Introduction

My name is Filippo Velardocchia and I'm the CEO of Frankernom Flechter. That's the complete name of the company and why am I here? It's because, like, basically Luca asked, so that's the reason.

Company Overview

Now, but without any further ado, what do we do at Frankernom Flechter? It's basically, like, we are basically a research lab in the financial context, especially stocks.

like we are a quantitative firm like and yeah we are the first beneficiaries of what we do but since none of us basically come from a rich family like we started the company as a startup and not as a fund for a moment that will be

a second stage and anyway like why the name the name come comes from my grandfather motto my father was in the Navy my grandfather sorry was in the Navy and it should stand for resilience and integrity.

Methodology and Models

We also completed it with our own model that is like always evolving and that's basically what our models do because we have a very important part corresponding to machine learning models applied to markets and then another part that's more deterministic to define the execution.

execution.

Quantitative + Fundamental Approach

Anyway, like our approach is fundamental. It's like maybe a complex term, but not really. It means simply like using quantitative methods through like the analysis also of the fundamentals of the company, of the companies.

Signals, Allocation, and Clients

Our models give back basically signals to operate on the market.

Then you can observe this signal through certain lenses. And just for us, there There is also an allocation part that allows us to operate on the markets.

Obviously, our clients, I should have specified it later, as you can see in the at -a -glance box, are mainly institutional investors.

And because what our models give to you is basically a great information advantage, and so we cannot give it to everybody.

Products and Business Model

Product Lineup (Sara, Ugo, Buck)

and anyway the products are this free as you may understand the naming is not the strong side of the company so like you have Sara, Ugo and Buck.

Sara is what's operating now on the markets and it's what provides you day by day or better

like every day informational advantage like when you have Ugo that's basically basically like a macroeconomic analyzer and portfolio analyzer and then a back that's basically a reporter.

Revenue Streams and Licensing

What happens is that each of these products can be also like a separate license like because at the moment we have three revenue streams that's basically that are you know the internal use of the models, SAS, and yeah and then like there is a third one but still not

but obviously since we have been funded in January this year so we are quite newborn, nothing like that.

There will be also capital gain fee on the managed capitals.

Performance and Results

Anyway, like the results that we attained like I built a database that's basically spanning 17 years of US markets and like these are the main results for 2025 like unfortunately I was highly suggested to not show the returns so you have something that's maybe not as readable so you have sharp

How to Read the Metrics (Sharpe and Max Drawdown)

1ratio marks drawdown if you are not into finance like sharp ratio basically means like how much you are rewarded for the risk you are taking and the max drawdown basically means like how much can you can lose and in respect like to like we

Portfolio Construction and Market Regimes

built basically a portfolio with 35 stocks spanning in 11 sectors in the US markets and these were the results the most important part is that like our our most efficient context is the high volatility one.

So I cannot show you also like how we performed during the Iran crisis, but the numbers are not that different.

Baseline Comparison and Model Impact

And here you have basically like, well, the baseline is not really representative. It should be more, it should be closer to 0 .96, more closer to the S &P 500.

under the baseline accounts for a simple strategy that we applied following the use of the models. But you can see that in any case,

if you consider the tickers without the models and you operate on the market without, on the same tickers, without, so the same stocks, without the model's informations,

you are basically like obtaining gaining very lower returns compared to the risk you are taking.

Team and Next Steps

And so we are five founders, I am the CEO, these are the rest of the team. We have also welcomed to the team in an official way a guy that worked for 10 years in an hedge fund in London, and an unofficial investor, but just because we started our fundraising raising a week ago is a guy that works for Azimut.

Conclusion and Q&A

And thank you for the attention. I tried to condense a bit.

Platform Access and What to Ask

I cannot show you the platform because it's quite secretive, I have to be completely honest.

But feel free to ask anything about the AI side and also all the deterministic part because that's what we do. And thanks.