FRM part I review (May 2017, Singapore)

Finally, after weeks of intensive study of financial concepts from a non-finance major undergraduate, I managed to get through this. Why FRM, not CFA? If you take a look at the FRM 2017 learning objectives, you will realise that GARP does not make reference to books from CFA (the exam provider herself) but references authors who are able to explain in clear details with examples on challenging financial concepts. FRM learning objectives, I would say, lean towards ALM (asset liability management), debts, counterparties and collateral/margin/leverage concepts.

As I am moving on to FRM part II, another topic would be more interesting to buy side analyst with a craze on how to generate alpha. Expected returns written by Antti Ilmanen does a detailed breakdown of a few important factors that are more relevant, or so far had a track record in the past.

**Note: we only need these factors to outperform a couple of times (for testing of consistency of outperformance) so that we are able to identify the underlying business conditions and monetary, fiscal regime to know when will they outperform their “benchmark” (subjective) the next time… In other words, if the strategy shows to outperform in year 1,3,11,14 out of last 20 years, and overall the backtesting P/L curve is pointing to the downside, its alright as no one strategy can outperform throughout all weather or regimes. Its called smart beta investing, in a nugget, being able to identify upcoming change in regime and recognise which factors, and hence tactical asset (bundle of overlapping risk exposure) allocation, will be positioned to outperform the “benchmark”.

  • Factors or risk premium (spreads) are usually reference to the spread of returns from the highest and lowest ranking synthetic portfolio (great if there is a ETF that tracks it for a low cost, otherwise, there might be basis risk with proxies) ranked on forward looking indicators (synthetically make one if its not implied volatility from options, which always implicitly include short-volatility premium so that it becomes higher than realised volatility… e.g. lagged beta/momentum/yield against future returns). Why spreads, not directional exposure? Because its a premium! Because it neutralise all other commonalities between High and Low earnings yield such as market exposure.. but what if it happens to be the case where Low earnings yields are coupled with low beta, and R ~ B1(High yield – Low Yield) + B2(Low Beta – High Beta) is both factors are netting each other such that B1 and B2 and underestimated? Multidimensional slicing might be needed to really control the spread to be representative of true premium for yields

Definition of tactical

  1. 1:  of or relating to combat tactics: such asa (1) :  of or occurring at the battlefront a tactical defense a tactical first strike (2) :  using or being weapons or forces employed at the battlefront tactical missilesb of an air force :  of, relating to, or designed for air attack in close support of friendly ground forces

  2. 2a :  of or relating to tactics: such as (1) :  of or relating to small-scale actions serving a larger purpose (2) :  made or carried out with only a limited or immediate end in view b :  adroit in planning or maneuvering to accomplish a purpose

  • To be tactical, we must be able to identify the next regime or factors that will outperform so that we can re-position our asset allocation (or risk exposure)… How to do that? Some posts from CAIA’s allaboutalpha wrote on smart beta here. Key concepts are: Does regimes have a cycle that’s influenced by business cycles? Or in a data driven approach, what is the future underlying condition we are shifting towards and when did it last happen in history and which asset exposures outperform? Maybe MDE might fill in this gap…

 

Back to FRM part I review, after digressing…….

Wrote a review of how I felt after taking the exams here..  I reposted them below…

Just completed part 1, its challenging in terms of completing all 100 qns within 4 hours, where each qns are done with clear confidence and working e.g. 2qns on 2-steps bionomial American & European option valuation

Did guessed for a few questions which :(

GARP did a very goob job spreading out all the questions throughout all reading materials ! Reflected the proportion of marks allocation well! Thumbs up!

Saw questions from new topics such as:
– insurance benefit and contribution plans, breakeven premium.. on top of SMM CPR from MBS
– bank optimal risk appetite (BK 1: FRBNY Economic Policy Review) where it depends on business model i.e. AAA- better than AAA
– no qns on exotic options, besides tricky qns on convertibility of callable bonds (sample paper 2017 has ki + ko = regular)
– stress testing scenarios: what can a CRO recommend within his job scope and responsibility? which methods in stress testing are most appropriate when almost all looks like one :( along with ERM
(actually, if I recall correctly, many new questions from stress testing)

My view on the type of qns:
– very fundamental where concepts are broken in building blocks and pieced together in ways that’s novel and test your concepts thoroughly… e.g. rates relationship with putable bonds (put + bond), put call parity options on bond
– tricky qns/or those that i though were challenging:
1) Fermi “guestimate” qns missing some input which requires guessing…
e.g. given par, guess spot, which is + few bp higher than par
2) Compounding/Discounting kind…
e.g. forwards is PV of FV of strike vs. futures is FV underlying, forwards, futures DV01, Beta hedging
e.g. replication of bond’s cashflow for same TTM (3 Yr) bonds but different coupon (given 5% coupon, find mkt value of 3% coupon)
3) Hedging kind…
e.g. A-L qns with multiple currency exposure and appropriate rates hedging, of course, be mindful of which curr the company is receiving and what curr is asked for in the answer
4) FX scenario qns…
e.g. hedge with forward 1y1y, and given 1y spot and forward 2y1y, which numbers spot or forward to use…
5) volatility term structure where current instantaneous vol is higher than long term variance, so would a contango changed towards backwardation as VIX mean reverts to long term variance? Or remain contango, or flatten, or become a hump/butterfly? (
6) cost of carry: storage cost given in absolute term than yield
7) bank capital requirement: unexpected loss rather than unexpected loss volatility formula….
8) is barbell or bullet YTM higher or lower given rexpective bonds duration, yield, coupon, term
9) CCP: objective T/F qns on mechanics…
10) FRA valuation: (float – fixed rate) x (time…) x Notional
11) regression: finding beta coefficient and intercept from SSE, SSR?
12) probability: conditional…
13) GARCH correlation forecasting (not volatility.. so covariance (r1 x r2))… tricky with qns like correlation is wrong and updated so what happens to beta? Eh, proportional in CAPM except risk-free rate is there? And, assumptions of MA invertibility, wold’s theorem, AR stationary cov…
14) CAPM: quite a few questions on finding highest sharpe ratio possible.. and assumptions like can stocks be shorted? unlimited financing capital?
e.g. given 2 stocks, where one is negatively correlation but lower return, and the other has higher return but zero correlation
16) appropriate statistics for testing: excess kurtosis vs kurtosis
17) calculating PD and need formula of poisson pdf given average rate
18) many tricky questions on volatility vs variance scaling and scaling on standard deviation.. same for continuously compounding on forward rates derivation from par/spot/d(t)
e.g. VaR confidence interval: given 1 day 99% VaR, whats 20 days 98% VaR?
19) gamma-vega-delta hedging.. need to inverse gamma-vega matrix and solve for inverse to know number of underlying shares (gamma, vega=0) to hedge last free variable delta
20) country risk with credit rating and GARP COC
21) Didn’t encounter any CTD bonds, nor AI/dirty/clean price… Swaps were simply comparative adavantage.. no loss valuation on default midway OTC swap exposure
22) Not much on duration or convexity… But there were qns on multi-factor hedging where tricky part is using T-bond to hedge zero-coupon bonds (rather than the other way) and residual lower term rate exposure are hedged with a mismatched 2 yr for 5 yr.. so expecting overhedge with 30yr, and 5 yr to offset 2yr rate exposure…

Many more which I cannot really remember… Till now, i cannot give myself a confidence interval of how many qns I answered right

Many tricky qns… but also many simple, give away qns (duration, convexity, financial disaster (barring, metallgesellchaft), multifactor shocks)

I think I failed because many calculated answers didn’t tally :(:(
Its challenging (time constraint is a big challenge!!! so if you think a qns would take a long time, skipped it! But you cannot skip all! :(:(

 

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