Optimizing the Four-Index Integral Transform Using Data Movement Lower Bounds Analysis

This paper examines the price performance of call warrants in China's securities market. A recent sample of daily call warrant prices observed during the period from August 2005 to March 2007 is used. To the best of our knowledge this is the only recent study to using data from China and as such it greatly enhances our understanding of this particular market. On average, we find that the observed market prices are irrationally higher than the Black-Scholes model prices by 80.38% (using 180-day historical volatility) and 140.50% (using EGARCH volatility). However, we find another anomalous phenomenon that some of the call warrants prices are not only lower than the model prices, but have also recently been anomalously under their lower bounds. This finding seems to violate the "no arbitrage" principle. Among the convincing reasons, our findings indicate that trading mechanism constraints in China's securities market prevent rational investors from driving the prices of these call warrants to a reasonable level. Arbitrage chances are found to exist in some specific cases when the call warrant prices are below their lower bounds.

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Automated derivation of parametric data movement lower bounds for affine programs

Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation ◽

10.1145/3385412.3385989 ◽

2020 ◽

Cited By ~ 2

Author(s):

Auguste Olivry ◽

Julien Langou ◽

Louis-Noël Pouchet ◽

P. Sadayappan ◽

Fabrice Rastello

Keyword(s):

Lower Bounds ◽

Data Movement ◽

Parametric Data ◽

Automated Derivation

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Mean-cyclic-error lower bounds via integral transform of likelihood-ratio function

2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) ◽

10.1109/sam.2016.7569646 ◽

2016 ◽

Cited By ~ 1

Author(s):

Eyal Nitzan ◽

Tirza Routtenberg ◽

Joseph Tabrikian

Keyword(s):

Likelihood Ratio ◽

Lower Bounds ◽

Integral Transform

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Reconstruction Of Cluster Mass Distributions: Application And Results For CL0939+4713

Symposium - International Astronomical Union ◽

10.1017/s0074180900231124 ◽

1996 ◽

Vol 173 ◽

pp. 129-130

Author(s):

Carolin Seitz

Keyword(s):

Mass Distribution ◽

Lower Bounds ◽

Light Distribution ◽

Cluster Member ◽

Mass Distributions ◽

Cluster Mass ◽

Data Field ◽

Using Data ◽

Mass Reconstruction

We show the reconstructed mass distribution of the cluster CL0939+4713 (zd = 0.4) using data obtained with the WFPC2 instrument on HST. We find a remarkable correlation with the light distribution of the bright galaxies, which are probably cluster member galaxies. A bootstrapping analysis confirms this correlation, whereas an anti-correlation between the mass distribution and the faint galaxies - used for the mass reconstruction - is found. We give lower bounds on the mass inside the data field, and confirm that this cluster is indeed quite massive.

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On Using the Roofline Model with Lower Bounds on Data Movement

ACM Transactions on Architecture and Code Optimization ◽

10.1145/2693656 ◽

2015 ◽

Vol 11 (4) ◽

pp. 1-23 ◽

Cited By ~ 3

Author(s):

Venmugil Elango ◽

Naser Sedaghati ◽

Fabrice Rastello ◽

Louis-Noël Pouchet ◽

J. Ramanujam ◽

...

Keyword(s):

Lower Bounds ◽

Data Movement ◽

Roofline Model

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Estimating Lower Bounds for COVID-19 Mortality from Northern Italian Towns

10.1101/2020.06.10.20125005 ◽

2020 ◽

Author(s):

Thomas S. Coleman

Keyword(s):

Infection Rate ◽

Lower Bounds ◽

Excess Mortality ◽

Fatality Rate ◽

Epidemiological Modeling ◽

Specific Mortality ◽

Italian Provinces ◽

Using Data ◽

The Town ◽

Age And Sex

AbstractFor COVID-19 the Infection Fatality Rate or IFR – a crucial variable in epidemiological modeling – is difficult to estimate because many cases are asymptomatic and the overall infection rate is generally not known. Circumstances in the Italian provinces of Milano, Bergamo, Brescia, and Lodi allow estimation of lower bounds for age- and sex-specific all-cause excess mortality (a proxy for IFR) since anecdotal reports indicate some towns were close to fully infected. Using data from ISTAT on mortality from January 1 through April 15 for 2020 and the three preceding years, I estimate excess mortality by sex and age categories (0-14, 15-54, 55-64, 65-74, and 75+ years) while controlling for town-specific mortality that proxies for town-specific infection rate. The 99th percentile from the tail of the town distribution gives a lower-bound estimate for COVID-19 mortality. The overall population-weighted mortality at the 99th percentile is 1.09 percent (95% CI 1.06-1.14). The age- and sex-specific rates vary considerably: for men age 65-74 the estimate is 2.10 percent (95% CI 1.94-2.28) which is 3.5-times higher than men 55-64 and 2.7-times higher than women 65-74.

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