Artificial intelligence is having a hugely disruptive impact on every industry and their respective workforces, and just hearing the words “AI anything” causes quite a stir. But is AI responsible for making calculated predictions about the stock market (^DJI, ^IXIC, ^GSPC), and should investors trust those predictions?
Kaiju Worldwide Global Chairman and CEO Ryan Pannell joins Market Domination to discuss the place of predictive AI models in public and private investment strategies.
“It doesn’t really fit into the global macro. [predictions]” explains Pannell. But the long term is not. And I don’t see that changing.”
For more expert insights and the latest market trends, click here to watch the full episode of Market Domination.
This post was written by luke carberry morgan.
video transcript
It’s been another AI-centric earnings season this year as investors chase the next best thing in AI trading.
But what if, instead of just investing in AI, traders could leverage AI to drive other public and private investment strategies? We’re here to discuss Ryan Pannell Ryan, CEO and Global Chairman of Kaju Worldwide.
I’m glad to be here.
Thank you, thank you for coming back, and I’m glad to be here in person this time.
So, Ryan, let me ask you a question. Maybe if we just start focusing, the AI’s predictions will be accurate, right?
As opposed to the generational AI that we spend a lot of time talking about on this show, right?
And all kinds of companies that spend a lot of time, money, and effort there may start there.
Ryan explained to viewers the difference between the two and then explained how Kaiju actually integrates the technology.
So, as you say, what most people are familiar with is this generative AI. Most of the time you get an undefined, non-standard dataset, and on the internet you don’t have ownership of the data to train your model. It is not always clearly defined.
Free use and copyright infringement are in conflict, trying to answer questions that someone else can answer, or asking questions and trying to make something new out of it.
Draw a picture and write an essay.
If you say, “It’s you, so make me a movie,” then you have the hallucination problem that comes with that.
So, no questions asked.
This is a very powerful technology with a bright future ahead.
Predictive AI uses easily purchased or collected source data for pricing such as time and quantity.
And I’m trying to answer a specific question.
So in our case, we are trying to identify the price time and quantity pattern immediately preceding the price action we want to take advantage of. I’ve checked this many times and have some certainty and can use it for: The end of it.
Basically, that’s all there is to it, and it’s not fundamental analysis at all, it’s just based on it.
Therefore, this is an effective predictive AI based on some level of technical analysis. If you want to share your secret sauce, Wii knew it was coming.
If you think about it, every positive investment decision leads to trading, yes, it doesn’t matter what the asset class is, whether it’s real estate derivatives, stock options, fundamentals, doing analysis. Technically there is an investment committee and it will end eventually.
If it’s a “go-ahead”, it will affect the transaction, and you can, but not always, see a pattern in the transaction. However, for a given transaction, you can reverse engineer the investment decisions that led to the example transaction with some degree of certainty. If you look at rotation and distribution, they will have very different intentions.
So they are very different patterns and the panic looks different too. We buy quietly because you are there, we are confident that profits will be positive, we don’t want to disturb the price, and we are thinking about what will happen 5 years from now, so we don’t buy indiscriminately. Stock prices will be more positive, there will be different patterns, different outcomes.
If you can identify them, you can prey on them.
I’m interested.
So, that’s interesting, right?
Did you, you, find some tasks where you think so?
Well, my world’s predictive AI doesn’t make sense.
I know what this technology is, but is there anything that makes me think it’s not suitable for its purpose and I wouldn’t want to apply it?
Yeah.
of course.
absolutely.
Obviously anything that has a long term duration.
It doesn’t matter if it’s a human or a machine, there’s no human, there’s no system, there’s no predictive AI that can tell you with certainty what stock prices will be six months from now, and anyone who says otherwise. is just trying to sell you something.
In other words, it doesn’t really fit into the global macro picture. As you know, President Putin invaded Ukraine. How will the global economy react to this over the next 12 months?
There is no system that can immediately exploit stock derivative price fluctuations in the short term.
Yes, it’s very good in that regard, but I don’t see it changing in the long run.
I made a comment at the beginning drawing a contrast with generative AI, and it sounds like you’re a little skeptical about that model, the way it collects information, the ownership of data or lack thereof.
correct?
So I’d like to know your views on gender AI, whether you think there should be rules around such things.
Well, that’s a big question to ask and answer in that any question can potentially be answered.
No, it needs to be this wide.
These large language models are huge and obviously incredibly expensive to run. Because you can’t decide what someone needs, requests, or wants to review. Sometimes it’s information gathering, sometimes it’s creation.
As a result, predictive AI needed to be given considerable freedom to perform one specific task with a high degree of certainty, whether it was flying a plane, driving a boat, or trading stocks.
So the challenges surrounding these data are important and, thankfully, consistent with that kind of technology, but for large systems, how do you limit the data to achieve the same performance? I don’t know, Ryan.
Thank you for visiting us.
you’re welcome.
thank you.
