In order to master the future operation and stability of power grid exactly, and gasp the weak point accurately, the requirement of power data quality become strict, and the data timeliness of power gird change into o...In order to master the future operation and stability of power grid exactly, and gasp the weak point accurately, the requirement of power data quality become strict, and the data timeliness of power gird change into outstandingly more and more, because of this, in this paper propose the SMS notifying method of intra-day scheduling data based on safely data principle. The principle is mainly complied with the data source existed or not, the data is coincident to the power grid model, the data is unbroken or not and it is reasonable with the physical reality, then it can obtain better convergence and reasonable intra-day check power data. In order to accelerate the information and network pace of the power grid, the SMS notifying can monitoring data quality without time delay. It dredge the vast path for the future power market into use with the wide range, then, can more effective to ensure the convergence and accuracy of safe check calculation, it provides an effective guarantee with the safe and stable operation of the power grid, in the same way, it is also an efficient method to provides effective guarantee for power grid safe operation from the data source.展开更多
As the crypto-asset ecosystem matures,the use of high-frequency data has become increasingly common in decentralized finance literature.Using bibliometric analysis,we characterize the existing cryptocurrency literatur...As the crypto-asset ecosystem matures,the use of high-frequency data has become increasingly common in decentralized finance literature.Using bibliometric analysis,we characterize the existing cryptocurrency literature that employs high-frequency data.We highlighted the most influential authors,articles,and journals based on 189 articles from the Scopus database from 2015 to 2022.This approach enables us to identify emerging trends and research hotspots with the aid of co-citation and cartographic analyses.It shows knowledge expansion through authors’collaboration in cryptocurrency research with co-authorship analysis.We identify four major streams of research:(i)return prediction and measurement of cryptocurrency volatility,(ii)(in)efficiency of cryptocurrencies,(iii)price dynamics and bubbles in cryptocurrencies,and(iv)the diversification,safe haven,and hedging properties of Bitcoin.We conclude that highly traded cryptocurrencies’investment features and economic outcomes are analyzed predominantly on a tick-by-tick basis.This study also provides recommendations for future studies.展开更多
This paper firstly analyzes the Brexit’s impact on the US stock market using a novel interval methodology. The interval-valued dummy variables are proposed to measure the direction and magnitudes of the changes in th...This paper firstly analyzes the Brexit’s impact on the US stock market using a novel interval methodology. The interval-valued dummy variables are proposed to measure the direction and magnitudes of the changes in the inter-day trend and the intra-day volatility of S&P500 returns simultaneously. It is found that both the trend and the volatility of S&P500 returns increased before the Brexit. Besides, the Brexit negatively affected S&P500 returns’ trend in the short term after the event,while its impact on market volatility was positive, which slowly decayed across time. Furthermore, a new interesting finding is that there are both short-term momentum effects(i.e., positive autocorrelation of trends) and volatility clustering in stock markets.展开更多
We report the progress on Very Long Baseline Interferometry(VLBI) observations of Gigahertz Peaked Spectrum(GPS) radio sources,and single-dish observations of active galactic nuclei(AGNs).The GPS sources are a kind of...We report the progress on Very Long Baseline Interferometry(VLBI) observations of Gigahertz Peaked Spectrum(GPS) radio sources,and single-dish observations of active galactic nuclei(AGNs).The GPS sources are a kind of young AGNs observable in radio.From our VLBI observations at 1.6 and 5 GHz with the European VLBI Network(EVN) including the Urumqi and Shanghai stations,most GPS sources show compact doubles with sizes less than 1 kiloparsec.We have classified the sources into double-lobes,core-jets,and complex structures according to the spectral indices as well as images.We also estimated the values of the jet viewing angle for the symmetric objects.In addition,we are monitoring a few samples of AGNs with the Urumqi 25-meter radio telescope,in order to find flux variability.We detected rapid flux variability in quasar 1156+295,and relatively slow variability in a few of the others.The origin of the rapid variability is discussed.Moreover,we launched a radio-optical monitoring program called Fermi-AGN in 2009.展开更多
Trading rules performing well on a given data set seldom lead to promising out-of-sample results, a problem which is a consequence of the in-sample data snooping bias. Efforts to justify the selection of trading rules...Trading rules performing well on a given data set seldom lead to promising out-of-sample results, a problem which is a consequence of the in-sample data snooping bias. Efforts to justify the selection of trading rules by assessing the out-of-sample performance will not really remedy this predica- ment either, because they are prone to be trapped in what is known as the out-of-sample data-snooping bias. Our approach to curb the data-snooping bias consists of constructing a framework for trading rule selection using a-priori robustness strategies, where robustness is gauged on the basis of time- series bootstrap and multi-objective criteria. This approach focuses thus on building robustness into the process of trading rule selection at an early stage, rather than on an ex-post assessment of trading rule fitness. Intra-day FX market data constitute the empirical basis of the proposed investigations. Trading rules are selected from a wide universe created by evolutionary computation tools. The authors show evidence of the benefit of this approach in terms of indirect forecasting accuracy when investing in FX markets.展开更多
This paper proposes a double Markov model of the double continuous auction for describing intra-day price changes. The model splits intra-day price changes as the repetition of one tick price moves and assumes order a...This paper proposes a double Markov model of the double continuous auction for describing intra-day price changes. The model splits intra-day price changes as the repetition of one tick price moves and assumes order arrivals are independent Poisson random processes. The dynamic process of price formation is described by a birth-death process of the double M/M/1 server queue corresponding to the best bid/ask. The initial depths of the best bid and ask are defined as different constants depending on the last price change. Thus, the price changes in the model follow a first-order Markov process. As the initial depth of the best bid/ask is originally larger than that of the opposite side when the last price is down/up, the model may explain the negative autocorrelations of the price of the best bid/ask. The estimated parameters are based on the real tick-by-tick data of the Nikkei 225 futures listed in Osaka Stock Exchanges. The authors find the model accurately predicts the returns of Osaka Stock Exchange average.展开更多
文摘In order to master the future operation and stability of power grid exactly, and gasp the weak point accurately, the requirement of power data quality become strict, and the data timeliness of power gird change into outstandingly more and more, because of this, in this paper propose the SMS notifying method of intra-day scheduling data based on safely data principle. The principle is mainly complied with the data source existed or not, the data is coincident to the power grid model, the data is unbroken or not and it is reasonable with the physical reality, then it can obtain better convergence and reasonable intra-day check power data. In order to accelerate the information and network pace of the power grid, the SMS notifying can monitoring data quality without time delay. It dredge the vast path for the future power market into use with the wide range, then, can more effective to ensure the convergence and accuracy of safe check calculation, it provides an effective guarantee with the safe and stable operation of the power grid, in the same way, it is also an efficient method to provides effective guarantee for power grid safe operation from the data source.
文摘As the crypto-asset ecosystem matures,the use of high-frequency data has become increasingly common in decentralized finance literature.Using bibliometric analysis,we characterize the existing cryptocurrency literature that employs high-frequency data.We highlighted the most influential authors,articles,and journals based on 189 articles from the Scopus database from 2015 to 2022.This approach enables us to identify emerging trends and research hotspots with the aid of co-citation and cartographic analyses.It shows knowledge expansion through authors’collaboration in cryptocurrency research with co-authorship analysis.We identify four major streams of research:(i)return prediction and measurement of cryptocurrency volatility,(ii)(in)efficiency of cryptocurrencies,(iii)price dynamics and bubbles in cryptocurrencies,and(iv)the diversification,safe haven,and hedging properties of Bitcoin.We conclude that highly traded cryptocurrencies’investment features and economic outcomes are analyzed predominantly on a tick-by-tick basis.This study also provides recommendations for future studies.
基金partially supported by the National Natural Science Foundation of China under Grant Nos.71703156, 71701199, 71988101, 72073126Fujian Provincial Key Laboratory of Statistics (Xiamen University) under Grant No. 201601。
文摘This paper firstly analyzes the Brexit’s impact on the US stock market using a novel interval methodology. The interval-valued dummy variables are proposed to measure the direction and magnitudes of the changes in the inter-day trend and the intra-day volatility of S&P500 returns simultaneously. It is found that both the trend and the volatility of S&P500 returns increased before the Brexit. Besides, the Brexit negatively affected S&P500 returns’ trend in the short term after the event,while its impact on market volatility was positive, which slowly decayed across time. Furthermore, a new interesting finding is that there are both short-term momentum effects(i.e., positive autocorrelation of trends) and volatility clustering in stock markets.
基金supported by the National Basic Research Program of China (Grant No. 2009CB824800)the National Natural Science Foundation of China (Grant No. 10773019)
文摘We report the progress on Very Long Baseline Interferometry(VLBI) observations of Gigahertz Peaked Spectrum(GPS) radio sources,and single-dish observations of active galactic nuclei(AGNs).The GPS sources are a kind of young AGNs observable in radio.From our VLBI observations at 1.6 and 5 GHz with the European VLBI Network(EVN) including the Urumqi and Shanghai stations,most GPS sources show compact doubles with sizes less than 1 kiloparsec.We have classified the sources into double-lobes,core-jets,and complex structures according to the spectral indices as well as images.We also estimated the values of the jet viewing angle for the symmetric objects.In addition,we are monitoring a few samples of AGNs with the Urumqi 25-meter radio telescope,in order to find flux variability.We detected rapid flux variability in quasar 1156+295,and relatively slow variability in a few of the others.The origin of the rapid variability is discussed.Moreover,we launched a radio-optical monitoring program called Fermi-AGN in 2009.
文摘Trading rules performing well on a given data set seldom lead to promising out-of-sample results, a problem which is a consequence of the in-sample data snooping bias. Efforts to justify the selection of trading rules by assessing the out-of-sample performance will not really remedy this predica- ment either, because they are prone to be trapped in what is known as the out-of-sample data-snooping bias. Our approach to curb the data-snooping bias consists of constructing a framework for trading rule selection using a-priori robustness strategies, where robustness is gauged on the basis of time- series bootstrap and multi-objective criteria. This approach focuses thus on building robustness into the process of trading rule selection at an early stage, rather than on an ex-post assessment of trading rule fitness. Intra-day FX market data constitute the empirical basis of the proposed investigations. Trading rules are selected from a wide universe created by evolutionary computation tools. The authors show evidence of the benefit of this approach in terms of indirect forecasting accuracy when investing in FX markets.
基金supported by the National Natural Science Foundation of China under Grant Nos.71173060,71031003the Fundamental Research Funds for the Central Universities under Grant No.HIT.HSS.201120partially supported by JSPS KAKENHI under Grant No.22560059
文摘This paper proposes a double Markov model of the double continuous auction for describing intra-day price changes. The model splits intra-day price changes as the repetition of one tick price moves and assumes order arrivals are independent Poisson random processes. The dynamic process of price formation is described by a birth-death process of the double M/M/1 server queue corresponding to the best bid/ask. The initial depths of the best bid and ask are defined as different constants depending on the last price change. Thus, the price changes in the model follow a first-order Markov process. As the initial depth of the best bid/ask is originally larger than that of the opposite side when the last price is down/up, the model may explain the negative autocorrelations of the price of the best bid/ask. The estimated parameters are based on the real tick-by-tick data of the Nikkei 225 futures listed in Osaka Stock Exchanges. The authors find the model accurately predicts the returns of Osaka Stock Exchange average.
