I introduce a reduced form two-sided market model to study prediction and identification in two-sided markets. The model generates the hallmark features of two-sided markets: potentially below cost or even negative prices to one side of the market, and the "see-saw" or "waterbed" effect of a...

We propose a granular framework that makes use of advanced statistical methods to approximate developments in economy-wide expected corporate earnings. In particular, we evaluate the dynamic network structure of stock returns in the United States as a proxy for the transmission of shocks through...

Information aggregation mechanisms are designed explicitly for collecting and aggregating dispersed information. An excellent example of the use of this "wisdom of crowds" is a prediction market. The purpose of our Twitter-based prediction market is to suggest that carefully designed market...

We study an adverse-selection model in which the distribution of the asset is affected by unobservable actions of the seller. The seller's equilibrium behavior is characterized by a risk-seeking disposition, and a competitive market, in which the underlying distribution of the traded asset is...

This article examines, in the light of recent events, the origins of the difficulties that current macroeconomic models have in encompassing the sort of sudden crisis which we are currently observing. The reasons for this are partly due to fundamental problems with the underlying General...

For users of the Ethereum network, the gas price is a crucial parameter that determines how swiftly the decentralized consensus protocol confirms a transaction. This paper studies the statistics of the Ethereum gas price. We start with some conceptual discussion of the gas price notion in view...

We propose a granular framework that makes use of advanced statistical methods to approximate developments in economy-wide expected corporate earnings. In particular, we evaluate the dynamic network structure of stock returns in the United States as a proxy for the transmission of shocks through...

We investigate the benefits of forecast combination for timing equity factors based on predictive regressions using macro predictors. Relative to standard predictive regression models, forecast combination reduces the noise of forecasts and hence improves their out-of-sample predictive accuracy....

The literature argues that industry network effects imply the predictability of industry returns, while the return predictability can estimate the industry network in reverse. The paper employs rolling window adaptive lasso regressions to test the robustness of return predictions, showing the...