Main And Wall

are never going to love each other? (from am article in Time magazine, November 9, 2009). Meaning Main Street and Wall Street, synonymous for real economy and financial markets.

IMO, they are tightly bound to each other since we have instruments as media for asynchronous economic transactions: when Main has an idea but no liquidity or Main has liquidity but no idea, Wall shall have an answer.

Both interplay in good balance if their innovativeness balances well?

It is not so few saying: quantitative finance has cultured artificial complexity and this complexity has to be factorized out of the system. I agree. There is noise (uncertainty) output from certain models and methods.

If models have too many factors, parameters distribute randomly, if you tried to optimize the objective functions, or you get lost in the numerical jungle of PDE solving. If you are not able to manage the inverse problems of calibration correctly, you inherit oscillations from small noise.

Yes, try to keep it simple (Leonardo da Vinci: Simplification is the real sophistication).

But simplifying properly, needs in-depth insight and knowledge why the complex fails. See

When Good ENUF is Great .

Andreas Binder has now designed a seminar series to give full explanation on the details, fruit of challenging research and practical experience. Structured in modules and sections, covering models-and-underlyings, instruments-and-case-studies, numerical-schemes, Montecarlo-and-Longstaff-Schwartz, calibration, the seminar is outlined for a total of 15 days, to be scheduled and configured individually.

Good simplification is intellectually challenging. In Main and in Wall.