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Risk Manager(Banks,Asset Management,Insurance) Profile picture
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25 Mar, 4 tweets, 2 min read
useful lecture for those who are interested in applying statistical knowledge to problem-solving in risk management, insurance, financial engineering, banking, and actuarial mathematics and modelling.
The biggest problem faced by the statisticians is that they over-rely on the computational characteristics of the Bell-shaped Normal Distribution Model.
Hence, we saw what happened to such risk models during the #GFC of 2008, as most of the incoherent #risk measures used by #actuaries and quants, underestimated the #probabilistic consequences of negative risk-based outcomes aka hazards

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More from @SAH16928046

Risk Manager(Banks,Asset Management,Insurance) Profile picture
27 Mar
Which are some interesting stylized facts about Risk Management and IAD Failures across global corporations?
@PRMIA @GARP_Risk @BIS_org
Quantitative Risk Management when turned into a profession, does not work in reality in most cases, as witnessed now outside the Insurance Sector!
Insurance is different because the profession is led by well-trained quantitative professionals such as Actuaries!
The multiple reasons for the failure of Risk Management and Auditing Departments at firms could be the following =>
Read 19 tweets
Risk Manager(Banks,Asset Management,Insurance) Profile picture
22 Mar
What are the future opportunities if I start my career in Financial Computational Modelling?
@CQFInstitute @CFAinstitute @GARP_Risk @PRMIA
Financial Modeling has many connotations. Modelling on Financial Variables is FM - Financial Modeling.
However, a model has many variants.
Please do read Dr Emanuel Derman, if you are interested in analyzing and understanding the computational (quantitative) methodology that taxonomizes model and model risks.
•Financial Modeling in Risk takes on various forms such as Econometric Modeling/ Volatility Modeling and so on etc.

•FM in Equity research is a structural analysis of the business and financial model of the company in which you would like to invest.
Read 17 tweets
Risk Manager(Banks,Asset Management,Insurance) Profile picture
10 Mar
How much importance is the FRM certification course?
@GARP_Risk
If you have no background in Banking and Finance subjects, it is better for you to do an FRM / PRM and the other professional qualifications in risk offered by various bodies and institutes around the world.
I am sorry, but with this sort of garbage, you won’t be able to impress employers at the highest level, who are looking for mature #ERM Specialists with industry-specific experiences and learning or Quants with exceptional degrees from the top most unis.
Read 10 tweets
Risk Manager(Banks,Asset Management,Insurance) Profile picture
27 Feb
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!
Read 14 tweets
Risk Manager(Banks,Asset Management,Insurance) Profile picture
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
Risk Manager(Banks,Asset Management,Insurance) Profile picture
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

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