December 11, 2017· 34 min
Two Researchers Explain How Quants Are Going To Revolutionize Long-Term Investing
Orality
Model
71%
Oral-dominant (speeches, podcasts, storytelling)
Speaker Breakdown
HostTracy Alloway(1,367 words)
M:27%
GuestZachary Lipton(1,308 words)
M:26%
GuestJohn Alberg(2,830 words)
M:28%
Oral Indicators
Agonistic29%
certainly, very, absolutely
Engagement78%
you, our, your
Memory Aids100%
listen, so, like
Repetition100%
like (85x), know (83x), what (61x)
Parallelism100%
And I'm Tracy Alloway...., But, ideally, you know, what t..., And I think the most obvious e...
Sound Patterns68%
44 question(s), alliteration: "markets move", alliteration: "barclays brief"
Formulaic Phrases9%
you know what, i mean, so to speak
Literate Indicators
Hedging11%
could, might, maybe
Passive Voice10%
is forced, be expressed, is anchored
Abstract Nouns15%
investment, business, evolution
Subordination6%
because, hence, though
Sentence Length50%
Avg: 17.5 words/sentence
Word Complexity46%
investment, analyze, anticipate
Academic Markers5%
according to
Impersonal Style22%
503 personal pronouns found
Descriptive Style100%
apply, really, constantly
Description
When we think of computer-driven or "quant" investing, we often think fast moves, algorithms making buy and sell orders at incredibly short timeframes. So in theory, the likes of great long-term investors, like Warren Buffett, should be safe from the robot revolution. But maybe not so fast! On this week's Odd Lots podcast, we speak to John Alberg of Euclidean Technologies and Zachary Lipton of Carnegie Mellon, about their new research on the next generation of quant investing. Alberg and Lipton explain a recent paper in which they used machine learning to forecast the future fundamentals of companies, and the opportunity that offers in terms of beating the market over the long term. See omnystudio.com/listener for privacy information.