scholarly journals Estimating the quadratic covariation matrix for asynchronously observed high frequency stock returns corrupted by additive measurement error

2016 ◽  
Vol 191 (2) ◽  
pp. 325-347 ◽  
Author(s):  
Sujin Park ◽  
Seok Young Hong ◽  
Oliver Linton
Keyword(s):  
Measurement Error ◽  
Stock Returns ◽  
High Frequency ◽  
Covariation Matrix ◽  
Quadratic Covariation

scholarly journals Diffusion approximations for randomly arriving expert opinions in a financial market with Gaussian drift

2021 ◽  
Vol 58 (1) ◽  
pp. 197-216 ◽  
Author(s):  
Jörn Sass ◽  
Dorothee Westphal ◽  
Ralf Wunderlich
Keyword(s):  
Stock Returns ◽  
Financial Market ◽  
Discrete Time ◽  
High Frequency ◽  
Utility Maximization ◽  
Limit Theorems ◽  
Approximate Solutions ◽  
Diffusion Approximations ◽  
Expert Opinions ◽  
Arrival Intensity

AbstractThis paper investigates a financial market where stock returns depend on an unobservable Gaussian mean reverting drift process. Information on the drift is obtained from returns and randomly arriving discrete-time expert opinions. Drift estimates are based on Kalman filter techniques. We study the asymptotic behavior of the filter for high-frequency experts with variances that grow linearly with the arrival intensity. The derived limit theorems state that the information provided by discrete-time expert opinions is asymptotically the same as that from observing a certain diffusion process. These diffusion approximations are extremely helpful for deriving simplified approximate solutions of utility maximization problems.

Does time-varying illiquidity matter for the Indian stock market? Evidence from high-frequency data

2021 ◽  
pp. 031289622110102
Author(s):  
Mousumi Bhattacharya ◽  
Sharad Nath Bhattacharya ◽  
Sumit Kumar Jha
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
High Frequency ◽  
Jel Classification ◽  
Exogenous Shock ◽  
Intraday Data ◽  
Day Of The Week ◽  
Holiday Effects ◽  
Indian Stock Market ◽  
The Impact

This article examines variations in illiquidity in the Indian stock market, using intraday data. Panel regression reveals prevalent day-of-the-week, month, and holiday effects in illiquidity across industries, especially during exogenous shock periods. Illiquidity fluctuations are higher during the second and third quarters. The ranking of most illiquid stocks varies, depending on whether illiquidity is measured using an adjusted or unadjusted Amihud measure. Using pooled quantile regression, we note that illiquidity plays an important asymmetric role in explaining stock returns under up- and down-market conditions in the presence of open interest and volatility. The impact of illiquidity is more severe during periods of extreme high and low returns. JEL Classification: G10, G12

scholarly journals Estimating dynamic copula dependence using intraday data

2015 ◽  
Vol 19 (4) ◽  
Author(s):  
Lidan Grossmass ◽  
Ser-Huang Poon
Keyword(s):  
Stock Returns ◽  
Long Memory ◽  
High Frequency ◽  
Time Varying ◽  
Credit Crisis ◽  
Dynamic Copula ◽  
Tick Data ◽  
Out Of Sample ◽  
Intraday Data ◽  
Better Than

AbstractWe estimate the dynamic daily dependence between assets by applying the Semiparametric Copula-Based Multivariate Dynamic (SCOMDY) model on intraday data. Using tick data of three stock returns of the period before and during the credit crisis, we find that our dependence estimator better captures the steep increase in dependence during the onset of the crisis as compared to other commonly used time-varying copula methods. Like other high-frequency estimators, we find that the dependence estimator exhibits long memory and forecast it using a HAR model. We show that for out-of-sample forecasts, our dependence estimator performs better than the constant estimator and other commonly used time-varying copula dependence estimators.

scholarly journals Effects of Noise and Absorption on High Frequency Measurements of Acoustic-Backscatter from Fish

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Masahiko Furusawa
Keyword(s):  
Measurement Error ◽  
Environmental Conditions ◽  
High Frequency ◽  
Signal To Noise Ratio ◽  
Target Strength ◽  
Acoustic Backscatter ◽  
Signal To Noise ◽  
Absorption Coefficients ◽  
Frequency Measurements ◽  
Multiple Frequencies

Quantitative echosounders operating at multiple frequencies (e.g., 18, 38, 70, 120, 200, 333, and 710 kHz) are often used to observe fish and zooplankton and identify their species. At frequencies above 100 kHz, the absorption attenuation increases rapidly and decreases the signal-to-noise ratio (SNR). Also, incomplete compensation for the attenuation may result in measurement error. This paper addresses the effects of the attenuation and noise on high frequency measurements of acoustic backscatter from fish. It is shown that measurements of a fish with target strength of −40 dB at 200 m depth are limited by SNR to frequencies up to about 100 kHz. Above 100 kHz, absorption coefficients must be matched to local environmental conditions.

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