We have been playing with some new equations; looking to see if anything interesting can be learned from benchmarking assets per employee across various firms. (It turns out that adding this analytic to our suite of other "per employee" metrics yields significant insights.) In the figure below, we took the top 10 hedge funds ranked by assets under management (AUM) and then re-ranked that list by AUM per employee. We also tossed in Virtu Financial and KCG (Getco) for giggles - and to test the extremes. Notice anything interesting? Based on what you might know about these trading companies, how would you label the X-axis? Here's some additional data to consider: The correlation between assets and headcount is not perfect by any stretch, but it is signal-worthy. Also, this trick works best on mature, ongoing firms whose operations and business are relatively consistent. Headcount level doesn't seem to matter. Albeit at the extremes of tradings firms, Virtu Financial generated nearly US$800 million in revenue (2015) with 148 employees - so [...]
adjusted net trading revenue Aflac AI Aite Group Alan Greenspan Allston Alphabet Alphacution research vision Alphacution Riffs Amazon Apollo Management Apple AQR Capital artifical intelligence artificial intelligence asset management asset managers 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 benchmarks Betterment BGC Partners BlackRock Blackstone blockchain BNP CooperNeff Bridgewater brokers business process outsourcing capex Carlyle Group CBOE Central Banks Charles Schwab Chopper Trading Citadel Citi Cloudera CME CME Group cognitive solutions Cognizant Technology Solutions collaboration collective intellect competitive intelligence Context Machine contextual data contiguous modeling Credit Suisse CRT CSC CyberCorp 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 DLT Dodd Frank Dr. Evil DRW DTCC DXC Technology E*Trade EDS Enterprise IT eVestment exchanges Facebook fake news FANGs FinTech FIS Flow Traders Form ADV FRTB GETCO Goldman Sachs Google hardware spending Headcount headcount index headcount segmentation hedge funds Hewlett Packard Enterprise HFT HP HPE HPQ Hudson River 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 Leucadia machine learning Man Group MapR market-making market data market data fees Marty Chavez McKinsey &Co MiFID II Millennium mission modeling methodology model library Morgan Stanley Mr. Bigglesworth Nanex Nasdaq NationsBank navigational intelligence Netflix Northern Trust Numerix Video Blog O'Connor & Associates Och-Ziff operational agility operational alpha operational analytics operational beta operational leverage operational risk opex Optiver Peak6 Personal Capital Point72 post-trade processing private equity process automation process efficiencies process re-engineering process replacement productivity engines proprietary trading prop shops Q4-2016 quantitative research Quantitative Trading Quantlab quote stuffing rant RBC relative-value Renaissance research strategy return on technology Revenue Analysis revenue per employee RGM RGM Advisors Riffs Robo-Advisors robotic process automation RPA RPE RPE Analysis sales enablement Sam Harris SEC smart touch SOES bandits software costs software development Sudoku Puzzle SunGard Sun Trading supply chain management Susquehanna Swiss Bank Sympohony Innovate 2017 T-Greeks T-Spread T-VOL Tata Consultancy Services TCO TCO/e tech debt technical infrastructure technical leverage technical leverage gap technical signature technology capital benchmark technology debt technology economics technology spending benchmarks technology spending volatility The Context Machine Thomson Reuters Timber Hill Tower Research Capital trade automation T R Price Two Sigma Two Sigma Investments UBS Vanguard Viking Global Virtu Virtu Financial VIX volatility Waking Up Podcast Webinar Wells Fargo Winton Capital Wolverine Wolverine Trading workflow automation XL Group
What Does Citadel* Spend on Technology?April 18th, 2018
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