Backtesting VaR Accuracy: A New Simple Test

This paper proposes a new test of Value at Risk (VaR) validation. Our test exploits the idea that the sequence of VaR violations (Hit function) - taking value 1-α, if there is a violation, and -α otherwise - for a nominal coverage rate α verifies the properties of a martingale difference if the model used to quantify risk is adequate (Berkowitz et al., 2005). More precisely, we use the Multivariate Portmanteau statistic of Li and McLeod (1981) - extension to the multivariate framework of the test of Box and Pierce (1970) - to jointly test the absence of autocorrelation in the vector of Hit sequences for various coverage rates considered as relevant for the management of extreme risks. We show that this shift to a multivariate dimension appreciably improves the power properties of the VaR validation test for reasonable sample sizes.Value-at-Risk; Risk Management; Model Selection

Test accuracy of drug and antibody assays for predicting response to anti-Tumour Necrosis Factor treatment in Crohn’s disease : a systematic review and meta-analysis

Objective: To present meta-analytic test accuracy estimates of levels of anti-TNF and antibodies to anti-TNF to predict loss of response or lack of regaining response in anti-TNF managed Crohn’s disease patients. Methods: MEDLINE, Embase, the Cochrane Library and Science Citation Index were searched from inception to October / November 2014 to identify studies which reported 2x2 table data of the association between levels of anti-TNF or its antibodies and clinical status. Hierarchical / bivariate meta-analysis was undertaken with the user-written “metandi” package of Harbord and Whiting using Stata 11 software, for Infliximab, Adalimumab, anti-Infliximab and anti-Adalimumab levels as predictors of loss of response. Prevalence of Crohn’s disease in included studies was meta-analysed using a random effects model in MetaAnalyst software to calculate positive and negative predictive values. The search was updated in January 2017. Results: 31 studies were included in the review. Studies were heterogeneous with respect to type of test used, criteria for establishing response and loss of response, population examined, and results. Metaanalytic summary point estimates for sensitivity and specificity were 65.7% and 80.6% for Infliximab trough levels and 56% and 79% for antibodies to Infliximab, respectively. Pooled results for Adalimumab trough levels and antibodies to Adalimumab were similar. Pooled positive and negative predictive values ranged between 70% and 80% implying that between 20% and 30% of both positive and negative test results may be incorrect in predicting loss of response. Conclusion: The available evidence suggests that these tests have modest predictive accuracy for clinical status, direct test accuracy comparisons in the same population are needed. More clinical trial evidence from test-treat studies is required before the clinical utility of the tests can be reliably evaluated

Sacrificing Accuracy for Reduced Computation: Cascaded Inference Based on Softmax Confidence

We study the tradeoff between computational effort and accuracy in a cascade of deep neural networks. During inference, early termination in the cascade is controlled by confidence levels derived directly from the softmax outputs of intermediate classifiers. The advantage of early termination is that classification is performed using less computation, thus adjusting the computational effort to the complexity of the input. Moreover, dynamic modification of confidence thresholds allow one to trade accuracy for computational effort without requiring retraining. Basing of early termination on softmax classifier outputs is justified by experimentation that demonstrates an almost linear relation between confidence levels in intermediate classifiers and accuracy. Our experimentation with architectures based on ResNet obtained the following results. (i) A speedup of 1.5 that sacrifices 1.4% accuracy with respect to the CIFAR-10 test set. (ii) A speedup of 1.19 that sacrifices 0.7% accuracy with respect to the CIFAR-100 test set. (iii) A speedup of 2.16 that sacrifices 1.4% accuracy with respect to the SVHN test set

Segment-level evaluation of the simulated aggregation test: US corn and soybean exploratory experiment

An evaluation of the corn and soybean proportion-estimation accuracy and dot labeling accuracy of the Simulated Aggregation Test, U.S. Corn and Soybean Exploratory Experiment, is presented. These results are in turn compared with the corn and soybean proportion-estimation accuracy and dot labeling accuracy of the Classification Procedures Verification Test

Accuracy Combination Test of Classical and Modern Technical Analysis: a Case Study in Stock of PT Wijaya Karya Tbk

The research aimed to measure the accuracy and combination of Classic and Modern Technical Analysis. PT Wijaya Karya Tbk (WIKA)'s stock in two periods is the sample of research. Technical analysis was used to predict stock prices by observing changes in historical share price. Practically, technical analysis is divided into Classic Technical and Modern. Research was conducted by library study and using a computer software. Microsft Excel was used for the simulation and Chart Nexus for analyzing Modern Technical Analysis. The research period started in January 1, 2013 until December 31, 2013 and January 1, 2014 until December 31, 2014. The Classic Technical Analysis used Support, Resistance, Trendline, and Flag Patern. Meanwhile for Modern Technical Analysis used Moving Average, Stochastic, Moving Average Convergence Divergence (MACD) indicator. The Classical Technical Analysis gave less result than Modern Technical Analysis. The classical give 14 investment decisions in two periods. The average return of Classical Technical is 15,50%. Meanwhile the Modern Technical Analysis gave 18 investment decisions in two periods. The average return of Modern Technical is 18,14%. Combining Classic Technical Analysis and Modern Technical Analysis gave 20 investment decisions with the average rate of return 20,41%

The Right to Challenge the Accuracy of Breath Test Results Under Alaska Law

Section 28.90.020 of the Alaska Statutes provides that in prosecutions for drunk driving, if an offense described under this title requires that a chemical test of a person\u27s breath produce a particular result, and the chemical test is administered by a properly calibrated instrument approved by the Department of Public Safety, the result described by statute is not affected by the instrument\u27s working tolerance. This provision appears to prohibit the defense from calling into question the accuracy of a breath test by introducing evidence of uncertainty inherent in the testing procedure. The statute is problematic because due process requires that defendants be permitted to challenge the evidence presented against them. Moreover, there is a strong argument that basing conviction on a single breath sample that is within a known margin of error is a per se violation of due process, as it bases guilt or innocence on a purely fortuitous result. This Article examines the issues with Alaska\u27s statute and proposes using multiple breath tests as a simple, cost-effective solution to this potential abuse of due process