This paper develops a simulation-based solution method to solve large state space macrofinance models using machine learning. We use a neural network (NN) to approximate the expectations in the optimality conditions in the spirit of the stochastic parameterized expectations algorithm (PEA)....

We use supervised machine learning to approximate the expectations typically contained in the optimality conditions of an economic model in the spirit of the parameterized expectations algorithm (PEA) with stochastic simulation. When the set of state variables is generated by a stochastic...

Through the difference-in-differences (DID) methodology, we find that the connection of China’s high-speed railway (HSR) as an exogenous shock could improve analysts’ forecast performance, leading to more accurate forecasts, decrease the dispersion between analysts, stimulate more forecast...

Empirical evidence on the out-of-sample performance of asset-pricing anomalies is mixed so far and arguably is often subject to data-snooping bias. This paper proposes a method that can significantly reduce this bias. Specifically, we consider a long-only strategy that involves only published...

You're probably familiar, at least in passing, with the 'convexity' of long-term bonds - i.e. that yields dropping 1% produce a bigger price move than yields rising 1%. A significant amount of brainpower has gone into understanding all the ramifications of this convexity in the fixed income...

This paper is the first to use the WeChat platform, one of the largest social networks, to conduct an online experiment of artificial investment games. We investigate how people's forecasts about the financial market and investment decisions are shaped by whether they can observe others'...

The paper examines the problem of portfolio selection based on the forecasts of unknown quality in a mean-variance framework. Early work by Treynor and Black (1973) established a relationship between the correlation of forecasts, the number of independent securities available and the Sharpe...

This paper examines the impact of teamwork on sell-side analysts' performance. Using a hand-collected sample of over 50,000 analyst research reports, we find that analyst teams issue more than 70% of annual earnings forecasts. In contrast, most prior research implicitly assumes that forecasts...

This book is a collection of papers for the Special Issue "Quantitative Methods for Economics and Finance" of the journal Mathematics. This Special Issue reflects on the latest developments in different fields of economics and finance where mathematics plays a significant role. The book gathers...