China Retail Investor Sentiment Analytics provides sentiment analytics of Chinese retail investors based on 2 stock forums, Guba (GACRIS dataset) and Xueqiu (XACRIS dataset), the most popular stock forums in China from 2007.

By utilizing in-house NLP models which are dedicatedly optimized for Chinese stock forum posts and trained on a proprietary manually labeled and cross-checked training data, the dataset provides accurate text analytics of post content, including but not limited to quality, sentiment, and relevant stocks with relevance score. In addition to the aggregated statistics of stock sentiment and popularity, the dataset also provides rich and fine-grained information for each user/post in record level. For example, it reports the registration time, number of followers for each user, and also the replies/readings and province being published for each post. Moreover, these meta data are processed in point-in-Time (PIT) manner since 2019.

The dataset could help clients easily capture the sentiment and popularity among millions of Chinese retail investors. On the other hand, it also offers flexibility for clients to customize novel analytics, such as studying the sentiment (conformity/divergence) of users of different level of influence or posts of different hotness, or simply filtering the posts published by users which are too active/positive/negative in a time window when aggregating the statistics.

Coverage: All A-share and Hong Kong stocks, 300+ popular US stocks Update Frequency: Daily or intra-day

Wealth Signal Generation AI Market Outlook

As per our latest research, the global Wealth Signal Generation AI market size reached USD 4.8 billion in 2024, demonstrating robust momentum with a CAGR of 27.4% projected through the forecast period. By 2033, the market is expected to escalate to USD 40.9 billion, fueled by rapid advancements in artificial intelligence, increased adoption of automation in wealth management, and the growing demand for data-driven investment strategies. The market’s expansion is primarily driven by the integration of AI-powered analytics in financial services, enabling institutions to generate actionable wealth signals with greater accuracy and speed.

A significant growth factor for the Wealth Signal Generation AI market is the increasing complexity of global financial markets. As investment instruments diversify and market volatility becomes more pronounced, financial institutions and individual investors are seeking advanced tools that can process vast datasets in real-time to identify lucrative opportunities and mitigate risks. AI-driven wealth signal generation platforms have become indispensable, leveraging machine learning and natural language processing to analyze market trends, news sentiment, and historical data. This capability not only enhances portfolio performance but also provides a competitive edge in an environment where milliseconds can make a difference in trading outcomes.

Another critical driver is the digital transformation sweeping across the financial sector. As wealth management firms, banks, and asset managers undergo digitalization, there is an increasing reliance on AI solutions to streamline operations, personalize client offerings, and automate routine tasks. Advanced AI algorithms can generate predictive signals for asset allocation, risk management, and investment timing, enabling financial advisors and portfolio managers to deliver more value-added services. Furthermore, the proliferation of cloud computing has made it easier for organizations of all sizes to deploy sophisticated AI tools without the need for significant upfront infrastructure investments, further accelerating market growth.

The democratization of investment advisory services through AI-powered platforms is also a prominent growth catalyst. Traditionally, sophisticated wealth management and signal generation tools were accessible only to large institutions or high-net-worth individuals. However, AI has leveled the playing field, allowing small and medium enterprises (SMEs) and retail investors to benefit from advanced analytics and signal generation capabilities. This trend is fostering greater market participation and driving innovation in product offerings, as vendors compete to provide user-friendly, cost-effective AI solutions tailored to diverse client segments.

From a regional perspective, North America currently dominates the Wealth Signal Generation AI market, accounting for the largest share due to its mature financial ecosystem, early adoption of advanced technologies, and strong presence of leading AI vendors. However, the Asia Pacific region is witnessing the fastest growth, propelled by rapid economic development, increasing digitalization in the financial sector, and the emergence of fintech hubs in countries like China, Singapore, and India. Europe also represents a significant market, driven by stringent regulatory requirements and a high concentration of wealth management firms. Latin America and the Middle East & Africa are gradually catching up, supported by rising investments in financial technology and growing awareness of the benefits of AI in wealth management.

Component Analysis

The Wealth Signal Generation AI market is segmented by component into software, hardware, and services, each playing a pivotal role in the ecosystem. The software segment holds the largest share, driven by the continuous evolution of AI algorithms and platforms that power signal generation. These software solutions encompass machine learning models, predictive analytics, and data visualization tools that enable financial professionals to extract actionable insights from vast datasets. The demand for customizable and scalable software solutions is particularly high among asset management firms and hedge funds, where agility and precision are paramount. Vendors are increasingly focusing on developing modular, API-driven platforms that can seamlessly integrate with existing financial systems, further boosting software adoption.&

Based on Bloomberg's Billionaires index...

The Bloomberg Billionaires Index is a daily ranking of the world's richest people. In calculating net worth, Bloomberg News strives to provide the most transparent calculations available, and each individual billionaire profile contains a detailed analysis of how that person's fortune is tallied.

The index is a dynamic measure of personal wealth based on changes in markets, the economy and Bloomberg reporting. Each net worth figure is updated every business day after the close of trading in New York. Stakes in publicly traded companies are valued using the share's most recent closing price. Valuations are converted to U.S. dollars at current exchange rates.

Closely held companies are valued in several ways, such as by comparing the enterprise value-to-Ebitda or price-to-earnings ratios of similar public companies or by using comparable transactions. Calculations of closely held company debt -- if net debt cannot be determined -- are based on the net debt-to-Ebitda ratios of comparable peers. The value of closely held companies adjusts daily based on market moves for peer companies or by applying the market movement of a relevant industry index. The criteria used to choose peer companies is based on the closely held asset's industry and size.

When ownership of closely held assets cannot be verified, they aren't included in the calculations. The specific valuation methodology for each closely held company is included in the net worth analysis section of a billionaire's profile. Additional details included in the valuation notes for each asset are available to subscribers of the Bloomberg Professional Service.

A standard liquidity discount of 5 percent is applied to most closely held companies where assets may be hard to sell. When a different percentage is used an explanation is given. No liquidity discounts are applied to the values of public stakes. In some instances, a country risk discount is also applied based on a person's concentration of assets and ease of selling them in a given geography. A country's risk is assessed based on Standard & Poor's sovereign debt ratings.

If a billionaire has pledged as collateral shares he or she holds in a public company, the value of those shares or the value of a loan taken against them is removed from the net worth calculation. If reliable information can be obtained about the ultimate use of those borrowed funds, that value is added back into the calculation.

Hedge fund businesses are valued using the average market capitalization-to-assets under management ratios of the most comparable publicly traded funds. Fee income is not considered because it cannot be uniformly verified. Personal funds invested along with outside capital are not included in the calculation. A "key man" risk discount of 25 percent is applied to funds whose performance is tied to a single individual. Assets under management are updated using ADV forms filed with the federal government and news reports, and returns are factored when sourced to reports from credible news outfits, the HFRI Index and industry analysts.

Net worth calculations include dividend income paid and proceeds from the sale of public and closely held shares. Taxes are deducted based on prevailing income, dividend and capital gains tax rates in a billionaire's country of residence. Taxes are applied at the highest rate unless there is evidence to support a lower percentage, in which case an explanation is given in the net worth summary. For calculations of cash and other investable assets, a hybrid return based on holdings in cash, government bonds, equities and commodities is applied.

No assumptions are made about personal debt. Family members often hold a portion of a billionaire's assets. Such transfers don't change the nature of who ultimately controls the fortune. As a result, Bloomberg News operates under the rule that all billionaire fortunes are inherently family fortunes and credit family fortunes to the founders or ranking family members who are determined to have direct control over the assets. When individual stakes can be verified and adult family members have an active role in a business, the value is credited to each individual.

Each billionaire -- or a representative -- is given an opportunity to respond to questions regarding the net worth calculation, including assets and liabilities.

Bloomberg News editorial policy is to not cover Bloomberg L.P. As a result, Michael Bloomberg, the founder and majority owner of Bloomberg L.P., isn't considered for this ranking.

Because calculating net worth requires a degree of estimation, bull and bear case scenarios that would make a person's fortune higher or lower than the Bloomberg Billionaires Index valuation are included on the Bloomberg Professional Service. A confidence rating also is included on each profile:

ESG Data for Retail Investors Market Outlook

According to our latest research, the global ESG Data for Retail Investors market size is valued at USD 2.3 billion in 2024, with a robust CAGR of 15.7% anticipated from 2025 to 2033. By 2033, the market is forecasted to reach USD 8.1 billion, driven by increasing regulatory requirements, heightened investor awareness, and the integration of ESG criteria into mainstream retail investment strategies. The growth trajectory is underpinned by a confluence of technological innovation, expanding data coverage, and a marked shift in investor preferences toward sustainable and responsible investment options.

One of the pivotal growth factors for the ESG Data for Retail Investors market is the surge in demand for transparency and accountability in investment decision-making. Retail investors are increasingly seeking actionable ESG insights to align their portfolios with personal values and societal expectations. As climate change, social inequality, and corporate governance scandals continue to dominate headlines, the appetite for granular, real-time ESG data has intensified. Regulatory authorities across major markets—including the European Union’s Sustainable Finance Disclosure Regulation (SFDR) and the US SEC’s proposed climate risk disclosure rules—are compelling financial institutions to provide more robust ESG disclosures, further fueling demand for high-quality ESG datasets tailored for retail consumption.

Another significant driver is the technological advancement in data collection, processing, and analytics. The proliferation of artificial intelligence and machine learning algorithms has enabled the aggregation and interpretation of vast unstructured datasets, transforming the way ESG information is sourced and delivered. Cloud-based platforms and APIs are making ESG data more accessible, affordable, and customizable for retail investors, democratizing access that was once exclusive to institutional players. The integration of ESG analytics into robo-advisors, mobile trading apps, and digital wealth management platforms is broadening the reach of ESG data, empowering individual investors to make informed, values-driven investment choices at the click of a button.

The evolving landscape of retail investment is also characterized by a shift in generational wealth and investment priorities. Millennials and Gen Z investors, who are set to inherit trillions in assets over the next decade, consistently rank ESG considerations among their top investment criteria. This demographic transition is catalyzing innovation in ESG data products and services, with providers racing to offer more granular, real-time, and interactive ESG insights. The rapid adoption of sustainable investment funds, green bonds, and impact investing vehicles is reinforcing the centrality of ESG data in retail investment workflows, prompting both fintech startups and established data vendors to expand their offerings in this high-growth segment.

From a regional perspective, North America and Europe collectively account for the lion’s share of the ESG Data for Retail Investors market, together representing over 65% of global revenues in 2024. These regions are characterized by mature financial markets, progressive regulatory frameworks, and high investor awareness of ESG issues. Asia Pacific, meanwhile, is emerging as the fastest-growing region, propelled by regulatory reforms, expanding middle-class wealth, and increased digitalization of financial services. Latin America and the Middle East & Africa are also witnessing steady growth, albeit from a smaller base, as local governments and financial institutions begin to prioritize ESG integration and reporting in response to global sustainability trends.

Data Type Analysis

The data type segment in the ESG Data for Retail Investors market is crucial, as it determines the depth, breadth, and relevance of ESG insights available to retail investors. Environmental data encompasses metrics on carbon emissions, energy usage, water consumption, waste management, and biodiversity impact. With the rising urgency of climate change, environmental data is increasingly prioritized by investors and regulators alike. Companies that provide real-time emissions tracking, climate risk modeling, and scenario analysis are witnessing heightened demand, especially as governments set ambitious net-zero targets and introduce

Question 2.3.1a: Are there numeric rules governing the size of withdrawals from the sovereign wealth fund?, 2.3.6c: From 2015 onwards, has the legislature reviewed the sovereign wealth fund's annual financial reports?, 2.3.3a: Is the sovereign wealth fund prohibited from investing in domestic assets without budgetary approval?, 2.3.3b: Is the sovereign wealth fund prohibited from investing in certain asset classes or investment types?

2.3.1a: Are there numeric rules governing the size of withdrawals from the sovereign wealth fund? 2.3.1b: Do rules require that withdrawals and spending from the sovereign wealth fund pass through the national budget? 2.3.3a: Is the sovereign wealth fund prohibited from investing in domestic assets without budgetary approval? 2.3.5a: Is the sovereign wealth fund required to produce annual financial reports? 2.3.5b: Is the sovereign wealth fund required to publicly disclose these annual financial reports? 2.3.5c: Do rules require an external body to periodically audit the sovereign wealth fund's annual financial reports? 2.3.5d: Is the legislature required to review the sovereign wealth fund's annual financial reports? 5.11a: Do rules require that funds transferred to/from the sovereign wealth fund are transferred via the government's general unified account (e.g. treasury account)?

Thank you to Norges Bank Investment Management for providing this invaluable resource.

Norges Bank Investment Management (NBIM) manages the Government Pension Fund Global, known as the Norwegian Oil Fund. Established in 1998, NBIM oversees approximately $1.5 trillion in assets as of 2023, making it one of the largest sovereign wealth funds globally.

NBIM's diversified investment strategy includes:

Equity: Investing in 9,000 public-traded companies worldwide, representing about 70% of the fund.

Fixed Income: Allocated to government and corporate bonds.

Real Estate: High-quality properties in major cities and global distribution networks, with up to 7% of the fund in unlisted real estate.

Infrastructure for Renewable Energy: Wind and solar projects in Europe and North America, with up to 2% of the fund in unlisted renewable energy infrastructure.

There are a total of five files: 'equity.xlsx' , 'fixed_income.xlsx', 'real_estate.xlsx', 'renewable_energy.xlsx', and 'norges.xlsx'. The file 'norges.xlsx' contains all the data, but I created the other four files to represent NBIM's investment strategies and make the information more readable and accessible.

This dataset is particularly interesting as it comes from the world's most transparent sovereign wealth fund, offering a unique insight into its management.

Source: https://www.nbim.no/