Bitcoin enters a breakout zone that historically has been followed by sustained explosive rallies. The Bitcoin Quantile Model ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of neural network quantile regression. The goal of a quantile regression problem is to predict a single numeric ...

Smithson With, a Bitcoin researcher, presented a new approach to predict Bitcoin’s cycle top price using a quantile regression model. In an X post, With explains that quantile regression ...

Existing studies on the relationship international trade and manufacturing employment often use a mean regression approach and focus mainly on developed countries. Few studies have applied a quantile ...

To mitigate this, past attempts explored nonparametric methods like quantile regression neural networks (QRNN) and their variants, designed to output quantiles reflecting value ranks in the ...

In this paper we propose a semi-parametric, parsimonious value-at-risk forecasting model based on quantile regression and readily available market prices of option contracts from the over-the-counter ...

One solution is to ditch the standard linear regression and replace it with quantile regression, which is less vulnerable to extreme data points. What’s the difference in these regressions?

The remainder of this paper is organized as follows. First, we provide details of the quantile regression model for right-censored data, the inference, and the goodness of fit. Next, we illustrate the ...