IMPACT OF INVESTOR SENTIMENT ON CROSS SECTIONAL TESTS OF ALTERNATIVE ASSET PRICING MODELS: EVIDENCES FROM INDIAN EQUITY MARKET

ABSTRACT This paper tests the cross sectional return predictability of alternative asset pricing models in Indian stock market by considering investor sentiment as conditioning information variable. The sample period spans over January 2003 till March 2011. For the cross sectional tests of alternative asset pricing models we have used both the Fama and Macbeth and Generalized Method of Moments estimation techniques. Cross sectional test results suggest that investor sentiment as a conditioning information variable contains significant information for making the discount factors time varying. In the conditional specifications all the risk factors scaled with investor sentiment significantly influence the pricing kernel. Model comparison test statistics suggests that for Indian stock market considering investor sentiment as the conditioning information the cross sectional tests of alternative asset pricing model reveal that the Five Factor Model that augments Carhart four factor model with a liquidity factor performs better than the other conditional models. JEL code: C51, G12, E2

Sentiment and Accruals Earnings Management: Does Governance and Regulatory Environment Matter?

This paper examines the implications of firm-level governance mechanisms and the regulatory environment on the relationship between investor sentiment and accrual-based earnings management. Our findings confirm the positive impact of sentiment on earnings management through accruals. Our results confirm that in the presence of a stringent regulatory environment, the likelihood of abnormal accruals following a positive sentiment environment is low. We document that a stringent regulatory environment reduces the likelihood of abnormal accruals following a positive sentiment environment. Results further confirm that improved governance characteristics like larger board, increased board independence, and stringent related party transaction norms help to monitor corporate behaviour and mitigates opportunistic earnings management activity of managers with an exogeneous effect of market sentiment. Thus, our results have important implications for regulators and policymakers for strengthening the regulatory and monitoring environment. Investors may also use earnings announcement news during an optimistic market sentiment scenario in a more informative way

Do Oil Shocks Affect Financial Stress? Evidence from Oil-Exporting and -Importing Countries

In recent years, there is increasing attention to examining the relationship between oil prices, financial markets, and the economy. Relatively little is known about the dynamic relationship between structural oil shocks and financial market stress of countries, which are majorly dependent on oil price fluctuations. This paper examines the impact of structural oil shocks (oil supply shocks, global aggregate demand shocks, speculative shocks, and other oil shocks) on the financial stress of major oil-exporting and-importing economies. In this study, we construct a financial stress index and using a structural vector autoregression model, we investigate the effects of oil price shocks on the financial stress of major oil-exporting and importing economies. We find evidence that global demand shocks, followed by speculative demand shocks, have significant impacts on financial stress. Furthermore, the US subprime crisis has a significant bearing on the response of the financial stress index to structural oil shocks. The magnitude of oil price shocks on financial stress has subdued during the post-crisis period

Beam test performance of a prototype module with Short Strip ASICs for the CMS HL-LHC tracker upgrade

The Short Strip ASIC (SSA) is one of the four front-end chips designed for the upgrade of the CMS Outer Tracker for the High Luminosity LHC. Together with the Macro-Pixel ASIC (MPA) it will instrument modules containing a strip and a macro-pixel sensor stacked on top of each other. The SSA provides both full readout of the strip hit information when triggered, and, together with the MPA, correlated clusters called stubs from the two sensors for use by the CMS Level-1 (L1) trigger system. Results from the first prototype module consisting of a sensor and two SSA chips are presented. The prototype module has been characterized at the Fermilab Test Beam Facility using a 120 GeV proton beam

Test beam performance of a CBC3-based mini-module for the Phase-2 CMS Outer Tracker before and after neutron irradiation

The Large Hadron Collider (LHC) at CERN will undergo major upgrades to increase the instantaneous luminosity up to 5–7.5×10$^{34}$ cm$^{-2}$s$^{-1}$. This High Luminosity upgrade of the LHC (HL-LHC) will deliver a total of 3000–4000 fb-1 of proton-proton collisions at a center-of-mass energy of 13–14 TeV. To cope with these challenging environmental conditions, the strip tracker of the CMS experiment will be upgraded using modules with two closely-spaced silicon sensors to provide information to include tracking in the Level-1 trigger selection. This paper describes the performance, in a test beam experiment, of the first prototype module based on the final version of the CMS Binary Chip front-end ASIC before and after the module was irradiated with neutrons. Results demonstrate that the prototype module satisfies the requirements, providing efficient tracking information, after being irradiated with a total fluence comparable to the one expected through the lifetime of the experiment

Household pandemic Internet search intensity and stock returns: A case of tourism industry resiliency

This paper uses the Google Internet search volume index to capture pandemic attention and examines the effect of COVID-19 on the stock returns of the tourism industry. We find a significant negative effect of pandemic attention sentiment on tourism industry stock returns. The results are robust to the inclusion of alternative pandemic information variables and firm and business cycle controls. Results suggest that large-size firms, firms with better growth opportunities, and value stocks are more resilient to mitigate uncertainty induced by the pandemic. Investors welcome governmental economic policy interventions and thus adjust their return expectations less negatively. Finally, we find that the country's cultural dimension, government efficiency, stable financial system, and health system help to mitigate the downside risk of stock price movements induced by the pandemic

Identification of Putative Plant Based Antiviral Compounds to Fight Against SARS-CoV-2 Infection

Background: This study aimed to examine the efficacy of some natural compounds and their derivatives in inhibiting the nucleocapsid protein N-terminal RNA binding domain (NSP-NTD), of SARS-CoV-2 virus by using the molecular doacking approach. Methods: Physiochemical and drug likeness properties of the compounds were characterized by using SWISS ADME server tool. ADMET and TOPKAT modules of Discovery studio 4.0 were used for prediction of pharmacokinetic properties and toxicity of the compounds. Molecular docking of the ligands with the target protein (NSP-NTD) was carried out using the receptor-ligand interactions module of DS 4.0. The CDOCKER energy, CDOCKER interaction energy and binding energy of the interactions were calculated to identify the best interacting compounds. Results: Four compounds including 4-hydroxybenzoic acid, benzoic acid, 4-aminobenzoic acid and salicylic acid have been predicted as effective compounds to inhibit the NSP-NTD (responsible for packing the viral RNA into the crown like capsid) vis-à-vis combat the SARS-Cov-2 virus infection. Conclusions: In vitro and in vivo evaluation of these compounds against SARS-CoV-2 virus is required prior to assuring their potential roles in SARS-CoV-2 infection control.</p

Pharmaceutical characterization and exploration of Arkeshwara rasa in MDA-MB-231 cells.

BACKGROUND The diverse specificity mode of cancer treatment targets and chemo resistance demands the necessity of drug entities which can address the devastating dynamicity of the disease. OBJECTIVES To check the anti-tumour potential of traditional medicine rich in polyherbal components and metal nanoparticle namely Arkeshwara rasa (AR). MATERIAL METHODS The AR was prepared in a modified version with reference from Rasaratna Samuchaya and characterized using sophisticated instrumental analysis including XRD, SEM-EDAX, TEM, TGA-DSC, and LC-MS and tested against the MDA-MB-231 cell line to screen cell viability and the cytotoxicity with MTT, SRB and the AO assay. RESULTS XRD pattern shows cubic tetrahedrite structure with Sb, Cu, S peaks and trace elements like Fe, Mg, etc. The particle size of AR ranges between 20 and 30 nm. The TGA points thermal decomposition at 210 °C and the metal sulphide peaks in DSC. LC-MS analysis reveals the components of the formulation more on the flavonoid portion. The IC50 value of MTT and SRB are 25.28 μg/mL and 31.7 μg/mL respectively. The AO colorimeter substantiated the cell viability and the apoptosis figures of the same cell line. The AR exhibits cytotoxicity and reaffirms the apoptosis fraction with SRB assay. CONCLUSIONS The Hesperidine, Neohesperidin, Rutin components in the phytochemical pool can synergize the anti-tumour potential with either influencing cellular pathways or decreasing chemo resistance to conventional treatment. AR need to be further experimented with reverse transcription, flow cytometry, western blotting, etc