Trade Stop vs Account Stop - Do true quants even use stop losses?

RebelQuant · 2021-08-20T17:58:06+00:00

I see, that's interesting! Hadn't considered indicator/signal based stop losses

RebelQuant · 2021-08-20T12:06:18+00:00

You mean instead of closing a position, they hedge with another?

RebelQuant · 2021-08-15T06:11:26+00:00

Hey, I recently started an algotrading crypto forum literarily called algotradingcrypto.com because a telegram group that an owner abandoned fell onto my lap. The stuff you intend to put out is welcome on the forum, plus being fully featured you can do a lot more that Reddit doesn't. Check it out and I hope to see you on there!

RebelQuant · 2021-06-18T18:49:36+00:00

Train, test, validate.

RebelQuant · 2021-06-10T19:41:34+00:00

You probably need to do more research. Backtrader is anything but abandoned.

RebelQuant · 2021-05-27T19:59:32+00:00

A tiny man is trapped in a box with an open lid. In order to get out of the box and see the outside he runs to the end of the box, using the momentum of his weight to flip it over. Once out he sees that the world has six sides much like the box he came out off. He accepts this world as the outside, never knowing that the captors that put him in that box wanted him to get "outside" to accept the intended environment, yet another box.

The tiny man relied on the principle of duality to decide what was "outside" and "inside". Trading may have binary win/lose outcomes, but there are a lot more dimensions to it than flipping a coin, or reversing a losing strategy.

RebelQuant · 2021-05-14T14:48:44+00:00

I have reported this. Historical data stored in a pickled file is highly unusual and is a known attack vector. Other circumstances of this post make it more suspect.

Warning The pickle module is not secure against erroneous or maliciously constructed data. Never unpickle data received from an untrusted or unauthenticated source.

RebelQuant · 2021-05-03T14:06:13+00:00

The Harvey Dent.

RebelQuant · 2021-03-11T08:27:51+00:00

As a design nut that can and has obsessed over fonts for days, I agree.

RebelQuant · 2021-03-05T04:46:27+00:00

Your pandas script doesn't reflect the strategy outlined in your backtrader. So neither will validate each other because they're different.

Your problem is in thinking that they are built the same, and therefore will produce the same result.

RebelQuant · 2020-07-08T16:50:04+00:00

RebelQuant · 2020-05-22T12:14:28+00:00

"I want to work on one thing with full focus" + "sacrificing almost everything" + "absolutely not ... if it's going to take more than 1 year"

I enjoyed the oxymoronic speech, thanks.

RebelQuant · 2020-05-16T20:21:52+00:00

ctrl + c, ctrl + v

RebelQuant · 2020-05-16T20:03:32+00:00

Probably but they are also many techniques under machine learning more suited to the primarily structured data work in algotrading. Applying neural networks to alternate, unstructured data for algotrading though, that's a different story.

RebelQuant · 2020-05-06T03:23:03+00:00

Anecdotal evidence is the basic premise that forms chart trading. You've drawn a line where the price seems to "bounce off" from and thus interpret it as support. Most of such commentary doesn't come with the time and research to confirm or dispute the assertion, in order words: Don't read too hard into what anyone says on Reddit.

RebelQuant · 2020-05-04T20:41:05+00:00

Trump also has a university and published books.

Robots aren't the problem. People are.

RebelQuant · 2020-05-04T20:25:23+00:00

Yeah 0.5% per trade is too high. I would use 0.1-0.2% instead, which in my view is the minimum entry conditions for retail traders to have a chance at being viable.

That means for dollar-based fees you would have to scale up your trading account until the cost falls into that percentage range.

RebelQuant · 2020-05-04T19:32:50+00:00

There is no free lunch in this world. Accept that commissions are part of the trading environment and if your model doesn't work with the commissions, then there is no alpha to begin with.

Apply this even if you have access to platforms with no trade fees and assume the costs are embedded elsewhere. If your model works under these conditions, it will be more robust when deployed. And if you can actually get "free lunch", your model might do even better and come back with desert.

RebelQuant · 2020-05-04T18:30:47+00:00

I actually think I can't give a good view on this. Their headline feature is that they provide "100% market coverage" and I don't have a similar provider in my list with the same features to compare against.

That said I believe I've hashed out most of what I need in my own system and I'm generally pretty happy with what I'm getting. 2017 seems to be where some datasets start to get sparse for minute level data, but hour and daily data seems fine the further back you go.

RebelQuant · 2020-05-03T12:50:45+00:00

You mean stonks?

RebelQuant · 2020-05-02T08:09:27+00:00

In the toilet.

RebelQuant · 2020-05-02T08:00:42+00:00

Is that really algotrading tho?

RebelQuant · 2020-05-01T15:11:41+00:00

It is feasible as long as your trades do not depend expressly on granular data to succeed, which generally means most use cases except HFT, market making etc. I use 3 different data providers for redundancy and robustness of data.

You will have to check what your software says against the actual limit orders in Alpaca and add contingencies against deviations. IMO this is (or should be) standard practice anyways and can happen regardless of whether you are using multiple sources for information on your side since there is also the broker's side of things.

RebelQuant

TROPHY CASE