Daily win probabilities for the 2016 U.S. presidential election candidates, derived from betting quotes, from 2016-03-10 to 2016-11-09 (237 calendar days including weekends). Candidate columns are probabilities on the 0-1 scale; they need not sum to one across candidates (they are raw one-sided quotes). The Trump series is the one used in the accompanying working paper.
Format
A tibble with 237 rows and 9 columns:
- date
Calendar date (
Date).- trump, clinton, sanders, cruz, kasich, biden, mcmullin
Win probabilities per candidate.
- volume
Betting volume (exchange units).
Source
See brexit2016.
Examples
data(us2016)
ep <- as_event_prices(us2016, time = "date", price = "trump",
event_date = as.Date("2016-11-08"))
event_clock(ep, from = as.Date("2016-10-10"))
#> # A tibble: 5 × 10
#> market_id from to horizon n_obs n_incr n_gaps max_gap_days
#> <chr> <date> <date> <chr> <int> <int> <int> <dbl>
#> 1 NA 2016-10-10 2016-11-09 2016-11-09 31 30 0 1
#> 2 NA 2016-10-10 2016-11-09 2016-11-09 31 30 0 1
#> 3 NA 2016-10-10 2016-11-09 2016-11-09 31 30 0 1
#> 4 NA 2016-10-10 2016-11-09 2016-11-09 31 30 0 1
#> 5 NA 2016-10-10 2016-11-09 2016-11-09 31 30 0 1
#> # ℹ 2 more variables: method <chr>, A <dbl>