Large portfolio allocation using high-frequency financial data

Asset allocation strategy involves dividing an investment portfolio among different assets according to their risk levels. In recent decades, estimating volatilities of asset returns based on high-frequency data has emerged as a topic of interest in financial econometrics. However, most available methods are not directly applicable when the number of assets involved is large, since small component-wise estimation errors could accumulate to large matrix-wise errors. In this paper, we introduce a method to carry out efficient asset allocation using sparsity-inducing regularization on the realized volatility matrix obtained from intraday high-frequency data. We illustrate the new method with the high-frequency price data on stocks traded in New York Stock Exchange over a period of six months in 2013. Simulation studies based on popular volatility models are also presented. The proposed methodology is theoretically justified. Numerical results also show that our approach performs well in portfolio allocation by pooling together the strengths of regularization and estimation from a high-frequency finance perspective

Multiple regression analysis of C242T genotypes.

<p>HDL = high density lipoprotein.</p><p>LogTG = Log transformation of the triglycerides.</p>*<p>Adjusted for sex, age, body height, body weight, antihypertensive medication, antidiabetic medication, current smoking, alcohol intake and heart rate.</p>#<p>Adjusted for sex, age, body height, body weight, antihypertensive medication, antidiabetic medication, alcohol intake and heart rate.</p

Trend surface changes in the coupling coordination of urban quality and technological innovation in the Guangdong-Hong Kong-Macao Greater Bay Area.

Trend surface changes in the coupling coordination of urban quality and technological innovation in the Guangdong-Hong Kong-Macao Greater Bay Area.</p

Spatial distribution of the estimated regression coefficients of the GWR model for the coupled coordination level of urban quality and technology innovation.

Spatial distribution of the estimated regression coefficients of the GWR model for the coupled coordination level of urban quality and technology innovation.</p

Technology innovation index system.

The coordinated development of urban quality and technology innovation is an important element of China’s technology innovation development strategy in the new era. Based on entropy TOPSIS, coupling coordination models, the gravity center and standard deviation ellipse method, the geographic probe, the GWR, and other methods, we explore the spatial variation and influencing factors of the coupling coordination relationship between urban quality and technology innovation in the Guangdong-Hong Kong-Macao Greater Bay Area from 2011 to 2020. It is found that: (1) the spatial distribution of the coupling coordination shows a characteristic of "high in the middle and low in the surroundings," and (2) the level of benign interaction in the central region is becoming more prominent. The center of gravity of coupling coordination moves toward the northeast, and the standard deviation ellipse shows a contraction trend away from the southwest. (3) Agglomeration capacity, human capital, cultural development, and infrastructure can significantly drive the improvement of the coupling coordination of urban quality and technology innovation, and the two-factor influence is significantly increased after the interaction. (4) The feedback effects of the coupling and coordination states of different cities on each factor have significant spatial differences and show the characteristics of hierarchical band distribution.</div

Technology roadmap of the research.

The coordinated development of urban quality and technology innovation is an important element of China’s technology innovation development strategy in the new era. Based on entropy TOPSIS, coupling coordination models, the gravity center and standard deviation ellipse method, the geographic probe, the GWR, and other methods, we explore the spatial variation and influencing factors of the coupling coordination relationship between urban quality and technology innovation in the Guangdong-Hong Kong-Macao Greater Bay Area from 2011 to 2020. It is found that: (1) the spatial distribution of the coupling coordination shows a characteristic of "high in the middle and low in the surroundings," and (2) the level of benign interaction in the central region is becoming more prominent. The center of gravity of coupling coordination moves toward the northeast, and the standard deviation ellipse shows a contraction trend away from the southwest. (3) Agglomeration capacity, human capital, cultural development, and infrastructure can significantly drive the improvement of the coupling coordination of urban quality and technology innovation, and the two-factor influence is significantly increased after the interaction. (4) The feedback effects of the coupling and coordination states of different cities on each factor have significant spatial differences and show the characteristics of hierarchical band distribution.</div

Urban quality index descriptive statistics.

The coordinated development of urban quality and technology innovation is an important element of China’s technology innovation development strategy in the new era. Based on entropy TOPSIS, coupling coordination models, the gravity center and standard deviation ellipse method, the geographic probe, the GWR, and other methods, we explore the spatial variation and influencing factors of the coupling coordination relationship between urban quality and technology innovation in the Guangdong-Hong Kong-Macao Greater Bay Area from 2011 to 2020. It is found that: (1) the spatial distribution of the coupling coordination shows a characteristic of "high in the middle and low in the surroundings," and (2) the level of benign interaction in the central region is becoming more prominent. The center of gravity of coupling coordination moves toward the northeast, and the standard deviation ellipse shows a contraction trend away from the southwest. (3) Agglomeration capacity, human capital, cultural development, and infrastructure can significantly drive the improvement of the coupling coordination of urban quality and technology innovation, and the two-factor influence is significantly increased after the interaction. (4) The feedback effects of the coupling and coordination states of different cities on each factor have significant spatial differences and show the characteristics of hierarchical band distribution.</div

Standard deviation ellipse.

The coordinated development of urban quality and technology innovation is an important element of China’s technology innovation development strategy in the new era. Based on entropy TOPSIS, coupling coordination models, the gravity center and standard deviation ellipse method, the geographic probe, the GWR, and other methods, we explore the spatial variation and influencing factors of the coupling coordination relationship between urban quality and technology innovation in the Guangdong-Hong Kong-Macao Greater Bay Area from 2011 to 2020. It is found that: (1) the spatial distribution of the coupling coordination shows a characteristic of "high in the middle and low in the surroundings," and (2) the level of benign interaction in the central region is becoming more prominent. The center of gravity of coupling coordination moves toward the northeast, and the standard deviation ellipse shows a contraction trend away from the southwest. (3) Agglomeration capacity, human capital, cultural development, and infrastructure can significantly drive the improvement of the coupling coordination of urban quality and technology innovation, and the two-factor influence is significantly increased after the interaction. (4) The feedback effects of the coupling and coordination states of different cities on each factor have significant spatial differences and show the characteristics of hierarchical band distribution.</div

Difference of prevalence of metabolic syndrome between C242T genotypes in all participants and smokers.

<p>The odds of prevalence of metabolic syndrome in genotypic group is expressed relative to the overall risk of all participants (A) or smokers (B), and adjusted for age, sex, body height, body weight, antihypertensive medication, antidiabetic medication, current smoking, alcohol intake and heart rate. Vertical lines denote 95% confidence intervals. For each genotype, the number of participants is given.</p

Coupling coordination center of gravity shift.

The coordinated development of urban quality and technology innovation is an important element of China’s technology innovation development strategy in the new era. Based on entropy TOPSIS, coupling coordination models, the gravity center and standard deviation ellipse method, the geographic probe, the GWR, and other methods, we explore the spatial variation and influencing factors of the coupling coordination relationship between urban quality and technology innovation in the Guangdong-Hong Kong-Macao Greater Bay Area from 2011 to 2020. It is found that: (1) the spatial distribution of the coupling coordination shows a characteristic of "high in the middle and low in the surroundings," and (2) the level of benign interaction in the central region is becoming more prominent. The center of gravity of coupling coordination moves toward the northeast, and the standard deviation ellipse shows a contraction trend away from the southwest. (3) Agglomeration capacity, human capital, cultural development, and infrastructure can significantly drive the improvement of the coupling coordination of urban quality and technology innovation, and the two-factor influence is significantly increased after the interaction. (4) The feedback effects of the coupling and coordination states of different cities on each factor have significant spatial differences and show the characteristics of hierarchical band distribution.</div