Bicorrelations and cross-bicorrelations as non-linearity tests and tools for exchange rate forecasting

This paper proposes and implements a new methodology for forecasting time series, based on bicorrelations and cross-bicorrelations. It is shown that the forecasting technique arises as a natural extension of, and as a complement to, existing univariate and multivariate non-linearity tests. The formulations are essentially modified autoregressive or vector autoregressive models respectively, which can be estimated using ordinary least squares. The techniques are applied to a set of high-frequency exchange rate returns, and their out-of-sample forecasting performance is compared to that of other time series models

Can portmanteau nonlinearity tests serve as general mis-specification tests?

A number of recent papers have employed the BDS test as a general test for mis-specification for linear and nonlinear models. We show that for a particular class of conditionally heteroscedastic models, the BDS test is unable to detect a common mis-specification. Our results also demonstrate that specific rather than portmanteau diagnostics are required to detect neglected asymmetry in volatility. However for both classes of tests reasonable power is only obtained using very large sample sizes.

Portmanteau model diagnostics and tests for nonlinearity: a comparative Monte Carlo study of two alternative methods

This paper employs an extensive Monte Carlo study to test the size and power of the BDS and close return methods of testing for departures from independent and identical distribution. It is found that the finite sample properties of the BDS test are far superior and that the close return method cannot be recommended as a model diagnostic. Neither test can be reliably used for very small samples, while the close return test has low power even at large sample sizes

Tests of non-linearity using LIFFE futures transactions price data

This paper presents and implements a number of tests for non-linear dependence and a test for chaos using transactions prices on three LIFFE futures contracts: the Short Sterling interest rate contract, the Long Gilt government bond contract, and the FTSE 100 stock index futures contract. While previous studies of high frequency futures market data use only those transactions which involve a price change, we use all of the transaction prices on these contracts whether they involve a price change or not. Our results indicate irrefutable evidence of non-linearity in two of the three contracts, although we find no evidence of a chaotic process in any of the series. We are also able to provide some indications of the effect of the duration of the trading day on the degree of non-linearity of the underlying contract. The trading day for the Long Gilt contract was extended in August 1994, and prior to this date there is no evidence of any structure in the return series. However, after the extension of the trading day we do find evidence of a non-linear return structure.

Selection of potential probiotic lactic acid bacteria from fermented olives by in vitro tests

The present study aims to evaluate the probiotic potential of lactic acid bacteria (LAB) isolated from naturally fermented olives and select candidates to be used as probiotic starters for the improvement of the traditional fermentation process and the production of newly added value functional foods. Seventy one (71) lactic acid bacterial strains (17 Leuconostoc mesenteroides, 1 Ln. pseudomesenteroides, 13 Lactobacillus plantarum, 37 Lb. pentosus, 1 Lb. paraplantarum, and 2 Lb. paracasei subsp. paracasei) isolated from table olives were screened for their probiotic potential. Lb. rhamnosus GG and Lb. casei Shirota were used as reference strains. The in vitro tests included survival in simulated gastrointestinal tract conditions, antimicrobial activity (against Listeria monocytogenes, Salmonella Enteritidis, Escherichia coli O157:H7), Caco-2 surface adhesion, resistance to 9 antibiotics and haemolytic activity. Three (3) Lb. pentosus, 4 Lb. plantarum and 2 Lb. paracasei subsp. paracasei strains demonstrated the highest final population (>8 log cfu/ml) after 3 h of exposure at low pH. The majority of the tested strains were resistant to bile salts even after 4 h of exposure, while 5 Lb. plantarum and 7 Lb. pentosus strains exhibited partial bile salt hydrolase activity. None of the strains inhibited the growth of the pathogens tested. Variable efficiency to adhere to Caco-2 cells was observed. This was the same regarding strains' susceptibility towards different antibiotics. None of the strains exhibited β-haemolytic activity. As a whole, 4 strains of Lb. pentosus, 3 strains of Lb. plantarum and 2 strains of Lb. paracasei subsp. paracasei were found to possess desirable in vitro probiotic properties similar to or even better than the reference probiotic strains Lb. casei Shirota and Lb. rhamnosus GG. These strains are good candidates for further investigation both with in vivo studies to elucidate their potential health benefits and in olive fermentation processes to assess their technological performance as novel probiotic starters.

Criteria for validation and selection of cognitive tests for investigating the effects of foods and nutrients.

This review is an output of the International Life Sciences Institute (ILSI) Europe Marker Initiative, which aims to identify evidence-based criteria for selecting adequate measures of nutrient effects on health through comprehensive literature review. Experts in cognitive and nutrition sciences examined the applicability of these proposed criteria to the field of cognition with respect to the various cognitive domains usually assessed to reflect brain or neurological function. This review covers cognitive domains important in the assessment of neuronal integrity and function, commonly used tests and their state of validation, and the application of the measures to studies of nutrition and nutritional intervention trials. The aim is to identify domain-specific cognitive tests that are sensitive to nutrient interventions and from which guidance can be provided to aid the application of selection criteria for choosing the most suitable tests for proposed nutritional intervention studies using cognitive outcomes. The material in this review serves as a background and guidance document for nutritionists, neuropsychologists, psychiatrists, and neurologists interested in assessing mental health in terms of cognitive test performance and for scientists intending to test the effects of food or food components on cognitive function.

Human misidentification in Turing tests

This paper presents some important issues on misidentification of human interlocutors in text-based communication during practical Turing tests. The study here presents transcripts in which human judges succumbed to theconfederate effect, misidentifying hidden human foils for machines. An attempt is made to assess the reasons for this. The practical Turing tests in question were held on 23 June 2012 at Bletchley Park, England. A selection of actual full transcripts from the tests is shown and an analysis is given in each case. As a result of these tests, conclusions are drawn with regard to the sort of strategies which can perhaps lead to erroneous conclusions when one is involved as an interrogator. Such results also serve to indicate conversational directions to avoid for those machine designers who wish to create a conversational entity that performs well on the Turing test.

Effects of lying in practical Turing tests

Interpretation of utterances affects an interrogator’s determination of human from machine during live Turing tests. Here, we consider transcripts realised as a result of a series of practical Turing tests that were held on 23 June 2012 at Bletchley Park, England. The focus in this paper is to consider the effects of lying and truth-telling on the human judges by the hidden entities, whether human or a machine. Turing test transcripts provide a glimpse into short text communication, the type that occurs in emails: how does the reader determine truth from the content of a stranger’s textual message? Different types of lying in the conversations are explored, and the judge’s attribution of human or machine is investigated in each test.

Tests of sunspot number sequences: 3. Effects of regression procedures on the calibration of historic sunspot data

We use sunspot group observations from the Royal Greenwich Observatory (RGO) to investigate the effects of intercalibrating data from observers with different visual acuities. The tests are made by counting the number of groups RB above a variable cut-off threshold of observed total whole-spot area (uncorrected for foreshortening) to simulate what a lower acuity observer would have seen. The synthesised annual means of RB are then re-scaled to the full observed RGO group number RA using a variety of regression techniques. It is found that a very high correlation between RA and RB (rAB > 0.98) does not prevent large errors in the intercalibration (for example sunspot maximum values can be over 30 % too large even for such levels of rAB). In generating the backbone sunspot number (RBB), Svalgaard and Schatten (2015, this issue) force regression fits to pass through the scatter plot origin which generates unreliable fits (the residuals do not form a normal distribution) and causes sunspot cycle amplitudes to be exaggerated in the intercalibrated data. It is demonstrated that the use of Quantile-Quantile (“Q  Q”) plots to test for a normal distribution is a useful indicator of erroneous and misleading regression fits. Ordinary least squares linear fits, not forced to pass through the origin, are sometimes reliable (although the optimum method used is shown to be different when matching peak and average sunspot group numbers). However, other fits are only reliable if non-linear regression is used. From these results it is entirely possible that the inflation of solar cycle amplitudes in the backbone group sunspot number as one goes back in time, relative to related solar-terrestrial parameters, is entirely caused by the use of inappropriate and non-robust regression techniques to calibrate the sunspot data.

Tests of sunspot number sequences: 1. Using ionosonde data

More than 70 years ago it was recognised that ionospheric F2-layer critical frequencies [foF2] had a strong relationship to sunspot number. Using historic datasets from the Slough and Washington ionosondes, we evaluate the best statistical fits of foF2 to sunspot numbers (at each Universal Time [UT] separately) in order to search for drifts and abrupt changes in the fit residuals over Solar Cycles 17-21. This test is carried out for the original composite of the Wolf/Zürich/International sunspot number [R], the new “backbone” group sunspot number [RBB] and the proposed “corrected sunspot number” [RC]. Polynomial fits are made both with and without allowance for the white-light facular area, which has been reported as being associated with cycle-to-cycle changes in the sunspot number - foF2 relationship. Over the interval studied here, R, RBB, and RC largely differ in their allowance for the “Waldmeier discontinuity” around 1945 (the correction factor for which for R, RBB and RC is, respectively, zero, effectively over 20 %, and explicitly 11.6 %). It is shown that for Solar Cycles 18-21, all three sunspot data sequences perform well, but that the fit residuals are lowest and most uniform for RBB. We here use foF2 for those UTs for which R, RBB, and RC all give correlations exceeding 0.99 for intervals both before and after the Waldmeier discontinuity. The error introduced by the Waldmeier discontinuity causes R to underestimate the fitted values based on the foF2 data for 1932-1945 but RBB overestimates them by almost the same factor, implying that the correction for the Waldmeier discontinuity inherent in RBB is too large by a factor of two. Fit residuals are smallest and most uniform for RC and the ionospheric data support the optimum discontinuity multiplicative correction factor derived from the independent Royal Greenwich Observatory (RGO) sunspot group data for the same interval.