Measuring timely high-resolution socioeconomic outcomes is critical for policy making and evaluation, but hard to reliably obtain. With the help of machine learning and cheaply available data such as social media and nightlight, it is now possible to predict such indices in fine granularity....

The study area is focused on the Philippine Trench, a hadal trench located in the axe of the collision of the Philippine Sea Plate and Sunda Plate, west Pacific Ocean. The research is aimed at the analysis of the trench geomorphology by a correlation between changes in slope steepness and...

GLOBAL FINANCE LIQUIDITY RISK REVISITED: Development of A Framework for Liquidity Assessment in Portfolio Construction Process: Presentations to the JP Morgan Global Head of Quant Research & Analytics and US Head of Portfolio Construction Teams:Presentations To: JP Morgan Global Head of Quant...

GLOBAL FINANCE LIQUIDITY RISK REVISITED: JP Morgan Alternative Assets Portfolio Liquidity Assessment Framework & Models: $500 Billion Fund of Funds: 17 Asset ClassesPresentations atJP Morgan World HQ, 270 Park Ave, Manhattan, NY, USAToJP Morgan Global Head of Quant Research & Analytics, JP...

Structured additive regression (STAR) models are a rich class of regression models that include the generalized linear model (GLM) and the generalized additive model (GAM). STAR models can be fitted by Bayesian approaches, component-wise gradient boosting, penalized least-squares, and deep...

Democratization of the mysterious art of data science via Amazon Web Services, Google Cloud Platform, Microsoft Azure, and other machine learning (ML) service providers might make it too easy to apply ML. To underline this we present a worked-out example in R (including sources in the appendix),...

This research aims to specify critical urban sustainability issues by mining unstructured text data derived from the C40 city datasets of the Carbon Disclosure Project. The current study identifies underlying topical issues exhibited by text corpora, enables creation of smarter data...

We present a new type of unsupervised learning problem in which we find a small set of representative regions that approximates a larger dataset. These regions may be presented to a practitioner along with additional information in order to help the practitioner explore the data set. An...

We present a way to compute additive marginal contributions for the six capital measures forming the capital computation under the new Basel III market risk regime, commonly named “Fundamental Review of the Trading Book regime” (FRTB). Marginal contributions are most useful for the...

We present a worked out example in R (including sources in the appendix), where deep learning falls behind much simpler methods. It is an already published application of a LeNet style convolutional neural network (CNN) for image recognition. We show that this complex CNN is outperformed by a...