If you think of going on the “offensive”, then be mentally prepared for pain and unsuccessful investment with disappointing ROTI
Opening example — I had 3M of fixation on tibrv^JMS. Just look at my blogposts. I go beyond interview topics. This fixation hopefully shines through on interviews.
Ken Li (Citi-muni) was probably a sharp observer of my personality and once said “If you are interested in software development then you will have a long career till retirement … no need to worry. A lot of developers lack that interest.”
Very few candidates had more than 3M personal spare time engaged in any tech topic.. Something like a deep dive. (Even fewer can sustain 12M focus.) Consider XR’s interest in machine learning. Consider grandpa.
Apparently, many interviewers are personally interested in these same details (the whys/hows/whats) so they seek out like-minded enthusiasts. This is one hypothetical explanation why those crazy theoretical QQ questions come up so often.
Other examples of personal fixation that (hopefully) shine through
- sockets — blocking operations …; unplugged
- clustered index
- timer hardware interrupts
- userland vs kernel mode
- nested classes across languages
- compiler rules on overriding
Now, many of the weeks spent has low ROTI but I was not fixated on ROTI since my earliest engaging studies in 1998 — first deep dive in unix + C programming + perl. As it turned out
- unix and linux became dominant on server side and enhanced my career
- perl became m entry point into programming career
- C domain was hopeless, but with c++ I was able to capitalize on it
Still, many of my engaging studies had low ROTI, but what if I didn’t capture my interest? I think I would end up wasting my spare energy!
Striking balance — too much “engaging” –> regretful ROTI; too little “engaging” –> bored and unfulfilled.
Like assembly programming, I thought the “hard” (hardware-friendly) languages were giving way to easier, “productivity” languages in the Internet era. Who would care about a few microsec? Wrong…. The harder languages still dominate high-end jobs.
* An electronics engineering graduate stuck in a small, unsuccessful wafer fab
* An uneducated pretty girl unable to speak well, dress well.
Today (2017) my resume features java/c++/py + algo trading, quant, latency … and I have some accumulated insight on core c++/c#, SQL, sockets, connectivity, ..
 See also fear@large codebase
 To my surprise, some of these lighter technologies became enterprise —
- http intranet apps
I wanted c++ ROTI. After so many years of trial and error, I got two
- G3  The CVA $122/hr offer
- G3  SCB-FM S$210k offer, unthinkable in my Singapore job search.
- In terms of base, This one is about $$190k. My “reasonable” target was S$150k and my “high” target was $170k.
- G5  SIG technical win
- G5  BNP forex prop trading contract offer
-  MLP-sg java connectivity team actually has a small c++ requirement.
- G9 overcame fear@large codebase]c++/j and emerged above most developers.
I often feel bad that all of my efforts in my spare time had no tangible ROTI, but look around, who fared better?
Note this post is more about peer comparison (recrec blog), less about my spare time usage (open blog)
For the record my spare time effort did produce some tangible outcomes
- coding drill in github and wordpress. I think most of my friends didn’t bother to record. Their practice is short-term.
- yoga, jogging
- blogging on housing (and school districts) — our real needs. The time spent convinced me to live in Bayonne
- blogging on personal investment — complex. The time spent directly affected my investment decisions
- blogging, discussion on boy. The time spent directly influenced my views, decisions and communications with family members
- helping friends (Deepak,Ashish,YH) with job hunting
- helping my kids with sports, piano, renzi
- –less tangible:
- studying risk systems, data science, crypto-currency? Helps way-finding and navigating the job market
fixation@ROTI/payoff/success/result/accu … dampens job satisfaction+joy@learning.
This affects my “engagement”. Granted, we should not Ignore these ROTI factors, or those “smells” … instead we should evaluate our direction and take stock, but let’s not overdo it.
- +ve Eg: Barcap option math
- +ve Eg: Barcap swing learning
- +ve Eg: RTS socket programming
- -ve Eg: git
- -ve Eg: curve building
- -ve Eg: WCF
Consider a tour guide aiming for the tip at the end.
Consider Grandpa in his research career.
Consider a singer like 王杰 or the last few years of 邓丽君。
Consider Einstein’s violin
Q: has that increased your income or benchmark score? # more time in office, shorter commute, MSFM, c# ….
- This question can be posed to grandpa.
- This question can be posed to any education institute including the “top schools 名校”. Ironically the same questioners seem to be /fixated/ on these top schools for their kids. So for these people, this question is self-contradictory.
- This question can be posed to my friends engaged in quantitative investment analysis.
This question is harmful, misleading, derogatory, discriminatory, browbeating, pessimistic/fatalistic, myopic, … This question tosses aside many important things to our lives, our joys, and satisfaction —
- career safety net
- exploration of personal talents and personal interests
- “in-demand” satisfaction
- market depth
- mobility between firms
- freedom — I don’t want to feel “trapped”
- observation (even conviction) on various topics, based on in-depth personal research
Note this effort is after my basic bond math study, though I often count this effort as part of the broader “bond math” study.
Basic bond-math knowledge has robust demand on Wall St. Without hard evidence I feel ROTI is decent in basic bond math study. Q1: How is the ROTI in this study?
I feel many of the jargon terms in this space are common and essential knowledge:)
- swap rate; comparative advantage;
- OIS; Libor;
- basis risk;
- curve building
However, this self-study rarely helped me:
- MSFM course
- Stirt job interview
Q1b: How is the market depth and robust demand of this skill?
A: not used much in the trading buy-side, but some asset management and most sell-side do need this know-how.
Note this topic is generally math-lite and much simpler than option math, so I was able to self-study:) See fixation@ROTI…dampens job satisfaction+joy@learning
Q2: how is the knowledge retention rate?
A2: decent. Thin->thick yes but not yet thick->thin
I already give up several “investments”. If I take a java job, I would again forgo so many years of investment in c++. Now after I got more c++ offers, I feel /triumphant/vindicative/.
|swing||py||c#||quant 2010~13||quant af 2013||c/c++||(Zoom out …)|
|up to USD20k/Y pretax||opportunity cost|
|6M||2Y since barc||2Y||1Y||3Y||6Y since 1998||nominal effort|
|3M||4M||1Y||6M||2.5Y||4Y||serious effort incl. STS|
|3M||2M||1M||2M||2Y||2Y||spare time sacrificed(STS)|
|-2||-3||-6||-5 #more than py||-15||-16||points invested|
|Barx||passed some IVs||OC, Bbg, Reuters||95G/OC||Stirt/Mac/CVA||~18 offers||job “offers”|
|Trex,bbg..||DRW; Nomura; Mako; Trex; Pimco analytics||too many||help interviews|
|helps my WPF xx||value@algo IV||deepens java nlg||brain teasers; math cfd; contrarian insight into bigData/quantTrading;||see y re-enter c++||other ROTI|
|3 #built real
|more than invested||9 #50%+||more than invested||points SCORED|
|no loss?||no loss||-3||no loss||-7||no loss||net points lost|
Take a long, hard look back at my past career decisions.
When I next return to SG, Perhaps it’s time to stop tryingSomethingNew and stop paying the costs. (In the U.S. I still can afford to try…)
Note the ROTI yardstick I’m using to measure the effort are harsh and arguably unfair. See ##in hind sight: trySomethingNew
Update — Is the xx fortified with job IV success? Yes to some extent.
Background – my learning capacity is NOT unlimited. In terms of QQ and ZZ (see post on tough topics with low leverage), many technical subjects require substantial amount of /laser energy/, not a few weeks of cram — remember FIX, tibrv and focus+engagement2dive into a tech topic#Ashish. With limited resources, we have to economize and plan long term with vision, instead of shooting in all directions.
Actually, at the time, c#+java was a common combination, and FIX, tibrv … were all considered orgro to some extent.
Example – my time spent on XAML now looks not organic growth, so the effort is likely wasted. So is Swing…
However, on the other extreme, staying in my familiar zone of java/SQL/perl/Linux is not strategic. I feel stagnant and left behind by those who branch out (see https://bintanvictor.wordpress.com/2017/02/22/skill-deependiversifystack-up/). More seriously, I feel my GTD capabilities are possibly reducing as I age, so I feel a need to find new “cheese station”.
My Initial learning curves were steeper and exciting — cpp, c#, SQL.
Since 2008, this has felt like a fundamental balancing act in my career.
Unlike most of my peers, I enjoy (rather than hate) learning new things. My learning capacity is 7/10 or 8/10 but I don’t enjoy staying in one area too long.
How about data science? I feel it’s kind of organic based on my pricing knowledge and math training. Also it could become a research/teaching career.
I have a habit of “touch and go”. Perhaps more appropriately, “touch, deep dive and go”. I deep dived on 10 to 20 topic and decided to move on: (ranked by significance)
- linux kernel
- classic algorithms for IV #2D/recur
- bond math, forex
- black Scholes and option dnlg
- c#, WCF
- Excel, VBA
- in-mem DB #gemfire
- functional programming
- java threading and java core language
- SQL joins and tuning, stored proc
Following such a habit I could spread out too thin.
These java features are powerful and practical at work, but seldom asked in IV, so ROTI is lower during job hunting.
annotations for code generation
2000 – 2002 are the first few years I spent in IT and had a deep impact on my outlook. However, there are many overstatements:
- Too early to say — perl was widely used on Wall St and was a key factor to my survival in GS.
- SQL — skills I acquired in GS is not completely irrelevant. Many (financial etc) systems still use it. Perhaps less used on west coast in web 2.0 shops.
- php — investment was not 100% lost. It did provide me a job at NBC. I think this is still a valuable skill on west coast. My php confidence is an asset.
- mysql — investment was not completely lost. I would say my mysql experience gave me enough confidence and competence to take on other database systems.
- apache — investment gave me valuable insight into network servers. I think apache is still widely used outside Wall St.
- weblogic — investment was 90% lost but luckily I didn’t invest too much
background: My laser (and time) is a scarce resource. Need to economize it and prioritize.
Upshot — Perhaps algo practice has higher ROTI than quant xx…
Both are seldom needed on the job but valuable to IV. Which one is more valuable? See post on algo IV for bbg
Most of Quant math is too hard to self-study, though the probability quizzes are manageable.
Context — learning a new software language, API, entire server (OS, DB..) or toolkit, with non-trivial concepts embedded therein.
The more common pattern is the learning curve. Initial gradient is often higher as pick up speed. After 6 months (or 1, or 12..) it flattens and tapers off and you experience diminishing returns.
A 2nd pattern is “gaining traction” . For the first 4 weeks (or 1 or 20..), you spend a lot of time reading and experimenting but without growing confidence…
- after a while, you start to connect the dots via thick->thin, often in a series of incremental breakthroughs.
- thick -> thin is not merely (superficial) accumulation of knowledge
- you often need perseverance and sustained focus. See focus+engagement2dive into a tech topic#Ashish
- knowledge gap build-up above the new entrants
- high ROTI
- high retention rate
- gaining-traction is opposite of wheel-spinning
I experienced and overcame this wheel-spinning process in ..
– C++, – java, c#
– JMS, RV
– drv pricing
A related pattern is engagement