Recent content by DaveDaGr8

After the success of last week, this week has been a bit of a bust. I am close to implementing an LSTM, it was a bit more work than i originally intended and still not done so i have no results to compare yet. I am training it ok and It's definately a beast. I had to shrink the size of the...

Yep, still using Norgate. I'm not really following their tutorial to a tee because I've already built a lot of the modules already that i'll just reuse, ie fetching data from Norgate, Index/Watchlist checking, pre processing the variables, scaling etc. The biggest change so far is there's an...

My mission today is to convert my Simple NN to an LTSM. I have done this before, but i know that training is slower and memory requirements are higher !!! https://www.datacamp.com/tutorial/lstm-python-stock-market While i won't be following this tutorial, It could be a good reference to help...

LSTM (Long Short-Term Memory) Layers: Type: Recurrent Neural Network (RNN) layer. Purpose: To process sequences and remember patterns over long sequences. They are specifically designed to avoid long-term dependency issues. Structure: Consists of memory cells that are connected through gates...

You don't really need to know to much of python, this is actually my first Python project. I've spent a lot of years programming in c/c++ though. Understanding programming concepts, Some Machine Learning concepts and some basics in Python is really what you need and chatGPT can fill in the...

Definitely a separate model. One thought is to have an agent that would take the signals from various NN's. Market sentiment, price rise, reversal, breakout etc and make the best decision and allocation based on these factors. That's a long way off yet though. Keeping each NN doing an...

It's a tricky one. I don't want to diminish the ability to pick high returning stocks in sideways or upward markets, just the ability to decide when to apply it (Not in downward markets). I am going to add index data into the models input, that extra dimension might allow it to learn good or...

This bit i have covered. I have an AWS server in singapore that trades with IB in Hong Kong and some custom software to do real time trading. Current order execution is between 5mS to 20mS from me placing a trade to IB sending confirmation or order being placed. The decision to use AWS was...

Thanks for the link, there's a lot of information in there, lots to digest and some to implement. :xyxthumbs When i implemented the 3 outputs for the 10,50,90 percentiles, i was hoping it would create it's own risk reward type scenario, but it's not quite doing that and it just chooses the path...

I retrained the annual networks and increased their dimensions considerably. I increased the network size from 70MB to 1GB. Most years benefitted with a massive increase in return. The downside was 2008 MDD was a staggering 74%. No WAY is this acceptable. The index dropped 49%, but we still...

Here are some findings from interrogating the network this morning. I implemented the rolling window last night, and trained annual networks at 5 years of data, 2005 through to 2023. Running the model through the test years from 2005 the results exceeded the NDX index in almost every year...

All the large firms would have teams of people now. Even something as simple as institutions trying to buy $100 Million dollars of BHP. This can't be done in one hit and used to be outsourced, but now AI could do it for them in house. These are things we take for granted. As hobbyists we have...

After retraining with data up until 1-1-2023 I managed to get some improvement out of the 2023 results. Still did not manage to beat the market though, but CAR went up from 15% to 24%.

So this morning i managed to Import into AB. While python has a lot of libraries like Zipline, i still like AB reports. AI Vs NDX 2021 - 2022 - 2023

Not to mention future leaks. It was encouraging to know that the model could learn to use future leaking data, even just one column of it and produce unrealistically good results. Just like AB. Hiding part of the process: This is an interesting topic. My Neural Network has 100's of millions of...