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Thursday, April 28, 2016

The Physics of Wall Street / James Owen Weatherall

A comprehensive history / story of quants, scientists, and engineers which includes the concepts of return distributions (standard normal vs fat tails), self-organization / herding effects in bubbles and bursts, and so forth.

All (financial) models are destined to fail in a certain point because of false assumptions and/or unconsidered factors (e.g., black swans). Like natural scientific approaches, we have to learn from failures, get it tested again, and improve the models.

Financial models are not for pursuit of truth that can solve any problems under any conditions. Rather, finding formulae that work under several conditions and clarifying how / when to be used. That is more realistic and practical goal because global economy, regulations/rules, and people's behaviour are always changing. (e.g., innovation) Financial models themselves are not only monitoring cameras but also engines that move markets.

The Physics of Wall Street / James Owen Weatherill
amazon.com
amazon.co.jp

Deep Learning (Regression, Multiple Features/Explanatory Variables, Supervised Learning): Impelementation and Showing Biases and Weights

Deep Learning (Regression, Multiple Features/Explanatory Variables, Supervised Learning): Impelementation and Showing Biases and Weights ...