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The folly of forecasting : the effects of a disaggregated demand forecasting system on forecast error, forecast positive bias, and inventory levels

Brüggen, Alexander; Grabner, Isabella; Sedatole, Karen - 2020

Persistent link: https://www.econbiz.de/10012259272

The effect of visibility on forecast and inventory management performance during the COVID-19 pandemic

Dehkhoda, Kaveh; Bélanger, Valérie; Cousineau, Martin - 2023

Persistent link: https://www.econbiz.de/10014252864

Exchange return co-movements and volatility spillovers before and after the introduction of euro

Antonakakis, Nikolaos - 2012

This paper examines co-movements and volatility spillovers in the returns of the euro, the British pound, the Swiss franc and the Japanese yen vis-à-vis the US dollar before and after the introduction of the euro. Based on dynamic correlations, variance decompositions, generalized VAR analysis,...

Persistent link: https://www.econbiz.de/10011347744

When the Fed sneezes - spillovers from U.S. monetary policy to emerging markets

Meinusch, Annette - 2017

This paper aims to shed light on the role mean and volatility spillovers of U.S. monetary policy played for asset markets of several emerging market economies in a period from January 2000 to October 2014. We employ multi-variate GARCH models in which we distinguish between a conventional and an...

Persistent link: https://www.econbiz.de/10011672704

Risk analysis and security countermeasure selection

Norman, Thomas L. - 2010

Persistent link: https://www.econbiz.de/10003887758

CRIX or evaluating blockchain based currencies

Härdle, Wolfgang; Trimborn, Simon - 2015

More and more companies start offering digital payment systems. Smartphones evolve to a digital wallet such that it seems like we are about to enter the era of digital finance. In fact we are already inside an digital economy. The market of e-x (x = "finance", "money", "book", you name it . . ....

Persistent link: https://www.econbiz.de/10011349496

Winning with futures : the smart way to recognize opportunities, calculate risk, and maximize profits

Thomsett, Michael C. - 2009

Persistent link: https://www.econbiz.de/10003722010

Dynamic Factor Trees and Forests: A theory-led machine learning framework for non-linear and state-dependent short-term U.S. GDP growth predictions

Wochner, Daniel - 2020

Factor Forests (DFF) for macroeconomic forecasting, which synthesize the recent machine learning, dynamic factor model and … proposed in Zeileis, Hothorn and Hornik (2008). DFTs and DFFs are non-linear and state-dependent forecasting models, which … powerful tree-based machine learning ensembles conditional on the state of the business cycle. The out-of-sample forecasting …

Persistent link: https://www.econbiz.de/10012546027

The role of commodity prices in forecasting U.S. core inflation

Gospodinov, Nikolaj - 2016

This note documents a curious finding about the substantial forecast ability of a simple aggregator of three commodity futures prices for U.S. core inflation. The proposed aggregator reduces the out-of-sample root mean squared error for 12-month-ahead inflation forecasts of the benchmark AR(1)...

Persistent link: https://www.econbiz.de/10011428084

Forecasting US recessions with macro factors

Fossati, Sebastian - 2013

Persistent link: https://www.econbiz.de/10009731422

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