High quality topic extraction from business news explains abnormal financial market volatility

Understanding the mutual relationships between information flows and social activity in society today is one of the cornerstones of the social sciences. In financial economics, the key issue in this regard is understanding and quantifying how news of all possible types (geopolitical, environmental, social, financial, economic, etc.) affect trading and the pricing of firms in organized stock markets. In this article, we seek to address this issue by performing an analysis of more than 24 million news records provided by Thompson Reuters and of their relationship with trading activity for 206 major stocks in the S&P US stock index. We show that the whole landscape of news that affect stock price movements can be automatically summarized via simple regularized regressions between trading activity and news information pieces decomposed, with the help of simple topic modeling techniques, into their "thematic" features. Using these methods, we are able to estimate and quantify the impacts of news on trading. We introduce network-based visualization techniques to represent the whole landscape of news information associated with a basket of stocks. The examination of the words that are representative of the topic distributions confirms that our method is able to extract the significant pieces of information influencing the stock market. Our results show that one of the most puzzling stylized fact in financial economies, namely that at certain times trading volumes appear to be "abnormally large," can be partially explained by the flow of news. In this sense, our results prove that there is no "excess trading," when restricting to times when news are genuinely novel and provide relevant financial information.Comment: The previous version of this article included an error. This is a revised versio

Prediction of ESG Compliance using a Heterogeneous Information Network

Negative screening is one method to avoid interactions with inappropriate entities. For example, financial institutions keep investment exclusion lists of inappropriate firms that have environmental, social, and government (ESG) problems. They create their investment exclusion lists by gathering information from various news sources to keep their portfolios profitable as well as green. International organizations also maintain smart sanctions lists that are used to prohibit trade with entities that are involved in illegal activities. In the present paper, we focus on the prediction of investment exclusion lists in the finance domain. We construct a vast heterogeneous information network that covers the necessary information surrounding each firm, which is assembled using seven professionally curated datasets and two open datasets, which results in approximately 50 million nodes and 400 million edges in total. Exploiting these vast datasets and motivated by how professional investigators and journalists undertake their daily investigations, we propose a model that can learn to predict firms that are more likely to be added to an investment exclusion list in the near future. Our approach is tested using the negative news investment exclusion list data of more than 35,000 firms worldwide from January 2012 to May 2018. Comparing with the state-of-the-art methods with and without using the network, we show that the predictive accuracy is substantially improved when using the vast information stored in the heterogeneous information network. This work suggests new ways to consolidate the diffuse information contained in big data to monitor dominant firms on a global scale for better risk management and more socially responsible investment

Predicted and Verified Deviations from Zipf's law in Ecology of Competing Products

Zipf's power-law distribution is a generic empirical statistical regularity found in many complex systems. However, rather than universality with a single power-law exponent (equal to 1 for Zipf's law), there are many reported deviations that remain unexplained. A recently developed theory finds that the interplay between (i) one of the most universal ingredients, namely stochastic proportional growth, and (ii) birth and death processes, leads to a generic power-law distribution with an exponent that depends on the characteristics of each ingredient. Here, we report the first complete empirical test of the theory and its application, based on the empirical analysis of the dynamics of market shares in the product market. We estimate directly the average growth rate of market shares and its standard deviation, the birth rates and the "death" (hazard) rate of products. We find that temporal variations and product differences of the observed power-law exponents can be fully captured by the theory with no adjustable parameters. Our results can be generalized to many systems for which the statistical properties revealed by power law exponents are directly linked to the underlying generating mechanism

CHANGE IN MECHANICAL PROPERTIES OF TRICEPS SURAE MUSCLE-TENDON UNIT AND RACE PERFORMANCE AFTER 1 YEAR IN WELL TRAINED DISTANCE RUNNERS

The purpose of this study was to determine change in relationship between stiffness of triceps surae muscle-tendon unit and race performance after one year with continuous training in well trained long distance runners. For 9 long distance runners, official race record and stiffness indexes of both muscle and tendon were investigated in pre and post measurements (after one year). The race performance (1.9%), passive torque of ankle joint (13.2%), and muscle stiffness index (73.6%) increased significantly between pre and post. Although significant correlations were not found between increment of race performance and change in all parameters, 6 of the 9 athletes showed increments of both race performance and stiffness index of muscle tissue. These results suggest that an increment of stiffness of the ankle joint and triceps muscle could be related to improvement of race performance in distance running

Sales Distribution of Consumer Electronics

Using the uniform most powerful unbiased test, we observed the sales distribution of consumer electronics in Japan on a daily basis and report that it follows both a lognormal distribution and a power-law distribution and depends on the state of the market. We show that these switches occur quite often. The underlying sales dynamics found between both periods nicely matched a multiplicative process. However, even though the multiplicative term in the process displays a size-dependent relationship when a steady lognormal distribution holds, it shows a size-independent relationship when the power-law distribution holds. This difference in the underlying dynamics is responsible for the difference in the two observed distributions

Structural insights into the agonists binding and receptor selectivity of human histamine H₄ receptor

慢性アレルギー疾患に関わるヒスタミン受容体の構造解明 --新規アトピー性皮膚炎・喘息治療薬の開発に貢献--. 京都大学プレスリリース. 2023-10-23.Histamine is a biogenic amine that participates in allergic and inflammatory processes by stimulating histamine receptors. The histamine H₄ receptor (H₄R) is a potential therapeutic target for chronic inflammatory diseases such as asthma and atopic dermatitis. Here, we show the cryo-electron microscopy structures of the H₄R-Gq complex bound with an endogenous agonist histamine or the selective agonist imetit bound in the orthosteric binding pocket. The structures demonstrate binding mode of histamine agonists and that the subtype-selective agonist binding causes conformational changes in Phe344[7.39], which, in turn, form the “aromatic slot”. The results provide insights into the molecular underpinnings of the agonism of H₄R and subtype selectivity of histamine receptors, and show that the H₄R structures may be valuable in rational drug design of drugs targeting the H₄R

LOCAL RECURRENCE OF RECTAL CANCER

One hundred twenty-six rectal cancers were operated upon in the First Department of Surgery, Nagasaki University School of Medicine. Local recurrence occurred in thirty-three (26.2%). In this study, contributing factors in causing local recurrence were local excision of the surgical approach, advanced stage, depth of cancer invasion, location of carcinoma of the rectum below the peritoneal reflection (Rb) or above (Rba) and nodal involvement of n2 or more. As far as advanced rectal cancer and cancer location of Rb are concerned, it is suggested on the basis of this study that the incidence of local recurrence should be high

B-L assisted Anomaly Mediation and the radiative B-L symmetry breaking

Anomaly mediated supersymmetry breaking implemented in the minimal supersymmetric standard model (MSSM) is known to suffer from the tachyonic slepton problem leading to breakdown of electric charge conservation. We show however that when MSSM is extended to explain small neutrino masses by gauging the B-L symmetry, the slepton masses can be positive due to the Z' mediation contributions. We obtain various soft supersymmetry breaking mass spectra, which are different from those obtained in the conventional anomaly mediation scenario. Then there would be a distinct signature of this scenario at the LHC.Comment: 20 pages, 7 figures; version to appear in Phys. Lett.

Ability of minimally invasive surgery to decrease incisional surgical site infection occurrence in patients with colorectal cancer and other gastroenterological malignancies

BackgroundSurgical site infection (SSI) is one of the most important complications of surgery for gastroenterological malignancies because it leads to a prolonged postoperative hospital stay and increased inpatient costs. Furthermore, SSI can delay the initiation of postoperative treatments, including adjuvant chemotherapy, negatively affecting patient prognosis. Identifying the risk factors for SSI is important to improving intra- and postoperative wound management for at-risk patients.MethodsPatients with gastroenterological malignancies who underwent surgery at our institution were retrospectively reviewed and categorized according to the presence or absence of incisional SSI. Clinicopathological characteristics such as age, sex, body mass index, malignancy location, postoperative blood examination results, operation time, and blood loss volume were compared between groups. The same analysis was repeated of only patients with colorectal malignancies.ResultsA total of 528 patients (330 men, 198 women; mean age, 68 ± 11 years at surgery) were enrolled. The number of patients with diseases of the esophagus, stomach, small intestine, colon and rectum, liver, gallbladder, and pancreas were 25, 150, seven, 255, 51, five, and 35, respectively. Open surgery was performed in 303 patients vs. laparoscopic surgery in 225 patients. An incisional SSI occurred in 46 patients (8.7%). Multivariate logistic regression analysis showed that postoperative hyperglycemia (serum glucose level ≥140 mg/dl within 24 h after surgery), colorectal malignancy, and open surgery were independent risk factors for incisional SSI. In a subgroup analysis of patients with colorectal malignancy, incisional SSI occurred in 27 (11%) patients. Open surgery was significantly correlated with the occurrence of incisional SSI (P = 0.024).ConclusionsPostoperative hyperglycemia and open surgery were significant risk factors for SSI in patients with gastroenterological malignancies. Minimally invasive surgery could reduce the occurrence of incisional SSI