• Title/Summary/Keyword: ARMA International

Search Result 10, Processing Time 0.027 seconds

Records and Information Management Issues and Trends Traced from ARMA's 'Information Management' ('Information Management'지에 나타난 기록정보관리 분야의 이슈와 동향)

  • Yoon, Yeo Hyun;Lee, Bo Ram;Choi, Dong Woon;Choi, Yun Jin;Yim, Jin Hee
    • Journal of the Korean Society for information Management
    • /
    • v.33 no.4
    • /
    • pp.245-267
    • /
    • 2016
  • ARMA International has been leading education and publication in records and information management industry worldwide. This study aimed to trace issues and trends in international records and information management field through analysing the articles brought up in Information Management, which is ARMA International's official magazine. Further analysis was also conducted on noticeable subjects from the magazine in order to realize where we currently are. Scanning the contents of Information Management would definitely provide with implications and suggestions to Korean private companies as well as records management communities.

Volatility analysis and Prediction Based on ARMA-GARCH-typeModels: Evidence from the Chinese Gold Futures Market (ARMA-GARCH 모형에 의한 중국 금 선물 시장 가격 변동에 대한 분석 및 예측)

  • Meng-Hua Li;Sok-Tae Kim
    • Korea Trade Review
    • /
    • v.47 no.3
    • /
    • pp.211-232
    • /
    • 2022
  • Due to the impact of the public health event COVID-19 epidemic, the Chinese futures market showed "Black Swan". This has brought the unpredictable into the economic environment with many commodities falling by the daily limit, while gold performed well and closed in the sunshine(Yan-Li and Rui Qian-Wang, 2020). Volatility is integral part of financial market. As an emerging market and a special precious metal, it is important to forecast return of gold futures price. This study selected data of the SHFE gold futures returns and conducted an empirical analysis based on the generalised autoregressive conditional heteroskedasticity (GARCH)-type model. Comparing the statistics of AIC, SC and H-QC, ARMA (12,9) model was selected as the best model. But serial correlation in the squared returns suggests conditional heteroskedasticity. Next part we established the autoregressive moving average ARMA-GARCH-type model to analysis whether Volatility Clustering and the leverage effect exist in the Chinese gold futures market. we consider three different distributions of innovation to explain fat-tailed features of financial returns. Additionally, the error degree and prediction results of different models were evaluated in terms of mean squared error (MSE), mean absolute error (MAE), Theil inequality coefficient(TIC) and root mean-squared error (RMSE). The results show that the ARMA(12,9)-TGARCH(2,2) model under Student's t-distribution outperforms other models when predicting the Chinese gold futures return series.

Simplified Machine Diagnosis Techniques Using ARMA Model of Absolute Deterioration Factor with Weight

  • Takeyasu, Kazuhiro;Ishii, Yasuo
    • Industrial Engineering and Management Systems
    • /
    • v.8 no.4
    • /
    • pp.247-256
    • /
    • 2009
  • In mass production industries such as steel making that have large equipment, sudden stops of production process due to machine failure can cause severe problems. To prevent such situations, machine diagnosis techniques play important roles. Many methods have been developed focusing on this subject. In this paper, we propose a method for the early detection of the failure on rotating machine, which is the most common theme in the machine failure detection field. A simplified method of calculating autocorrelation function is introduced and is utilized for ARMA model identification. Furthermore, an absolute deterioration factor such as Bicoherence is introduced. Machine diagnosis can be executed by this simplified calculation method of system parameter distance with weight. Proposed method proved to be a practical index for machine diagnosis by numerical examples.

Adaptive Kalman Filter Design for an Alignment System with Unknown Sway Disturbance

  • Kim, Jong-Kwon;Woo, Gui-Aee;Cho, Kyeum-Rae
    • International Journal of Aeronautical and Space Sciences
    • /
    • v.3 no.1
    • /
    • pp.86-94
    • /
    • 2002
  • The initial alignment of inertial platform for navigation system was considered. An adaptive filtering technique is developed for the system with unknown and varying sway disturbance. It is assumed that the random sway motion is the second order ARMA(Auto Regressive Moving Average) model and performed parameter identification for unknown parameters. Designed adaptive filter contain both a Kalman filter and a self-tuning filter. This filtering system can automatically adapt to varying environmental conditions. To verify the robustness of the filtering system, the computer simulation was performed with unknown and varying sway disturbance.

Useful Control Equations for Practitioners on Dynamic Process Control

  • Suzuki, Tomomichi;Ojima, Yoshikazu
    • International Journal of Quality Innovation
    • /
    • v.3 no.2
    • /
    • pp.174-182
    • /
    • 2002
  • System identification and controller formulation are essential in dynamic process control. In system identification, data for system identification are obtained, and then they are analyzed so that the system model of the process is built, identified, and diagnosed. In controller formulation, the control equation is derived based on the result of the system identification. There has been much theoretical research on system identification and controller formulation. These theories are very useful when they are appropriately applied. To our regret, however, these theories are not always effectively applied in practice because the engineers and the operators who manage the process often do not have the necessary understanding of required time series analysis methods. On the other hand, because of widespread use of statistical packages, system identification such as estimating ARMA models can be done with little understanding of time series analysis methods. Therefore, it might be said that the most theoretically difficult part in practice is the controller formulation. In this paper, lists of control equations are proposed as a useful tool for practitioners to use. The tool supports bridging the gap between theory and practice in dynamic process control. Also, for some models, the generalized control equations are obtained.

The Contagion of Covid-19 Pandemic on The Volatilities of International Crude Oil Prices, Gold, Exchange Rates and Bitcoin

  • OZTURK, M. Busra Engin;CAVDAR, Seyma Caliskan
    • The Journal of Asian Finance, Economics and Business
    • /
    • v.8 no.3
    • /
    • pp.171-179
    • /
    • 2021
  • In the international markets, financial variables can be volatile and may affect each other, especially in the crisis times. COVID-19, which began in China in 2019 and spread to many countries of the world, created a crisis not only in the global health system but also in the international financial markets and economy. The purpose of this study is to analyze the contagious effect of the COVID-19 pandemic on the volatility of selected financial variables such as Bitcoin, gold, oil price, and exchange rates and the connections between the volatilities of these variables during the pandemic. For this aim, we use the ARMA-EGARCH model to measure the impact of volatility and shocks. In other words, it is aimed to measure whether the impact of the shock on the financial variables of the contagiousness of the epidemic is also transmitted to the markets. The data was collected from secondary and daily data from September 2th 2019 to December 20th, 2020. It can be said that the findings obtained have statistically significant effects on the conditional variability of the variables. Therefore, there are findings that the shocks in the market are contaminated with each other.

Extension of the VSACF for Modelling Seasonal Time Series (계절적 시계열 모형화를 위한 VSACF 의 확장)

  • 전태준
    • Journal of the Korean Operations Research and Management Science Society
    • /
    • v.16 no.1
    • /
    • pp.68-75
    • /
    • 1991
  • The purpose of this thesis is to develop the new technique for the analysis of seasonal time series by extending the vector sample auto-correlation function(VSACF), which was developed for ARMA modelling procedure. After the problems of VSACF for modelling seasonal time series are investigated, the adjacent variance is defined and used for decomposing the seasonal factor from the seasonal time series. The seasonal indices are calculated and the VSACF is applied to the transformed series. The automatic procedure for modelling seasonal time series is suggested and applied to the real data, the international airline passenger travel.

  • PDF

Gust Response and Active Suppress based on Reduced Order Models

  • Yang, Guowei;Nie, Xueyuan;Zheng, Guannan
    • International Journal of Aerospace System Engineering
    • /
    • v.2 no.2
    • /
    • pp.44-49
    • /
    • 2015
  • A gust response analyses method based on Reduced Order Models (ROMs) was developed in the paper. Firstly, taken random signal as the input signal and adopt Single Input-Multi-Output (SIMO) training fashion, a ROM based on Auto-Regressive and Moving Average model (ARMA) was established and validated with the comparison of CFD/CSD and experiment. Then, by introducing control surface deflection and control laws, flutter active suppress was studied. Lastly, through filtering and transferring function, the gust temporal signal is obtained based on Dryden gust model, and gust response and suppress were simulated.

Do Roads Enhance Regional Trade? Evidence Based on China's Provincial Data

  • RAHMAN, Imran Ur;SHARMA, Buddhi Prasad;FETUU, Enitilina;YOUSAF, Muhammad
    • The Journal of Asian Finance, Economics and Business
    • /
    • v.7 no.12
    • /
    • pp.657-664
    • /
    • 2020
  • We investigate the impact of roads and highways within the provinces on the regional trade of China using the augmented Gravity Model and theory of modeling trade. We take a panel data covering 31 provinces of China over 20 years period (1998-2017) for the estimations. We apply ARMA-OLS model, fixed and random effects, and robust findings by Hausman test. The results imply that road and highway lengths within the provinces have a significantly positive impact on the value of the province-wise exports. The positive impact is due to the fact the increased coverage of roads and highways increase accessibility to resources and mobility of goods and services within the regions. Moreover, employment in the transportation sector, per capita GDP and population of the provinces also illustrate positive and significant influence on regional exports and trade. The impact of China's WTO accession on regional exports has been positive, while the financial crisis has had a negative impact. The year dummies show that, in the years following the financial crisis, China was able to regress from the external shock as trade within the provinces increased. The increase in exports after financial crisis is mainly due to the government policies and support to every province.

Estimation of Smoothing Constant of Minimum Variance and Its Application to Shipping Data with Trend Removal Method

  • Takeyasu, Kazuhiro;Nagata, Keiko;Higuchi, Yuki
    • Industrial Engineering and Management Systems
    • /
    • v.8 no.4
    • /
    • pp.257-263
    • /
    • 2009
  • Focusing on the idea that the equation of exponential smoothing method (ESM) is equivalent to (1, 1) order ARMA model equation, new method of estimation of smoothing constant in exponential smoothing method is proposed before by us which satisfies minimum variance of forecasting error. Theoretical solution was derived in a simple way. Mere application of ESM does not make good forecasting accuracy for the time series which has non-linear trend and/or trend by month. A new method to cope with this issue is required. In this paper, combining the trend removal method with this method, we aim to improve forecasting accuracy. An approach to this method is executed in the following method. Trend removal by a linear function is applied to the original shipping data of consumer goods. The combination of linear and non-linear function is also introduced in trend removal. For the comparison, monthly trend is removed after that. Theoretical solution of smoothing constant of ESM is calculated for both of the monthly trend removing data and the non monthly trend removing data. Then forecasting is executed on these data. The new method shows that it is useful especially for the time series that has stable characteristics and has rather strong seasonal trend and also the case that has non-linear trend. The effectiveness of this method should be examined in various cases.