Analysis of stock recruitment (SR) data is most often done by fitting various SR relationship curves to the data. Fish population dynamics data often have stochastic variations and measurement errors, which usually re...Analysis of stock recruitment (SR) data is most often done by fitting various SR relationship curves to the data. Fish population dynamics data often have stochastic variations and measurement errors, which usually result in a biased regression analysis. This paper presents a robust regression method, least median of squared orthogonal distance (LMD), which is insensitive to abnormal values in the dependent and independent variables in a regression analysis. Outliers that have significantly different variance from the rest of the data can be identified in a residual analysis. Then, the least squares (LS) method is applied to the SR data with defined outliers being down weighted. The application of LMD and LMD based Reweighted Least Squares (RLS) method to simulated and real fisheries SR data is explored.展开更多
This study shows that the stock-recruitment relationship (SRR) for Pacific bluefin tuna and the Pacific stock of Japanese sardine can be expressed by the same SRR model. That is, (environmental factors), where Rt and ...This study shows that the stock-recruitment relationship (SRR) for Pacific bluefin tuna and the Pacific stock of Japanese sardine can be expressed by the same SRR model. That is, (environmental factors), where Rt and St-1 denote the recruitment in year t and spawning stock biomass in year t - 1, and f(.) is a function that evaluates the effect of environmental factors in year t. The simulations showed that when the fluctuation in environmental factors cyclically changed, 1) the shape of the apparent SRR assumed clockwise loops for the shorter maturity age of fish, and 2) the apparent SRR comprised scattered anticlockwise loops for the longer maturity age of fish. These features coincided well with those observed. This finding gives us a new paradigm in SRR, which is far different from the concept that has predominated in the field for more than 60 years.展开更多
After the 19th National Congress of the Chinese Communist Party,the introduction of the economic theory has promoted the integration of the global socialist market economy.Thereafter,this integration of the domestic a...After the 19th National Congress of the Chinese Communist Party,the introduction of the economic theory has promoted the integration of the global socialist market economy.Thereafter,this integration of the domestic and international market has been preliminarily completed,the role of the factor market in resource allocation has been improved,and a sturdy environment has been established for the development of Chinese enterprises.With the effective implementation of a series of policies after the financial system reform,the roles of the financial market in regulating macro-economy and revitalizing the market have become increasingly prominent.In regard to that,it has effectively promoted the financial market as a trade to"enrich people."This paper analyzes the relationship between monetary policy and stock market liquidity in terms of the influence of the former on the latter and suggests strategies to enhance the liquidity effect of monetary policy.展开更多
The article first addresses the following questions:“Why does gross domestic product(GDP)rises,but the stock market value falls?”;“Among the macroeconomic factors,which factor has a greater impact on the promotion ...The article first addresses the following questions:“Why does gross domestic product(GDP)rises,but the stock market value falls?”;“Among the macroeconomic factors,which factor has a greater impact on the promotion of investment value in the securities market?”.With these questions in mind,we put forward a hypothesis emphasizing on the impact of macroeconomic factors on the value of the stock market based on existing research and used the regression method to verify this hypothesis.The following conclusions were drawn:(1)variables that have a positive nonlinear relationship with stock market value include balance of payments surplus,rising GDP level,M1,the whole society’s fixed asset investment,and national per capita disposable income;(2)variables that have a negative nonlinear relationship with stock market value include deposit,loan interest rate,new RMB loan amount,consumer price index(CPI),and producer price index;(3)deposit reserve ratio has an S-shaped curve relationship with stock market value;(4)exchange rate has an inverted U-shaped curve relationship with stock market value.展开更多
Human activities widely exhibit a power-law distribution.Considering stock trading as a typical human activity in the financial domain,the first aim of this paper is to validate whether the well-known power-law distri...Human activities widely exhibit a power-law distribution.Considering stock trading as a typical human activity in the financial domain,the first aim of this paper is to validate whether the well-known power-law distribution can be observed in this activity.Interestingly,this paper determines that the number of accumulated lead–lag days between stock pairs meets the power-law distribution in both the U.S.and Chinese stock markets based on 10 years of trading data.Based on this finding this paper adopts the power-law distribution to formally define the lead–lag effect,detect stock pairs with the lead–lag effect,and then design a pure lead–lag investment strategy as well as enhancement investment strategies by integrating the lead–lag strategy into classic alpha-factor strategies.Tests conducted on 20 different alpha-factor strategies demonstrate that both perform better than the selected benchmark strategy and that the lead–lag strategy provides useful signals that significantly improve the performance of basic alpha-factor strategies.Our results therefore indicate that the lead–lag effect may provide effective information for designing more profitable investment strategies.展开更多
This study proposes a simulation model that well reproduces the spawning stock biomass of Pacific bluefin tuna. Environmental factors were chosen to estimate the recruitment per spawning stock biomass, and a simulatio...This study proposes a simulation model that well reproduces the spawning stock biomass of Pacific bluefin tuna. Environmental factors were chosen to estimate the recruitment per spawning stock biomass, and a simulation model that well reproduced the spawning stock biomass was developed. Then, effects of various fisheries regulations were evaluated using the simulation study. The results were as follows: 1) arctic oscillations, Pacific decadal oscillations and the recruitment number of the Pacific stock of Japanese sardine were chosen as the environmental factors that determined the recruitment per spawning stock biomass;2) spawning stock biomass could be well reproduced using a model that reproduced the recruitment per spawning stock biomass and the survival process of the population that included the effect of fishing;and 3) the effects of various fisheries regulation could be evaluated using the simulation model mentioned above. The effective regulation in the simulations conducted in this paper was a prohibition of fishing for 0- and 1-year-old fish in terms of recovering the spawning stock biomass. The reduction of fishing mortality coefficients for all age fish to 50% of actual values also showed a good performance. The recent reductions of the recruitment and spawning stock biomass were likely caused by heavy harvesting, especially of immature fish, since 2004.展开更多
This study developed a recruitment forecasting model based on a new concept of the stock recruitment relationship. No density-dependent effect in the relationship was assumed in the model, which showed that fluctuatio...This study developed a recruitment forecasting model based on a new concept of the stock recruitment relationship. No density-dependent effect in the relationship was assumed in the model, which showed that fluctuations in recruitment and spawning stock biomass of Japanese sardine in the northwestern Pacific can be explained mainly by environmental factors and the effects of fishing. The February Arctic Oscillation (AO) and sea surface temperature over the southern area of the Kuroshio Extension (30 - 35°N and 145 - 180°E;KEST) were used as the environmental factors. The recruitment forecasting model is proposed: The values for recruitment (), spawning stock biomass, (), in year t, forecast by this model accurately reproduced those estimated by tuning virtual population analysis (VPA), and the pattern of variability in the stock recruitment relationship was also reproduced well. In conclusion, a density-dependent effect does not necessarily have to be included to explain the large variations in recruitment and the spawning stock biomass of the Japanese sardine.展开更多
Delay-difference models are intermediate between simple surplus-production models and complicated age-structured models. Such intermediate models are more efficient and require less data than age-structured models. In...Delay-difference models are intermediate between simple surplus-production models and complicated age-structured models. Such intermediate models are more efficient and require less data than age-structured models. In this study, a delay-difference model was applied to fit catch and catch per unit effort(CPUE) data(1975–2011) of the southern Atlantic albacore(Thunnus alalunga) stock. The proposed delay-difference model captures annual fluctuations in predicted CPUE data better than Fox model. In a Monte Carlo simulation, white noises(CVs) were superimposed on the observed CPUE data at four levels. Relative estimate error was then calculated to compare the estimated results with the true values of parameters α and β in Ricker stock-recruitment model and the catchability coefficient q. α is more sensitive to CV than β and q. We also calculated an 80% percentile confidence interval of the maximum sustainable yield(MSY, 21756 t to 23408 t; median 22490 t) with the delay-difference model. The yield of the southern Atlantic albacore stock in 2011 was 24122 t, and the estimated ratios of catch against MSY for the past seven years were approximately 1.0. We suggest that care should be taken to protect the albacore fishery in the southern Atlantic Ocean. The proposed delay-difference model provides a good fit to the data of southern Atlantic albacore stock and may be a useful choice for the assessment of regional albacore stock.展开更多
With the highly integration of the Internet world and the real world, Internet information not only provides real-time and effective data for financial investors, but also helps them understand market dynamics, and en...With the highly integration of the Internet world and the real world, Internet information not only provides real-time and effective data for financial investors, but also helps them understand market dynamics, and enables investors to quickly identify relevant financial events that may lead to stock market volatility. However, in the research of event detection in the financial field, many studies are focused on micro-blog, news and other network text information. Few scholars have studied the characteristics of financial time series data. Considering that in the financial field, the occurrence of an event often affects both the online public opinion space and the real transaction space, so this paper proposes a multi-source heterogeneous information detection method based on stock transaction time series data and online public opinion text data to detect hot events in the stock market. This method uses outlier detection algorithm to extract the time of hot events in stock market based on multi-member fusion. And according to the weight calculation formula of the feature item proposed in this paper, this method calculates the keyword weight of network public opinion information to obtain the core content of hot events in the stock market. Finally, accurate detection of stock market hot events is achieved.展开更多
文摘Analysis of stock recruitment (SR) data is most often done by fitting various SR relationship curves to the data. Fish population dynamics data often have stochastic variations and measurement errors, which usually result in a biased regression analysis. This paper presents a robust regression method, least median of squared orthogonal distance (LMD), which is insensitive to abnormal values in the dependent and independent variables in a regression analysis. Outliers that have significantly different variance from the rest of the data can be identified in a residual analysis. Then, the least squares (LS) method is applied to the SR data with defined outliers being down weighted. The application of LMD and LMD based Reweighted Least Squares (RLS) method to simulated and real fisheries SR data is explored.
文摘This study shows that the stock-recruitment relationship (SRR) for Pacific bluefin tuna and the Pacific stock of Japanese sardine can be expressed by the same SRR model. That is, (environmental factors), where Rt and St-1 denote the recruitment in year t and spawning stock biomass in year t - 1, and f(.) is a function that evaluates the effect of environmental factors in year t. The simulations showed that when the fluctuation in environmental factors cyclically changed, 1) the shape of the apparent SRR assumed clockwise loops for the shorter maturity age of fish, and 2) the apparent SRR comprised scattered anticlockwise loops for the longer maturity age of fish. These features coincided well with those observed. This finding gives us a new paradigm in SRR, which is far different from the concept that has predominated in the field for more than 60 years.
文摘After the 19th National Congress of the Chinese Communist Party,the introduction of the economic theory has promoted the integration of the global socialist market economy.Thereafter,this integration of the domestic and international market has been preliminarily completed,the role of the factor market in resource allocation has been improved,and a sturdy environment has been established for the development of Chinese enterprises.With the effective implementation of a series of policies after the financial system reform,the roles of the financial market in regulating macro-economy and revitalizing the market have become increasingly prominent.In regard to that,it has effectively promoted the financial market as a trade to"enrich people."This paper analyzes the relationship between monetary policy and stock market liquidity in terms of the influence of the former on the latter and suggests strategies to enhance the liquidity effect of monetary policy.
文摘The article first addresses the following questions:“Why does gross domestic product(GDP)rises,but the stock market value falls?”;“Among the macroeconomic factors,which factor has a greater impact on the promotion of investment value in the securities market?”.With these questions in mind,we put forward a hypothesis emphasizing on the impact of macroeconomic factors on the value of the stock market based on existing research and used the regression method to verify this hypothesis.The following conclusions were drawn:(1)variables that have a positive nonlinear relationship with stock market value include balance of payments surplus,rising GDP level,M1,the whole society’s fixed asset investment,and national per capita disposable income;(2)variables that have a negative nonlinear relationship with stock market value include deposit,loan interest rate,new RMB loan amount,consumer price index(CPI),and producer price index;(3)deposit reserve ratio has an S-shaped curve relationship with stock market value;(4)exchange rate has an inverted U-shaped curve relationship with stock market value.
基金supported by the National Natural Science Foundation of China(72171059,71771041)the Fundamental Research Funds for the Central Universities(FRFCU5710000220)the Natural Science Foundation of Heilongjiang Province,China(No.YQ2020G003).
文摘Human activities widely exhibit a power-law distribution.Considering stock trading as a typical human activity in the financial domain,the first aim of this paper is to validate whether the well-known power-law distribution can be observed in this activity.Interestingly,this paper determines that the number of accumulated lead–lag days between stock pairs meets the power-law distribution in both the U.S.and Chinese stock markets based on 10 years of trading data.Based on this finding this paper adopts the power-law distribution to formally define the lead–lag effect,detect stock pairs with the lead–lag effect,and then design a pure lead–lag investment strategy as well as enhancement investment strategies by integrating the lead–lag strategy into classic alpha-factor strategies.Tests conducted on 20 different alpha-factor strategies demonstrate that both perform better than the selected benchmark strategy and that the lead–lag strategy provides useful signals that significantly improve the performance of basic alpha-factor strategies.Our results therefore indicate that the lead–lag effect may provide effective information for designing more profitable investment strategies.
文摘This study proposes a simulation model that well reproduces the spawning stock biomass of Pacific bluefin tuna. Environmental factors were chosen to estimate the recruitment per spawning stock biomass, and a simulation model that well reproduced the spawning stock biomass was developed. Then, effects of various fisheries regulations were evaluated using the simulation study. The results were as follows: 1) arctic oscillations, Pacific decadal oscillations and the recruitment number of the Pacific stock of Japanese sardine were chosen as the environmental factors that determined the recruitment per spawning stock biomass;2) spawning stock biomass could be well reproduced using a model that reproduced the recruitment per spawning stock biomass and the survival process of the population that included the effect of fishing;and 3) the effects of various fisheries regulation could be evaluated using the simulation model mentioned above. The effective regulation in the simulations conducted in this paper was a prohibition of fishing for 0- and 1-year-old fish in terms of recovering the spawning stock biomass. The reduction of fishing mortality coefficients for all age fish to 50% of actual values also showed a good performance. The recent reductions of the recruitment and spawning stock biomass were likely caused by heavy harvesting, especially of immature fish, since 2004.
文摘This study developed a recruitment forecasting model based on a new concept of the stock recruitment relationship. No density-dependent effect in the relationship was assumed in the model, which showed that fluctuations in recruitment and spawning stock biomass of Japanese sardine in the northwestern Pacific can be explained mainly by environmental factors and the effects of fishing. The February Arctic Oscillation (AO) and sea surface temperature over the southern area of the Kuroshio Extension (30 - 35°N and 145 - 180°E;KEST) were used as the environmental factors. The recruitment forecasting model is proposed: The values for recruitment (), spawning stock biomass, (), in year t, forecast by this model accurately reproduced those estimated by tuning virtual population analysis (VPA), and the pattern of variability in the stock recruitment relationship was also reproduced well. In conclusion, a density-dependent effect does not necessarily have to be included to explain the large variations in recruitment and the spawning stock biomass of the Japanese sardine.
基金supported by the Fundamental Research Funds for the Central Universities of China (Grant No. 201022001)
文摘Delay-difference models are intermediate between simple surplus-production models and complicated age-structured models. Such intermediate models are more efficient and require less data than age-structured models. In this study, a delay-difference model was applied to fit catch and catch per unit effort(CPUE) data(1975–2011) of the southern Atlantic albacore(Thunnus alalunga) stock. The proposed delay-difference model captures annual fluctuations in predicted CPUE data better than Fox model. In a Monte Carlo simulation, white noises(CVs) were superimposed on the observed CPUE data at four levels. Relative estimate error was then calculated to compare the estimated results with the true values of parameters α and β in Ricker stock-recruitment model and the catchability coefficient q. α is more sensitive to CV than β and q. We also calculated an 80% percentile confidence interval of the maximum sustainable yield(MSY, 21756 t to 23408 t; median 22490 t) with the delay-difference model. The yield of the southern Atlantic albacore stock in 2011 was 24122 t, and the estimated ratios of catch against MSY for the past seven years were approximately 1.0. We suggest that care should be taken to protect the albacore fishery in the southern Atlantic Ocean. The proposed delay-difference model provides a good fit to the data of southern Atlantic albacore stock and may be a useful choice for the assessment of regional albacore stock.
文摘With the highly integration of the Internet world and the real world, Internet information not only provides real-time and effective data for financial investors, but also helps them understand market dynamics, and enables investors to quickly identify relevant financial events that may lead to stock market volatility. However, in the research of event detection in the financial field, many studies are focused on micro-blog, news and other network text information. Few scholars have studied the characteristics of financial time series data. Considering that in the financial field, the occurrence of an event often affects both the online public opinion space and the real transaction space, so this paper proposes a multi-source heterogeneous information detection method based on stock transaction time series data and online public opinion text data to detect hot events in the stock market. This method uses outlier detection algorithm to extract the time of hot events in stock market based on multi-member fusion. And according to the weight calculation formula of the feature item proposed in this paper, this method calculates the keyword weight of network public opinion information to obtain the core content of hot events in the stock market. Finally, accurate detection of stock market hot events is achieved.
