A Security Check on the Dow Jones Industrial Average

This paper investigates performance attribution measures as a basis for constraining portfolio optimization. We employ optimizations that minimize conditional value-at-risk and investigate two performance attributes, asset allocation (AA) and the selection effect (SE), as constraints on asset weights. The test portfolio consists of stocks from the Dow Jones Industrial Average index. Values for the performance attributes are established relative to two benchmarks, equi-weighted and price-weighted portfolios of the same stocks. Performance of the optimized portfolios is judged using comparisons of cumulative price and the risk-measures: maximum drawdown, Sharpe ratio, Sortino–Satchell ratio and Rachev ratio. The results suggest that achieving SE performance thresholds requires larger turnover values than that required for achieving comparable AA thresholds. The results also suggest a positive role in price and risk-measure performance for the imposition of constraints on AA and SE.

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Appendix Six. Functions of Border Security Check and Administration

The Right to Leave and Return and Chinese Migration Law ◽

10.1163/ej.9789004156142.i-428.96 ◽

2007 ◽

pp. 343-344

Keyword(s):

Border Security ◽

Security Check

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Experimentally feasible security check forn-qubit quantum secret sharing

Physical Review A ◽

10.1103/physreva.82.062311 ◽

2010 ◽

Vol 82 (6) ◽

Cited By ~ 35

Author(s):

Stefan Schauer ◽

Marcus Huber ◽

Beatrix C. Hiesmayr

Keyword(s):

Secret Sharing ◽

Quantum Secret Sharing ◽

Security Check

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Performance Analysis of a Security-Check System with Four Types of Inspection Channels for High-Speed Rail Stations in China

Smart Service Systems, Operations Management, and Analytics - Springer Proceedings in Business and Economics ◽

10.1007/978-3-030-30967-1_2 ◽

2019 ◽

pp. 7-16 ◽

Cited By ~ 1

Author(s):

Chia-Hung Wang ◽

Xiaojing Wu

Keyword(s):

Performance Analysis ◽

High Speed ◽

High Speed Rail ◽

Check System ◽

Security Check

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Mexican Stock Exchange Performance after the Crisis of 2008: Application of Data Mining

Dimensión Empresarial ◽

10.15665/dem.v18i(1).2246 ◽

2020 ◽

Vol 18 ((1)) ◽

Author(s):

Eliseo Ramírez Reyes ◽

Arturo Morales Castro ◽

Néstor Juan Sanabria Landazábal

Keyword(s):

Neural Networks ◽

Default Risk ◽

Regression Models ◽

Prediction Models ◽

Stock Exchange ◽

Sovereign Default ◽

Linear Regression Models ◽

Exchange Performance ◽

Sovereign Default Risk ◽

Dow Jones Industrial Average

Different prediction models are explored to analyze the performance of the Mexican Stock Exchange (PQI) after the 2008 crisis. These models have demonstrated a good prognostic capacity for both multivariable and univariable approaches given their non-parametric characteristics. The selected variables were: Dow Jones Industrial Average Index (DJIA), CPI, International Reserves (IR), CETES28, USDMX exchange rate, (M1) and the sovereign default risk of Mexico (MRDS). The models were evaluated with MAPE and compared with linear regression models (LR) and neural networks (NN). The results show that the models have a similar performance according to the percentages of error they presented.

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A Queueing Analysis of a Security-Check System with Two Types of Inspection Channels

Proceedings of the 2018 International Conference on Mathematics, Modelling, Simulation and Algorithms (MMSA 2018) ◽

10.2991/mmsa-18.2018.23 ◽

2018 ◽

Cited By ~ 2

Author(s):

Chia-Hung Wang

Keyword(s):

Queueing Analysis ◽

Check System ◽

Security Check

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Single step estimation of ARMA roots for non-fundamental nonstationary fractional models

Econometrics Journal ◽

10.1093/ectj/utac001 ◽

2022 ◽

Author(s):

Ignacio N Lobato ◽

Carlos Velasco

Keyword(s):

Stock Market ◽

Strong Evidence ◽

Long Memory ◽

Trading Volume ◽

Moving Average ◽

Single Step ◽

Arma Process ◽

Dow Jones Industrial Average ◽

Fractional Models ◽

Stock Market Trading

Abstract We propose a single step estimator for the autoregressive and moving-average roots (without imposing causality or invertibility restrictions) of a nonstationary Fractional ARMA process. These estimators employ an efficient tapering procedure, which allows for a long memory component in the process, but avoid estimating the nonstationarity component, which can be stochastic and/or deterministic. After selecting automatically the order of the model, we robustly estimate the AR and MA roots for trading volume for the thirty stocks in the Dow Jones Industrial Average Index in the last decade. Two empirical results are found. First, there is strong evidence that stock market trading volume exhibits non-fundamentalness. Second, non-causality is more common than non-invertibility.

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