@book{KunzeStrohe2010,
  author    = {Kunze, Karl-Kuno and Strohe, Hans Gerhard},
  title     = {Antipersistence in German Stock Returns},
  series = {Statistische Diskussionsbeitr{\"a}ge},
  volume    = {39},
  journal   = {Statistische Diskussionsbeitr{\"a}ge},
  publisher = {Univ.},
  address   = {Potsdam},
  issn      = {0949-068x},
  pages     = {16 S.},
  year      = {2010},
  language  = {en}
}
@phdthesis{Kunze2009,
  author    = {Kunze, Karl-Kuno},
  title     = {Persistenz und Antipersistenz im deutschen Aktienmarkt : eine empirische Untersuchung},
  series = {Reihe Quantitative {\"O}konomie},
  volume    = {158},
  journal   = {Reihe Quantitative {\"O}konomie},
  publisher = {Eul},
  address   = {Lohmar},
  isbn      = {978-3-89936-811-6},
  pages     = {XVI, 240 S. : graph. Darst.},
  year      = {2009},
  language  = {de}
}
@phdthesis{Kunze2000,
  author    = {Kunze, Karl-Kuno},
  title     = {Electrostatic Organization of DNA},
  pages     = {112 S.},
  year      = {2000},
  language  = {en}
}
@book{KauperKunze2011,
  author    = {Kauper, Benjamin and Kunze, Karl-Kuno},
  title     = {Modellierung von Aktienkursen im Lichte der Komplexit{\"a}tsforschung},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-52285},
  publisher      = {Universit{\"a}t Potsdam},
  year      = {2011},
  abstract  = {This paper offers empirical evidence on the power of Sornette et al's [2001] model of bubbles and crashes regarding the German stock market between 1960 and 2009. We identify relevant time periods and describe them with the function given by Sornette et al's model. Our results show some evidence in predicting crashes with the understanding of logarithmic periodic structures that are hidden in the stock price trajectories. It was shown that for the DAX most of the relevant parameters determining the shape of the logarithmic periodic structures are lying in the expected interval researched by Sornette et al. Further more the paper implicitly shows that the point of time of former crashes can be predicted with the presented formula. We conclude that the concept of financial time series conceived as purely random objects should be generalised as to admit complexity.},
  language  = {de}
}
@book{KunzeStrohe2010,
  author    = {Kunze, Karl-Kuno and Strohe, Hans Gerhard},
  title     = {Antipersistence in German stock returns},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-45582},
  publisher      = {Universit{\"a}t Potsdam},
  year      = {2010},
  abstract  = {Persistence of stock returns is an extensively studied and discussed theme in the analysis of financial markets. Antipersistence is usually attributed to volatilities. However, not only volatilities but also stock returns can exhibit antipersistence. Antipersistent noise has a somewhat rougher appearance than Gaussian noise. Heuristically spoken, price movements are more likely followed by movements in the opposite direction than in the same direction. The pertaining integrated process exhibits a smaller range - prices seem to stay in the vicinity of the initial value. We apply a widely used test based upon the modified R/S-Method by Lo [1991] to daily returns of 21 German stocks from 1960 to 2008. Combining this test with the concept of moving windows by Carbone et al. [2004], we are able to determine periods of antipersistence for some of the series under examination. Our results suggest that antipersistence can be found for stocks and periods where extraordinary corporate actions such as mergers \& acquisitions or financial distress are present. These effects should be properly accounted for when choosing and designing models for inference.},
  language  = {en}
}
@book{KunzeStrohe2010,
  author    = {Kunze, Karl-Kuno and Strohe, Hans Gerhard},
  title     = {Time-varying persistence in the German stock market},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-42046},
  publisher      = {Universit{\"a}t Potsdam},
  year      = {2010},
  abstract  = {This paper studies the persistence of daily returns of 21 German stocks from 1960 to 2008. We apply a widely used test based upon the modified R/S-Method by Lo [1991]. As an extension to Lux [1996] and Carbone et al. [2004] and in analogy to moving average or moving volatility, the statistics is calculated for moving windows of length 4, 8, and 16 years for every time series. Periods of persistence or long memory in returns can be found in some but not all time series. Robustness of results is verified by investigating stationarity and short memory effects.},
  language  = {en}
}