We show that in a consumption-based asset-pricing model with hyperbolic discounting leading to dynamically inconsistent time preferences value premium increases nonlin-early with the degree of discounting and thus affects cross section of returns. To test our model empirically, we relate the...

We use the database leak of Mt. Gox exchange to analyze the dynamics of the price of bitcoin from June 2011 to November 2013. This gives us a rare opportunity to study an emerging retail-focused, highly speculative and unregulated market with trader identifiers at a tick transaction level. Jumps...

We present a dynamic Rational Expectations (RE) bubble model of prices with the intention to evaluate it on optimal investment strategies applied to Bitcoin. Our bubble model is defined as a geometric Brownian motion combined with separate crash (and rally) discrete jump distributions associated...

We present a detailed bubble analysis of the Bitcoin to US Dollar price dynamics from January 2012 to February 2018. We introduce a robust automatic peak detection method that classifies price time series into periods of uninterrupted market growth (drawups) and regimes of uninterrupted market...

Using data for six metropolitan housing markets in three countries, this paper provides a comparison of methods used to measure house price bubbles. We use an asset pricing approach to identify bubble periods retrospectively and then compare those results with results produced by six other...

We report strong evidence that changes of momentum, i.e. "acceleration", defined as the first difference of successive returns, provide better performance and higher explanatory power than momentum. The corresponding Γ-factor explains the momentum-sorted portfolios entirely but not the reverse....

This paper shows that the latest generation of asset pricing models with long-run risk exhibits economically significant nonlinearities, and thus the ubiquitous Campbell--Shiller log-linearization can generate large numerical errors. These errors in turn translate to considerable errors in the...