Predicting the unpredictable : New experimental evidence on forecasting random walks

Fiche du document

Date

1 janvier 2023

Type de document
Périmètre
Langue
Identifiants
Collection

Archives ouvertes




Citer ce document

Te Bao et al., « Predicting the unpredictable : New experimental evidence on forecasting random walks », HAL-SHS : droit et gestion, ID : 10670/1.d5soen


Métriques


Partage / Export

Résumé En

We investigate how individuals use measures of apparent predictability from price charts to predict future market prices. Subjects in our experiment predict both random walk times series, as in the seminal work by Bloomfield and Hales (2002) (BH), and stock price time series. We successfully replicate the experimental findings in BH that subjects are less trend-chasing when there are more reversals in random walk times series. We do not find evidence that subjects overreact less to the trend when there are more reversals in the stock price prediction task. Our subjects also appear to use other variables such as autocorrelation coefficient, amplitude and volatility as measures of predictability. However, as random walk theory predicts, relying on apparent patterns in past data does not improve their prediction accuracy.

document thumbnail

Par les mêmes auteurs

Sur les mêmes sujets

Sur les mêmes disciplines

Exporter en