Palynological analyses in the laminated sediment of Lake Holzmaar (Eifel, Germany): duration of Lateglacial and Preboreal biozones

The laminated sediment of Lake Holzmaar (Germany) has provided a continuous varve chronology for the last 3500 varve years (vy) and beyond that a floating varve chronology back to more than 22500 vy BP. This chronology in calendar years, in combination with palynology, enables us to determine the timing. and the magnitude of Lateglacial and Early Holocene environmental changes on land (from 13838 to 10930 vy BP). The palynological diagram has a mean time resolution of 27 vy between samples. This paper establishes for the first time the biozonation for Lake Holzmaar below the Leacher see Tephra. Fifteen pollen subzones grouped in four biozones are defined by cluster analysis. After a period disturbed by microturbidites, only a parr of the Belling is present. Three cold periods have been evidenced by pollen analyses: the Older Dryas (96-vy-long), the Younger Dryas (654-vy-long) and the Rammelbeek phase (237-vy-long). The Allerod (883-vy-long) is bipartite with a first Betula-dominated period followed by a Pinus-dominated one. The Younger Dryas is also bipartite, with first a decrease of winter temperatures along with a change to a more continental climate. It is followed by a drier phase with a second decrease in temperatures. probably this time also affecting summer temperatures. The Preboreal is 702-yr-long. The duration of most phases corresponds to published records, except for that of the Younger Dryas. Cluster and rare-of-change analyses indicate a sharp change in the terrestrial vegetation assemblages that may be caused by a sedimentary hiatus of erosive origin during this cold and dry period. As a result the chronology of Holzmaar has to be revised most likely below the middle of the Younger Dryas. Comparison with the varve record of Meerfelder Maar, a neighbour maar lake, suggests adding 320 vy below 12025 vy

Intraday Stochastic Volatility in Discrete Price Changes: The Dynamic Skellam Model

<p>We study intraday stochastic volatility for four liquid stocks traded on the New York Stock Exchange using a new dynamic Skellam model for high-frequency tick-by-tick discrete price changes. Since the likelihood function is analytically intractable, we rely on numerical methods for its evaluation. Given the high number of observations per series per day (1000 to 10,000), we adopt computationally efficient methods including Monte Carlo integration. The intraday dynamics of volatility and the high number of trades without price impact require nontrivial adjustments to the basic dynamic Skellam model. In-sample residual diagnostics and goodness-of-fit statistics show that the final model provides a good fit to the data. An extensive day-to-day forecasting study of intraday volatility shows that the dynamic modified Skellam model provides accurate forecasts compared to alternative modeling approaches. Supplementary materials for this article are available online.</p