MUST KNOW TOPICS TO LEARN IN QUANTITATIVE FINANCE #Finance

hi in this CashNews.co I’m going to talk about uh which study if you want to become a Quant so what are the topics that you need to know before you can apply for uh Quant jobs in uh in Banks or in in private funds Insurance companies uh or even fexs right so this is a

broad list of topics I’ve come up with um uh it’s very useful actually if for uh if for someone who is interested uh or someone who is looking for uh an opportunity in the Quant Quant field okay so if you want to become Quant I think one must thing to know is uh about the probability

and statistics so you really have to be strong in probability and statistics uh if I’ve done some courses in your bachelor program or in your in your master’s program I think that’s well and good but if you really want to brush up your probability and statistics I would highly

recommend you know going through some courses on uh K Academy or doing some courses on CER actually you know they have really good some uh probability and statistic courses uh you need to focus on probability distribution hypothesis testing sampling you know these topics okay um you don’t

have to study statistics uh a lot like you don’t have to be a master in statistics uh in order to you know work in Quant you really need uh only the applied statistics right in in statistics actually you learn a lot of Theory actually that’s uh you know much of that is not of much you

know not of use in Quant Finance uh whereas applications of Statistics is very very uh important in the Quant field right probability is a very theoretical concept but it is quite uh heavily

used in many Advanced theories in Quant Finance so probability as such is not used but uh it’s it’s uh you know you need to understand probability um at a deeper level before you

can sort of understand more uh uh more complicated sophisticated uh topics for example you know pricing of derivative you know those topics right you need to have good understanding of financial none;">Markets it’s not a Quant topic per se but uh without having proper understanding of financial products different types of Markets uh you know primary Market secondary Market

Etc Market uh micr structure you know the different jargons use in trading and lending it will be difficult for you to work in uh the Quant field so only when if you have understanding of you know these nonquant uh related topics uh will then be able you will then be able to relate you know the

mathematical models to you know the applied World um right because quantitive Finance is an applied field it uses a lot of uh academic uh Fields uh it’s it’s for instance

statistics computer science uh physics mathematics um but it’s an applied field right so unless you understand the actual products in the applied World whether it’s stocks or Bonds or Commodities uh you know derivatives you need to have you know some understanding of

that um you know there are primarily two types of product trading product and you have lending product okay trading product will have you know the traded Assets such as stocks and Bonds and commodities and Interest Rates derivatives Etc lending

will be more about Loan right so they are different kinds of Loan unsecured Loan secured Loan you know then you have further categorization you know wholesale Loan retail Loans even within

wholesale and Retail you will have you know further categorizations you need to have solid understanding of those concept right as a beginner people will not expect you to have thorough understanding but if you really want to be successful as a Quant I think goes without showing that you need to

have good understanding of the financial Markets and the products and so on um you know a lot of people don’t give much importance to you know the the the the the the business side of

things but you know without knowing the business side of things you’ll never be uh very successful uh if you’re a beginner actually you will still be asked some you know fun you know basic questions about financial Market uh even though you don’t have a a

href="https://cashnews.co/finance" style="font-weight: bold; color: #1a73e8; text-decoration: none;">Finance background you still will be asked some of the questions not at a great detail but you need to have at least high level understanding of you know the financial products and the

financial Markets okay uh another technical topic that you need to know is financial econometrics uh it’s it’s you know um it’s a part of econometrics actually econometrics

is a topic which deals with the use of statistical modeling in the field of economics and Financial econometrics in particular is all about use of econometrics in the field of Finance right

um you know it’s quite heavily used in the field of Finance whether you know both in the trading area but also in the lending area the many uh academic models which are you know quite

heavily Ed regression models are used you know whether it’s linear regression logistic regression quantile regression beta regression negative binomial regression um Cox proportional Hazard you know those sort of models so all kinds of these models are used um you also need to have good

understanding of time Sage models especially in in trading area time Sage models are uh heavily used right time models are used for Forecasting uh prices and returns of financial Assets so these models such as arima Arch garge error correction model these models

are quite um heavily used in the field of quantity Finance especially if you want to work in the trading area or investment area uh you’ll also need to know some thing about panel data

which is uh yeah not heavily used but still good to have this understanding you need to have understanding of survival anal analysis so Financial econometrics is is a very important um you know topic that you need to know it’s a course in itself actually if you do a master in quantitative

href="https://cashnews.co/finance" style="font-weight: bold; color: #1a73e8; text-decoration: none;">Finance or financial engineering one of the module will be uh financial econometrics and you will be learning a lot of theoretical stuff you’ll also be using those models in the act you

know with real world data right so you know quite important um this is also related to machine learning but uh you know the way you build machine learning models um is actually quite different from that in financial econometrics although there are you know overlaps like regression models are also

part of machine learning for example um then another topic would be the financial math right financial math is is an academic discipline in itself and there you know it’s a very um you know heavy mathematical topic uh so you need really need to be really good good in probability and statistic

before you can um you can you know start Financial M right you need to have good understanding of calculus for example differential calculus integral calculus uh you need to have solid understanding of probability uh right set theory um relation function you know those concept before you can you

know do well in MA Financial mathematics uh know stochastic calculus is is heavily used in the you know cell side quantied Quant area right uh especially if you work in big Banks you’ll be working with uh you know derivative areas stochastic calculus is quite heavily used and that’s

part of fin National math and uh yeah that’s something you need to know um machine learning is becoming very popular nowadays um with more advancement in and successes in other fields machine learning is now ging popularity in the field of

style="font-weight: bold; color: #1a73e8; text-decoration: none;">Finance not as much as it is popular in other fields such as in e-commerce or in you know other uh other fields but but certainly it is gaining popularity uh um so you know to have good understanding of regression models but you

know when you build regression models in machine learning actually it’s the approach is bit different compared to that in econometrics right you you use cross validation for example um in um in machine learning something that you do not use in econometrics um okay and then uh you don’t

use sort of you know the P value you don’t really care about the statistically statistical significance of estimates those things are not you know part of machine learning so there are certain differences but the the reason why you build a machine learning model is also very different right

you’re more um focused on the predictions rather than the uh finding the relationship between variables and that’s um yeah there are many ways uh to you can do that and you can use uh uh you know a lot of models right compared to that in econometrics you will have lot more at your

disposal for for example the tree Bas models there are you know many types of tree Bas model whether decision tree boosting bagging random Forest within b b boosting and bagging you have also you know adaptive boosting gradient boosting and so on so forth um right and you also have support Vector

machine and if you really want to go into the more neural network area then you can you know also try deep learning reinforcement learning is getting some popularity in the Portfolio Management Area uh also in in investment area trading area as well um so you know very very

important if you really want to V Quant in 21st C well in in in 2024 2025 you must learn machine learning actually that was not the case actually you know 20 years back if you had to you know study for Quant jobs back then then machine learning wasn’t really popular in fact not at all popular

but nowadays you really need to know machine learning um and if you know Advanced machine learning like deep learning and and reinforcement learning that really A Plus on your CV um derivative pricing is is uh is a very important topic to be you know you need to know before you want to be become a

Quant uh you should have good understanding of how to price derivatives right it may not be needed actually if you really want to work in the lending area uh right if you want to work in more Loan based product then you know you don’t need to know derivative pricing but um if

you know actually you’ll have more flexibility you can go to pricing and in know those fields uh which are you know more lucrative actually you can make more money in you know becoming a Quant in pricing area right in derivative areas compared to you know in more Loan side so

yeah you need to know Blackstone model you know all kinds of theoretical models uh to price different derivative different kinds of derivatives you know um bide also you really need to know you know the fixed Income security also finix Income security and uh yeah

those you know risk areas right um yeah Portfolio management and how to sort of uh you know Greeks for example you know all these things you will also learn you know while learning derivative pricing uh but these are use in in more than just derivative pricing um you should have

you know decent amount of understanding of the lending and trading I’ve said this before but it it it is very important that you have some understanding of Credit analysis you should know how to you know how to assess Credit worthiness of a customer

especially a Wholesale customer looking at the Financial Ratios and so on so forth you can automate that through a model but before you do that can you do that yourself manually right that understanding will really help you to good build good model similarly trading is very

important right you have some understanding of how to trade you must have you know traded yourself at least for some time um just to get get a you know a feel of how how you know what are the things that that really are important in trading before you can build models for those things right so

getting that fast firstand experience uh or more of front office experience is is very crucial you may not have that experience you probably will never get that if you work in the industry because you can’t work in both side but uh you know if I studied something that really helps then risk

modeling right risk modeling is one area where most quants actually work okay uh there are many areas of risk modeling where is Credit risk modeling Market risk modeling operational risk modeling asset liability management modeling all these areas so these are very you know very uh

domain specific areas actually you know you will probably not get much of content about you know these areas uh on the public domain uh the the content that you will find may be very academic in nature uh but you really need to you know have some understanding of you know these models such as the

PD lgd Ed models in Credit risk you know the market risk models as valuate risk expected sful type models Alm models and you know these are more regulatory models so having understanding of these things on you and and if you put this you know names on the CV actually really really

impress the interviewer actually uh so you know good to have understanding of that um right um the beside that uh yeah if you really uh want to be a Quant in a hes fund or a private fund or family office you need to have understanding of how to do you know quantitative trading right so um you know

some of the models for example the SMA EMA models the mean reversion models um how to do you know pair trading um there some simple Quant trading models but there are also some more academic more uh you know academic type models uh which you must have some understanding of that of course you know

the real world is very different actually in the Quant trading area you’ll never be able to learn the real world problems through a course or through a book actually but having Basics understanding of the basics will go a long way right so these are some of the models that you know you should

try learning um then beside you also need to learn some of the Finance related topics such as Corporate #1a73e8; text-decoration: none;">Finance uh uh you know Valuation techniques behavioral Finance you should have understanding of macroeconomics you should have

understanding of Risk Management uh or you know regulations related to Risk Management whether it’s Credit Risk Management uh Market Risk Management all of that um it’s never easy to find all these

topics in one area but yes if you really want to learn you you need to do a course or you need to study some books I do have have a course you know you can find the details here if you want to reach out to me let me know um I can provide the details you will learn most of these topics in that

course uh beside that uh on the programming side you need to have you know some experience with python um yeah Python and one other language right python is the most popular language nowadays in Quant field but uh SAS is also used in Banks R is also used many places C++ is used in the derivative

side um mat live is also used now you know it’s been in used for many many time right there are other languages such as C and all even Java is use in Quant development areas uh you can’t be a master in everything just you know pick one or two languages I think that should be enough uh

all right so if you really want if you enjoy this CashNews.co if you want to know more about this topics you really want to be uh Quant in the future let me know uh if I can help you with anything I do have a course uh with uh in all these topics uh let me know you can contact me you can find the

contact details here actually these are the contacts but uh you can also find in the description section of this CashNews.co uh you know I have a very beginner friendly comprehensive course um with all these topics covered right suitable for someone who is a beginner and um yeah it’s

it’s quite comprehensive so you will you will learn a lot of lot of the stuff very applied stuff not just plain Theory but very applied stuff okay thanks for watching thanks