J.P.Morgan's massive guide to machine learning and big data jobs in finance

["Dave Farber" <farber () gmail com>]

Begin forwarded message:

> From: Dewayne Hendricks <dewayne () warpspeed com>
> Date: June 2, 2017 at 5:25:42 PM EDT
> To: Multiple recipients of Dewayne-Net <dewayne-net () warpspeed com>
> Subject: [Dewayne-Net] J.P.Morgan's massive guide to machine learning and big data jobs in finance
> Reply-To: dewayne-net () warpspeed com
>
> [Note:  This item comes from reader Randall Head.  DLH]
>
> J.P.Morgan’s massive guide to machine learning and big data jobs in finance
> By Sarah Butcher
> May 31 2017
> <http://news.efinancialcareers.com/uk-en/285249/machine-learning-and-big-data-j-p-morgan>
>
> Financial services jobs go in and out of fashion. In 2001 equity research for internet companies was all the rage. In 
> 2006, structuring collateralised debt obligations (CDOs) was the thing. In 2010, credit traders were popular. In 
> 2014, compliance professionals were it. In 2017, it’s all about machine learning and big data. If you can get in 
> here, your future in finance will be assured.
>
> J.P. Morgan’s quantitative investing and derivatives strategy team, led Marko Kolanovic and Rajesh T. Krishnamachari, 
> has just issued the most comprehensive report ever on big data and machine learning in financial services.
>
> Titled, ‘Big Data and AI Strategies’ and subheaded, ‘Machine Learning and Alternative Data Approach to Investing’, 
> the report says that machine learning will become crucial to the future functioning of markets. Analysts, portfolio 
> managers, traders and chief investment officers all need to become familiar with machine learning techniques. If they 
> don’t they’ll be left behind: traditional data sources like quarterly earnings and GDP figures will become 
> increasingly irrelevant as managers using newer datasets and methods will be able to predict them in advance and to 
> trade ahead of their release.
>
> At 280 pages, the report is too long to cover in detail, but we’ve pulled out the most salient points for you below.
>
> 1. Banks will need to hire excellent data scientists who also understand how markets work
>
> J.P. Morgan cautions against the fashion for banks and finance firms to prioritize data analysis skills over market 
> knowledge. Doing so is dangerous. Understanding the economics behind the data and the signals is more important than 
> developing complex technical solutions.
>
> 2. Machines are best equipped to make trading decisions in the short and medium term
>
> J.P. Morgan notes that human beings are already all but excluded from high frequency trading. In future, they say 
> machines will become increasingly prevalent over the medium term too: “Machines have the ability to quickly analyze 
> news feeds and tweets, process earnings statements, scrape websites, and trade on these instantaneously.” This will 
> help erode demand for fundamental analysts, equity long-short managers and macro investors.
>
> In the long term, however, humans will retain an advantage: “Machines will likely not do well in assessing regime 
> changes (market turning points) and forecasts which involve interpreting more complicated human responses such as 
> those of politicians and central bankers, understanding client positioning, or anticipating crowding,” says J.P. 
> Morgan. If you want to survive as a human investor, this is where you will need to make your niche,
>
> [snip]
>
> Dewayne-Net RSS Feed: <http://dewaynenet.wordpress.com/feed/>



-------------------------------------------
Archives: https://www.listbox.com/member/archive/247/=now
RSS Feed: https://www.listbox.com/member/archive/rss/247/18849915-ae8fa580
Modify Your Subscription: https://www.listbox.com/member/?member_id=18849915&id_secret=18849915-aa268125
Unsubscribe Now: 
https://www.listbox.com/unsubscribe/?member_id=18849915&id_secret=18849915-32545cb4&post_id=20170602213650:1BC37BF4-47FD-11E7-BD9E-B19E9476F84E
Powered by Listbox: http://www.listbox.com