The scope is professional life and financial security.
update — to keep the killer sharp, you need sustained focus and continuous improvement.
eg: my dad is a top researcher in his fields. His research papers are heavy weight and top quality. Someone like him may have many limited skills on many other aspects (tech) but that one killer talent compensates for everything. Crucially, his research output has a financial reward. Otherwise it’s hard to sustain the effort.
eg: sales dragons are simply good at hitting sales numbers. A sales dragon may not understand the products, or remain loyal to the firm, or take care of the clients… Still this is a killer talent to keep her successful, that (kind of) compensates for everything.
eg: I know many IT professionals who are sub-standard technically, but can survive or even thrive in a job for a long time because they keep the boss happy — Killer talent… However, compared to other killer talents this one isn’t as weather-proof as other killer talents. The next boss may not be so easy to please. The company may go under…
eg: at least in my first 10 years of my career, I always could get my jobs done. I was always technically up to the job. This talent did compensates for everything.
eg: On Wall St, my job hunting skill is a killer talent. This is one of the most effective kill talents known to me.
eg: Some people manage to amass a small fortune and invest successfully, to get a decent return (like $5k/m). I guess Anthony Lin, Lian Zhong, Chun Tih .. all had multiple properties.
There are many ways to derive the BS-E(quation). See [[Crack]]. Roger Lee covered at least two routes.
There are many ways to derive the BS-F(ormula). See P116 [[Crack]]
There are many ways to interpret the BS-F. Roger Lee and [[Crack]] covered them extensively.
Q: BS-F is a solution to the BS-E, but is BS-F based on BS-E?
A: I would say yes, though some BS-F derivations don’t use any PDE (BS-E is PDE) at all.
BS-E is simpler than BS-F IMO. The math operations in the BS-F are non-trivial and not so intuitive.
BS-F only covers European calls and puts.
BS-E covers American and more complex options. See P74 [[Crack]]
BS-E has slightly fewer assumptions:
– Stock is assumed GBM
– no assumption about boundary condition. Can be American or exotic options. – constant vol?
I asked a relatively young quant I respect.
She said most sell side models do not have jump feature. The most advanced models tend to be stochastic vol. A simpler model is the local vol model.
I said the Poisson jump model is well-regarded – but she said it’s not that mature.
I said the Poisson jump model is needed since a stock price often exhibits jumps – but her answer gave me the impression that a model without this “indispensable” feature can be good enough in practice.
When you actually put the jump model into practice, it may not work better than a no-jump model. This is reality vs theory.
It’s kinda hard to measure 2 developers’ output. Given my background within my past teams, I now feel I did reasonably well on GTD, not super productive or super slow.
In OC, I took care of Guardian, Quest, Excel interface, Bloomberg and other part of GMDS. I helped out on GMDS testing a few times. I wrote the web-based log viewer in WCF….
In 95Green and Barcap my GTD was not much higher, but the value of my output was higher than team peers.
I feel in most major economies the central bank manages interest rate which directly affects FX rate. FX rate doesn't affect interest rate, not directly.
http://www.investopedia.com/articles/basics/04/050704.asp — higher interest rates attract foreign capital and cause the currency to appreciate.
http://www.economicshelp.org/macroeconomics/exchangerate/factors-influencing/ — Higher interest rates cause an appreciation.
http://fxtrade.oanda.com/learn/top-5-factors-that-affect-exchange-rates – When interest rates go up, so do yields for assets denominated in that currency; this leads to increased demand by investors and causes an increase in the value of the currency in question.
Rate hike leads to inflation, which hurts the currency in question?
Rate hike hurts corporations (including exporters) and balance of payment. Would hurt the currency in question? I doubt it.
Fed rate hike is carefully managed based on growth data. Therefore, rate hike is conditional on US recovery, which means stronger USD.
Economic growth could also mean reduced government bond issue i.e. reduced QE, i.e. slower national debt growth which helps the USD.
[[Numerical methods and optimization in finance]] has simple examples
of a PDE numerical solver. This book is more in-depth than [[basic
I think the Daniel Duffy book also covers Finite Difference method
Brute-force — often there's no other solution (like mathematician
tackling a proof) to a PDE. Numerical solution is kinda versatile.
An Singapore ANZ telephone interviewer (Ivan?) 2011?) drilled me down — “just why is MOM more reliable than a blocking synchronous call without a middleware?” I feel this is a typical “insight” question, but by no means academic or theoretical. There are theories and (more importantly) there are empirical evidence. Here I will just talk about the theoretical explanations.
Capacity — MOM can hold a lot more pending requests than a synch service. A RMI or web server can have a limited queue. The TCP socket can hold requests in a queue, but all limited. In contrast, MOM queue can be on disk or in the broker host’s memory. Hundreds or possibly millions time higher capacity.
Burst of request can bring down an RMI system even if it is loaded lightly 99% of the time.
But what if the synch service has enough capacity so no caller needs to wait? I feel this is wishful thinking. For the same hardware capacity, MOM can support 10x or 100x more concurrent requests. For now, let’s assume capacity isn’t the issue.
Long-running — if some of the requests take a long time (like a few sec) to complete then we don’t want too many “on-going” tasks at the same time. They compete for CPU/memory/bandwidth and can reduce stability and reliability. Even logging can benefit from async MOM design.
But again let’s assume the requests take no time to complete.
ACID — Reliable MOM always persists messages before replying with a positive ACK.
In the US, at 65 you could work as a developer. (Actually that’s not the mainstream for most immigrant techies. What do they do? Should ask Ed? Anirudh? Liu Shuo, ZR…)
Why SG is different? Here’s my answer, echoing my earlier posts.
* US employers are more open to older techies
* US culture respects technologists. Main street techies get paid higher than SG main street techies
* high-end technical work – more comon to get in the US than SG, partly because wage premium is smaller, like 100k -> 140k
Many people are put off by the uncertainties and risks, and don’t see I the light at end of the tunnel
who move my cheese?