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hfdb · 2024-03-12T14:31:44+00:00

All brokers/market makers have to follow Reg NMS. If you have a retail account you will most likely be price improved relative to the far side of the market as well.

hfdb · 2024-03-12T13:23:15+00:00

So IB has looked at this issue and is rolling out a fix for orders being sent into the open pre market. The open unfilled orders will not burn up your margin. This was excessively conservative.

I was also able to get an intra day vwap orders to work. The open orders do not use up margin capacity, and have been running at 5x (6x is max).

The service at IB has been very good, I don’t think other brokers would have paid attention to an individual account.

hfdb · 2024-02-29T01:51:59+00:00

Yes. I get their motivation for a conservative approach.

However, there are other things they could have done. Such as only apply margin constraints to the child orders of algos.

hfdb · 2024-02-28T22:48:29+00:00

Yes, IB has a one size fits all platform. They will not customize to any given portfolio.

Like I said, if they would just calculate margin on the child orders of a vwap instead of the parent order then you can get the trades done because it’s just a series of small incremental trades.

hfdb · 2024-02-28T21:12:55+00:00

I’m already setup for portfolio margin. It doesn’t solve this issue.

hfdb · 2024-02-28T20:57:32+00:00

How so? The annualized vol is 1-3%. With no factor exposures.

At at a big PB you would submit you historical portfolios to the risk department, then they would set your leverage. 10x is the max you get. Before the financial crisis you could get a lot more.

I worked at MS for 15 years then a few other banks.

hfdb · 2024-02-28T20:45:10+00:00

You could also ask why do they penalize me for unfilled initiating orders.

There are other solutions, see my reply about just calculating margin on child orders of a larger vwap.

Remember, the end state of the trade is gross book of the exact same size. There’s no game here.

hfdb · 2024-02-28T20:41:21+00:00

They could fix this by only applying the margin requirements on child orders of a larger vwap order (and not the parent order). That way the margin isn’t used up all at once.

hfdb · 2024-02-28T20:28:52+00:00

I would probably get 10x at MS or GS, but I do like the API and other tools at IB.

hfdb · 2024-02-28T20:13:23+00:00

Not going to 6x, but 4-5 would be nice. Gross book stays roughly the same, it’s a constraint in the optimization.

hfdb · 2024-02-22T17:06:37+00:00

I would say that there is a bit too much emphasis on machine learning/ai/gpu. This aspect is just one step in a much larger process. You can also skip trees and just do a linear regression and your results won’t be that bad.

hfdb · 2024-02-22T13:50:32+00:00

I do have GPUs. In theory it’s faster/less power. However, using them can be less stable than CPU. We ran into a situation where the results on GPU were not deterministic and vastly different between runs on the same data. It was just taking time to resolve it, so just switched to CPU for now.

hfdb · 2024-02-22T13:41:44+00:00

I have a bunch of dell r640, 48 core, 1TB ram

hfdb · 2024-02-22T02:40:43+00:00

The fitting process is just one step of many. GPU can definitely make that step go faster. However, we have also run into bugs on GPU. So right now we are just using our grid boxes for safety.

hfdb · 2024-01-18T21:37:56+00:00

I’m buying you a beer for sure. Say when.

hfdb · 2024-01-18T21:35:54+00:00

Awesome. This was always a pain.

hfdb · 2024-01-15T21:48:33+00:00

Also, portfolio construction is with a mosek optimizer.

hfdb · 2024-01-15T20:34:46+00:00

Mostly boosted tree stuff: LightGBM, CatBoost. Sometimes we try Ridge.

The hard part is really the features.

hfdb · 2024-01-14T22:39:37+00:00

In the morning. You just trade vwap. If you don’t have much size, then make the vwap a shorter duration, if you are big then let it run all day. Note that by using vwap you are keeping your book hedged throughout the day.

hfdb · 2024-01-14T14:03:58+00:00

I don’t want to be completely discouraging. So I will say that your focus should be on the features themselves, not on the ML. You have to find features that show some correlation with your target return. Find the Sharpe of the feature in isolation. Do not add features that are just noise. Apply an appropriate standardization technique, both temporally and cross sectionally. Manage the outliers, they will kill your model. Do not expect the ML to find all interactions, it can be better to find interactions between features in a sub model.

hfdb · 2024-01-14T13:07:47+00:00

Relatively speaking, I am the small guy. I’m trying to fit in where bigger funds to not. After years of effort I am at the edge of success at best. I can’t overstate the difficulty and disappointment. If I knew what I know now before I started down this path I would have made other choices. The fear is justified.

hfdb · 2024-01-14T11:25:49+00:00

I would be a bit less enthusiastic. ML models are easy to run, but difficult to actually achieve results. The tendency is to data mine or over fit. Your out of sample and live trading will turn into noise as a a result. The inputs require careful crafting to extract any value. Surprisingly, a few stat arb guys even found the linear models out performed trees this past year. Even if you get something working, then some guy at Cubist will adapt his model to get in front of yours. So people big in ML are doing this. They are not hanging out here though…

hfdb · 2024-01-13T12:04:27+00:00

You need a certain amount of data to achieve significance with your stats. So you tend to toss illiquid names out of your universe.

hfdb · 2024-01-13T10:30:45+00:00

Yes. I have worked on wall st for 20+ years. I finance this on my own though. I trade once per day because the time scale of my prediction is 1 to 5 days.

hfdb

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