This paper employs Granger causality analysis and the generalized impulse response function(GIRF)to study the higher-order moment spillover effects among Bitcoin,stock markets,and foreign exchange markets in the U.S.U...This paper employs Granger causality analysis and the generalized impulse response function(GIRF)to study the higher-order moment spillover effects among Bitcoin,stock markets,and foreign exchange markets in the U.S.Using intraday high-frequency data,the research focuses on the interactions across higher-order moments,including volatility,jumps,skewness,and kurtosis.The results reveal significant bidirectional spillover effects between Bitcoin and traditional financial assets,particularly in terms of volatility and jump behavior,indicating that the cryptocurrency market has become a crucial component of global financial risk transmission.This study provides new theoretical perspectives and policy recommendations for global asset allocation,market regulation,and risk management,underscoring the importance of proactive management measures in addressing the complex risk interactions between cryptocurrencies and traditional financial markets.展开更多
In this study,an investigation is conducted into the phenomenon of price clustering in Bitcoin(BTC)denominated in the Japanese yen(JPY).It answers two questions using tick-by-tick data.The first is whether price clust...In this study,an investigation is conducted into the phenomenon of price clustering in Bitcoin(BTC)denominated in the Japanese yen(JPY).It answers two questions using tick-by-tick data.The first is whether price clustering exists in BTC/JPY transactions,and the other is how the scale of price clustering varies throughout a trading day.With the assistance of statistical measures,the last two digits of BTC price were discovered to cluster at the numbers that end with’00’.In addition,the scales of BTC/JPY clustering at’00’tended to decline at the specific hour intervals.This study contributes to the emerging literature on price clustering and investor behavior.展开更多
Intraday polarization angle swings of ～180° observed in two sources (QSO0917+624 and QSO 1150+812) are discussed in the framework of refractive interstellar scintillationby a continuous interstellar medium. Mode...Intraday polarization angle swings of ～180° observed in two sources (QSO0917+624 and QSO 1150+812) are discussed in the framework of refractive interstellar scintillationby a continuous interstellar medium. Model-fits to the I-, Q- and U- light curves were made for bothsources. It is shown that for the case of 0917+624 both the intraday intensity variations and thepolarization angle swing of ～180° could be explained consistently in terms of a four-componentmodel, which comprises one steady and two scintillating polarized components and one furthernon-polarized scintillating component. The polarization angle swing of ～180° observed in 1150+812,which occurred when the polarized flux density was almost constant, could not be explained in termsof refractive scintillation by a continuous medium and might be due to other mechanisms (e.g.,scintillation by interstellar clouds).展开更多
This paper proposes a simple two-step nonparametric procedure to estimate the intraday jump tail and measure the jump tail risk in asset price with noisy high frequency data. We first propose the pre-averaging thresho...This paper proposes a simple two-step nonparametric procedure to estimate the intraday jump tail and measure the jump tail risk in asset price with noisy high frequency data. We first propose the pre-averaging threshold approach to estimate the intraday jumps occurred, and then use the peaks-over-threshold (POT) method and generalized Pareto distribution (GPD) to model the intraday jump tail and further measure the jump tail risk. Finally, an empirical example further demonstrates the power of the proposed method to measure the jump tail risk under the effect of microstructure noise.展开更多
This paper builds on the literature of the relationship between oil spot and futures prices from the NYNEX market,both in their means and in their conditional volatilities,to investigate whether the association is lin...This paper builds on the literature of the relationship between oil spot and futures prices from the NYNEX market,both in their means and in their conditional volatilities,to investigate whether the association is linear or not.The novelty of this work is based on intraday data from both markets.The empirical findings indicate the presence of nonlinearities both in means and conditional volatilities.Moreover,non-linear causality estimations both in means and in volatilities reveal the presence of bi-directional causality,a fact that provides additional support to the hypothesis that both markets are driven by the same information sets.展开更多
Correlated radio-optical variations on intraday timescales have been observed （e.g. in BLO 0716＋714） and such radio intraday variability is suggested to have an intrinsic origin. Recently, multi-wavelength observat...Correlated radio-optical variations on intraday timescales have been observed （e.g. in BLO 0716＋714） and such radio intraday variability is suggested to have an intrinsic origin. Recently, multi-wavelength observations, simultaneous at radio, mm-submm, optical and hard X-rays, of 0716＋714, show that during a period of intraday/interday variations at radio and mm wavelengths, the apparent brightness temperature of the source exceeded the Compton-limit （-10^12 K） by 2-4 orders of magnitude, but no Compton catastrophe （or no high luminosity of inverse-Compton radiation） was detected. It is also found that the intraday/interday variations at mm-submm wavelengths are consistent with the evolutionary behavior of a standard synchrotron source and for the intraday/interday variations at centimeter wavelengths opacity effects can play a significant role, which is consistent with the interpretation suggested previously by Qian et al. Thus the apparent high brightness temperatures may probably be explained in terms of Doppler boosting effects due to bulk relativistic motion of the source. We will argue a scenario to simulate the correlations between the radio and optical variations on intraday timescales observed in BLO 0716＋714 in terms of a relativistic shock propagating through a jet with a dual structure.展开更多
Intraday variations of compact extragalactic radio sources in flux density and polarization are generally interpreted in terms of refractive scintillation from the continuous interstellar medium of our Galaxy. However...Intraday variations of compact extragalactic radio sources in flux density and polarization are generally interpreted in terms of refractive scintillation from the continuous interstellar medium of our Galaxy. However, continuous polarization angle swings of - 180° （for example, the one observed in the QSO 0917＋624） could not be interpreted in this way. Qian et al. have shown that the polarization angle swing observed in the QSO 1150＋812 can be explained in terms of focusing-defocusing effect by an interstellar cloud, which occults two closely-placed polarized components. Here we further show that the polarization angle swing event observed in the QSO 0917＋624 can also be explained in this way. We also found evidence for the cloud eclipsing a non-polarized （core） component during a short period out- side the swing. A particular （and specific） plasma-lens model is proposed to model-fit the polarization swing event of 0917＋624. Some physical parameters related to the plasma-lens and the source components are estimated. The brightness temperatures of the two lensed components are estimated to be -1.6× 10^13 K. Thus bulk relativistic motion with a Lorentz factor less than -20 may be sufficient to avoid the inverse - Compton catastrophe.展开更多
Using stock market data over 16 years for Chinese stock markets and over 3 years for U.S.stock markets,this study explores the explanatory power of early intraday market-wide up and down movements to the subsequent in...Using stock market data over 16 years for Chinese stock markets and over 3 years for U.S.stock markets,this study explores the explanatory power of early intraday market-wide up and down movements to the subsequent intraday returns within the same trading day.As compared to the closing of the previous trading day,we introduce two intraday market-wide up/down indicators in terms of the index return and the proportional difference in the numbers of stocks moving upwards to downwards at each minute.A time series analysis shows an economically and statistically significant positive relation between the intraday indicators and the subsequent intraday returns of the market indices.Intraday trading strategies that exploit this intraday relationship lead to monthly returns of 4.1%in the Chinese market and 2.8%in the U.S.market.In addition,the strategies are more profitable in markets with high activity of individual investors(i.e.,high trading value,low trading volume per transaction,small-cap,high B/M ratio,low institutional ownership,low price,and high number of shareholders).The results indicate that simple intraday market-wide up/down movements in the earlier trading affect the sentiment of retail investors,resulting in market movements in the same direction within the trading day.展开更多
This paper proposes a dynamic model to forecast intraday volume percentages by decomposing the trade volume into two parts: The average part as the intraday volume pattern and the residual term as the abnormal changes...This paper proposes a dynamic model to forecast intraday volume percentages by decomposing the trade volume into two parts: The average part as the intraday volume pattern and the residual term as the abnormal changes. An empirical test on data spanning half-a-year gold futures and S&P 500 futures reveals that a rolling average of the previous days' volume percentages shows great predictive ability for the average part. An SVM approach with the input pattern consisting of two categories is employed to forecast the residual term. One is the previous days' volume percentages in the same time interval and the other is the most recent volume percentages. The study shows that this dynamic SVM-based forecasting approach outperforms the other commonly used statistical methods and enhances the tracking performance of a VWAP strategy greatly.展开更多
This paper uses minute by minute data series from Chinese commodity futures markets to study patterns of intraday effect and discovers the L pattern of absolute return and volume.It is different from stock market,whic...This paper uses minute by minute data series from Chinese commodity futures markets to study patterns of intraday effect and discovers the L pattern of absolute return and volume.It is different from stock market,which has a distinctive pattern of U-shaped.The financial market microstructure theory,traders' psychology and trading mechanism are applied to explain it.Then this paper studies the factors that influence volatility of return and the lagged orders.The results show that there is a bilateral Granger causality among any two of the absolute return,volume and open interest,and it is different from the empirical results of the stock market,in the sense that there is only a unilateral Granger causal relationship from volume to absolute return.The authors also analyze the dynamic relationship among these three factors.The empirical results tell that the influence of open interest on volatility of absolute return and volume is weak,and there is a strong correlation between absolute return and volume.Some investment suggestions are offered from the analysis mentioned above.展开更多
Wind power generation has been developing rapidly in recent years.Therefore,the mechanism for promoting wind power integration becomes increasingly important.In this paper,a novel mechanism of intraday market is propo...Wind power generation has been developing rapidly in recent years.Therefore,the mechanism for promoting wind power integration becomes increasingly important.In this paper,a novel mechanism of intraday market is proposed,which can utilize updating information of wind power and effectively exploit the shiftable load.The mechanism is compatible with the existing market framework,and promotes wind power producers(WPPs)to be more competitive in the market.Thus,the WPPs could make decisions for multiple market transactions in various trading timescales according to the market price.Moreover,the WPPs can optimize their decisions continuously in the intraday market at different time points in the model.The case study on IEEE-RTS verifies the proposed method is valid and feasible.It can support wind power integration and increase the benefit of the whole system as well.展开更多
This paper analyses the herding behaviour among exchanges around the expiration of bitcoin futures traded on the Chicago Mercantile Exchange(CME).The database extends from December 2017 to October 2020,taking as a ref...This paper analyses the herding behaviour among exchanges around the expiration of bitcoin futures traded on the Chicago Mercantile Exchange(CME).The database extends from December 2017 to October 2020,taking as a reference the main exchanges that trade bitcoin(Binance,Bitfinex,Bitstamp,Coinbase,itBit,Kraken,and Gemini)and using hourly closing prices and trading volumes in bitcoin and US dollars.Adapting the proposal of Chang,Cheng and Khorana(2000)(CCK)to test conditional herding,we obtain results that indicate that the herding effect is significant during the week before expiration.After expiration,the herding effect lasts for a few hours and disappears.Information overload originating,among other causes,from sophisticated investors’strategies may generate this mimetic behaviour.The results show the relevance of intraday data applied to specific events such as expiration since the unconditional analysis shows,in general,anti-herding behaviour throughout the period of study.展开更多
This paper evaluates the efficiency of the SARFIMA model at forecasting high-frequency long memory series with especially long periods. Three other models, the ARFIMA, ARMA and PAR models, are also included to compare...This paper evaluates the efficiency of the SARFIMA model at forecasting high-frequency long memory series with especially long periods. Three other models, the ARFIMA, ARMA and PAR models, are also included to compare their forecasting performances with that of the SARFIMA model. For the artificial SARFIMA series, if the correct parameters are used for estimating and forecasting, the model performs as well as the other three models. However, if the parameters obtained by the WHI estimation are used, the performance of the SARFIMA model falls far behind that of the other models. For the empirical intraday volume series, the SARFIMA model produces the worst performance of all of the models, and the ARFIMA model performs best. The ARMA and PAR models perform very well both for the artificial series and for the intraday volume series. This result indicates that short memory models are competent in forecasting periodic long memory series.展开更多
This article presents an analysis of the economic impact of non-dispatchable generation on the cost of the energy supply. It aims to analyze the economic impact of the renewable generation in Spanish production and th...This article presents an analysis of the economic impact of non-dispatchable generation on the cost of the energy supply. It aims to analyze the economic impact of the renewable generation in Spanish production and thus to help prospective investors in renewable generation projects to analyze the situation of the Spanish electricity market. With that target, the current situation in Spain is shown and then using a MATLAB program, the economic impact of the renewable generation on the Spanish daily is analyzed.展开更多
Electricity price forecasting plays a vital role inthe strategy decision making for almost all power marketparticipants. This article investigates statistical background andpotential relations between different power ...Electricity price forecasting plays a vital role inthe strategy decision making for almost all power marketparticipants. This article investigates statistical background andpotential relations between different power market products (e.g.day-ahead prices, intraday prices, etc.). Danish and Croatianpower markets are used for the purpose of the case studyto present the methods used in this article. First, Danish andCroatian power market structures are shortly explained to clarifythe context of the problem. The data collection and preprocessingmethods are described, followed by the core focus of the study:statistical analysis. In addition to the presented histograms ofrespective power market components, we examine interrelationships through statistical analysis, demonstrating significantcorrelations both numerically and graphically. Furthermore,price spreads are investigated as a logical next step of the noticedcorrelations. Our comparative analysis of Danish and Croatianmarket peculiarities reveals three key findings: i) statisticallysignificant relationships between specific market components,ii) distinct behavioral patterns among observed factors, and iii) anopen-access analytical tool with accompanying dataset for futureresearch. Finally, the findings of this article present to marketparticipants an efficient tool to adjust business strategies andincrease profit.展开更多
With the rising extension of renewable energies, the intraday electricity markets have recorded a growingpopularity amongst traders as well as electric utilities to cope with the induced volatility of the energysupply...With the rising extension of renewable energies, the intraday electricity markets have recorded a growingpopularity amongst traders as well as electric utilities to cope with the induced volatility of the energysupply. Through their short trading horizon and continuous nature, the intraday markets offer the abilityto adjust trading decisions from the day-ahead market or reduce trading risk in a short-term notice. Producersof renewable energies utilize the intraday market to lower their forecast risk, by modifying their providedcapacities based on current forecasts. However, the market dynamics are complex due to the fact that thepower grids have to remain stable and electricity is only partly storable. Consequently, robust and intelligenttrading strategies are required that are capable to operate in the intraday market. In this work, we proposea novel autonomous trading approach based on Deep Reinforcement Learning (DRL) algorithms as a possiblesolution. For this purpose, we model the intraday trade as a Markov Decision Process (MDP) and employ theProximal Policy Optimization (PPO) algorithm as our DRL approach. A simulation framework is introducedthat enables the trading of the continuous intraday price in a resolution of one minute steps. We test ourframework in a case study from the perspective of a wind park operator. We include next to general tradeinformation both price and wind forecasts. On a test scenario of German intraday trading results from 2018,we are able to outperform multiple baselines with at least 45.24% improvement, showing the advantage of theDRL algorithm. However, we also discuss limitations and enhancements of the DRL agent, in order to increasethe performance in future works.展开更多
文摘This paper employs Granger causality analysis and the generalized impulse response function(GIRF)to study the higher-order moment spillover effects among Bitcoin,stock markets,and foreign exchange markets in the U.S.Using intraday high-frequency data,the research focuses on the interactions across higher-order moments,including volatility,jumps,skewness,and kurtosis.The results reveal significant bidirectional spillover effects between Bitcoin and traditional financial assets,particularly in terms of volatility and jump behavior,indicating that the cryptocurrency market has become a crucial component of global financial risk transmission.This study provides new theoretical perspectives and policy recommendations for global asset allocation,market regulation,and risk management,underscoring the importance of proactive management measures in addressing the complex risk interactions between cryptocurrencies and traditional financial markets.
基金supported by the Japan Society for the Promotion of Science,Grant-in-Aid for Scientific Research(C)17K03657.
文摘In this study,an investigation is conducted into the phenomenon of price clustering in Bitcoin(BTC)denominated in the Japanese yen(JPY).It answers two questions using tick-by-tick data.The first is whether price clustering exists in BTC/JPY transactions,and the other is how the scale of price clustering varies throughout a trading day.With the assistance of statistical measures,the last two digits of BTC price were discovered to cluster at the numbers that end with’00’.In addition,the scales of BTC/JPY clustering at’00’tended to decline at the specific hour intervals.This study contributes to the emerging literature on price clustering and investor behavior.
文摘Intraday polarization angle swings of ～180° observed in two sources (QSO0917+624 and QSO 1150+812) are discussed in the framework of refractive interstellar scintillationby a continuous interstellar medium. Model-fits to the I-, Q- and U- light curves were made for bothsources. It is shown that for the case of 0917+624 both the intraday intensity variations and thepolarization angle swing of ～180° could be explained consistently in terms of a four-componentmodel, which comprises one steady and two scintillating polarized components and one furthernon-polarized scintillating component. The polarization angle swing of ～180° observed in 1150+812,which occurred when the polarized flux density was almost constant, could not be explained in termsof refractive scintillation by a continuous medium and might be due to other mechanisms (e.g.,scintillation by interstellar clouds).
文摘This paper proposes a simple two-step nonparametric procedure to estimate the intraday jump tail and measure the jump tail risk in asset price with noisy high frequency data. We first propose the pre-averaging threshold approach to estimate the intraday jumps occurred, and then use the peaks-over-threshold (POT) method and generalized Pareto distribution (GPD) to model the intraday jump tail and further measure the jump tail risk. Finally, an empirical example further demonstrates the power of the proposed method to measure the jump tail risk under the effect of microstructure noise.
文摘This paper builds on the literature of the relationship between oil spot and futures prices from the NYNEX market,both in their means and in their conditional volatilities,to investigate whether the association is linear or not.The novelty of this work is based on intraday data from both markets.The empirical findings indicate the presence of nonlinearities both in means and conditional volatilities.Moreover,non-linear causality estimations both in means and in volatilities reveal the presence of bi-directional causality,a fact that provides additional support to the hypothesis that both markets are driven by the same information sets.
文摘Correlated radio-optical variations on intraday timescales have been observed （e.g. in BLO 0716＋714） and such radio intraday variability is suggested to have an intrinsic origin. Recently, multi-wavelength observations, simultaneous at radio, mm-submm, optical and hard X-rays, of 0716＋714, show that during a period of intraday/interday variations at radio and mm wavelengths, the apparent brightness temperature of the source exceeded the Compton-limit （-10^12 K） by 2-4 orders of magnitude, but no Compton catastrophe （or no high luminosity of inverse-Compton radiation） was detected. It is also found that the intraday/interday variations at mm-submm wavelengths are consistent with the evolutionary behavior of a standard synchrotron source and for the intraday/interday variations at centimeter wavelengths opacity effects can play a significant role, which is consistent with the interpretation suggested previously by Qian et al. Thus the apparent high brightness temperatures may probably be explained in terms of Doppler boosting effects due to bulk relativistic motion of the source. We will argue a scenario to simulate the correlations between the radio and optical variations on intraday timescales observed in BLO 0716＋714 in terms of a relativistic shock propagating through a jet with a dual structure.
文摘Intraday variations of compact extragalactic radio sources in flux density and polarization are generally interpreted in terms of refractive scintillation from the continuous interstellar medium of our Galaxy. However, continuous polarization angle swings of - 180° （for example, the one observed in the QSO 0917＋624） could not be interpreted in this way. Qian et al. have shown that the polarization angle swing observed in the QSO 1150＋812 can be explained in terms of focusing-defocusing effect by an interstellar cloud, which occults two closely-placed polarized components. Here we further show that the polarization angle swing event observed in the QSO 0917＋624 can also be explained in this way. We also found evidence for the cloud eclipsing a non-polarized （core） component during a short period out- side the swing. A particular （and specific） plasma-lens model is proposed to model-fit the polarization swing event of 0917＋624. Some physical parameters related to the plasma-lens and the source components are estimated. The brightness temperatures of the two lensed components are estimated to be -1.6× 10^13 K. Thus bulk relativistic motion with a Lorentz factor less than -20 may be sufficient to avoid the inverse - Compton catastrophe.
基金Financial support from the National Natural Science Foundation of China(71201112,71320107003 and 71532009)。
文摘Using stock market data over 16 years for Chinese stock markets and over 3 years for U.S.stock markets,this study explores the explanatory power of early intraday market-wide up and down movements to the subsequent intraday returns within the same trading day.As compared to the closing of the previous trading day,we introduce two intraday market-wide up/down indicators in terms of the index return and the proportional difference in the numbers of stocks moving upwards to downwards at each minute.A time series analysis shows an economically and statistically significant positive relation between the intraday indicators and the subsequent intraday returns of the market indices.Intraday trading strategies that exploit this intraday relationship lead to monthly returns of 4.1%in the Chinese market and 2.8%in the U.S.market.In addition,the strategies are more profitable in markets with high activity of individual investors(i.e.,high trading value,low trading volume per transaction,small-cap,high B/M ratio,low institutional ownership,low price,and high number of shareholders).The results indicate that simple intraday market-wide up/down movements in the earlier trading affect the sentiment of retail investors,resulting in market movements in the same direction within the trading day.
文摘This paper proposes a dynamic model to forecast intraday volume percentages by decomposing the trade volume into two parts: The average part as the intraday volume pattern and the residual term as the abnormal changes. An empirical test on data spanning half-a-year gold futures and S&P 500 futures reveals that a rolling average of the previous days' volume percentages shows great predictive ability for the average part. An SVM approach with the input pattern consisting of two categories is employed to forecast the residual term. One is the previous days' volume percentages in the same time interval and the other is the most recent volume percentages. The study shows that this dynamic SVM-based forecasting approach outperforms the other commonly used statistical methods and enhances the tracking performance of a VWAP strategy greatly.
基金supported by the National Science Fund of China under Grant Nos.71471182 and 71071170Program for New Century Excellent Talents in University under Grant No.NCET-11-0750Program for Innovation Research in Central University of Finance and Economics
文摘This paper uses minute by minute data series from Chinese commodity futures markets to study patterns of intraday effect and discovers the L pattern of absolute return and volume.It is different from stock market,which has a distinctive pattern of U-shaped.The financial market microstructure theory,traders' psychology and trading mechanism are applied to explain it.Then this paper studies the factors that influence volatility of return and the lagged orders.The results show that there is a bilateral Granger causality among any two of the absolute return,volume and open interest,and it is different from the empirical results of the stock market,in the sense that there is only a unilateral Granger causal relationship from volume to absolute return.The authors also analyze the dynamic relationship among these three factors.The empirical results tell that the influence of open interest on volatility of absolute return and volume is weak,and there is a strong correlation between absolute return and volume.Some investment suggestions are offered from the analysis mentioned above.
文摘Wind power generation has been developing rapidly in recent years.Therefore,the mechanism for promoting wind power integration becomes increasingly important.In this paper,a novel mechanism of intraday market is proposed,which can utilize updating information of wind power and effectively exploit the shiftable load.The mechanism is compatible with the existing market framework,and promotes wind power producers(WPPs)to be more competitive in the market.Thus,the WPPs could make decisions for multiple market transactions in various trading timescales according to the market price.Moreover,the WPPs can optimize their decisions continuously in the intraday market at different time points in the model.The case study on IEEE-RTS verifies the proposed method is valid and feasible.It can support wind power integration and increase the benefit of the whole system as well.
文摘This paper analyses the herding behaviour among exchanges around the expiration of bitcoin futures traded on the Chicago Mercantile Exchange(CME).The database extends from December 2017 to October 2020,taking as a reference the main exchanges that trade bitcoin(Binance,Bitfinex,Bitstamp,Coinbase,itBit,Kraken,and Gemini)and using hourly closing prices and trading volumes in bitcoin and US dollars.Adapting the proposal of Chang,Cheng and Khorana(2000)(CCK)to test conditional herding,we obtain results that indicate that the herding effect is significant during the week before expiration.After expiration,the herding effect lasts for a few hours and disappears.Information overload originating,among other causes,from sophisticated investors’strategies may generate this mimetic behaviour.The results show the relevance of intraday data applied to specific events such as expiration since the unconditional analysis shows,in general,anti-herding behaviour throughout the period of study.
文摘This paper evaluates the efficiency of the SARFIMA model at forecasting high-frequency long memory series with especially long periods. Three other models, the ARFIMA, ARMA and PAR models, are also included to compare their forecasting performances with that of the SARFIMA model. For the artificial SARFIMA series, if the correct parameters are used for estimating and forecasting, the model performs as well as the other three models. However, if the parameters obtained by the WHI estimation are used, the performance of the SARFIMA model falls far behind that of the other models. For the empirical intraday volume series, the SARFIMA model produces the worst performance of all of the models, and the ARFIMA model performs best. The ARMA and PAR models perform very well both for the artificial series and for the intraday volume series. This result indicates that short memory models are competent in forecasting periodic long memory series.
文摘This article presents an analysis of the economic impact of non-dispatchable generation on the cost of the energy supply. It aims to analyze the economic impact of the renewable generation in Spanish production and thus to help prospective investors in renewable generation projects to analyze the situation of the Spanish electricity market. With that target, the current situation in Spain is shown and then using a MATLAB program, the economic impact of the renewable generation on the Spanish daily is analyzed.
基金supported in part by the Croatian Science Foundation and the European Union through the European Social Fund under the Project of Flexibility of Converter-based Micro-grids—FLEXIBASE(PZS-2019-02-7747)in part by the European Structural and Investment Funds under KK.01.2.1.02.0066 Electric Vehicle Charging Station with Integrated Battery Storage.
文摘Electricity price forecasting plays a vital role inthe strategy decision making for almost all power marketparticipants. This article investigates statistical background andpotential relations between different power market products (e.g.day-ahead prices, intraday prices, etc.). Danish and Croatianpower markets are used for the purpose of the case studyto present the methods used in this article. First, Danish andCroatian power market structures are shortly explained to clarifythe context of the problem. The data collection and preprocessingmethods are described, followed by the core focus of the study:statistical analysis. In addition to the presented histograms ofrespective power market components, we examine interrelationships through statistical analysis, demonstrating significantcorrelations both numerically and graphically. Furthermore,price spreads are investigated as a logical next step of the noticedcorrelations. Our comparative analysis of Danish and Croatianmarket peculiarities reveals three key findings: i) statisticallysignificant relationships between specific market components,ii) distinct behavioral patterns among observed factors, and iii) anopen-access analytical tool with accompanying dataset for futureresearch. Finally, the findings of this article present to marketparticipants an efficient tool to adjust business strategies andincrease profit.
文摘With the rising extension of renewable energies, the intraday electricity markets have recorded a growingpopularity amongst traders as well as electric utilities to cope with the induced volatility of the energysupply. Through their short trading horizon and continuous nature, the intraday markets offer the abilityto adjust trading decisions from the day-ahead market or reduce trading risk in a short-term notice. Producersof renewable energies utilize the intraday market to lower their forecast risk, by modifying their providedcapacities based on current forecasts. However, the market dynamics are complex due to the fact that thepower grids have to remain stable and electricity is only partly storable. Consequently, robust and intelligenttrading strategies are required that are capable to operate in the intraday market. In this work, we proposea novel autonomous trading approach based on Deep Reinforcement Learning (DRL) algorithms as a possiblesolution. For this purpose, we model the intraday trade as a Markov Decision Process (MDP) and employ theProximal Policy Optimization (PPO) algorithm as our DRL approach. A simulation framework is introducedthat enables the trading of the continuous intraday price in a resolution of one minute steps. We test ourframework in a case study from the perspective of a wind park operator. We include next to general tradeinformation both price and wind forecasts. On a test scenario of German intraday trading results from 2018,we are able to outperform multiple baselines with at least 45.24% improvement, showing the advantage of theDRL algorithm. However, we also discuss limitations and enhancements of the DRL agent, in order to increasethe performance in future works.
