This paper discusses three classical kinds of quantitative trading: the high-frequency trading, arbitrage, and factor investing. It then the tests five well-known stock factors on the S&P 500 over 24 months, from August 2024 to August 2026. Only momentum clearly made money, gaining 16.9% a year with a Sharpe ratio of 0.84. Value gained 3.1% and size 0.8%, which is close to nothing given how much both swung. The quality lost 14.2% and low volatility lost 31.4%. The market explains much of this. It was a strong bull market, but a narrow one, and the wildest stocks rose 48% a year while the calmest rose only 6.5%. Sorting stocks inside their own industry lifts value to 12.0% and size to 8.4%, so the plain sorts were partly bets on industries. Two years is a short test. These results mostly show how easily a short window can hide a long-run pattern.

The construction industry accounts for approximately 37% of global greenhouse gas emissions and 40% of global energy consumption. Against the backdrop of the "Dual Carbon" goal, how to achieve deep decarbonization across the whole life cycle of buildings through the effective integration of low-carbon technologies has become a core issue in the field of sustainable construction. Based on the Life Cycle Assessment (LCA) method, this study systematically explores the integration pathways of low-carbon technologies in sustainable buildings. Adopting a combination of literature review and comparative case analysis, the study sorts out the application framework of LCA in building carbon emission assessment, and analyzes the emission reduction potential and synergistic effects of four types of technologies—low-carbon building materials, passive design, active systems, and renewable energy—across different life cycle stages. The findings show that the emission reduction effect of low-carbon technologies is highly dependent on technology combinations and early intervention in the design stage; the marginal benefit of a single technology decreases as its application level increases, while the synergistic integration of multiple technologies can achieve a significant superimposed emission reduction effect; and the integrated framework of LCA and BIM provides effective technical support for low-carbon decision-making in the design stage. This study proposes a three-stage low-carbon technology integration path model of "source carbon reduction – process carbon reduction – end-of-life carbon offset", which provides a theoretical reference and practical framework for low-carbon design and decision-making of sustainable buildings.

As China's consumer environment continues to mature, public consumption attitudes have shifted notably. In the past, consumers largely prioritised product quality, practicality and price when making purchases. By contrast, contemporary consumption behaviour is partly shaped by emotional experiences, psychological perceptions and brand affinity. Against a backdrop of market homogenisation, conventional marketing practices centred on price promotions, intensive advertising and traffic‑driven sales tend to trigger aesthetic fatigue and psychological resistance among some consumers, with marketing effectiveness gradually diminishing over time. Unlike utilitarian traditional marketing, warm‑hearted marketing is anchored in sincerity, gentleness and healing emotions. It downplays overt commercial persuasion and seeks to narrow the psychological distance between brands and consumers through thoughtful service experiences and life‑oriented emotional resonance. Rather than deliberately chasing viral traffic success, warm‑hearted marketing focuses more on gradually building consumer trust and reputation, aligning with the consumption inclinations of certain young demographic groups who seek emotional release and relaxed experiences. Drawing on consumer psychology, empathetic communication, and brand humanisation perspectives, this paper interprets the concept, characteristics, and scope of application of warm‑hearted marketing. It identifies its differentiated competitive advantages and puts forward targeted suggestions to address industry malpractices such as fabricated sentimentality, mindless imitation, over‑emphasis on publicity, and poor on‑the‑ground implementation. Constrained by the author's knowledge and accessible data sources, this study adopts a qualitative analytical approach. Its arguments may carry certain biases, yet it hopes to offer references for small‑and‑medium‑sized enterprise owners and new‑media practitioners conducting emotional marketing.

Customized online advertisements can be comfy and embarrassing simultaneously. A search may save a consumer time through a recommendation that comes after a search. However, it can also indicate how much a platform has been tracking the activity of that individual. This study employs a dual-path model, as the same advertisement may have a potential benefit, relevance, and two potential costs: privacy issues and intrusiveness. The evidence sources are 13 publications that were created in 2012-2026 and were structured into a theory-driven evidence map; a questionnaire was not included. H1-H7 were used practically as labels to sort findings. They were not tested on a new sample. A number of papers associated personalization or targeting with increased relevance, attention, positive attitudes, clicks, or purchase intention. This trend was not as favorable when data collection was hidden, a personal sign was sensitive, or users had no control. Whereas there are published results regarding the individual relationships postulated under H5 and H6, none of the reviewed studies illustrate the entire mediation process to support the direct effect. There is even less evidence to support H7. Age groups were also focused on Gen Z, with none of the 13 papers designed for Gen Z, Millennials, and Gen X. The testimony was such as to give a tentative response. Beneficial personalization might be reasonable, as long as individuals can comprehend the data practices and do not find it overwhelming.

The popularisation of mobile Internet has reshaped the information dissemination and consumption path of domestic cosmetics, and Xiaohongshu's marketing has become an important way for new cosmetics brands to break into the market. Relying on the layered blogger placement of the Xiaohongshu platform and the operation of UGC user content, Perfect Diary completed the explosive expansion of the early user scale, but also exposed the endogenous shortcomings of the traffic-driven mode. This article takes Perfect Diary as a case, comprehensively uses the literature research method, case analysis method, and content analysis method, and analyses along the logical chain of "social media marketing - brand exposure - consumer purchase decision - user growth - traffic mode limitation". Research shows that social marketing can help domestic cosmetics improve brand exposure at a lower cost, change the consumer information environment, and then intervene in purchasing decision-making, and achieve rapid growth of short-term users; however, the traffic model will have problems such as rising investment costs, weak user loyalty, and the rapid spread of negative public opinion, which is beyond product research and development. It is difficult to sustain long-term growth. This article provides countermeasures for short-term customer acquisition, long-term brand building, and public opinion risk control of domestic cosmetics. At the same time, it explains the limitations of the research and provides a reference for similar digital marketing research.

With the aggravation of the crisis of social technology system, people pay more and more attention to the theoretical framework and practical path necessary for the transformation to sustainable development. This study combines the Doughnut model with the Design for Social Innovation (DfSI) approach to a thematic discussion of humanity's path to future sustainability. There is limited research on the design of interventions to achieve the Doughnut's socio-ecological goals. Doughnut's vision requires change driven by collective social action, and DfSI is inherently capable of guiding collective change toward new modes of production and lifestyles. We believe that DfSI can be used as a viable way for national and local sustainable transformation so that they can reach the safe and just operating space (SJOS). From the perspective of the Doughnut model, this paper introduces a new perspective for DfSI to study how to combine the core principles of the Doughnut model to enhance its implementation. Finally, this paper proposes a five-step conceptual framework for transforming Doughnut theory into local practice.

This study is focused on how mean, covariance shrinkage and regularization methods works within Markowitz Portfolio Optimization based on a micro asset pool, in which return dispersion can be extreme and one or two winners can dominate the cross-section. The analysis proceeds in two stages. Firstly, this study is focused on how to make the estimation of mean and covariance matrix more accurately, including historical estimates, James-Stein mean shrinkage, Ledoit-Wolf covariance shrinkage, joint shrinkage, confidence-bound robust means, and Michaud resampling are compared over risk-aversion coefficients of 2, 3, and 5 and estimation windows of 1, 2, and 5 years. Secondly, based on estimation window of 1 year with risk-aversion coefficients of 2, this study introduced different regularization methods including higher moments, an L2 weight penalty, a 25% position cap, a turnover penalty, and short selling with gross exposure limited to 1.5. Every test includes an equal position sizing portfolio and S&P 500 ETF as baselines. Furthermore, to avoid the bias of asset choosing manually, this study made 500 resampled asset pool with 7 stocks from a 36-stock historical Dow Jones constituent union. The result shows that Ledoit-Wolf shrinkage increases little in performance in the chosen asset pool while 25% position cap attains the highest median Sharpe ratio, 0.724, and exceeds the 1/N Sharpe ratio in 70.0% of samples across random pools, which indicates that model complexity is not uniformly valuable in a micro-universe: a method improves performance only when its reduction in estimation error exceeds the cost of suppressing informative cross-sectional signals.

This study explores how beauty influencer marketing affects consumers' purchase intention and purchase behavior. The study takes the S-O-R Model as the main framework, taking influencer characteristics as Stimulus factors, consumer trust and parasocial relationships as Organism factors, and purchase intention and purchase behavior as Response factors. The study adopts a qualitative multiple-case study method, with Perfect Diary as the common brand background, and selects three beauty influencers with different audience sizes, content styles, and product presentation methods: Li Jiaqi, Rong Dian'er, and Mia Mitang. The research uses public social media content, consumer reviews, corporate reports, and previous academic research results as secondary data. The study found that expertise can reduce information uncertainty, authenticity helps to enhance consumer trust, and similarity and long-term interaction can promote the establishment of parasocial relationships. In addition, influencer–product fit can also make the recommendation more natural. In general, this study shows that the impact of influencer marketing depends not only on exposure or follower count, but also on the psychological relationship between influencers and consumers.

This paper examines whether the growth of China's pet market is associated with higher wages and more jobs in Chinese cities. This paper uses two datasets: one is from the China Pet Industry White Paper, and the city data come from the China City Statistical Yearbook. From these datasets, this paper constructs a pet-shock measure by combining the 2019 share of pet owners reported for 20 cities with changes in national spending on dogs and cats. This paper then uses the lagged pet-shock variable as the independent variable to estimate regression models for wages and employment with city and year fixed effects. This paper finds that cities with greater lagged exposure tend to have higher average wages and more jobs in urban non-private units. The estimates are also positive for employment in health and social welfare and in accommodation and catering. These results suggest that growth in the pet market is associated with stronger local labor demand and with higher wages and employment in some urban service sectors.

This paper examines how IKEA combines a common sustainability strategy with market-level communication in the United Kingdom and China. The analysis is based on IKEA's global sustainability and circularity pages, together with country-specific webpages on household energy saving and circular services. Rather than assuming that Western consumers are addressed mainly through ethical language while Chinese consumers are addressed mainly through cost savings, the comparison finds a more mixed pattern. Both the UK and China pages connect energy use with household bills, promote energy-saving products and practices, and encourage customers to extend the life of furniture. The global strategy also sets common objectives for circular design, recycled or renewable materials, and circular services. Local adaptation is more visible in the language, service labels, and digital routes through which these ideas are presented. The case therefore suggests that IKEA standardizes the operational direction of sustainability while adapting the consumer-facing route through which the strategy becomes understandable in each market.