John Maynard Keynes composed The General Theory as a response to the Great Crash and Great Depression with all their devastating consequences for the US macro economy and financial markets, as well as the rest of the world. The role of expectations his new theory set out has been widely...

This paper investigates sentiment in the US economy from 1920 to 1934 using digitized articles from the Wall St Journal. We derive a monthly sentiment index and use a ten variable vector error correction model to identify sentiment shocks that are orthogonal to fundamentals. We show the timing...

This paper investigates sentiment in the US economy from 1920 to 1934 using digitized articles from the Wall St Journal. We derive a monthly sentiment index and use a ten variable vector error correction model to identify sentiment shocks that are orthogonal to fundamentals. We show the timing...

John Maynard Keynes composed The General Theory as a response to the Great Crash and Great Depression with all their devastating consequences for the US macro economy and financial markets, as well as the rest of the world. The role of expectations his new theory set out has been widely...

John Maynard Keynes composed The General Theory as a response to the Great Crash and Great Depression with all their devastating consequences for the US macro economy and financial markets, as well as the rest of the world. The role of expectations his new theory set out has been widely...

Conviction narrative theory (CNT), a social psychological approach to the way economic agents take deisions under Knightian uncertainty, together with the new methodology of directed algorithmic text analysis (DATA), provide the opportunity for a theory of economic sentiment or animal sprits...

This paper applies algorithmic analysis to large amounts of financial market text-based data to assess how narratives and sentiment play a role in driving developments in the financial system. We find that changes in the emotional content in market narratives are highly correlated across data...

This paper applies algorithmic analysis to large amounts of financial market text-based data to assess how narratives and sentiment play a role in driving developments in the financial system. We find that changes in the emotional content in market narratives are highly correlated across data...