Initial Public Offering Effects on Volatility in US Stock Market

This paper aims to investigate the effect of Initial Public Offerings (IPOs) on stock market volatility in the United States using the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model. The study utilizes daily data from January 2020 to October 2022 on the Standard & Poor's 500 Index (S&P 500) and IPO firms listed on the New York Stock Exchange (NYSE) their IPO dates during the same period. The GARCH model is employed to estimate the volatility of the S&P 500 index stock prices after the IPOs announcements during the first day, first five days, and first ten days. The study finds that IPOs significantly impact volatility in the US market, and the effect is more pronounced in the short term. We discovered that IPOs after their announcements during the first five days have a negative impact on other stock prices in the S&P500 index. The effects are stronger for the first day of initial public offering come to the market while there is a negative impact on the 10th day of IPOs in the market but it is not statistically significant. The downward-sloping demand curve hypothesis is supported by these findings. These results have important implications for investors, market regulators, and policymakers. Investors should be aware of the potential for increased volatility during periods of IPO activity and adjust their investment strategies accordingly. Market regulators may need to consider implementing measures to mitigate the impact of IPOs on market volatility. Policymakers may also need to consider the potential economic effects of IPOs and the associated increase in market volatility to ensure a stable and efficient stock market

PVTx Properties of a Two-phase CO2 Jet from Ruptured Pipeline

Span and Wagner equation of state (SW EOS) have been used to investigate changes in the thermodynamic properties of CO2 during a depressurization process from a pipeline into marine environment. The process is assumed to be isenthalpic, as only the thermodynamic change at the moment of depressurization is considered. The calculations show that the depth location of the pipeline influences greatly the density, temperature and volume changes, because of the difference in the surrounding pressures. In general the two-phase area is reached at depths shallower than 600 meters, which yields for the Norwegian Continental Shelf, as it is mainly shallower than 500 meters depth. There is a rapid decrease in density in the two-phase area causing a rapid expansion in the volume of CO2 from 4 MPa to 1 MPa. At the shallowest depth considered (100m) the volume fraction consist almost entirely of gas, and the density change give a significant increase in volume.publishedVersio

Initial Public Offering Effects on Volatility in US Stock Market

This paper aims to investigate the effect of Initial Public Offerings (IPOs) on stock market volatility in the United States using the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model. The study utilizes daily data from January 2020 to October 2022 on the Standard & Poor's 500 Index (S&P 500) and IPO firms listed on the New York Stock Exchange (NYSE) their IPO dates during the same period. The GARCH model is employed to estimate the volatility of the S&P 500 index stock prices after the IPOs announcements during the first day, first five days, and first ten days. The study finds that IPOs significantly impact volatility in the US market, and the effect is more pronounced in the short term. We discovered that IPOs after their announcements during the first five days have a negative impact on other stock prices in the S&P500 index. The effects are stronger for the first day of initial public offering come to the market while there is a negative impact on the 10th day of IPOs in the market but it is not statistically significant. The downward-sloping demand curve hypothesis is supported by these findings. These results have important implications for investors, market regulators, and policymakers. Investors should be aware of the potential for increased volatility during periods of IPO activity and adjust their investment strategies accordingly. Market regulators may need to consider implementing measures to mitigate the impact of IPOs on market volatility. Policymakers may also need to consider the potential economic effects of IPOs and the associated increase in market volatility to ensure a stable and efficient stock market

Optimal sensors placement for detecting CO2 discharges from unknown locations on the seafloor

Assurance monitoring of the marine environment is a required and intrinsic part of CO2 storage project. To reduce the costs related to the monitoring effort, the monitoring program must be designed with optimal use of instrumentation. Here we use solution of a classical set cover problem to design placement of an array of fixed chemical sensors with the purpose of detecting a seep of CO2 through the seafloor from an unknown location. The solution of the problem is not unique and different aspects, such as cost or existing infrastructure, can be added to define an optimal solution. We formulate an optimization problem and propose a method to generate footprints of potential seeps using an advection–diffusion model and a stoichiometric method for detection of small seepage CO2 signals. We provide some numerical experiments to illustrate the concepts

Using Bayes Theorem to Quantify and Reduce Uncertainties when Monitoring Varying Marine Environments for Indications of a Leak

Monitoring the marine environment for leaks from geological storage projects is a challenge due to the variability of the environment and the extent of the area that migrating CO2 might seep through the seafloor. Due to the environmental risk associated leaks should not be allowed to continue undetected. There is also a cost issue since marine operations are expensive, so false alarms should be avoided. The main question is then: how large a deviation in the monitoring data should cause mobilization of confirmation and localization procedures? Here Baye’s theorem and Bayesian decision theory is suggested as a tool for quantifying certainties and to implement costs for false positives (false alarms) and false negatives (undetected leaks) in the decision procedure. The procedure is exemplified using modeled natural CO2 content variability and the predicted CO2 signal from a simulated leak

The Nordic Seas carbon budget: Sources, sinks, and uncertainties

A carbon budget for the Nordic Seas is derived by combining recent inorganic carbon data from the CARINA database with relevant volume transports. Values of organic carbon in the Nordic Seas' water masses, the amount of carbon input from river runoff, and the removal through sediment burial are taken from the literature. The largest source of carbon to the Nordic Seas is the Atlantic Water that enters the area across the Greenland-Scotland Ridge; this is in particular true for the anthropogenic CO2. The dense overflows into the deep North Atlantic are the main sinks of carbon from the Nordic Seas. The budget show that presently 12.3 ± 1.4 Gt C yr−1 is transported into the Nordic Seas and that 12.5 ± 0.9 Gt C yr−1 is transported out, resulting in a net advective carbon transport out of the Nordic Seas of 0.17 ± 0.06 Gt C yr−1. Taking storage into account, this implies a net air-to-sea CO2 transfer of 0.19 ± 0.06 Gt C yr−1 into the Nordic Seas. The horizontal transport of carbon through the Nordic Seas is thus approximately two orders of magnitude larger than the CO2 uptake from the atmosphere. No difference in CO2 uptake was found between 2002 and the preindustrial period, but the net advective export of carbon from the Nordic Seas is smaller at present due to the accumulation of anthropogenic CO2

Seasonal variations of hydrographic parameters off the Sudanese coast of the Red Sea, 2009–2015

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Regional Studies in Marine Science 18 (2018): 1-10, doi:10.1016/j.rsma.2017.12.004.The variations of temperature and salinity in the Sudanese coastal zone of the Red Sea are studied for the first time using measurements acquired from survey cruises during 2009–2013 and from a mooring during 2014–2015. The measurements show that temperature and salinity variability above the permanent pycnocline is dominated by seasonal signals, similar in character to seasonal temperature and salinity oscillations observed further north on the eastern side of the Red Sea. Using estimates of heat flux, circulation and horizontal temperature/salinity gradients derived from a number of sources, we determined that the observed seasonal signals of temperature and salinity are not the product of local heat and mass flux alone, but are also due to alongshore advection of waters with spatially varying temperature and salinity. As the temperature and salinity gradients, characterized by warmer and less saline water to the south, exhibit little seasonal variation, the seasonal salinity and temperature variations are closely linked to an observed seasonal oscillation in the along-shore flow, which also has a mean northward component. We find that the inclusion of the advection terms in the heat and mass balance has two principal effects on the computed temperature and salinity series. One is that the steady influx of warmer and less saline water from the south counteracts the long-term trend of declining temperatures and rising salinities computed with only the local surface flux terms, and produces a long-term steady state in temperature and salinity. The second effect is produced by the seasonal alongshore velocity oscillation and most profoundly affects the computed salinity, which shows no seasonal signal without the inclusion of the advective term. In both the observations and computed results, the seasonal salinity signal lags that of temperature by roughly 3 months.The SPS surveys were funded by the Norwegian Norad’s Program for Master Studies and organized by IMR–RSU in Port Sudan. The central Red Sea mooring data were acquired as part of a WHOI–KAUST collaboration funded by Award Nos. USA00001, USA00002, and KSA00011 to the WHOI by the KAUST in the Kingdom of Saudi Arabia. The work of I. Skjelvan and A.M. Omar was partly supported by the Research Council of Norway through the MIMT Center for Research-based Innovation. This work is part of a Ph.D. project at GFI–UiB funded by the Norwegian Quota program

Tilførselsprogrammet 2011. Overvåking av forsuring av norske farvann

Denne rapporten gjelder undersøkelser av havforsuring som er utført av IMR, NIVA og BCCR i oppdrag fra Klif i 2011. Den er basert på målinger mellom Bergen-Kirknes og Tromsø-Longyearbyen utført av NIVA. Prøvetaking av vertikalen fra Torungen-Hirtshals, Svinøy-NW, Gimsøy-NW og Fugløya-Bjørnøya er utført av IMR. Resultatene fra Norskehavet viser en klar sesongvariasjon i øvre 100 m av vannsøylen, som for det meste er styrt av styrken på primærproduksjonen. I tillegg påvirkes karboninnholdet av kystvannet som brer seg vestover i løpet av sommeren. Metningsgraden for aragonitt (Ar) er mellom 1.95 til 1.6 på 300 m dyp. I Norskehavet befinner =1.6 seg på 500 m dyp, og i Nordsjøen på ca 200 m. I Norskehavet er det undermetning fra like under 1500 meters dyp av aragonitt og overmetning av kalsitt i hele vannsøylen. I Barentshavet lå Ar mellom 1.07-2.62 med min. verdier i kystområdet mellom Kirkenes og Tromsø i januar (1.07-2.03), mens Ar var 1.49-2.52 i desember, og karakterisert av en stor variasjon fra 1.67 til 2.62 som skyldes en økt biologisk produksjon. Historiske data er sammenlignet på Havforskningens hydrografiske seksjoner i 2011 og CARINA databasen. Primært ble data fra 1997-2011 i nord-vestlig retning fra Gimsøy og Svinøy benyttet for å studere trender i Norskehavet, men analysen omfatter også data fra Barentshavet. Trender viser en økning av karbonkonsentrasjonene målt i 2011 relativt til historiske data. Dette gjenspeiler hovedsakelig havets opptak av menneskeskapt CO2. Konklusjonen er at de fleste områder studert i denne rapporten er mettet i forhold til kalsitt, og undermetning av aragonitt viser seg på 1500 meters dyp i Norskehavet.Kli

Detection and quantification of CO2 seepage in seawater using the stoichiometric Cseep method:Results from a recent subsea CO2 release experiment in the North Sea

Carbon Capture and Storage (CCS) is a potential significant mitigation strategy to combat climate change and ocean acidification. The technology is well understood but its current implementation must be scaled up nearly by a hundredfold to become an effective tool that helps meet mitigation targets. Regulations require monitoring and verification at storage sites, and reliable monitoring strategies for detection and quantification of seepage of the stored carbon need to be developed. The Cseep method was developed for reliable determination of CO2 seepage signal in seawater by estimating and filtering out natural variations in dissolved inorganic carbon (C). In this work, we analysed data from the first-ever subsea CO2 release experiment performed in the north-western North Sea by the EU STEMM−CCS project. We successfully demonstrated the ability of the Cseep method to (i) predict natural C variations around the Goldeneye site over seasonal to interannual time scales; (ii) establish a process-based baseline C concentration with minimal variability; (iii) determine CO2 seepage detection threshold (DT) to reliably differentiate released−CO2 signal from natural variability and quantify released−CO2 dissolved in the sampled seawater. DT values were around 20 % of the natural C variations indicating high sensitivity of the method. Moreover, with the availability of DT value, the identification of released−CO2 required no pre-knowledge of seepage occurrence, but we used additional available information to assess the confidence of the results. Overall, the Cseep method features high sensitivity, automation suitability, and represents a powerful future monitoring tool both for large and confined marine areas