• 제목/요약/키워드: risk forecasting

검색결과 219건 처리시간 0.022초

Causal temporal convolutional neural network를 이용한 변동성 지수 예측 (Forecasting volatility index by temporal convolutional neural network)

  • 신지원;신동완
    • 응용통계연구
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    • 제36권2호
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    • pp.129-139
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    • 2023
  • 변동성의 예측은 자산의 리스크에 대비하는 데에 중요한 역할을 하기때문에 필수적이다. 인공지능을 통하여 이러한 복잡한 특성을 지닌 변동성 예측을 시도하였는데 기존 시계열 예측에 적합하다 알려진 LSTM (1997)과 GRU (2014)은 기울기 소실로 인한 문제, 방대한 연산량의 문제, 그로 인한 메모리양의 문제 등이 존재하였다. 변동성 데이터는 비정상성(non-stationarity)과 정상성(stationarity)을 모두 가지고 있는 특성이 있으며, 자산 가격 하방 쇼크에 더 큰 폭으로 상승하는 비대칭성과 상당한 장기 기억성, 시장에 큰 사건이 발생할 때 기존의 값들에 비해 이상치라 할 수 있을 정도의 예측할 수 없는 큰 값이 발생하는 특성들이 존재한다. 이렇게 여러 가지 복잡한 특성들은 하나의 모형으로 구조화되기 어려워서 전통적인 방식의 모형으로는 변동성에 대한 예측력을 높이기 어려운 면이 있다. 이러한 문제를 해결하기 위해 1D CNN의 발전된 형태인 causal TCN (causal temporal convolutional network) 모형을 변동성 예측에 적용하고, 예측력을 최대화 할 수 있는 TCN 구조를 설계하고자 하였다. S&P 500, DJIA, Nasdaq 지수에 해당하는 변동성 지수 VIX, VXD, and VXN, 에 대하여 예측력 비교를 하였으며, TCN 모형이 RNN 계열의 모형보다도 전반적으로 예측력이 높음을 확인하였다.

기계학습알고리즘을 이용한 위험회복지수의 개발과 활용 (Development and Application of Risk Recovery Index using Machine Learning Algorithms)

  • 김선웅
    • Journal of Information Technology Applications and Management
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    • 제23권4호
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    • pp.25-39
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    • 2016
  • Asset prices decline sharply and stock markets collapse when financial crisis happens. Recently we have encountered more frequent financial crises than ever. 1998 currency crisis and 2008 global financial crisis triggered academic researches on early warning systems that aim to detect the symptom of financial crisis in advance. This study proposes a risk recovery index for detection of good opportunities from financial market instability. We use SVM classifier algorithms to separate recovery period from unstable financial market data. Input variables are KOSPI index and V-KOSPI200 index. Our SVM algorithms show highly accurate forecasting results on testing data as well as training data. Risk recovery index is derived from our SVM-trained outputs. We develop a trading system that utilizes the suggested risk recovery index. The trading result records very high profit, that is, its annual return runs to 121%.

복부초음파 영상에서 담낭담석을 예측하는 혈액학적 수치의 분석 (Analysis of Hematological Factor to Predict of the Gallbladder Stone in Abdominal Ultrasound Images)

  • 안현;황철환;임인철
    • 한국방사선학회논문지
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    • 제11권3호
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    • pp.131-137
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    • 2017
  • 본 연구는 부산 경남지역의 담낭담석의 위험인자를 알아보고자 하였다. 실험대상은 2016년 6월~12월까지 2016년 12월까지 부산 P병원을 내원하여 복부초음파를 실시한 대상으로 하였다. 그 중 복부초음파와 혈청학적 검사를 동시에 실시한 353명을 대상으로 위험인자를 분석하였다. 초음파 검사 상 담낭담석과 관련있는 위험인자들의 통계분석은 독립표본 t검정(independent t-test)과 카이제곱 검정(chi-square test)을 시행하였다. 차이검정 결과를 고려하여 독립변수에 대한 상대 위험비(odds ratio, OR) 산출을 위해 다중 로지스틱 회귀분석(multiple logistic regression analysis)을 시행하여 변수들로부터 예측모형을 산정하여 타당성을 검정하였다. 그 결과 담낭담석 위험인자로 확인된 연령, ${\gamma}GTP$로 예측모형 및 예측 확률값을 산출하였다. 연령에서 민감도 49.7%, 특이도 82.2%를 보였으며, ROC 곡선하면적이 0.724를 나타내었다. ${\gamma}GTP$에서는 민감도 69.3%, 특이도 62.4%를 보였으며, ROC 곡선하면적이 0.699를 나타내어 예측모형의 타당성을 확인할 수 있었다.

The Development of a Risk Management System in the Field of Industrial Safety in the Republic of Kazakhstan

  • Kudryavtsev, Sergey S.;Yemelin, Pavel V.;Yemelina, Natalya K.
    • Safety and Health at Work
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    • 제9권1호
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    • pp.30-41
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    • 2018
  • Background: The purpose of the work is to develop a system that allows processing of information for analysis and industrial risk management, to monitor the level of industrial safety and to perform necessary measures aimed at the prevention of accidents, casualties, and development of professional diseases for effective management of industrial safety at hazardous industrial sites. Methods: Risk assessment of accidents and incidents is based on expert evaluations. Based on the lists of criteria parameters and their possible values, provided by the experts, a unified information and analytical database is compiled, which is included in the final interrogation questionnaires. Risk assessment of industrial injuries and occupational diseases is based on statistical methods. Results: The result of the research is the creation of Guidelines for risk management on hazardous industrial sites of the Republic of Kazakhstan. The Guidelines determine the directions and methods of complex assessment of the state of industrial safety and labor protection and they could be applied as methodological basis at the development of preventive measures for emergencies, casualties, and incidents at hazardous industrial sites. Conclusion: Implementation of the information-analytical system of risk level assessment allows to analyze the state of risk of a possible accident at industrial sites, make valid management decisions aimed at the prevention of emergencies, and monitor the effectiveness of accident prevention measures.

Robustness of Bayes forecast to Non-normality

  • Bansal, Ashok K.
    • Journal of the Korean Statistical Society
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    • 제7권1호
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    • pp.11-16
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    • 1978
  • Bayesian procedures are in vogue to revise the parameter estimates of the forecasting model in the light of actual time series data. In this paper, we study the Bayes forecast for demand and the risk when (a) 'noise' and (b) mean demand rate in a constant process model have moderately non-normal probability distributions.

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부분적으로 반복되는 프로젝트를 위한 프로젝트 내$\cdot$외 학습을 이용한 프로젝트기간예측과 위험분석 (Project Duration Estimation and Risk Analysis Using Intra-and Inter-Project Learning for Partially Repetitive Projects)

  • 조성빈
    • 한국경영과학회지
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    • 제30권3호
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    • pp.137-149
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    • 2005
  • This study proposes a framework enhancing the accuracy of estimation for project duration by combining linear Bayesian updating scheme with the learning curve effect. Activities in a particular project might share resources in various forms and might be affected by risk factors such as weather Statistical dependence stemming from such resource or risk sharing might help us learn about the duration of upcoming activities in the Bayesian model. We illustrate, using a Monte Carlo simulation, that for partially repetitive projects a higher degree of statistical dependence among activity duration results in more variation in estimating the project duration in total, although more accurate forecasting Is achievable for the duration of an individual activity.

Foreign Exchange Risk Control in the Context of Supply Chain Management

  • Park, Koo-Woong
    • 유통과학연구
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    • 제13권2호
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    • pp.15-24
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    • 2015
  • Purpose - Foreign exchange risk control is in an important component in the international supply chain management. This study shows the importance of the reference period in forecasting future exchange rates with a specific illustration of KIKO currency option contracts, and suggests feasible preventive measures. Research design, data, and methodology - Using monthly Won-Dollar exchange rate data for January 1995~July 2007, I evaluate the statistical characteristics of the exchange rate for two sub-periods; 1) a shorter period after the East Asian financial crisis and 2) a longer period including the financial crisis. The key instrument of analysis is the basic normal distribution theory. Results - The difference in the reference period could lead to an unexpected development in contract implementation and a consequent financial loss. We may avoid foreign exchange loss by using derivatives such as forwards or currency options. Conclusions - We should consider not only level values but also the volatilities of financial variables in making a binding financial contract. Appropriate measures may differ depending on the specific supply chain pattern. We may extend the study with surveys on actual risk measures.

The Information Content of Option Prices: Evidence from S&P 500 Index Options

  • Ren, Chenghan;Choi, Byungwook
    • Management Science and Financial Engineering
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    • 제21권2호
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    • pp.13-23
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    • 2015
  • This study addresses the question as to whether the option prices have useful predictive information on the direction of stock markets by investigating a forecasting power of volatility curvatures and skewness premiums implicit in S&P 500 index option prices traded in Chicago Board Options Exchange. We begin by estimating implied volatility functions and risk neutral price densities every minute based on non-parametric method and then calculate volatility curvature and skewness premium using them. The rationale is that high volatility curvature or high skewness premium often leads to strong bullish sentiment among market participants. We found that the rate of return on the signal following trading strategy was significantly higher than that on the intraday buy-and-hold strategy, which indicates that the S&P500 index option prices have a strong forecasting power on the direction of stock index market. Another major finding is that the information contents of S&P 500 index option prices disappear within one minute, and so one minute-delayed signal following trading strategy would not lead to any excess return compared to a simple buy-and-hold strategy.

Identification and risk management related to construction projects

  • Boughaba, Amina;Bouabaz, Mohamed
    • Advances in Computational Design
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    • 제5권4호
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    • pp.445-465
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    • 2020
  • This paper presents a study conducted with the aim of developing a model of tendering based on a technique of artificial intelligence by managing and controlling the factors of success or failure of construction projects through the evaluation of the process of invitation to tender. Aiming to solve this problem, analysis of the current environment based on SWOT (Strengths, Weaknesses, Opportunities, and Threats) is first carried out. Analysis was evaluated through a case study of the construction projects in Algeria, to bring about the internal and external factors which affect the process of invitation to tender related to the construction projects. This paper aims to develop a mean to identify threats-opportunities and strength-weaknesses related to the environment of various national construction projects, leading to the decision on whether to continue the project or not. Following a SWOT analysis, novel artificial intelligence models in forecasting the project status are proposed. The basic principal consists in interconnecting the different factors to model this phenomenon. An artificial neural network model is first proposed, followed by a model based on fuzzy logic. A third model resulting from the combination of the two previous ones is developed as a hybrid model. A simulation study is carried out to assess performance of the three models showing that the hybrid model is better suited in forecasting the construction project status than RNN (recurrent neural network) and FL (fuzzy logic) models.

ARIMA-Intervention 시계열모형을 활용한 제주 국내선 항공여객수요 추정 (A Study on the Air Travel Demand Forecasting using time series ARIMA-Intervention Model)

  • 김민수;김기웅;박성식
    • 한국항공운항학회지
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    • 제20권1호
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    • pp.66-75
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    • 2012
  • The purpose of this study is to analyze the effect of intervention variables which may affect the air travel demand for Jeju domestic flights and to anticipate the air travel demand for Jeju domestic flights. The air travel demand forecasts for Jeju domestic flights are conducted through ARIMA-Intervention Model selecting five intervention variables such as 2002 World Cup games, SARS, novel swine-origin influenza A, Yeonpyeongdo bombardment and Japan big earthquake. The result revealed that the risk factor such as the threat of war that is a negative intervention incident and occurred in Korea has the negative impact on the air travel demand due to the response of risk aversion by users. However, when local natural disasters (earthquakes, etc) occurring in neighboring courtiers and global outbreak of an epidemic gave the negligible impact to Korea, negative intervention incident would have a positive impact on air travel demand as a response to find alternative due to rational expectation of air travel customers. Also we realize that a mega-event such as the 2002 Korea-Japan World Cup games reduced the air travel demand in a short-term period unlike the perception in which it will increase the air travel demand and travel demands in the corresponding area.