some of my controversial decisions #YJL

Hi Junli,

You don’t need to reply. This is my periodic review of "everything in my life".

I have recently implemented a few controversial decisions about my career, investment, family..

(As an example, the biggest is moving back to U.S. alone and starting the green card process.)

I make major decisions carefully and slowly (unless decisiveness needed), but an observer may say I’m not a good decision maker and point out my track record. Actually I don’t remember anyone pointed them out, not even my family members. The person who point a finger at my "unwise" decisions is the "judge" in my head…

Here are some of those controversial decisions
* I will not give up Singapore citizenship, and I will retire in Singapore, relying on the Singapore government for my retirement. Singapore system is much more caring and efficient than China or U.S. systems.

* I plan to work till 70 or older. I will keep up my interview skills.

* I feel my relationship and communication skills are not my strengths so through a series of trials-and-errors I have decided to stick to a technical career.

* I have stayed away from most of the new technologies — javascript, mobile apps, big data, social media, noSQL, block-chain …

* I’m staying in Bayonne, planning to buy my first home here. The schools are just above average.

* I have always preferred home locations that doesn’t need a car.


Math+intelligence ] trading != high value-add

  • –Examples of math usage outside well-known quant domains (like VaR
  • Trade analytics, execution analytics systems ….Look at some past executions, and uses statistic tools to derive some empirical or parametric distribution.
  • Sell-side pre-trade analytics to evaluate a proposed trade….
  • Real-time risk analytics

Q: How much math? Not that much.

Q: Python? Possibly.

Q: Value-add? Questionable. That’s one reason why most companies don’t spend billions building such systems.

Q: Who would want to pay to use these systems? Few.

Is equities simpler than FICC@@

I agree that FICC products are more complex, even if we exclude derivatives

  • FI product valuations are sensitive to multiple factors such as yield curve, credit spread
  • FI products all have an expiry date
  • We often calculate a theoretical price since market price is often unavailable or illiquid.
  • I will omit other reasons, because I want to talk more (but not too much) about …

I see some complexities (mostly) specific to equities. Disclaimer — I have only a short few years of experience in this space. Some of the complexities here may not be complex in many systems but may be artificially, unnecessarily complex in one specific system. Your mileage may vary.

  • Many regulatory requirements, not all straightforward
  • Restrictions – Bloomberg publishes many types of restrictions for each stock
  • Short sale — Many rules and processes around short sale
  • Benchmarks, Execution algorithms and alphas. HFT is mostly on equities (+ some FX pairs)
  • Market impact – is a non-trivial topic for quants
  • Closing auctions and opening auctions
  • Market microstructure
  • Order books – are valuable, not easy to replicate, and change by the second
  • Many orders in a published order book get cancelled quickly. I think some highly liquid government bonds may have similar features
  • Many small rules about commission and exchange fees
  • Aggregate exposure — to a single stock… aggregation across accounts is a challenge mostly in equities since there are so many trades. You often lose track of your aggregate exposure.
  • Exchange connectivity
  • Order routing
  • Order management

hearsay c++IV: Cubist

Q: TCP connection close .. handshakes?

Q3: why is new() so slow?

Q3b: what if I used array-new but then regular delete?

Q: implement Fib calculation at compile time

Q: write code to extract names and floating point numbers from a free-form string (no constraints)