• East Asian Economic Review
• /
• v.27 no.3
• /
• pp.213-242
• /
• 2023

This paper investigates whether the price of cryptocurrency is determined by the US dollar index, the price of investment assets such gold and oil, and the implied volatility of the KOSPI. Overall, the returns on cryptocurrencies are best predicted by the trading volume of the cryptocurrency both in-sample and out-of-sample. The estimates of gold and the dollar index are negative in the return prediction, though they are not significant. The dollar index, gold, and the cryptocurrencies seem to share characteristics which hedging instruments have in common. When investors take notice of the imminent market risks, they increase the demand for one of these assets and thereby increase the returns on the asset. The most notable result in the out-of-sample predictability is the predictability of the returns on value-weighted portfolio by gold. The empirical results show that the restricted model fails to encompass the unrestricted model. Therefore, the unrestricted model is significant in improving out-of-sample predictability of the portfolio returns using gold. From the empirical analyses, we can conclude that in-sample predictability cannot guarantee out-of-sample predictability and vice versa. This may shed light on the disparate results between in-sample and out-of-sample predictability in a large body of previous literature.

• Journal of Computing Science and Engineering
• /
• v.8 no.1
• /
• pp.34-42
• /
• 2014

Time-predictability of computing is critical for hard real-time and safety-critical systems. However, currently there is no metric available to quantitatively evaluate time-predictability, a feature crucial to the design of time-predictable processors. This paper first proposes the concept of architectural time-predictability, which separates the time variation due to hardware architectural/microarchitectural design from that due to software. We then propose the standard deviation of clock cycles per instruction (CPI), a new metric, to measure architectural time-predictability. Our experiments confirm that the standard deviation of CPI is an effective metric to evaluate and compare architectural time-predictability for different processors.

• Atmosphere
• /
• v.30 no.4
• /
• pp.335-346
• /
• 2020

Three free parameters included in a cumulus parameterization are optimized by using micro-genetic algorithm for three precipitation cases occurred in the Korea Peninsula during the summer season in order to reduce biases in a regional model associated with the uncertainties of the parameters and thus to improve the predictability of precipitation. The first parameter is the one that determines the threshold in convective trigger condition. The second parameter is the one that determines boundary layer forcing in convective closure. Finally, the third parameter is the one used in calculating conversion parameter determining the fraction of condensate converted to convective precipitation. Optimized parameters reduce the occurrence of convections by suppressing the trigger of convection. The reduced convection occurrence decreases light precipitation but increases heavy precipitation. The sensitivity experiments are conducted to examine the effects of the optimized parameters on the predictability of precipitation. The predictability of precipitation is the best when the three optimized parameters are applied to the parameterization at the same time. The first parameter most dominantly affects the predictability of precipitation. Short-range forecasts for July 2018 are also conducted to statistically assess the precipitation predictability. It is found that the predictability of precipitation is consistently improved with the optimized parameters.

• Ocean and Polar Research
• /
• v.43 no.2
• /
• pp.53-63
• /
• 2021

Changes in a marine environment have a broad socioeconomic implication on fisheries and their relevant industries so that there has been a growing demand for the medium-range (months to years) prediction of the marine environment Using a medium-range ocean prediction model (Ocean Mid-range prediction System, OMIDAS) for the northwest Pacific, this study attempted to assess seasonal difference in the mid-range predictability of the sea surface temperature (SST), focusing on the Korea seas characterized as a complex marine system. A three-month re-forecast experiment was conducted for each of the four seasons in 2016 starting from January, forced with Climate Forecast System version 2 (CFSv2) forecast data. The assessment using relative root-mean-square-error was taken for the last month SST of each experiment. Compared to the CFSv2, the OMIDAS revealed a better prediction skill for the Korea seas SST, particularly in the Yellow sea mainly due to a more realistic representation of the topography and current systems. Seasonally, the OMIDAS showed better predictability in the warm seasons (spring and summer) than in the cold seasons (fall and winter), suggesting seasonal dependency in predictability of the Korea seas. In addition, the mid-range predictability for the Korea seas significantly varies depending on regions: the predictability was higher in the East Sea than in the Yellow Sea. The improvement in the seasonal predictability for the Korea seas by OMIDAS highlights the importance of a regional ocean modeling system for a medium-range marine prediction.

• East Asian Economic Review
• /
• v.23 no.4
• /
• pp.333-351
• /
• 2019

We use a data-mining bootstrap procedure to investigate the predictability test in the eight Asia-Pacific regional stock markets using in-sample and out-of-sample forecasting models. We address ourselves to the data-mining bias issues by using the data-mining bootstrap procedure proposed by Inoue and Kilian and applied to the US stock market data by Rapach and Wohar. The empirical findings show that stock returns are predictable not only in-sample but out-of-sample in Hong Kong, Malaysia, Singapore, and Korea with a few exceptions for some forecasting horizons. However, we find some significant disparity between in-sample and out-of-sample predictability in the Korean stock market. For Hong Kong, Malaysia, and Singapore, stock returns have predictable components both in-sample and out-of-sample. For the US, Australia, and Canada, we do not find any evidence of return predictability in-sample and out-of-sample with a few exceptions. For Japan, stock returns have a predictable component with price-earnings ratio as a forecasting variable for some out-of-sample forecasting horizons.

• Atmosphere
• /
• v.17 no.1
• /
• pp.27-44
• /
• 2007

The purpose of this study is to investigate predictability of the seasonal simulation by the METRI (Meteorological Research Institute) AGCM (Atmospheric General Circulation Model), which is a long-term prediction model for the METRI 3-month prediction system. We examine the performance skill of climate simulation and predictability by the analysis of variance of the METRI AGCM, focusing on the precipitation, 850 hPa temperature, and 500 hPa geopotential height. According to the result, the METRI AGCM shows systematic errors with seasonal march, and represents large errors over the equatorial region, compared to the observation. Also, the response of the METRI AGCM by the variation of the sea surface temperature is obvious for the wintertime and springtime. However, the METRI AGCM does not show the significant ENSO-related signal in autumn. In case of prediction over the east Asian region, errors between the prediction results and the observation are not quite large with the lead-time. However, in the predictability assessment using the analysis of variance method, longer lead-time makes the prediction better, and the predictability becomes better in the springtime.

• Journal of Preventive Medicine and Public Health
• /
• v.20 no.1 s.21
• /
• pp.114-119
• /
• 1987

The author investigated the effect of some variables such as age, sex and the experience of past vaccination on the validity of PHA. The changing pattern of the validity with the change of PHA diagnostic criteria, and the relationship between PHA test result and RIA Ratio Unit were also studied. The results obtained were as follow; 1) No statistically significant difference was found in sensitivity, specificity and negative predictability by sex, but positive predictability was significantly higher in male than that in female. 2) Positive predictability was shown to become higher with the increase of age and nagative predictability was found to be significally different among age groups, but no statistically significant difference was found in sensitivity and specificity by age group. 3) Significantly low specificity and high positive predictability were found in past vaccined group, but no statistically significant difference was found in sensitivity and negative predictability between past vaccined group and non-vaccined group. 4) False negative cases by PHA were found to be the weak positive reactors by RIA and false positive rate of PHA was as high as 46.3 per cent. 5) Sensitivity and specificity of PHA at the diagnostic criteria of HBsAb titer 1:2 were 98.4% and 53.8% respectively, but after increasing the HBsAb titer to 1:64 as the diagnostic criteria the results were 60.0% and 95.6% respectively.

• Journal of Korean Academy of Nursing Administration
• /
• v.14 no.3
• /
• pp.249-259
• /
• 2008

Purpose: This study was performed to identify the patient characteristics significantly affecting nursing outcomes and their predictability in gastrointestinal surgery patients. Method: The subjects were 149 abdominal surgery patients from 3 general surgical nursing units of 3 general hospitals. Two instruments were used to measure nursing outcomes and acuity of the subjects. The nursing outcomes were measured at post-operation 4 and 7days using review of patients' records, observation of patients, and interviews with patients by a trained nurse. For data analysis, T-test or ANOVA, Pearson Correlation and Stepwise Multiple Regression were done. Result: Age, severity score, diagnosis, cancer or not, operation site were the subjects' characteristics that were significantly related to the nursing outcomes in both post-operation 4 and 7days. Cancer or not, age, diagnosis and severity score were the significant predictors for the scores of nursing outcome in post-operation 4days and the predictability was 34.9%. The predictability of cancer or not was highest, 22.6%. Age, diagnosis and cancer or not were the significant predictors for the scores of nursing outcome in post-operation 7days and the predictability was 27.8%. The predictability of age was highest, 17.3%. Conclusions: The patient characteristics affecting nursing outcomes should be considered when nursing care is planned and provided. Especially, careful attention should be given to the patients with cancer and older age. And, these patient characteristics should be adjusted for correct estimation of the effectiveness of nursing interventions on nursing outcomes.

• Atmosphere
• /
• v.24 no.4
• /
• pp.503-514
• /
• 2014

Evaluation of predictability of numerical models for tropical cyclone track was performed using along-and cross-track component. The along-and cross-track bias were useful indicators that show the numerical models predictability associated with cause of errors. Since forecast errors, standard deviation and consistency index of along-track component were greater than those of cross-track component, there was some rooms for improvement in alongtrack component. There was an overall slow bias. The most accurate model was JGSM for 24-hour forecast and ECMWF for 48~96-hour forecast in direct position error, along-track error and cross-track error. ECMWF and GFS had a high variability for 24-hour forecast. The results of predictability by track type showed that most significant errors of tropical cyclone track forecast were caused by the failure to estimate the recurvature phenomenon.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.12
• /
• pp.2218-2224
• /
• 2016

Opportunistic routing is designed for an environment where there is no stable end-to-end routing path between source node and destination node, and messages are forwarded via intermittent contacts between nodes and routed using a store-carry-forward mechanism. In this paper, we consider PRoPHET(Probabilistic Routing Protocol using History of Encounters and Transitivity) protocol as a base opportunistic routing protocol and propose an efficient context-aware opportunistic routing protocol by using the context information of delivery predictability and node type, e.g., pedestrian, car, and tram. In the proposed protocol, the node types of sending node and receiving node are checked. Then, if either sending node or receiving node is tram, messages are forwarded by comparing the delivery predictability of receiving node with predefined delivery predictability thresholds depending on the combination of sending node and receiving node types. Otherwise, messages are forwarded if the delivery predictability of receiving node is higher than that of sending node, as defined in PRoPHET protocol. Finally, we analyze the performance of the proposed protocol from the aspect of delivery ratio, overhead ratio, and delivery latency. Simulation results show that the proposed protocol has better delivery ratio, overhead ratio, and delivery latency than PRoPHET protocol in most of the considered simulation environments.