Does Fear has Stronger Impact than Confidence on Stock Returns? The Case of Asia-Pacific Developed Markets

Employing data from Australia, Hong Kong, and Japan over the period between January 2004 to December 2017, this study investigates the relationship between investor sentiment and stock returns. We analyze two reversed sentiment indicators, namely Consumer Confidence Index (CCI) and Volatility Index (VIX), in two conversing situations: low and high sentiment. The empirical evidence suggests that sentiment has a significant link with concurrent returns, but its influence seems to wipe out quickly as the little to no return predictability is detected. More importantly, we find that “investor fear gauge” (VIX) generates a more significant contemporaneous effect on market returns than investor confidence. The impact on future returns, on the contrary, is inconclusive since low CCI and VIX dominate the opposite ones most of the time.JEL Codes - G10; G15; G4

Damage assessment in beam-like structures by correlation of spectrum using machine learning

Damage assessment in the actual operating process of the structure is a modern and exciting problem of construction engineering due to several practical knowledge about the current condition of the inspected structures. However, the problem faced is the difficulty in controlling the excitation in structures. Therefore, the output-based structural damage identification method is becoming attractive because of its potential to be applied to an actual application without being constrained by the collection of the information excitation source. An approach of damage assessment based on supervised Machine Learning is introduced in this study by using the correlation of spectral signal as an input feature for artificial neural network (ANN) and decision tree. The output of machine learning algorithms consists of the appearance of new cuts, the level of cutting and the cutting position. A supported beam model was constructed as an experiment to determine if the method is reasonable for engineering structures. Two machine learning algorithms have been applied to check the relevance of the proposed feature from vibration data. This study contributes a standard in the damage identification problem based on spectral correlation

Foreign Ownership and Stock Return Volatility in Vietnam: the Destabilizing Role of Firm Size

This study aims to examine the relevance of foreign ownership to stock return volatility in the Vietnam stock market over ten years (2008 - 2017). After applying the fixed effects regressions and the extended instrumental variable regressions with fixed effects, we find that foreign ownership decreases the volatility of stock returns. However, the stabilizing impact of foreign ownership on stock return volatility becomes weaker in large firms since the coeffcient of the interaction term between firm size and foreign ownership turns out to be significantly positive. The estimated results remain robust when we use the future one-year volatility, other than the current one, as an alternative measure of the dependent variable

Chemical composition and antibacterial activities of essential oils from fruits of Melicope pteleifolia (Champ. Ex Benth.) T.G. Hartley grown in Lam Dong Province, Vietnam

In the present study, chemical composition and antibacterial properties of essential oil obtained from the aerial parts of the Melicope pteleifolia (Champ. ex Benth.) T.G Hartley in Dalat were evaluated. Essential oil was isolated through hydro-distillation. Twenty-nine constituents comprising 100% of the essential oil were characterized by gas chromatography/mass spectrometry (GC-MS) techniques. The major compounds in the essential oil were (+)-Sabinene (34.73%), Cis-α-bergamotene (13.15%), Z-α-trans-bergamotol (5.28%), β-mycrene (4.98%), and 1,3,6-octatriene, 3,7-dimethyl-(4.71%). Antibacterial activities of Melicope pteleifolia essential oil were investigated against Gram-positive and-negative bacteria. Results showed significant activities against Streptococcus pyogenes and Escherichia coli using an agar well diffusion method. The application of this essential oil in preventing and eliminating bacteria could be useful in fields as medicine and cosmetics.

Damage assessment in beam-like structures by correlation of spectrum using machine learning

Damage assessment in the actual operating process of the structure is a modern and exciting problem of construction engineering due to several practical knowledge about the current condition of the inspected structures. However, the problem faced is the difficulty in controlling the excitation in structures. Therefore, the output-based structural damage identification method is becoming attractive because of its potential to be applied to an actual application without being constrained by the collection of the information excitation source. An approach of damage assessment based on supervised Machine Learning is introduced in this study by using the correlation of spectral signal as an input feature for artificial neural network (ANN) and decision tree. The output of machine learning algorithms consists of the appearance of new cuts, the level of cutting and the cutting position. A supported beam model was constructed as an experiment to determine if the method is reasonable for engineering structures. Two machine learning algorithms have been applied to check the relevance of the proposed feature from vibration data. This study contributes a standard in the damage identification problem based on spectral correlation

Spatiotemporal evolution of SARS-CoV-2 Alpha and Delta variants during large nationwide outbreak of COVID-19, Vietnam, 2021

We analyzed 1,303 SARS-CoV-2 whole-genome sequences from Vietnam, and found the Alpha and Delta variants were responsible for a large nationwide outbreak of COVID-19 in 2021. The Delta variant was confined to the AY.57 lineage and caused >1.7 million infections and >32,000 deaths. Viral transmission was strongly affected by nonpharmaceutical interventions

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

Research introduction of new faculty

This paper introduces the research of Assistant Professor Vuong Bao Ngoc who started her post in April 2022. The first part describes research interest and academic background for investigating these topics. Some representative studies are presented in the next section. The final part summarizes the main findings and applications as well as introduces potential lines of future research

市場心理と株式収益率との関係および国固有要因の緩和効果に関する研究

広島大学(Hiroshima University)博士(経済学)Doctor of Economicsdoctora