That is your opinion, but if you look at the resumes of scientific active equity fund managers and quants, they all have it. Just understanding the quantitative side leads to vast underperformance over the course of market cycles...

Quants don't usually have CFAs. A phD in physics is more common to see. CFAs help you working in a real financial environment where you need to be aware of a lot of stuff. If you want to day trade at home, it's close to useless. Please nobody gets a CFA if what you want to do is learning day trading.

If you are just gambling with math at home, dont bother. If you want to understand finance like the op, better start learning. They have phds and cfas...

Re: Python For Finance: Algorithmic Trading

#105

Post by dsacco »

jaredbroad wrote: post #94
Veratyr wrote: post #74

Earlier quoted context omitted.

Worth noting though that Options data is super hard to get running on QuantConnect due to the memory limits and lack of index options.

Agree, we're working on making it easier now. We patched a bug today which should make it more efficient.

Do you have a public email for getting in touch with you? I'm interested in chatting.

Re: Python For Finance: Algorithmic Trading

#106

Post by bobbington »

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…

First, the market is 0 sum only in the very short term. But over the long term it always goes up, even when accounting for inflation.

Secondly, you can still use this because there are many trades that the big guys just can't profit enough from. For example if your algorithm can make only $200 a day, the big guys won't bother with it. So look for small stuff that doesn't scale and you may be able to do it.

Re: Python For Finance: Algorithmic Trading

#107

Post by 77pt77 »

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?

I like your script naming scheme...

Re: Python For Finance: Algorithmic Trading

#108

Post by brobinson »

The article mentions a few of the pitfalls of backtesting, but it does not mention one of the best tools at your disposal in backtesting: Walk Forward Optimization/Analysis

https://en.wikipedia.org/wiki/Walk_forward_optimization

See also: "The Evaluation and Optimization of Trading Strategies" by Robert Pardo

Re: Python For Finance: Algorithmic Trading

#109

Post by _e »

milcron wrote: post #81
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…

An economist and a normal person are walking down the street together. The normal person says “Hey, look, there’s a $20 bill on the sidewalk!” The economist replies by saying “That’s impossible- if it were really a $20 bill, it would have been picked up by now.”

This is why models are just for starting a conversation and not for predicting the future. Life has too many variables.

Re: Python For Finance: Algorithmic Trading

#110

Post by SomeStupidPoint »

tryitnow wrote: post #75
yonkshi wrote: post #58

Earlier quoted context omitted.

Even if it's a zero sum game (which it's not), most participants are not quant/algo based. As long as you can beat 50% percentile, you can make a profit. Sure you may not be as profitable as top quant companies, but do you really mind that much?

Why on earth do you think the top quant companies will leave alpha on the table for you to snatch up? That sounds too much like wishful thinking to me. Furthermore, if someone is really smart enough to beat the market consistently why on earth would they trade just on their own personal account? Work for a hedge fund and use other people's money to leverage your bets.

Some strategies only work with small investment sizes or require a lot of effort, so don't scale well.

Big firms leave tons of (for them) small opportunities on the table, because it's not worth their time.

Similarly, there are people who can regularly beat the market that don't have much to offer large funds because their methods don't scale.

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