An introduction to Markov chains for interested high school students

Markov Chains are introduced by only assuming some knowledge of the notion of probability. The modelling of a situation in a context of biology gives the opportunity to students to approach various concepts of probability theory themselves. --

Recognizing mathematical talent : an approach using discriminant analysis

The aim of this paper is to extract mathematically talented students out of a group of arbitrary high school students. We do this by applying a stepwise discriminant analysis modified for ordinal data to the results of German high school students at the international mathematics competition ?Kangaroo of Mathematics?. It turns out that three of the thirty given problems are enough to discriminate between laureates, which we assume to be mathematically talented, and non-laureates. The three chosen problems are from different mathematical fields. --Discriminant analysis for ordinal data,discrete kernel estimation,testing mathematical talent,multiple choice competition

Pricing of options under different volatility models

In this paper we compare the price of an option with one year maturity of the German stock index DAX for several volatility models including long memory and leverage effects. We compute the price by applying a present value scheme as well as the Black-Scholes and Hull-White formulas which includes stochastic volatility. We find that long memory as well as asymmetry affect the Black-Scholes price significantly whereas the Hull-White price is hardly affected by long memory but still by including asymmetries. --Option Pricing,GARCH,Long Memory,Leverage Effect

Tests of Bias in Log-Periodogram Regression

This paper proposes simple Hausman-type tests to check for bias in the log-periodogram regression of a time series believed to be long memory. The statistics are asymptotically standard normal on the null hypothesis that no bias is present, and the tests are consistent.Long memory, log periodogram regression, Hausman test.

Distinguishing between long-range dependence and deterministic trends

We provide a method for distinguishing long-range dependence from deterministic trends such as structural breaks. The method is based on the comparison of standard log-periodogram regression estimation of the memory parameter with its tapered counterpart. The difference of these estimators provides the desired test. Its asymptotic distribution depends on the true memory parameter under the null, and is therefore estimated by bootstrapping. The test is applied to inflation rates of three industrialized countries. --Long memory,trends,log-periodogram regression,inflation rates

Spatial autoregressive fractionally integrated moving average model

In this paper, we introduce the concept of fractional integration for spatial autoregressive models. We show that the range of the dependence can be spatially extended or diminished by introducing a further fractional integration parameter to spatial autoregressive moving average models (SARMA). This new model is called the spatial autoregressive fractionally integrated moving average model, briefly sp-ARFIMA. We show the relation to time-series ARFIMA models and also to (higher-order) spatial autoregressive models. Moreover, an estimation procedure based on the maximum-likelihood principle is introduced and analysed in a series of simulation studies. Eventually, the use of the model is illustrated by an empirical example of atmospheric fine particles, so-called aerosol optical thickness, which is important in weather, climate and environmental science

The Power of the KPSS-Test for Cointegration when Residuals are Fractionally Integrated

We show that the power of the KPSS-test against integration, as measured by divergence rates of the test statistic under the alternative, remains the same when residuals from an OLS-regression rather than true observations are used. This is in stark contrast to residual based tests of the null of integration in a cointegration setting, where power is drastically reduced when residuals are used. --cointegration,power,long memory,KPSS-Test

The cost for the default of a loan : Linking theory and practice

When calculating the cost of entering into a credit transaction the predominant stochastic component is the expected loss. Often in the credit business the one-year probability of default of the liable counterpart is the only reliable parameter. We use this probability to calculating the exact expected loss of trades with multiple cash ows. Assuming a constant hazard rate for the default time of the liable counterpart we show that the methodology used in practice is a linear Taylor approximation of our exact calculus. In a second stage we can generalize the calculation to arbitrary hazard rates for which we prove statistical evidence and develop an estimate from historical data. --

Long Memory, Spurious Memory: Persistence in Range-Based Volatility of Exchange Rates

This study considers the long memory and fractional integration in the range-based volatilities across 30 currencies against USD. Graphical analysis of the autocorrelation function at long lags and pole near zero frequencies in the periodogram suggests the existence of fractional integration. We apply semi-parametric methods to measure long-range dependence. We find a decrease in the memory estimates with an increase in the bandwidth, which indicates the presence of spurious memory rather true long memory. The hypothesis of long memory against the alternative of spurious memory is also tested by applying the different semi-parametric methods. Empirical results confirm the presence of spurious memory that may be a result of some shocks to the volatility estimator. Furthermore, the reduced memory estimates obtained by utilising an estimator accounting for level shifts also explains the inconsistency of the Local Whittle estimator. We also estimate the number of breaks for each series

Generating Schemes for Long Memory Processes: Regimes, Aggregation and Linearity

This paper analyses a class of nonlinear time series models exhibiting long memory. These processes exhibit short memory fluctuations around a local mean (regime) which switches randomly such that the durations of the regimes follow a power law. We show that if a large number of independent copies of such a process are aggregated, the resulting processes are Gaussian, have a linear representation, and converge after normalisation to fractional Brownian motion. Two cases arise, a stationary case in which the partial sums of the process converge, and a nonstationary case in which the process itself converges, the Hurst coefficient falling in the ranges ( 1/2 , 1) and (0, 1/2 ) respectively. However, a non-aggregated regime process is shown to converge to a Levy motion with infinite variance, suitably normalised, emphasising the fact that time aggregation alone fails to yield a FCLT. We comment on the relevance of our results to the interpretation of the long memory phenomenon, and also report some simulations aimed to throw light on the problem of discriminating between the models in practice