Arun Verma

Quant Research Solutions @Bloomberg. Interested in #AltData, #ML, #QuantitativeTrading. All views are mine.

[Tech At Bloomberg @TechAtBloomberg]

At @Bloomberg, we don't just build with #opensource — we contribute to it. Huge congrats to #QuantFinance Researcher Florian Bourgey from our Office of the CTO on being named a #SciPy maintainer. 50+ high-quality PRs. Real impact. Well deserved. 🙌
https://t.co/Qmmz2V2fuX

[Tech At Bloomberg @TechAtBloomberg]

Tune in next Wednesday, May 27 (5:30-7 PM EDT) for a livestream of this month's @Bloomberg #Quant (BBQ) Seminar, featuring a keynote by @CUSEAS' Ali Hirsa on the challenges of keeping asset management models stable over time + lightning talks
https://t.co/8gMUCeEmao
#QuantFinance

[Michael McDonough @M_McDonough]

The crowds are speaking—are you listening? 🗣️

Event-driven markets move fast. If you want to know exactly what’s capturing the market's attention right now, you need to look at the data.

Introducing MOSP<GO> on the Bloomberg Terminal. We aggregate prediction market data from @Kalshi and @Polymarket, weighted by price and volume, so you can see where the crowd is putting its attention.

Search by keyword to cut through the noise and track the markets that matter:

🗳️ Elections: Monitor the 2026 Midterms, Senate control, and early 2028 nominee odds.

🏦 Macro & Policy: Track Kevin Warsh’s odds for Fed Chair and complex economic scenarios.

🌎 Geopolitics: Follow global events, from European mayoral races to Iran

[Bloomberg Terminal @TheTerminal]

💡 From inflation estimates to earnings alerts, discover the data-driven breakthroughs developed with BQuant Enterprise at Bloomberg’s Code Crunch.

Access the full report ➡️ https://t.co/8PzUpz3W8V

[Tech At Bloomberg @TechAtBloomberg]

At #Ai42025 today, @ArunVermaQuant explores why generative #ML methods are well suited for estimating point values &amp; uncertainty -- and are therefore becoming more popular for financial data imputation &amp; forecasting asset prices
https://t.co/IKnfQz5XlY
#QuantFinance #MLinFinance

[ARC Prize @arcprize]

ARC-AGI-2 is our next iteration of ARC-AGI

It is designed to stress test the efficiency and capability of state-of-the-art AI reasoning systems

Read more about ARC-AGI: https://t.co/TvQQ5ZJ7uQ

[Tech At Bloomberg @TechAtBloomberg]

With #MCP, @Bloomberg isn’t just modernizing its own #GenAI infrastructure — it’s accelerating how financial intelligence is delivered &amp; empowering financial professionals with smarter, faster, #AI-powered tools in a rapidly evolving industry
https://t.co/aW0tsMLGw0

[Tech At Bloomberg @TechAtBloomberg]

We’re excited to announce @Bloomberg's Visiting Faculty Program, a unique chance to collaborate with our researchers on #AI for #finance &amp; tech. Gain access to world-class data &amp; have real-world impact.
Apply for sabbaticals &amp; part-time roles: https://t.co/UEwIN3IpOe
#research

[Tech At Bloomberg @TechAtBloomberg]

In "Understanding &amp; Mitigating Risks of Generative AI in Financial Services," authors studied existing guardrail solutions, found them insufficient in detecting domain-specific content risks &amp; proposed the 1st finance-specific #AI content risk taxonomy
#ResponsibleAI #GenAI
(1/7)

[Tech At Bloomberg @TechAtBloomberg]

Let’s examine the findings in @Bloomberg’s “RAG LLMs Are NOT Safer” paper:

It reveals that #RetrievalAugmentedGeneration (RAG) frameworks can *actually* make #LLMs less safe! Even “safe” #AI models combined with “safe” documents can produce “unsafe” outputs
#ResponsibleAI
(1/7)

[Tech At Bloomberg @TechAtBloomberg]

#AI researchers at @Bloomberg released two papers that have significant implications for how organizations deploy #GenAI systems safely &amp; responsibly, particularly in high-stakes domains like capital markets financial services

https://t.co/7rMHz4uKF2
#ResponsibleAI #AIinFinance

[Tech At Bloomberg @TechAtBloomberg]

Researchers in @Bloomberg’s #AI Engineering group, Data AI group &amp; CTO Office published two papers which expose significant risks in the use of #GenAI systems.

In this video, @sebgehr, Head of #ResponsibleAI, explains their findings:

Read more: https://t.co/eeO3q01cBp

[ARC Prize @arcprize]

Announcing ARC Prize.

A $1M+ competition to beat the ARC-AGI benchmark and open source the solution.

Hosted by @mikeknoop &amp; @fchollet.

https://t.co/TUr6bhwgz6

[Saeed @saeedamenfx]

NeuralBeta: Estimating Beta Using Deep Learning https://t.co/u3dgIzbH54 #QuantLinkADay

[Arun Verma @ArunVermaQuant]

@saeedamenfx Thanks for highlighting this @saeedamenfx !

[Ivan Blanco @iblanco_finance]

🔔 New Research Idea! "Generative Machine Learning for Multivariate Equity Returns"

This paper examines the effectiveness of ML/DL, particularly conditional importance-weighted autoencoders in modeling equity returns.

My sum up in under 3 min: 👇

[Tech At Bloomberg @TechAtBloomberg]

At the Research in Options: RiO 2023 conference @FGV in Brazil today (12 PM BRT), Bruno Dupire will deliver a talk about how "Signatures in Finance" can be used to speed up the computation of #VaR
https://t.co/YOLOQ610FM
#QuantitativeFinance #QuantFinance #AppliedMathematics

[Tech At Bloomberg @TechAtBloomberg]

Today, @FGV's Research in Options 2023 conference (3:30 PM BRT), #QuantitativeFinance Researcher Mohammad Fesanghary will present a novel, less computationally intensive algorithm for Causal Structure Learning in nonlinear time-series systems
https://t.co/iHze5XsLc3
#QuantFinance

[Tech At Bloomberg @TechAtBloomberg]

Researchers from @Bloomberg's #AI Engineering Group co-authored 4 papers at @emnlpmeeting in Singapore this week; learn more about their research, why the results are notable, and how their work will advance the state-of-the-art in #nlproc
https://t.co/rCg5eTLBGl
#EMNLP2023

[Tech At Bloomberg @TechAtBloomberg]

At the 19th #QuantitativeFinance Conference today (12 PM WEST), Achintya Gopal, #ML #Quant Researcher from the Quantitative Research group in our CTO Office, will discuss the efficacy of using modern ML methods to model equities' returns
https://t.co/HKXHxjPCYl
#MLinFinance