Forecasting interest rates: A Comparative assessment of some second generation non-linear model

Modelling and forecasting of interest rates has traditionally proceeded in the framework of linear stationary models such as ARMA and VAR, but only with moderate success. We examine here four models which account for several specific features of real world asset prices such as non-stationarity and non-linearity. Our four candidate models are based respectively on wavelet analysis, mixed spectrum analysis, non-linear ARMA models with Fourier coefficients, and the Kalman filter. These models are applied to weekly data on interest rates in India, and their forecasting performance is evaluated vis-…-vis three GARCH models (GARCH (1,1), GARCH-M (1,1) and EGARCH (1,1)) as well as the random walk model. The Kalman filter model emerges at the top, with wavelet and mixed spectrum models also showing considerable promise.Interest rates, wavelets, mixed spectra, non-linear ARMA, Kalman filter, GARCH, Forecast encompassing

FORECASTING INTEREST RATES - A COMPARATIVE ASSESSMENT OF SOME SECOND GENERATION NON-LINEAR MODELS

Modelling and forecasting of interest rates has traditionally proceeded in the framework of linear stationary models such as ARMA and VAR, but only with moderate success. We examine here four models which account for several specific features of real world asset prices such as non-stationarity and non-linearity. Our four candidate models are based respectively on wavelet analysis, mixed spectrum analysis, non-linear ARMA models with Fourier coefficients, and the Kalman filter. These models are applied to weekly data on interest rates in India, and their forecasting performance is evaluated vis--vis three GARCH models (GARCH (1,1), GARCH-M (1,1) and EGARCH (1,1)) as well as the random walk model. The Kalman filter model emerges at the top, with wavelet and mixed spectrum models also showing considerable promise.interest rates, wavelets, mixed spectra, non-linear ARMA, Kalman filter, GARCH, Forecast encompassing.

Non-Cognitive Abilities and Spanish Regional Differences in Student Performance in PISA 2009

The goal of this paper is to analyze the role that non-cognitive skills and, in particular, regional differences in those skills, play on the observed differences in 15-year-old student’s academic performance, across Spanish regions, on PISA 2009. Previous research has shown the relevance of differences in student’s personal, family and school characteristics in accounting for academic differences across Spanish regions but it has also found that a sizeable part of the observed differences remained unexplained. We have found that differences in the distribution of certain non-cognitive skills associated to academic performance like focus, perseverance and resilience play a prominent role in accounting for differences in student performance in PISA 2009. We observe these skills by developing new measures of student effort on standardized tests. In particular, our estimates suggest that a standard deviation reduction in the dispersion of non-cognitive skills across Spanish regions would lead to a 25% reduction in the magnitude of the observed differences in student performance across regions. This is a relevant effect as, for example, a one standard deviation reduction in the regional dispersion of parent’s educational levels or occupational status would only lead to at most a 2% reduction in the magnitude of observed differences in performance on PISA across Spanish regions. Put plainly, a substantial portion of the regional variation in test scores appears attributable to effort on the PISA test, and not necessarily just differences in actual knowledge

Genetic polymorphisms of the GNRH1 and GNRHR genes and risk of breast cancer in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3)

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract Background Gonadotropin releasing hormone (GNRH1) triggers the release of follicle stimulating hormone and luteinizing hormone from the pituitary. Genetic variants in the gene encoding GNRH1 or its receptor may influence breast cancer risk by modulating production of ovarian steroid hormones. We studied the association between breast cancer risk and polymorphisms in genes that code for GNRH1 and its receptor (GNRHR) in the large National Cancer Institute Breast and Prostate Cancer Cohort Consortium (NCI-BPC3). Methods We sequenced exons of GNRH1 and GNRHR in 95 invasive breast cancer cases. Resulting single nucleotide polymorphisms (SNPs) were genotyped and used to identify haplotype-tagging SNPs (htSNPS) in a panel of 349 healthy women. The htSNPs were genotyped in 5,603 invasive breast cancer cases and 7,480 controls from the Cancer Prevention Study-II (CPS-II), European Prospective Investigation on Cancer and Nutrition (EPIC), Multiethnic Cohort (MEC), Nurses' Health Study (NHS), and Women's Health Study (WHS). Circulating levels of sex steroids (androstenedione, estradiol, estrone and testosterone) were also measured in 4713 study subjects. Results Breast cancer risk was not associated with any polymorphism or haplotype in the GNRH1 and GNRHR genes, nor were there any statistically significant interactions with known breast cancer risk factors. Polymorphisms in these two genes were not strongly associated with circulating hormone levels. Conclusion Common variants of the GNRH1 and GNRHR genes are not associated with risk of invasive breast cancer in Caucasians.Published versio

Plasma Elaidic Acid Level as Biomarker of Industrial Trans Fatty Acids and Risk of Weight Change: Report from the EPIC Study

Background Few epidemiological studies have examined the association between dietary trans fatty acids and weight gain, and the evidence remains inconsistent. The main objective of the study was to investigate the prospective association between biomarker of industrial trans fatty acids and change in weight within the large study European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Methods Baseline plasma fatty acid concentrations were determined in a representative EPIC sample from the 23 participating EPIC centers. A total of 1,945 individuals were followed for a median of 4.9 years to monitor weight change. The association between elaidic acid level and percent change of weight was investigated using a multinomial logistic regression model, adjusted by length of follow-up, age, energy, alcohol, smoking status, physical activity, and region. Results In women, doubling elaidic acid was associated with a decreased risk of weight loss (odds ratio (OR) = 0.69, 95% confidence interval (CI) = 0.55-0.88, p = 0.002) and a trend was observed with an increased risk of weight gain during the 5-year follow-up (OR = 1.23, 95% CI = 0.97-1.56, p = 0.082) (p-trend<.0001). In men, a trend was observed for doubling elaidic acid level and risk of weight loss (OR = 0.82, 95% CI = 0.66-1.01, p = 0.062) while no significant association was found with risk of weight gain during the 5-year follow-up (OR = 1.08, 95% CI = 0.88-1.33, p = 0.454). No association was found for saturated and cis-monounsaturated fatty acids. Conclusions These data suggest that a high intake of industrial trans fatty acids may decrease the risk of weight loss, particularly in women. Prevention of obesity should consider limiting the consumption of highly processed foods, the main source of industrially-produced trans fatty acids

Non-invasive risk scores for prediction of type 2 diabetes (EPIC-InterAct) : a validation of existing models

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A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci.

We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10⁻¹²) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10⁻¹¹) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10⁻⁷) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10⁻¹¹) and a tag SNP for NAT2 acetylation status (P = 4 × 10⁻¹¹), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis

A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci.

We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10⁻¹²) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10⁻¹¹) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10⁻⁷) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10⁻¹¹) and a tag SNP for NAT2 acetylation status (P = 4 × 10⁻¹¹), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis

Identification of a novel susceptibility locus at 13q34 and refinement of the 20p12.2 region as a multi-signal locus associated with bladder cancer risk in individuals of european ancestry

Candidate gene and genome-wide association studies (GWAS) have identified 15 independent genomic regions associated with bladder cancer risk. In search for additional susceptibility variants, we followed up on four promising single-nucleotide polymorphisms (SNPs) that had not achieved genome-wide significance in 6911 cases and 11 814 controls (rs6104690, rs4510656, rs5003154 and rs4907479, P &lt; 1 7 10(-6)), using additional data from existing GWAS datasets and targeted genotyping for studies that did not have GWAS data. In a combined analysis, which included data on up to 15 058 cases and 286 270 controls, two SNPs achieved genome-wide statistical significance: rs6104690 in a gene desert at 20p12.2 (P = 2.19 7 10(-11)) and rs4907479 within the MCF2L gene at 13q34 (P = 3.3 7 10(-10)). Imputation and fine-mapping analyses were performed in these two regions for a subset of 5551 bladder cancer cases and 10 242 controls. Analyses at the 13q34 region suggest a single signal marked by rs4907479. In contrast, we detected two signals in the 20p12.2 region-the first signal is marked by rs6104690, and the second signal is marked by two moderately correlated SNPs (r(2) = 0.53), rs6108803 and the previously reported rs62185668. The second 20p12.2 signal is more strongly associated with the risk of muscle-invasive (T2-T4 stage) compared with non-muscle-invasive (Ta, T1 stage) bladder cancer (case-case P 64 0.02 for both rs62185668 and rs6108803). Functional analyses are needed to explore the biological mechanisms underlying these novel genetic associations with risk for bladder cancer