You can track shifting asset class and/or strategy allocations over several years for a long list of asset managers, and then add it all up to arrive at a data-driven industry trend. Easier said than done. This is an extremely heavy lift without the aid of a database that has already aggregated such information - if at all. But, we think there is another way to generate such a signal that yields a similar conclusion (if you know how to read the tea leaves). Hint: As always, it still comes down to the people... That preamble aside for the moment, we will spare you the geek-speak and give you the cart before the horse: In the exhibit below, based on US Securities and Exchange Commission Form ADV data for 181 large asset managers (w/ AUM >$10 billion) over the 5 years ending March 2017, Alphacution's newest analytic - assets under management per employee, or AUM/e - indicates, upon calculation of total weighted average AUM/e for all reporting funds per period, that strategy trade durations have been lengthening. Translation: On average, asset [...]
adjusted net trading revenue Aflac AI Aite Group Alan Greenspan Alphabet Alphacution research vision Alphacution Riffs Amazon Apollo Management Apple AQR Capital artifical intelligence artificial intelligence asset management assets per employee attention economy attention market AUM/e AUM per employee automation average daily revenue analysis AWS Azure BAML Bank of America banks Barclays BATS benchmarking Betterment BGC Partners BlackRock Blackstone Bridgewater brokers business process outsourcing capex Carlyle Group Central Banks Chopper Trading Citadel Citi Cloudera CME Group cognitive solutions Cognizant Technology Solutions collaboration collective intellect contextual data contiguous modeling Credit Suisse CSC Daniel Coleman data automation data fluency data products Dell D E Shaw Deutsche Bank digital attention crisis digital content digital culture digital disruption digital enterprise digital frontier digital platform digital research digital transformation DIKW pyramid Dodd Frank DRW DTCC DXC Technology E*Trade EDS Enterprise IT eVestment exchanges Facebook fake news FANGs FinTech FIS Flow Traders Form ADV GETCO Goldman Sachs Google hardware spending Headcount headcount index headcount segmentation hedge funds Hewlett Packard Enterprise HFT HP HPE HPQ human capital human capital costs human capital leverage human capital leverage benchmark human latency IaaS IBM ICAP IMC Indigenous Productivity Infosys ING Group innovation innovation laboratories Intel intelligence bottlenecks Interactive Brokers Interventionism ITG IT infrastructure costs IT outsourcing IT Services Janet Yellen Jefferies JPMC J P Morgan Jump Trading KCG Kensho Technologies KKR Knight Capital knowledge decay labor arbitrage machine learning Man Group MapR market-making market data market data fees Marty Chavez McKinsey &Co Millennium mission Morgan Stanley Nanex Nasdaq navigational intelligence Netflix Northern Trust Numerix Video Blog Och-Ziff operational agility operational alpha operational analytics operational beta operational leverage operational risk opex Personal Capital post-trade processing private equity process automation process efficiencies process re-engineering process replacement productivity engines Q4-2016 quantitative research Quantitative Trading quote stuffing rant RBC research strategy return on technology Revenue Analysis revenue per employee RGM Advisors Robo-Advisors RPE RPE Analysis Sam Harris SEC smart touch software costs software development Sudoku Puzzle SunGard supply chain management Sympohony Innovate 2017 T-Greeks T-Spread T-VOL Tata Consultancy Services TCO TCO/e technical infrastructure technical leverage technical leverage gap technical signature technology capital benchmark technology debt technology economics technology spending benchmarks technology spending volatility Thomson Reuters Timber Hill trade automation T R Price Two Sigma Two Sigma Investments UBS Viking Global Virtu Virtu Financial VIX volatility Waking Up Podcast Webinar Wells Fargo Winton Capital Wolverine Trading XL Group
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