Controlling precursor stability and evaporation through molecular design. Pseudo single source precursor approach to MOCVD SrTiO3 thin films

Strontium titanate SrTiO₃ thin films have attracted interest as a possible gate dielectric material. Preparation of its high quality coatings is hindered by difference in volatility of the homometallic precursors - strontium beta-diketonates and titanium alkoxides. The only earlier known single-source precursor, a sec-alkoxide derivative Sr₂Ti₂(thd)₄(OiPr)₈, has limited volatility. Bimetallic primary alkyl chain complexes, Sr₄Ti₂O(thd)₄(OR)₁₀(ROH)₂, R = Et, ⁿPr, are stable and volatile, but possess a wrong composition. Highly volatile precursor Sr₂Ti₂(thd)₄(OⁱBu)₈ has been prepared using an iso-alkoxide, combining proper ligand size with the sterical requirements, and characterized by multivariate evaporation analysis. Its evaporation is associated with complete decomposition into homometallic species, which, however, are evaporated in a single step. This permits to successfully use this novel precursor for SrTiO₃ thin film deposition by DLI-MOCVD technique in a sufficiently broad established temperature range. Using optimized experimental conditions, 100 nm thick strontium titanate films with high permittivity have been successfully obtained on (1 0 0) Si.     

Market volatility modeling for short time window

The gain or loss of an investment can be defined by the movement of the market. This movement can be estimated by the difference between the magnitudes of two stock prices in distinct periods and this difference can be used to calculate the volatility of the markets. The volatility characterizes the sensitivity of a market change in the world economy. Traditionally, the probability density function (pdf) of the movement of the markets is analyzed by using power laws. The contributions of this work is two-fold: (i) an analysis of the volatility dynamic of the world market indexes is performed by using a two-year window time data. In this case, the experiments show that the pdf of the volatility is better fitted by exponential function than power laws, in all range of pdf; (ii) after that, we investigate a relationship between the volatility of the markets and the coefficient of the exponential function based on the Maxwell-Boltzmann ideal gas theory. The results show an inverse relationship between the volatility and the coefficient of the exponential function. This information can be used, for example, to predict the future behavior of the markets or to cluster the markets in order to analyze economic patterns.     

Asset returns and volatility clustering in financial time series

An analysis of the stylized facts in financial time series is carried out. We find that, instead of the heavy tails in asset return distributions, the slow decay behaviour in autocorrelation functions of absolute returns is actually directly related to the degree of clustering of large fluctuations within the financial time series. We also introduce an index to quantitatively measure the clustering behaviour of fluctuations in these time series and show that big losses in financial markets usually lump more severely than big gains. We further give examples to demonstrate that comparing to conventional methods, our index enables one to extract more information from the financial time series.