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Bin Ren – text2quant (S7E2)
Manage episode 388840407 series 3500080
Το περιεχόμενο παρέχεται από το Corey Hoffstein. Όλο το περιεχόμενο podcast, συμπεριλαμβανομένων των επεισοδίων, των γραφικών και των περιγραφών podcast, μεταφορτώνεται και παρέχεται απευθείας από τον Corey Hoffstein ή τον συνεργάτη της πλατφόρμας podcast. Εάν πιστεύετε ότι κάποιος χρησιμοποιεί το έργο σας που προστατεύεται από πνευματικά δικαιώματα χωρίς την άδειά σας, μπορείτε να ακολουθήσετε τη διαδικασία που περιγράφεται εδώ https://el.player.fm/legal.
In this episode I speak with Bin Ren, founder of SigTech, a financial technology platform providing quantitative researchers with access to a state-of-the-art analysis engine.
This conversation is really broken into two parts. In the first half, we discuss Bin’s views on designing and developing a state-of-the-art backtesting engine. This includes concepts around monolithic versus modular design, how tightly coupled the engine and data should be, and the blurred line between where a strategy definition ends and the backtest engine begins.
In the second half of the conversation we discuss the significant pivot SigTech has undergone this year to incorporate large language models into its process. Or, perhaps more accurately, allow large language models to be a client to its data and services. Here Bin shares his thoughts on both the technical ramifications of integrating with LLMs as well as his philosophical views as to how the role of a quant researcher will change over time as AI becomes more prevalent.
I hope you enjoy my conversation with Bin Ren.
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