This study examined participants' willingness to pay for stock price forecasts provided by an algorithm, financial experts, and peers. Participants valued algorithmic advice more highly and relied on it as much as expert advice. This preference for algorithms - despite their similar or even...

We explore the application of integrated nested Laplace approximations for the Bayesian estimation of stochastic volatility models characterized by long memory. The logarithmic variance persistence in these models is represented by a Fractional Gaussian Noise process, which we approximate as a...