Embedded Files
The link above contains Python Code to calculate the worth of Prospects in Python using Prospect Theory. The google colab link at the bottom will also give the same results.
Below is a sample output for the Python code which can use exponential and power value along with K&T and Prelect Weightings. It also easily enables the comparison of prospects
You can easily access the probability weighting functions and utility functions associated with your inputs.
Calculator
You can calculate the PT values for any number of payoffs using the Google Colab site. You can also choose different value functions and probability warpings. If you put power utility and k&t warpings you should replicate the values obtained by Kobberling's website
Estimation of Prospect Theory Models using Hierachical Bayes
A Standard Prospect Theory model can be estimated on Pystan using the code above. The code above is a little dated and uses the old syntax for arrays. The basic Stan code should be adaptable to other platforms such as R-stan cmdstan etc., but requires some pre-processing to obtain cumulative and decumulative distributions which are inputted into the model rather than the probabilities themselves. This is a slightly simpler version than the model employed inthe paper below, but with the same data.
The design used in the paper below 'A Note on an Alternative Approach to Experimental Design of Lottery Prospects'
Page updated
Google Sites
Report abuse