Dear all,I've been research the difference between US and UK's master. It appears to me that the master in the US is more rigorous, usually an admission of master will also include an expectation of the phd, duration of about 2 years, while the UK usually is only one year.With an educational backgroud all the way been in the UK, I believe it's easier for me to get into a UK master, but also hoping to have a try on some US prestigious Uni such as MIT and Princeton etc. I'd like to ask some precious advice on how difficult is it to get admitted into US master course for UK graduates? and how usually different is the procedure like if there is any?Also, while I'm potentially considering a further phd in the US, I also wonder how's the compatibility between UK's master and US's phd programme, due to the 100% shorter length duration in the master study?Thank you.

the length of the master's programmes in the UK and US shouldn't be taken as an indication of rigor. in the UK, ppl get into their major courses of study earlier in the undergrad program, which means they only need a year of master's level courses. in the US, the first 2 yrs are typically spent taking general education courses unrelated to your master's (so the uni can make more money from you) and of course partying, which means you need to spend more time in the master's program "catching up", so to speak.

QuoteOriginally posted by: Jonathan2...Also, while I'm potentially considering a further phd in the US, I also wonder how's the compatibility between UK's master and US's phd programme, due to the 100% shorter length duration in the master study?...You are hereby banned from further quant work and banished to a career in sales, investment banking or consulting!

ElysianEagle is right, I often use the term "optimal ignorance" when advising on educational choices, if you know too little, the course will just be gibberish to you and if you know too much you are wasting time and money.Bearish is right, more right than you may think, this is the sort of thing than can kill you at interview because it speaks to another cliche of mine "reading the words, but not hearing the music".You have no doubt superior skills in a wide range of algebra, from set theory to PDEs, but do you "get it" ?Do you find yourself waiting for a bus and thinking about whether it is a Poisson process ? But more relevantly, are you applying the maths and finance you already know to deciding upon which course to choose ?What is the NPV of each option ?Are you thinking of the options as options ?Are you seeing your skill set as a portfolio ?What risk management are you doing ?Also have to say that your granularity is not optimal.There are a lot of MFEs, within walking distance of where I'm sitting there are >25, if I lean suicidally out of the windows I can see where 7 are taught, plus the CQF.The University of London all by itself has more than a dozen dfferent MFEs.I suppose I ought to know the number in the UK and US, but I don't, maybe there are 150, or some other number ?You need to find the course that suits you and I will share that "rigorous" is as valid on its own as the colour of the college flag.Also, you may find that a masters in statistics or operational research suits you better, or not, but as above we are doing a NPV calculation here.Being shit hot at stats is vastly more lucrative than mediocrity at MC evaluation of Bermudan options.What are you better at than other people ?

QuoteOriginally posted by: DominicConnorElysianEagle is right, I often use the term "optimal ignorance" when advising on educational choices, if you know too little, the course will just be gibberish to you and if you know too much you are wasting time and money.Bearish is right, more right than you may think, this is the sort of thing than can kill you at interview because it speaks to another cliche of mine "reading the words, but not hearing the music".You have no doubt superior skills in a wide range of algebra, from set theory to PDEs, but do you "get it" ?Do you find yourself waiting for a bus and thinking about whether it is a Poisson process ? But more relevantly, are you applying the maths and finance you already know to deciding upon which course to choose ?What is the NPV of each option ?Are you thinking of the options as options ?Are you seeing your skill set as a portfolio ?What risk management are you doing ?Also have to say that your granularity is not optimal.There are a lot of MFEs, within walking distance of where I'm sitting there are >25, if I lean suicidally out of the windows I can see where 7 are taught, plus the CQF.The University of London all by itself has more than a dozen dfferent MFEs.I suppose I ought to know the number in the UK and US, but I don't, maybe there are 150, or some other number ?You need to find the course that suits you and I will share that "rigorous" is as valid on its own as the colour of the college flag.Also, you may find that a masters in statistics or operational research suits you better, or not, but as above we are doing a NPV calculation here.Being shit hot at stats is vastly more lucrative than mediocrity at MC evaluation of Bermudan options.What are you better at than other people ?Interesting!Sometimes, particularly in London, it is not always clear if the best option is to wait for a bus or walk. Unlike the tube, the arrival of busses can be quite erratic. One measure is to look at how many people there are at the stop. If you arrive at the stop and it is empty this is a good indicator that bus has just been, particularly if it is a busy time and you would expect there to be many people (a prior belief... you know where I am going). So whether to get the bus is a Bayesian problem of the probability of a bus arriving within your expected walking time minus the expected bus journey time given the number of people observed at the stop. This method has worked pretty well for me. When I decide to walk rather than take the bus on one of my routes home, I am rarely passed by a bus on the road.I also now almost involutarily convert all of my spending into basis points of my annual income. This tends to make me more adverse to spending.

QuoteOriginally posted by: ElysianEaglethe length of the master's programmes in the UK and US shouldn't be taken as an indication of rigor. in the UK, ppl get into their major courses of study earlier in the undergrad program, which means they only need a year of master's level courses. in the US, the first 2 yrs are typically spent taking general education courses unrelated to your master's (so the uni can make more money from you) and of course partying, which means you need to spend more time in the master's program "catching up", so to speak.I'd go for a US masters, if you can get into a good uni. UK masters are of very uneven quality (IMHO everything outside Oxford and Cambridge is quite poor).

QuoteOriginally posted by: neuroguySometimes, particularly in London, it is not always clear if the best option is to wait for a bus or walk. Unlike the tube, the arrival of busses can be quite erratic. One measure is to look at how many people there are at the stop. If you arrive at the stop and it is empty this is a good indicator that bus has just been, particularly if it is a busy time and you would expect there to be many people (a prior belief... you know where I am going). So whether to get the bus is a Bayesian problem of the probability of a bus arriving within your expected walking time minus the expected bus journey time given the number of people observed at the stop. This method has worked pretty well for me. When I decide to walk rather than take the bus on one of my routes home, I am rarely passed by a bus on the road.Off topic but real time bus data has been available via feeds since 2011 IIRC. There are apps that have algos running to optimize this down +/- 2/3 minutes, CityMapper seems to be the favourite with the Old St. crowd at the moment.

QuoteOriginally posted by: HansiQuoteOriginally posted by: neuroguySometimes, particularly in London, it is not always clear if the best option is to wait for a bus or walk. Unlike the tube, the arrival of busses can be quite erratic. One measure is to look at how many people there are at the stop. If you arrive at the stop and it is empty this is a good indicator that bus has just been, particularly if it is a busy time and you would expect there to be many people (a prior belief... you know where I am going). So whether to get the bus is a Bayesian problem of the probability of a bus arriving within your expected walking time minus the expected bus journey time given the number of people observed at the stop. This method has worked pretty well for me. When I decide to walk rather than take the bus on one of my routes home, I am rarely passed by a bus on the road.Off topic but real time bus data has been available via feeds since 2011 IIRC. There are apps that have algos running to optimize this down +/- 2/3 minutes, CityMapper seems to be the favourite with the Old St. crowd at the moment.Off topic? In a wilmott thread? Never!Thanks for that, thats really cool.Looks like the data is public from TFL. Nice.HFT? Algotrading? How passe.Algo mass transit is obviously where its at!

Thanks all for the reply, especially bearish and Dominic. I'm by no mean to speak quanty (or cocky) by stating the numbers, but it just seems to be that the US MS ususally are linked to the phd programme while the UK ones can usually be viewed as an independent course, unless it's MRes. Please point me out if I'm wrong @Dominic: May I ask form some insider's point of view, how is the industry evolving overtime? Are the MFE students overly supplied? Do the markets (as in banks/HF) still like academic phd from Physics or Maths etc like many years ago, I'm just curious. What departments can Stat fit in the best? My apologies if I know too little to ask any valuable question. Any help will be much appreciated!

Thanks all for the reply, especially bearish and Dominic. I'm by no mean to speak quanty (or cocky) by stating the numbers, but it just seems to be that the US MS ususally are linked to the phd programme while the UK ones can usually be viewed as an independent course, unless it's MRes. Please point me out if I'm wrong @Dominic: May I ask form some insider's point of view, how is the industry evolving overtime? Are the MFE students overly supplied? Do the markets (as in banks/HF) still like academic phd from Physics or Maths etc like many years ago, I'm just curious. What departments can Stat fit in the best? My apologies if I know too little to ask any valuable question. Any help will be much appreciated!

originally posted by: Jonathan2Thanks all for the reply, especially bearish and Dominic. I'm by no mean to speak quanty (or cocky) by stating the numbers, but it just seems to be that the US MS ususally are linked to the phd programme while the UK ones can usually be viewed as an independent course, unless it's MRes. Please point me out if I'm wrong @Dominic: May I ask form some insider's point of view, how is the industry evolving overtime? Are the MFE students overly supplied? Do the markets (as in banks/HF) still like academic phd from Physics or Maths etc like many years ago, I'm just curious. What departments can Stat fit in the best? My apologies if I know too little to ask any valuable question. Any help will be much appreciated!I'm not fully versed on the quant market and apologise for jumping in ahead of others with more grasp of the market but the impression I get is the market is oversupplied. On another forum one user described that the situation is such that even if we had the same jobs market as we had 10 years ago it would still be very tough to get work. Also MFE is very specialised - get a 1st in that and outside of quantitative work you'll have trouble, even stuff like software development.Dominic's point about using what you've learnt is valuable - it's the thinking that's important. A lot of people can solve equations beyond my comprehension but still not don't see the link between quant thought and real life. Eg the higher the reward the higher the risk (up to a point) - this is understood with stocks, yet loads of people I've met fail to see the link between salaries and risk, naively thinking £70k pa is the same job as a £35k pa job. It's not like physics where you're on top of a process like Brownian motion and can predict easily - imagine being asked to price and trade and an option on the time it takes the N137 to get home on a bank holiday Sunday night and you get what I mean.Another classic case is modeling and current outlook - one change in your market and all that maths, stochastic etc goes out the window and hedging/contingencies are important. It's squeaky bum time then.Careers are the same - markets "doing brilliantly" means nothing and can suddenly change. I explained this a while back to someone contemplating MFE in 2006 and their snotty remark was "but markets are booming". Thing is they may have been right that markets were booming, but my point still stands (it didn't impress them when I explained this and that they'd better look up the definition of the word "but"). Also even if the credit crunch hadn't happened my point still would stand - markets always go down at some point.

QuoteOriginally posted by: liamoriginally posted by: Jonathan2Thanks all for the reply, especially bearish and Dominic. I'm by no mean to speak quanty (or cocky) by stating the numbers, but it just seems to be that the US MS ususally are linked to the phd programme while the UK ones can usually be viewed as an independent course, unless it's MRes. Please point me out if I'm wrong @Dominic: May I ask form some insider's point of view, how is the industry evolving overtime? Are the MFE students overly supplied? Do the markets (as in banks/HF) still like academic phd from Physics or Maths etc like many years ago, I'm just curious. What departments can Stat fit in the best? My apologies if I know too little to ask any valuable question. Any help will be much appreciated!I'm not fully versed on the quant market and apologise for jumping in ahead of others with more grasp of the market but the impression I get is the market is oversupplied. On another forum one user described that the situation is such that even if we had the same jobs market as we had 10 years ago it would still be very tough to get work. Also MFE is very specialised - get a 1st in that and outside of quantitative work you'll have trouble, even stuff like software development.Dominic's point about using what you've learnt is valuable - it's the thinking that's important. A lot of people can solve equations beyond my comprehension but still not don't see the link between quant thought and real life. Eg the higher the reward the higher the risk (up to a point) - this is understood with stocks, yet loads of people I've met fail to see the link between salaries and risk, naively thinking £70k pa is the same job as a £35k pa job. It's not like physics where you're on top of a process like Brownian motion and can predict easily - imagine being asked to price and trade and an option on the time it takes the N137 to get home on a bank holiday Sunday night and you get what I mean.Another classic case is modeling and current outlook - one change in your market and all that maths, stochastic etc goes out the window and hedging/contingencies are important. It's squeaky bum time then.Careers are the same - markets "doing brilliantly" means nothing and can suddenly change. I explained this a while back to someone contemplating MFE in 2006 and their snotty remark was "but markets are booming". Thing is they may have been right that markets were booming, but my point still stands (it didn't impress them when I explained this and that they'd better look up the definition of the word "but"). Also even if the credit crunch hadn't happened my point still would stand - markets always go down at some point.Its true about the risk reward profile of jobs. However to extend the analogy... low risk (vol) in a job is not necessarily good. For exactly this reason many jobs are 'value traps'.

IMHO low salary jobs are not necessarily much safer than high salary jobs, and higher paid jobs make it easier to build up savings and also (because they're perceived as "better") make it easier to find another well-paying job in the event they'll let you go. So if you optimize mostly for the salary, you're better off if you try naively to balance earnings vs risk. No job is safe in the City now, unless you're well-connected (in which case you don't need to get any advice from strangers on the internet).

dupe

Interesting, on top of the salary vs risk relationship, I'd also like stress the popularity vs competition in banking. Many graduates only know about ibank and consider as the first priority because of city tale they've heard in the past and advertisement by media of the bonus of bank on top. I'm amazed to see in the firm I'm working at, they've been trying to hire programmer but failed to, at first offering 50K/a and then raised to 70K/a, which is the same as some ibank salary level. But still it in the end spent about 3months to get someone on board, the guy is from BNP Paribas IT, he's retire age man from BNP IT. So it seems to me salary is not the only attractiveness in bank. Including also networking and other learning experience like katastrofa has pointed out.From the fresh grad pov, not only in MFE, across a lot of departments just have their candidates overly supply, candidates are just treated as one of the many nobody amongst the pile of incredibly fabulous looking CV, not to mention the queue in another pool of those that have direct family or business connection with the bank. It just feels to me as a candidate, we are made redundant, and as I don't think this is something health, it sometimes makes me lost. ;/