Petter Kolm

What is liquidity management and why is it important? Find out now: https://ow.ly/FwLw50Sk5XE #CQF #quant #finance #quantfinance #quantitativefinance #financialengineering #career #datascience #machinelearning #iquidity #asset #risk

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The IV curve, or volatility surface, describes how IV varies across different strikes and expirations.  Understanding the IV curve as a function of expiration is essential for option traders The Implied Volatility Curve as a Function of Expiration🧵 https://lnkd.in/gw3RHtZx

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This technology is here, now. I sat in on a presentation by another Chicago professor Anna Costello of her (unpublished) research on LLM's which seems to have also made a lot of progress. Inference engines following traditional financial statement analysis are going to be more efficient than humans covering small and mid caps (typically more cyclical than the high growth tech behemoths) even in the US. Globally, the costs of managing such a portfolio across multiple currencies, regulations and languages are now prohibitive vs. what the market is willing to pay *at best* i.e. 75 bps. (I am told the best translation engines for Asian languages would be from TikTok :). Whatever LinkedIn has seems to do a good job with German.) Aside from the fact that we have sorted out how to use AI to value high R&D / high growth companies, a boast explained another day, the point is human teams managing the typical SMID portfolio should be looking for an exit, while one is available. The most effective path is going to be to use a financial decision engine with tagged risks, along with a natural language processor combined with a translator to sift through disclosures and rank the results. My wild guess is the alpha enters double digits for now. I think a significant minority of companies would not qualify under ESG rules, and there would be a concentration in Japan, coming out of its corporate governance slumber, but those are discussions for another day as well. For now, I am scrambling to combine commercially available text processing technology with AI valuations, and improve the screening for my portfolios. Alexander Fleiss #AI #Naturallanguageprocessing #financialstatement #10k #secfiling #midcap #smallcap #globalinvesting #llm #valuation #markets #hedgefunds #equities #credit #marketneutral #nikkei #esg

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The Less-Efficient Market Hypothesis: Abstract of a paper by Clifford Asness of quant investor AQR Capital: Market efficiency is a central issue in asset pricing and investment management, but while the level of efficiency is often debated, changes in that level are relatively absent from the discussion. I argue that over the past 30+ years markets have become less informationally efficient in the relative pricing of common stocks, particularly over medium horizons. I offer three hypotheses for why this has occurred, arguing that technologies such as social media are likely the biggest culprit. Looking ahead, investors willing to take the other side of these inefficiencies should rationally be rewarded with higher expected returns, but also greater risks. I conclude with some ideas to make rational, diversifying strategies easier to stick with amid a less-efficient market. Read more of this story at Slashdot.

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Detailed thread on Understanding and Trading Vanna and Charm effect for trading🧵 Vanna and charm effects are important concepts in options trading and are closely related to the Greek metrics used to measure and manage risk https://lnkd.in/eTBNPNjt

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Monitor: US BSL CLO New Issue Arb Trend Since 2017 The median arbitrage metric YTD at 195 bps is actually lower than in both 2022 and 2023, but this year’s new issue volume has already far exceeded the past two years’ volume on an annualized basis. Similarly, 2018-vintage deals had the lowest median arbitrage metric at 191 bps, but 2018 was a record-breaking year for new issue #CLO volume at the time. On the other hand, 2020-vintage deals had the best median arbitrage metric at 243 bps, but their new issue volume was the lowest. If you’re interested in learning more about the premium content or would like a walkthrough of the website via Zoom, please don’t hesitate to email me at [email protected]. https://lnkd.in/e6sUTfjw

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Is ETH About to Plummet Below $3K or Will the Bulls Step In? (Ethereum Price Analysis) ➡️ Read All : https://lnkd.in/ePAD6xbm Following a period of consolidation near critical support marks defined by the 0.5 and 0.618 Fibonacci retracement levels, alongside the 100-day MA, Ethereum witnessed a... [...] #CryptoTrading, #BullishRebound, #ResistanceLevel, #FuturesMarket, #Liquidity, #Crypto, #Ethereum, #NBTC

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Fantastic talk from Blanka Horvath on 'Non-Adversarial Training of Neural SDEs with Signature Kernel Scores' live on the Quant Insights stage now! #cqf #cqfinstitute #quant #finance #quantfinance #quantinsightsconference #quantitativefinance #risk #derivatives #volatility #machinelearning #quantumcomputing

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Detailed Breakdown of Term Structure Trading: 🧵 Term structure trading focuses on the imbalances between different maturities in implied volatility surfaces. These imbalances, often driven by supply-demand mismatches, present trading opportunities.    https://lnkd.in/eZja7zFa 

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If you’ve been here — manual model monitoring for quant trading systems that doesn’t detect issues early enough Or here — deafening noise from alerts that makes it difficult to actually identify root causes and resolve issues efficiently, this one's for you. In our upcoming webinar 𝐌𝐨𝐝𝐞𝐥 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 𝐟𝐨𝐫 𝐐𝐮𝐚𝐧𝐭 𝐓𝐫𝐚𝐝𝐢𝐧𝐠 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 you’ll hear: + How to get granular insights and systematically reduce noise to minimize false positives and alert fatigue. + Best practices for tailoring monitoring approaches to your specific needs, ensuring that critical issues are detected without overwhelming your team. + Real-world examples of how data science teams have successfully navigated this conundrum to improve model performance and operational efficiency. 🗓️ Date: October 10th, 2024 🕒 Time: 11am ET | 8am PT 👉 Learn more and register: https://lnkd.in/eUNiD8Mh #QuantTrading #DataScience #ModelMonitoring #QuantModels #MLOps #Webinar #AlgorithmicTrading #AlgoTrading #Mona

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What are supervised learning techniques? What is a Naïve Bayes Classifier? What is the Kelly Criterion? Get answers to these questions and more in our Quant Finance 101 article: https://ow.ly/20gl50TIW4a #CQF #quant #finance #quantfinance #quantitativefinance #career #machinelearning #datascience #ai #riskmanagement #trading #portfoliomanagement

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Just released a new paper "Empirical Model of VIX Volatility and SPX Variance" on how one can relate VIX skew with that of SPX skew. https://lnkd.in/ekn_ZqxE

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Proposing a solution to the dynamic portfolio allocation problem for non-myopic agents faced with a stochastic investment opportunity set when trading is costly, from Pierre Collin-Dufresne, Kent D. Daniel, and Mehmet Sağlam https://lnkd.in/eTzytZ9n

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Read this new white paper by my friend and eminent practitioner-scholar Michael Mauboussin, coauthored with Dan Callahan, CFA. The paper explains how to apply valuation multiples like P/E and EV/EBITDA ratio for modern corporations. The message is consistent with my own research--be careful in mechanically using accounting numbers for modern tech companies--their accounting suffers from numerous deficiencies. This paper suggests precautions an analyst must exercise in using numbers and ratios, while offering concrete solutions.

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Ghislain needed to develop a more practical quant finance skillset, so decided to enroll on the CQF. Discover how the program has enhanced his career: https://ow.ly/Ke1150UfARP #CQF #quant #finance #quantfinance #quantitativefinance #career #machinelearning #datascience #riskmanagement #portfoliomanagement #trading #technology #quantstrategies #quantresearch

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