One of the first and most important questions we get from clients, forecasters, and consumers of our data is: “How accurate are these forecasts?”. In order to answer this question, we have utilized and built upon a widely accepted proper scoring rule, i.e. a way to measure accuracy for a probabilistic forecast.
Read post →
Joining a prediction market can be confusing and anxiety-inducing. It's easy to be overwhelmed by all the questions, to not understand the forecasting interface, or to have trouble forming opinions to base forecasts on. All of this is pretty natural--as a now-experienced forecaster, I can remember these feelings the first time I joined a prediction market. In this post I'll address a few specific emotional barriers that make it difficult to start forecasting.
Read post →
On a recent podcast, Jack Schultz and I discussed two razor companies that are poised to become unicorn companies. Unicorns--startups that grow to billion-dollar valuations while remaining private--are somewhat mysterious and the subject of continuous speculation.
Read post →
Wikipedia’s intro paragraph for prediction markets is the following:Prediction markets (also known as predictive markets, information markets, decision markets, idea futures, event derivatives, or virtual markets) are exchange-traded markets created for the purpose of trading the outcome of events.
Read post →
One use of prediction markets I've been really excited about is forecasting individual players' performances in major sports. These predictions are incredibly useful when playing fantasy sports--both daily fantasy and season-long leagues--and the forecasts that currently exist tend to be, in my experience, pretty mediocre. Prediction markets present an opportunity for the wisdom of the crowds to intervene, and will likely lead to more accurate forecasts.
Read post →
Two key take-aways from the emerging scandal surrounding Daily Fantasy sites: one, gambling data can be extremely valuable, and two: the only thing Americans love more than gambling is hating on gambling. Taken together, these findings illustrate why large-scale prediction markets present a path towards improving human knowledge in a wide range of topics.
Read post →
Amongst the leadership teams of the portfolio companies at any medium to large investment firm, there is an incredible amount of experience, wisdom, and perspective that is not collectively being taken advantage of.
Read post →
We recently started working with a Houston-based client in the Energy sector, who wanted to use a prediction market to help with internal operations, and to create greater transparency and communication within their company. We spent a couple months meeting with our client to learn about their business and objectives, and using test questions (e.g. asking about Houston sports teams) to help participants understand how prediction markets work. Our initial questions focused on specific operations
Read post →
Have you ever been tasked with driving a project you’ve felt was going nowhere? Maybe you were a project manager or project owner, coordinating a team that was working on something you felt wasn’t gaining traction within the organization.
Read post →
Basically, we want to find the base rate of similar events occurring, and then adjusting that percentage by taking into account the differences between this event and the similar ones.
Read post →
Holly Ramer has a piece up at the Washington Post about our work with the United States Holocaust Memorial Museum to identify risks of mass violence in different countries:
Read post →
In my last post analyzing my own forecasting history on Inkling Markets, I showed that I was consistently identifying long-shot bets that were more likely to pay off than their existing probability would suggest. In this post, I'll look at how my forecasts improve the accuracy of these markets, calculating how many the change in component Brier score within different percentiles.
Read post →
To analyze forecasts' accuracy, I looked specifically at forecasts that crossed percentile thresholds, and then examined how often the result being forecast actually occurred.
Read post →
We're developing some new tools to analyze forecasters' performance, biases, and ways to help them improve, and I've been digging into my own forecasting history on Inkling. I've focused on a set of 3,343 forecasts I've made in questions that use an LMSR algorithm and have already resolved. The first interesting finding is that most of my forecasts have been wrong.
Read post →
(You know, besides how to cheat...)The recent hack of Ashley Madison--a dating service marketed towards married people--revealed that almost no women were actively using the site. Rather, the site's almost entirely male userbase was paying to interact with non-existent, fake, or inactive female accounts.
Read post →
Prediction markets are generally very good at generating accurate forecasts, but a key secondary challenge is to determine which forecasters are contributing most to forecast accuracy. User scores are closely linked to their accuracy because the underlying market mechanism rewards users when they move a forecast closer to its actual result and penalizes them when they move the forecast away from the result.
Read post →
What is Crowdsourced Forecasting and Why is it the Best Forecasting Tool Around? Francis Galton was an English scientist who believed in the stupidity of the average human. Galton believed that, to have a healthy society, you needed to concentrate power in the select few who didn't fit that bill.
Read post →
On December 7 of last year, the Carolina Panthers were 3-8-1 and I spent about 1100 Inkles forecasting that they would make the playoffs. Even at long odds, this may seem like wasted Inkles--I'm pretty sure that a 3-8-1 had never gone on to make the playoffs. But there were a couple other important factors.
Read post →
As I've become more involved with prediction markets, I've grown increasingly frustrated with journalists who make predictions (aka pundits) without linking to prediction market questions. This is, in my opinion, lousy journalism, and insulting to readers.
Read post →
When my grandmother immigrated to the United States, she couldn't afford to call her family on the telephone. That was about 70 years ago. Today, I have a friend whose brother moved to Sri Lanka to become a Buddhist monk and literally lives in a cave. He and his family Skype. This is the power of the Internet--for a significant portion of the planet, it's now possible for any two people to communicate from anywhere, in real-time, basically for free.
Read post →
