The shape of the graph will depend a lot on what questions you ask. So it’s hard to interpret many aspects of the graph without seeing the questions that it’s based on (or at least a representative subset of questions).
In particular, my recollection is that some GJP questions took the form “Will [event] happen by [date]?”, where the market closed around the same time as the date that was asked about. These sorts of questions essentially become different questions as time passes—a year before the date they are asking if the event will happen in a one-year-wide future time window, but a month before the date they are instead asking if the event either will happen in a one-month-wide future time window or if it has already happened in an eleven-months-wide past time window. People can give more and more confident answers as the event draws closer because it’s easier to know if the event happened in the past than it is to know if the event will happen in the future, regardless of whether predicting the near future is easier than predicting the far future.
For example, consider the question “an earthquake of at least such-and-such magnitude will happen in such-and-such region between October 16 2019 and October 15 2020”. If you know that the propensity for such earthquakes is that they have a probability p of happening each day on average, and you have no information that allows you to make different guesses about different times, then the math on this question is pretty straightforward. Your initial estimate will be that there’s a (1-p)^365 chance of No Qualifying Earthquake. Each day that passes with no qualifying earthquake happening, you’ll increase the probability you put on No Qualifying Earthquake by reducing the exponent by 1 (“I know that an earthquake didn’t happen yesterday, so now how likely is to happen over the next 364 days?”, etc.). And if a qualifying earthquake ever does happen then you’ll change your prediction to a 100% chance of earthquake in that window (0% chance of No Qualifying Earthquake). You’re able to predict the near future (e.g. probability of an earthquake on October 17 2019) and the distant future (e.g. probability of an earthquake on October 14 2020) equally well, but with this [event] by [date] formulation of the question it’ll look like you’re able to correctly get more and more confident as the date grows closer.
The shape of the graph will depend a lot on what questions you ask. So it’s hard to interpret many aspects of the graph without seeing the questions that it’s based on (or at least a representative subset of questions).
In particular, my recollection is that some GJP questions took the form “Will [event] happen by [date]?”, where the market closed around the same time as the date that was asked about. These sorts of questions essentially become different questions as time passes—a year before the date they are asking if the event will happen in a one-year-wide future time window, but a month before the date they are instead asking if the event either will happen in a one-month-wide future time window or if it has already happened in an eleven-months-wide past time window. People can give more and more confident answers as the event draws closer because it’s easier to know if the event happened in the past than it is to know if the event will happen in the future, regardless of whether predicting the near future is easier than predicting the far future.
For example, consider the question “an earthquake of at least such-and-such magnitude will happen in such-and-such region between October 16 2019 and October 15 2020”. If you know that the propensity for such earthquakes is that they have a probability p of happening each day on average, and you have no information that allows you to make different guesses about different times, then the math on this question is pretty straightforward. Your initial estimate will be that there’s a (1-p)^365 chance of No Qualifying Earthquake. Each day that passes with no qualifying earthquake happening, you’ll increase the probability you put on No Qualifying Earthquake by reducing the exponent by 1 (“I know that an earthquake didn’t happen yesterday, so now how likely is to happen over the next 364 days?”, etc.). And if a qualifying earthquake ever does happen then you’ll change your prediction to a 100% chance of earthquake in that window (0% chance of No Qualifying Earthquake). You’re able to predict the near future (e.g. probability of an earthquake on October 17 2019) and the distant future (e.g. probability of an earthquake on October 14 2020) equally well, but with this [event] by [date] formulation of the question it’ll look like you’re able to correctly get more and more confident as the date grows closer.