Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Philipp Adämmer"'
Publikováno v:
SSRN Electronic Journal.
Publikováno v:
Review of Finance. 24:1313-1355
We introduce a novel strategy to predict monthly equity premia that is based on extracted news from more than 700,000 newspaper articles, which were published in The New York Times and Washington Post between 1980 and 2018. We propose a flexible data
Publikováno v:
SSRN Electronic Journal.
Publikováno v:
Bulletin of Economic Research. 69:57-76
North American and European agricultural futures markets faced significant changes in recent years, i.e., the financialization which originated in the USA, the increase of futures trading in Europe and the recent price turmoils in international commo
Publikováno v:
SSRN Electronic Journal.
We introduce a novel strategy to predict monthly equity premia that is based on extracted news from more than 700,000 newspaper articles, which were published in The New York Times and Washington Post between 1980 and 2018. We propose a flexible data
Publikováno v:
Journal of Futures Markets. 36:851-869
It is still an unanswered question how much trading activity is needed for efficient price discovery in commodity futures markets. For this purpose, we investigate the price discovery process of two thinly traded agricultural futures contracts traded
Autor:
Martin T. Bohl, Philipp Adämmer
Publikováno v:
The Quarterly Review of Economics and Finance. 55:67-76
We use the momentum threshold autoregressive (MTAR) approach to test for speculative bubbles in US corn, soybean and wheat prices. To approximate fundamental values of these agricultural commodities, we use real crude oil prices and real exchange rat
Autor:
Philipp Adämmer, Tom Philipp Dybowski
Publikováno v:
SSRN Electronic Journal.
We apply an unsupervised machine learning algorithm to revisit legislative lags of U.S. tax reforms and show that at least two lags have been longer than previously identified. Our approach offers an alternative way to approximate U.S. tax foresight,
Publikováno v:
SSRN Electronic Journal.
We combine a probabilistic topic model and a dictionary-based sentiment analysis to construct a time series, which indicates when and how (positive vs. negative) the U.S. president communicates his tax policy news to the public. The econometric analy