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

[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

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,



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