An empirical investigation of the level effect in Australian interest rates

An extensive literature examines the dynamics of interest rates, with particular attention given to the positive relationship between interest-rate volatility and the level of interest rates—the so-called level effect. This paper examines the interaction between the estimated level effect and competing parameterisations of interest-rate volatility for the Australian yield curve. We adopt a new methodology that estimates elasticity in a multivariate setting that explicitly accommodates the correlations that exist between various yield factors. Results show that significant correlations exist between the residuals of yield factors and that such correlations do indeed impact on model estimates. Within the multivariate setting, the level of the short rate is shown to be a crucial determinant of the conditional volatility of all three yield factors. Measures of model fit suggest that, in addition to the usual level effect, the incorporation of GARCH effects and possible regime shifts is important

Evaluating Specification Tests for Markov-Switching Time-Series Models

We evaluate the performance of several specification tests for Markov regime-switching time-series models. We consider the Lagrange multiplier (LM) and dynamic specification tests of Hamilton (1996) and Ljung–Box tests based on both the generalized residual and a standard-normal residual constructed using the Rosenblatt transformation. The size and power of the tests are studied using Monte Carlo experiments. We find that the LM tests have the best size and power properties. The Ljung–Box tests exhibit slight size distortions, though tests based on the Rosenblatt transformation perform better than the generalized residual-based tests. The tests exhibit impressive power to detect both autocorrelation and autoregressive conditional heteroscedasticity (ARCH). The tests are illustrated with a Markov-switching generalized ARCH (GARCH) model fitted to the US dollar–British pound exchange rate, with the finding that both autocorrelation and GARCH effects are needed to adequately fit the data.

Isopropylaminium 2-carboxy-4, 5-dichlorobenzoate

In the structure of the 1:1 proton-transfer compound of isopropylamine with 4,5-dichlorophthalic acid, C3H10N+·C8H3Cl2O4-, the three cation H-atom donors associate with three separate carboxyl O-atom anion acceptors, giving conjoint cyclic R44(12), R44(16) hydrogen-bonding cation-anion interactions in a one-dimensional ribbon structure. In the anions, the carboxyl groups lie slightly out of the plane of the benzene ring [maximum deviations = 0.439 (1) for a carboxylic acid O atom and 0.433 (1) Å for a carboxylate O atom]. However, the syn-related proton of the carboxylic acid group forms the common short intramolecular O-HOcarboxyl hydrogen bond.

Ethane-1,2-diaminium 4,5-dichlorophthalate

In the structure of the title compound, C2H10N22+·C8H2Cl2O42-, the dications and dianions form hydrogen-bonded ribbon substructures which enclose conjoint cyclic R21(7), R12(7) and R42(8) associations and extend down the c-axis direction. These ribbons inter-associate down b, giving a two-dimensional sheet structure. In the dianions, one of the carboxylate groups is essentially coplanar with the benzene ring, while the other is normal to it [C-C-C-O torsion angles = 177.67 (12) and 81.94 (17)°, respectively].

The distribution of the sample minimum-variance frontier

In this paper, we present a finite sample analysis of the sample minimum-variance frontier under the assumption that the returns are independent and multivariate normally distributed. We show that the sample minimum-variance frontier is a highly biased estimator of the population frontier, and we propose an improved estimator of the population frontier. In addition, we provide the exact distribution of the out-of-sample mean and variance of sample minimum-variance portfolios. This allows us to understand the impact of estimation error on the performance of in-sample optimal portfolios. Key Words: minimum-variance frontier; efficiency set constants; finite sample distribution

Three-dimensional hydrogen-bonded structures in the 1:1 proton-transfer compounds of L-tartaric acid with the associative-group monosubstituted pyridines 3-minopyridine, 3-carboxypyridine (nicotinic acid) and 2-carboxypyridine (picolinic acid).

The 1:1 proton-transfer compounds of L-tartaric acid with 3-aminopyridine [3-aminopyridinium hydrogen (2R,3R)-tartrate dihydrate, C5H7N2+·C4H5O6-·2H2O, (I)], pyridine-3-carboxylic acid (nicotinic acid) [anhydrous 3-carboxypyridinium hydrogen (2R,3R)-tartrate, C6H6NO2+·C4H5O6-, (II)] and pyridine-2-carboxylic acid [2-carboxypyridinium hydrogen (2R,3R)-tartrate monohydrate, C6H6NO2+·C4H5O6-·H2O, (III)] have been determined. In (I) and (II), there is a direct pyridinium-carboxyl N+-HO hydrogen-bonding interaction, four-centred in (II), giving conjoint cyclic R12(5) associations. In contrast, the N-HO association in (III) is with a water O-atom acceptor, which provides links to separate tartrate anions through Ohydroxy acceptors. All three compounds have the head-to-tail C(7) hydrogen-bonded chain substructures commonly associated with 1:1 proton-transfer hydrogen tartrate salts. These chains are extended into two-dimensional sheets which, in hydrates (I) and (III) additionally involve the solvent water molecules. Three-dimensional hydrogen-bonded structures are generated via crosslinking through the associative functional groups of the substituted pyridinium cations. In the sheet struture of (I), both water molecules act as donors and acceptors in interactions with separate carboxyl and hydroxy O-atom acceptors of the primary tartrate chains, closing conjoint cyclic R44(8), R34(11) and R33(12) associations. Also, in (II) and (III) there are strong cation carboxyl-carboxyl O-HO hydrogen bonds [OO = 2.5387 (17) Å in (II) and 2.441 (3) Å in (III)], which in (II) form part of a cyclic R22(6) inter-sheet association. This series of heteroaromatic Lewis base-hydrogen L-tartrate salts provides further examples of molecular assembly facilitated by the presence of the classical two-dimensional hydrogen-bonded hydrogen tartrate or hydrogen tartrate-water sheet substructures which are expanded into three-dimensional frameworks via peripheral cation bifunctional substituent-group crosslinking interactions.

A novel profluorescent dinitroxide for imaging polypropylene degradation

Free-radical processes underpin the thermo-oxidative degradation of polyolefins. Thus, to extend the lifetime of these polymers, stabilizers are generally added during processing to scavenge the free radicals formed as the polymer degrades. Nitroxide radical precursors, such as hindered amine stabilizers (HAS),1,2 are common polypropylene additives as the nitroxide moiety is a potent scavenger of polymer alkyl radicals (R¥). Oxidation of HAS by radicals formed during polypropylene degradation yields nitroxide radicals (RRNO¥), which rapidly trap the polymer degradation species to produce alkoxyamines, thus retarding oxidative polymer degradation. This increase in polymer stability is demonstrated by a lengthening of the “induction period” of the polymer (the time prior to a sharp rise in the oxidation of the polymer). Instrumental techniques such as chemiluminescence or infrared spectroscopy are somewhat limited in detecting changes in the polymer during the initial stages of degradation. Therefore, other methods for observing polymer degradation have been sought as the useful life of a polymer does not extend far beyond its “induction period”

How can flexible learning centres use social networking to improve their ongoing educational assessments?

Most online assessment systems now incorporate social networking features, and recent developments in social media spaces include protocols that allow the synchronisation and aggregation of data across multiple user profiles. In light of these advances and the concomitant fear of data sharing in secondary school education this papers provides important research findings about generic features of online social networking, which educators can use to make sound and efficient assessments in collaboration with their students and colleagues. This paper reports on a design experiment in flexible educational settings that challenges the dichotomous legacy of success and failure evident in many assessment activities for at-risk youth. Combining social networking practices with the sociology of education the paper proposes that assessment activities are best understood as a negotiable field of exchange. In this design experiment students, peers and educators engage in explicit, "front-end" assessment (Wyatt-Smith, 2008) to translate digital artefacts into institutional, and potentiality economic capital without continually referring to paper based pre-set criteria. This approach invites students and educators to use social networking functions to assess “work in progress” and final submissions in collaboration, and in doing so assessors refine their evaluative expertise and negotiate the value of student’s work from which new criteria can emerge. The mobile advantages of web-based technologies aggregate, externalise and democratise this transparent assessment model for most, if not all, student work that can be digitally represented.