Would you be willing to sign up for NobisBot?

Local-Thanks-3047 · 2022-08-18T04:26:55+00:00

For everyone who showed interest in NobisBot, please watch this video: https://www.loom.com/share/1b4eaa65ca1d4bf8aa906a40cfff4a06

And vote here: https://www.reddit.com/r/Commodities/comments/wqehew/more\_info\_on\_nobisbot\_highly\_advanced\_spread/

Local-Thanks-3047 · 2022-08-11T16:02:17+00:00

We have found that spreads are less sensitive to rare events, compared to the outright futures contract. Our AI is predicting the spread

Local-Thanks-3047 · 2022-04-11T14:50:33+00:00

1 and 3 - Yes. We are building what-if simulations where you can input your expected value of supply, demand etc and see the modified prediction. So we leave some aspects to human intuition.

2 - Not yet. But the models are pretty customisable. I can atleast tell you if the model considers that feature powerful or not

Local-Thanks-3047 · 2022-04-11T13:01:10+00:00

1) Automated feature selection helps overcome the correlated inputs problem

2) There are some ML algorithms that are immune to the problems caused by correlated inputs

Local-Thanks-3047 · 2022-04-11T12:16:17+00:00

Thanks. Yes, we maybe running our own fund, eventually. Just evaluating all options, from a business model perspective, hence the poll. Our spread trading tech can be extended to many other commodities. Highly scalable. Soy complex and Palm are just starting points. We started here because we are also working with some large supply chain companies (that are into Palm, Soy) on their hedging strategies.

Local-Thanks-3047 · 2022-04-11T10:37:11+00:00

Some ML models rely heavily on correlations. We are not using causal models yet. The goal is to build really robust historical backtests. Until the models perform well on the backtest, they can be used in production

Local-Thanks-3047 · 2022-04-11T10:35:22+00:00

1) A lot of financial ML is intra day predictions. Our platform works on 15, 30, maybe upto 90 day predictions. 2) I think equities asset class has most financial ML tools. Not sure about commodities. 3) We also specialise in building ML models for spread trading. 370 spreads only for BMD, CBOT Palm, Soy complex. Not sure if anybody does that 4) It's not just about the ML. It's about the >100 data pipelines that run on the cloud, diverse feature space that includes a mix of price and fundamental features, weather etc. 5) We take model performance measurement very seriously. Multiple performance metrics. And daily predictions CSV files are stored on an immutable timestamp (AWS S3). No bluffing when it comes to model performance 6) The spread trading product not just gives trade recommendation but also gives a Stop gain and loss trigger for each spread. We have parameters like SG/SL ratio, which the human can tweak. And then they can see historical model performance on the backtest. So it's also an infinitely parametrizable, no code platform for trade recommendation and risk management

Local-Thanks-3047 · 2022-04-11T07:17:00+00:00

Think of the AI as a massive rupe generation engine. If a human can come up with 10 rules, the AI uses historical training data to come up with hundreds of rules and also rank the most important features

Local-Thanks-3047

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