article thumbnail

The trinity of errors in financial models: An introductory analysis using TensorFlow Probability

O'Reilly on Data

They trade the markets using quantitative models based on non-financial theories such as information theory, data science, and machine learning. Whether financial models are based on academic theories or empirical data mining strategies, they are all subject to the trinity of modeling errors explained below. Thompson, L.S.

Modeling 134
article thumbnail

Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

Risk and Robustness Our estimates $widehat{beta}$ of the "true'' coefficients $beta$ of our model (1) depend on the random data we observe in experiments, and they are therefore random or uncertain. Springer New York, 2006. [17] Controlling Risks under Different Loss Functions: The Compromise Decision Problem.

article thumbnail

Misleading Statistics Examples – Discover The Potential For Misuse of Statistics & Data In The Digital Age

datapine

Drinking tea increases diabetes by 50%, and baldness raises the cardiovascular disease risk up to 70%! Did we forget to mention the amount of sugar put in the tea or the fact that baldness and old age are related – just like cardiovascular disease risks and old age? 3) Data fishing. So, can statistics be manipulated?