From 571e4a112397f968ba0cc14d1c755be1ce62d194 Mon Sep 17 00:00:00 2001 From: Nuno Sempere Date: Mon, 29 Jun 2020 21:25:59 +0200 Subject: [PATCH] Daily grind --- ea/ForecastingNewsletter/June2020.md | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/ea/ForecastingNewsletter/June2020.md b/ea/ForecastingNewsletter/June2020.md index 63b48ca..35a5cee 100644 --- a/ea/ForecastingNewsletter/June2020.md +++ b/ea/ForecastingNewsletter/June2020.md @@ -73,6 +73,7 @@ Ordered in subjective order of importance: - Youyang Gu's model, widely acclaimed as one of the best coronavirus models for the US, produces 95% confidence intervals which [seem too narrow](https://twitter.com/LinchZhang/status/1270443040860106753) when extended to [Pakistan](https://covid19-projections.com/pakistan). +- Some discussion on [twitter](https://twitter.com/vidur_kapur/status/1269749592867905537): "Only a fool would put a probability on whether the EU and the UK will agree a trade deal", says Financial Times correspondent, and other examples. ## Hard to categorize. @@ -132,6 +133,9 @@ Ordered in subjective order of importance: - Opinion: I'm not sure whether their results are going to be useful for things I'm interested in (like human forecasting tournaments, rather than Kaggle data analysis competitions). In practice, what I might do if I wanted to incentivize precision is to ask myself if this is a question where the answer is going to be closer to 50%, or closer to either of 0% or 100%, and then use either the Brier or the logarithmic scoring rules. That is, I don't want to minimize an l-norm of the error over [0,1], I want to minimize an l-norm over the region I think the answer is going to be in, and the paper falls short of addressing that. +- [How Innovation Works—A Review](https://quillette.com/2020/05/29/how-innovation-works-a-review/). The following quote stood out for me: + > Ridley points out that there have always been opponents of innovation. Such people often have an interest in maintaining the status quo but justify their objections with reference to the precautionary principle. + - [A list of prediction markets](https://docs.google.com/spreadsheets/d/1XB1GHfizNtVYTOAD_uOyBLEyl_EV7hVtDYDXLQwgT7k/edit#gid=0), and their fates, maintained by Jacob Laguerros. Like most startups, most prediction markets fail. Note to the future: All links are added automatically to the Internet Archive. In case of link rot, go [here](https://archive.org/)