If I want to work as a quant should I pursue a Masters in Data Science or a Master of Financial Engineering?
@CQFInstitute @MITSloan
I might be capable to offer my two cents based on my direct experiences as a risk manager working in the asset management and commercial banking sectors of the economy.
Hence, you might obtain a lopsided view, but something is worthier than nothing?
Data Science and Machine Learning are becoming all so popular these days.
I believe ML - Machine Learning in Finance and Investing will be the hottest talk of the town in the coming days!
We already hear of a FINTECH revolution approaching and with the rapidly changing face of the market due to digitization, mobile banking apps and other Online trading software apps, perhaps you will be better off with a degree in Data Sciences & Machine Learning and/or Analytics
If you have an interest in Financial Markets and coding, but at the same time you would like to do a degree that “keeps the baby in the bathtub” aka financial engineering, you can opt for a program that teaches the usual stuff such as BI - Business Intelligence Modeling
and Data Visualization using either Tableau or MS Power BI, Bayesian Networks in Finance, a decent level of programming in Python/R Code, a good level of SAS Software Applications,
NLP - Natural Language Processing, AI Artificial Intelligence Coding Methods and the Dashboard Financial Risk Analytics with an emphasis on derivatives and the relevant pricing/hedging models.
Doing a degree in Financing Engineering is also a good idea, but you won't be able to learn advance machine learning concepts.
However, Financial Engineering Students do learn Algo programming and code writing, using the C family of Languages and/or Matlab and /or VBA at most of the Engineering / Math Schools that work in conjunction with the Finance Departments at various universities.
I guess Financial Engineering will keep you constrained within the Quantitative Hedge Fund or the Investment Banking Service Industries.
Some might even apply to work as risk modellers at Retail Banks and asset management companies, but the choices do get restricted by staying mostly only within the Financial Sector.
Looking at the way people are thrown out of the Trading Markets during market downturns or due to any other plausible global financial systemic risk event, (like the one that shook the world in 2007), it comes down to a personal risk that you shall need to manage and live with
A degree in Data Sciences and Analytics will take you to higher places!

You will be able to hedge your career better.

Good luck!

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More from @SAH16928046

22 Feb
What is the difference between a master in financial risk management and a master in quantitative finance? Which is harder?
@GARP_Risk
Risk Management focuses on loss identification, measurement, management and monitoring.
It's a Negative or Hazardous Incidence Reporting focussed science which has to be perfected and practised as a management art.
In a standard Financial Risk Degree, you might learn Financial Risk Management, ERM - Enterprise Risk Management and other aspects of Actuarial Sciences and/or QRM - Quantitative Risk Management which becomes very mathematical in overall terms.
Read 14 tweets
20 Feb
Nations that fail economically gradually become Hyper-Nationalistic.
To name a few over the last century and in recent cases studied up to now included the 3rd Reich, Italy, possibly Imperial Japan due to USA Sanctions before WW2, USSR, and India and the USA(as seen under Trump).
Definitely, #China, as we study its example in a Political Science Masterclass, has become more and more nationalistic, since 79
The recent spade of CoronaVirus coupled with President Xi's style of governance will lead Chinese rhetoric to create more nationalistic hyperbole!
Also, Malaysia, which was largely a lame-duck nation with hardly any notable say on any sort of geostrategy or geopolitical matters, became extremely right-wing and Ultra-Nationalistic under @chedetofficial when the 1997 AFC- Asian Financial Crisis, swept away most of the region
Read 10 tweets
19 Feb
Oh, yes, quantitative engineers are vital to economic development and its wide-ranging processes!
However, nobody realized back in the early 1980s, that engineers would move out of tangible industries and services drove value-adding sectors of the real economy such as the constructions and productions engineering businesses and industries,
into the fast-moving and computing non-tangible sectors, which are banking, finance and asset management services economy.
Read 5 tweets
11 Feb
I have been asked to do a detailed write-up on what does and does not constitute risk management.
There is a lot of confusion within the scholarly cum practitioner domain, as many topics are unjustly added or deleted from academic curriculums and workshop topical course outlines
Risk Management has a wide scope both within the financial services and non-financial services industry.
Especially, Risk as a subject has greatly benefited from the transfer of applicable and vocational knowledge outside the Insurance Field, over the years.
Risk as a profession, which was and continues to be dominated by Applied Statisticians, and Mathematicians, generally fitted well into the #Actuarial Domain, but, only until recently, when scholars from other non-related professions jumped into the market, offering afresh ideas.
Read 19 tweets
5 Feb
What is Equity #Portfolio #Risk Management?
If I understand your question correctly, the Equity Portfolio Risk Management should be primarily be concerned with managing the market and liquidity risk of Equity or akin linked Securities.
@GARP_Risk @CQFInstitute @icmacentre @ICMA
Other Portfolio Investment Management Risks might include =>
1.Transactional Risk
2.Price and Fair Value Modelling Risk
3.Financial Reporting Risks
4.Trading Microstructure Risks
5.Legal Risk
6.Hedging Risk using Risk Financing Methods
Investments and/or trades in the Equity Securities aka company issued shares generally falls into three-segmented and specialized market categories =>
Read 17 tweets
28 Jan
If the connotation of risk is an intertwined concept and is difficult to quantify, how does a Risk Officer look at it?
Is there any way other than using copula models to determine systemic risk with long tails or a black swan event?
@CQFInstitute @GARP_Risk @SOActuaries
I guess we are worried about Market and Credit Risks or other interrelated financial risks which can create conjoint loss given events.
Any #Gaussian distribution model will enable you to model and predict potential Operational, Liquidity and Balance sheet AL - (Asset - liability) Mismatch, Market and Credit drove losses under normal market conditions.
Read 32 tweets

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