Moshi turns market data into portfolio-specific insights

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 5:46

   So Moshi, we are building the program that I wish I had when I was trading. So what we do is we provide real-time insights for financial traders, starting with commodity and energy markets and macro markets. So what we do is we process more data than is humanly possible to tell you everything that matters to your portfolio right now. What kind of data would you be processing that give us an idea of maybe types and then order of magnitude?

2. 6:16

   Types and order of magnitude. So let me start with order of magnitude. So a fun way I explain it to people is it takes me four seconds to say the sentence to you. And in the same amount of time, Moshi has learned 300 new things. So that's the type of volume of data that we process. In terms of the types of data, this very much comes to me like geeking out about how I would trade. I break the market up into all the different types of data, which a trader looks at to decide what trade to put on and how to manage the risk.

3. 6:53

   So what I do is I take the market and I say, well, there's structured data and unstructured data. There's the time series of the futures market and there's all of the technical analysis around it. So we're looking at all of this like statistical indicated, all of the different technical indicators, all of the moving averages. That's one data set. And obviously that is updating constantly. The next data set we look at is the time series for fundamentals markets.

4. 7:20

   So especially in some commodity markets, there's a lot of demand and supply. And then we look at the unstructured data. so the news is the obvious one but then there's also all this alternative data that exists for example there's x data there's audio data on podcast x twitter yes uv twitter okay so understanding all of these different types of data and that i would say is the like public availability of data and there's this whole other type of data which is the user's private data so if i'm sure you had that when you were trading which is you have the analysts you care about i can't come and tell you hey you should you know read this person because you have who you need and then you're going to have your um subscriptions that you care about you'll have your internal data right like some of the companies we speak to if they are uh trading markets trading energy markets

5. 8:18

   they will have their person for the amount of lng ships going through the strait of hormuz and so there's all this data which is personal to the user so we take those two data points together do all of the like data cleaning data transformation we then look at the statistics and machine learning tag it kind of create our whole ontology on top of it and then we put it into the moshi like n-dimensional graph and then we produce the output which is a piece of software which pushes data to you.

6. 8:51

   So every time you open Moshi, you see something new related to your portfolio and you can pull data. So LLM, I'm going to give you answers in 30 seconds, which would take you typically days.