CRIX an index for cryptocurrencies

The cryptocurrency market is unique on many levels: Very volatile, frequently changing market structure, emerging and vanishing of cryptocurrencies on a daily level. Following its development became a difficult task with the success of cryptocurrencies (CCs) other than Bitcoin. For fiat currency markets, the IMF offers the index SDR and, prior to the EUR, the ECU existed, which was an index representing the development of European currencies. Index providers decide on a fixed number of index constituents which will represent the market segment. It is a challenge to fix a number and develop rules for the constituents in view of the market changes. In the frequently changing CC market, this challenge is even more severe. A method relying on the AIC is proposed to quickly react to market changes and therefore enable us to create an index, referred to as CRIX, for the cryptocurrency market. CRIX is chosen by model selection such that it represents the market well to enable each interested party studying economic questions in this market and to invest into the market. The diversified nature of the CC market makes the inclusion of altcoins in the index product critical to improve tracking performance. We have shown that assigning optimal weights to altcoins helps to reduce the tracking errors of a CC portfolio, despite the fact that their market cap is much smaller relative to Bitcoin. The codes used here are available via www.quantlet.de

A liquidity constrained investment approach

Cryptocurrencies have left the dark side of the finance universe and become an object of study for asset and portfolio management. Since they have a low liquidity compared to traditional assets, one needs to take into account liquidity issues when one puts them into the same portfolio. We propose use a LIquidity Bounded Risk-return Optimization (LIBRO) approach, which is a combination of the Markowitz framework under the liquidity constraints. The results show that cryptocurrencies add value to a portfolio and the optimization approach is even able to increase the return of a portfolio and lower the volatility risk. The codes used to obtain the results in this paper are available via www.quantlet.d

Impact ionization mass spectra of anorthite cosmic dust analogue particles

Anorthite, the Ca-rich end-member of plagioclase feldspar, is a dominant mineral component of the Lunar highlands. Plagioclase feldspar is also found in comets, meteorites and stony asteroids. It is therefore expected to contribute to the population of interplanetary (and circumplanetary) dust grains within the solar system. After coating micron- and submicron-sized grains of Anorthite with a conductive layer of Platinum, the mineral was successfully accelerated to hypervelocity speeds in the Max Planck Institut für Kernphysik’s Van de Graaff accelerator. We present impact ionization mass spectra generated following the impacts of anorthite grains with a prototype mass spectrometer (the Large Area Mass Analyser, LAMA) designed for use in space, and discuss the behavior of the spectra with increasing impact energy. Correlation analysis is used to identify the compositions and sources of cations present in the spectra, enabling the identification of several molecular cations (e.g., CaAlO2, CaSiO2, Ca2AlO3/CaAlSi2O2) which identify anorthite as the progenitor bulk grain material

Investing with Cryptocurrencies - A Liquidity Constrained Investment Approach

Cryptocurrencies have left the dark side of the finance universe and become an object of study for asset and portfolio management. Since they have a low liquidity compared to traditional assets, one needs to take into account liquidity issues when one puts them into the same portfolio. We propose use a Liquidity Bounded Risk-return Optimization (LIBRO) approach, which is a combination of the Markowitz framework under the liquidity constraints. The results show that cryptocurrencies add value to a portfolio and the optimization approach is even able to increase the return of a portfolio and lower the volatility risk

Combined effects of CO2 and temperature on carbon uptake and partitioning by the marine diatoms Thalassiosira weissflogii and Dactyliosolen fragilissimus

Carbon uptake and partitioning of two globally abundant diatom species, Thalassiosira weissflogii and Dactyliosolen fragilissimus, was investigated in batch culture experiments under four conditions: ambient (15 degrees C, 400 atm), high CO2 (15 degrees C, 1000 atm), high temperature (20 degrees C, 400 atm), and combined (20 degrees C, 1000 atm). The experiments were run from exponential growth into the stationary phase (six days after nitrogen depletion), allowing us to track biogeochemical dynamics analogous to bloom situations in the ocean. Elevated CO2 had a fertilizing effect and enhanced uptake of dissolved inorganic carbon (DIC) by about 8% for T. weissflogii and by up to 39% for D. fragilissimus. This was also reflected in higher cell numbers, build-up of particulate and dissolved organic matter, and transparent exopolymer particles. The CO2 effects were most prominent in the stationary phase when nitrogen was depleted and CO2(aq) concentrations were low. This indicates that diatoms in the high CO2 treatments could take up more DIC until CO2 concentrations in seawater became so low that carbon limitation occurs. These results suggest that, contrary to common assumptions, diatoms could be highly sensitive to ongoing changes in oceanic carbonate chemistry, particularly under nutrient limitation. Warming from 15 to 20 degrees C had a stimulating effect on one species but acted as a stressor on the other species, highlighting the importance of species-specific physiological optima and temperature ranges in the response to ocean warming. Overall, these sensitivities to CO2 and temperature could have profound impacts on diatoms blooms and the biological pump