In 2024, ** percent of adults in the United States invested in the stock market. This figure has remained steady over the last few years, and is still below the levels before the Great Recession, when it peaked in 2007 at ** percent. What is the stock market? The stock market can be defined as a group of stock exchanges, where investors can buy shares in a publicly traded company. In more recent years, it is estimated an increasing number of Americans are using neobrokers, making stock trading more accessible to investors. Other investments A significant number of people think stocks and bonds are the safest investments, while others point to real estate, gold, bonds, or a savings account. Since witnessing the significant one-day losses in the stock market during the Financial Crisis, many investors were turning towards these alternatives in hopes for more stability, particularly for investments with longer maturities. This could explain the decrease in this statistic since 2007. Nevertheless, some speculators enjoy chasing the short-run fluctuations, and others see value in choosing particular stocks.

In 2023, 52 percent of the households in the United States owned shares in a mutual fund. This is a significant increase on the 5.7 percent recorded in 1980, but close to 46.3 percent found in 2013.Mutual fundsA mutual fund is a variety of collective investment vehicle, managed professionally that pools money from many investors in order to purchase securities. They play an important role in household finances in the United States of today, most notably in retirement planning. It is commonly applied only to the forms of collective investment that are regulated and are sold to the public at large. The majority of mutual funds are what is known as ‘open-ended’, meaning that shares can be bought or sold at anytime. There are a number of advantages associated with mutual funds as opposed to direct investment in individual securities. The nature of the fund as a collective investment vehicle provides increased diversification and ease of comparison to investors. The fact that they are managed professionally, and that the investment is pooled, enables participation in investments that would normally only be available to larger investors. Mutual funds are also stable in price as daily liquidity ensures minimum loss of value. Despite several advantages, as with every aspect of investment some disadvantages are to be taken into account. Fees are an inevitable part of a professionally managed fund, as is the inability to customize the investment. A common complains is also that the investor has less control over timing of the recognition of their gains.

Investment Tracking Apps Market Outlook

The global investment tracking apps market size was valued at approximately USD 2.5 billion in 2023 and is projected to reach USD 6.8 billion by 2032, growing at a compound annual growth rate (CAGR) of 11.5% during the forecast period. This robust growth can be attributed to the increasing adoption of digital financial tools, the rising popularity of mobile banking, and the growing need for efficient portfolio management solutions. As more individuals and institutions seek to optimize their investment strategies and track their financial assets in real-time, the demand for sophisticated investment tracking apps is poised to surge.

One of the key growth factors driving the market is the rapid advancement in financial technology (fintech). Innovations in fintech have led to the development of more user-friendly and feature-rich applications that make investment tracking more accessible and efficient. These advancements have simplified the complexities associated with financial management, enabling even novice investors to manage and monitor their portfolios with ease. Moreover, the integration of artificial intelligence (AI) and machine learning (ML) in these apps provides users with personalized insights and recommendations, enhancing their investment decision-making processes.

Another significant growth driver is the increasing awareness and interest in personal finance and investment among the global population. As financial literacy improves and more individuals recognize the importance of managing their finances, the demand for tools that aid in investment tracking and portfolio management has seen a substantial rise. Additionally, the COVID-19 pandemic has accelerated the shift towards digital financial services, as people sought contactless and remote ways to handle their finances. This shift has further fueled the adoption of investment tracking apps.

The rise in the number of retail investors entering the market has also contributed to the growth of investment tracking apps. Platforms such as Robinhood have democratized access to financial markets, allowing individuals to trade and invest with minimal barriers. This influx of new investors has created a demand for tools that provide comprehensive insights, real-time alerts, and performance analytics to aid in informed decision-making. Investment tracking apps have become essential tools for these investors to stay on top of their portfolios and market movements.

Regional growth trends indicate that North America holds the largest share of the investment tracking apps market, owing to its advanced technological infrastructure and high adoption rates of fintech solutions. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period. The increasing penetration of smartphones, rising disposable incomes, and growing interest in investment activities in countries like China and India are driving the market in this region. Europe and Latin America are also experiencing steady growth, supported by favorable regulatory environments and increasing financial awareness among their populations.

Platform Analysis

The investment tracking apps market is segmented by platform into iOS, Android, and web-based applications. Each of these platforms offers unique advantages and caters to different user preferences and requirements. iOS applications are known for their user-friendly interfaces, robust security features, and seamless integration with other Apple devices. This makes them particularly popular among high-net-worth individuals and professional investors who prioritize a premium and secure user experience. Additionally, iOS users are generally more willing to spend on premium features and subscriptions, contributing significantly to the revenue generated in this segment.

Android-based investment tracking apps, on the other hand, benefit from the wide adoption of Android devices globally. The Android platformÂ’s flexibility and compatibility with a diverse range of devices make it accessible to a broader audience, including individual investors and financial advisors. The open-source nature of Android allows developers to innovate and create highly customizable applications, adding to their appeal. The lower cost of Android devices also makes these apps more accessible to a wider demographic, including users in emerging markets where smartphone penetration is rapidly increasing.

Web-based investment tracking applications offer the advantage of cross-platform accessibility. Users can access

Mutual Funds Sales Market Outlook

As of 2023, the global mutual funds sales market size stands at approximately $56 trillion, with expectations to surpass $80 trillion by 2032, driven by a compound annual growth rate (CAGR) of 4.1%. The primary growth factors include increased investor awareness, technological advancements in financial services, and the rise of the middle-income population, particularly in emerging markets. This remarkable growth trajectory underscores a robust demand for diverse investment vehicles that cater to varying risk appetites and financial goals.

One of the pivotal growth factors for the mutual funds sales market is the increasing financial literacy and awareness among individuals globally. As more people become knowledgeable about financial planning and investment strategies, mutual funds have emerged as an appealing option due to their diversified risk profiles and potential for higher returns compared to traditional savings accounts. Governments and financial institutions are also playing a significant role by promoting financial education initiatives, which are further driving the adoption of mutual funds among retail investors.

Technological advancements and digital transformation in the financial services sector are also critical growth drivers. The rise of fintech platforms has streamlined the process of buying and managing mutual fund investments, making it more accessible and convenient for investors. Online platforms and mobile applications provide real-time data, personalized investment advice, and easy transaction processes, thus attracting a broader audience. These technological innovations are particularly resonating with younger, tech-savvy investors who prefer managing their investments digitally.

Another significant factor contributing to the market's growth is the economic development in emerging markets, particularly in the Asia Pacific and Latin America regions. The growing middle-income population in these regions is increasingly looking for investment opportunities that offer better returns than traditional savings. With increasing disposable income, more individuals are willing to invest in mutual funds to achieve their financial goals, such as retirement planning, education, and wealth accumulation. This trend is further bolstered by the improving regulatory frameworks and the expansion of financial services in these regions.

Regionally, North America continues to dominate the mutual funds sales market, accounting for a significant share due to its mature financial markets and high investor participation rates. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period, driven by rapid economic development, increasing financial inclusion, and technological advancements in the financial services sector. Europe, Latin America, and the Middle East & Africa also present significant growth opportunities, albeit at a slower pace compared to the Asia Pacific.

Fund Type Analysis

The mutual funds sales market can be segmented by fund type into equity funds, bond funds, money market funds, hybrid funds, and others. Each of these fund types caters to different risk appetites and investment goals, providing investors with a range of options to choose from. Equity funds, which invest primarily in stocks, are popular among investors seeking higher returns over the long term, despite their higher risk. As of 2023, equity funds constitute a substantial portion of the market, driven by bullish stock markets and investor optimism.

Bond funds, which invest in government and corporate bonds, appeal to risk-averse investors seeking stable income. These funds are less volatile compared to equity funds and provide regular interest income, making them attractive during periods of economic uncertainty. The demand for bond funds is expected to remain steady, supported by an aging population that prefers lower-risk investments and the need for income-generating assets in a low-interest-rate environment.

Money market funds, known for their high liquidity and safety, invest in short-term, high-quality debt instruments. These funds are ideal for investors looking for a safe place to park their money temporarily or those who need quick access to their funds. The market for money market funds has seen significant growth due to the ongoing economic uncertainties and the tendency of investors to seek safe-haven assets.

Hybrid funds, which combine elements of both equity and bond funds, offer a balanced approa

Statistics on the number of men who have developed alternative services to serve in various industries over the years

Passive ETF Market Outlook

In 2023, the global Passive ETF market size was valued at approximately USD 6.1 trillion and is projected to reach USD 11.4 trillion by 2032, growing at a CAGR of 7.2% over the forecast period. The primary growth factor for this market is the increasing preference for low-cost investment options among retail and institutional investors alike.

One of the significant growth factors driving the Passive ETF market is the rise in awareness and education about financial markets among retail investors. More individuals are becoming informed about the benefits of diversified, low-cost investment portfolios. Passive ETFs, which typically track a specific index, offer a cost-effective way for investors to gain broad market exposure without the need for intensive management. This factor is particularly appealing to new investors who wish to participate in the stock market with minimal fees and reduced risk.

Another critical driver is the surge in technological advancements and digitalization in financial services. Online trading platforms and robo-advisors are making it easier for investors to access a wide array of ETF products. These platforms often provide tools and resources that help investors make informed decisions, thereby encouraging more people to invest in Passive ETFs. The ease of use, coupled with low transaction costs, has further popularized Passive ETFs among various investor segments.

Institutional investors are also increasingly turning to Passive ETFs to optimize their investment strategies. With market volatility and economic uncertainties, institutional investors seek stable and predictable investment solutions. Passive ETFs offer a reliable way to achieve market returns without the need to actively manage individual securities. This stability is particularly important for pension funds, endowments, and insurance companies, which have long-term investment horizons and fiduciary responsibilities to their beneficiaries.

Regionally, North America continues to dominate the Passive ETF market, owing to its mature financial markets and large base of institutional and retail investors. However, other regions like Asia Pacific are catching up rapidly. The growing middle class, rising disposable incomes, and increasing financial literacy are significant factors contributing to the market's growth in this region. Additionally, favorable regulatory changes and the introduction of innovative financial products are expected to drive the market further in Asia Pacific.

Type Analysis

In the Passive ETF market, various types, including Equity ETFs, Bond ETFs, Commodity ETFs, Real Estate ETFs, and others, offer diverse investment opportunities. Equity ETFs hold the largest market share, primarily due to their ability to provide broad exposure to stock markets, mirroring the performance of major indices like the S&P 500 or the NASDAQ. As investors seek to capitalize on market growth while minimizing costs, the demand for Equity ETFs continues to rise. They are particularly popular among retail investors looking to gain diversified exposure to the equity market without picking individual stocks.

Bond ETFs are another critical segment within the Passive ETF market, offering investors a way to gain exposure to the fixed income market. These ETFs are essential for those looking to balance their portfolios with more stable, income-generating investments. Bond ETFs can provide access to government, corporate, and municipal bonds. The predictable income stream and lower risk compared to equities make Bond ETFs a favorite among conservative investors and retirees. Additionally, in a low-interest-rate environment, Bond ETFs become even more attractive as they offer better returns compared to traditional savings accounts.

Commodity ETFs cater to investors looking to diversify their portfolios with tangible assets like gold, silver, oil, and other commodities. These ETFs provide a convenient way to invest in commodities without the complexities involved in holding physical assets. Commodity ETFs are particularly popular during times of economic uncertainty and inflation, as they often serve as a hedge against market volatility and currency devaluation. The demand for these ETFs is expected to grow as investors seek more avenues to protect their wealth.

Real Estate ETFs provide exposure to the real estate market by investing in a diversified portfolio of real estate investment trusts (REITs). These ETFs offer a way to participate in the real estate market without th

Context

Netflix, Inc. is an American media company engaged in paid streaming and the production of films and series.

Market cap

Market capitalization of Netflix (NFLX)

Market cap: $517.08 Billion USD

As of June 2025 Netflix has a market cap of $517.08 Billion USD. This makes Netflix the world's 19th most valuable company by market cap according to our data. The market capitalization, commonly called market cap, is the total market value of a publicly traded company's outstanding shares and is commonly used to measure how much a company is worth.

Revenue

Revenue for Netflix (NFLX)

Revenue in 2025: $40.17 Billion USD

According to Netflix's latest financial reports the company's current revenue (TTM ) is $40.17 Billion USD. In 2024 the company made a revenue of $39.00 Billion USD an increase over the revenue in the year 2023 that were of $33.72 Billion USD. The revenue is the total amount of income that a company generates by the sale of goods or services. Unlike with the earnings no expenses are subtracted.

Earnings

Earnings for Netflix (NFLX)

Earnings in 2025 (TTM): $11.31 Billion USD

According to Netflix's latest financial reports the company's current earnings are $40.17 Billion USD. In 2024 the company made an earning of $10.70 Billion USD, an increase over its 2023 earnings that were of $7.02 Billion USD. The earnings displayed on this page is the company's Pretax Income.

End of Day market cap according to different sources

On Jun 12th, 2025 the market cap of Netflix was reported to be:

$517.08 Billion USD by Yahoo Finance

$517.08 Billion USD by CompaniesMarketCap

$517.21 Billion USD by Nasdaq

Content

Geography: USA

Time period: May 2002- June 2025

Unit of analysis: Netflix Stock Data 2025

Variables

Acknowledgements

This dataset belongs to me. I’m sharing it here for free. You may do with it as you wish.

Like several other app industries, stock trading and investment saw a huge spike in usage during the coronavirus pandemic. Millions of people stuck at home were able to take advantage of new...

Assets Under Management (AUM) Market Outlook

The global assets under management (AUM) market size was valued at approximately $123 trillion in 2023 and is projected to reach around $250 trillion by 2032, reflecting a compound annual growth rate (CAGR) of about 7.5%. The significant growth of the AUM market is driven by increasing global wealth, rising investor awareness, and technological advancements in wealth management services. Additionally, the growing interest in diversified investment portfolios and the expansion of investment opportunities across various asset classes are crucial factors contributing to the market's robust growth trajectory.

One of the primary growth factors in the AUM market is the continuous increase in global wealth, particularly in emerging economies. As more individuals and institutions accumulate wealth, the demand for professional asset management services rises. This trend is further supported by the increasing number of high-net-worth individuals (HNWIs) and the growing middle class with disposable income to invest. Moreover, the rising awareness and education about financial planning and investment options have encouraged more people to seek professional asset management services to optimize their returns and manage risks effectively.

Technological advancements in the financial sector have also played a significant role in the expansion of the AUM market. The adoption of artificial intelligence, big data analytics, and blockchain technology has revolutionized the asset management industry, making it more efficient, transparent, and accessible. These technologies enable asset managers to provide personalized investment strategies, improve decision-making processes, and reduce operational costs. Furthermore, the rise of robo-advisors has democratized access to asset management services, allowing retail investors to benefit from professional investment guidance at a lower cost.

The diversification of investment portfolios across various asset classes is another key driver of the AUM market's growth. Investors are increasingly looking beyond traditional asset classes like equities and fixed income to explore alternative investments such as real estate, private equity, and hedge funds. This shift is driven by the desire to achieve better risk-adjusted returns and to hedge against market volatility. As a result, asset managers are expanding their offerings to include a wider range of investment options, catering to the evolving preferences of their clients.

Regionally, North America continues to dominate the AUM market, followed by Europe and Asia Pacific. The mature financial markets, high concentration of wealth, and advanced investment infrastructure in North America contribute to its leading position. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period, driven by rapid economic development, increasing wealth accumulation, and the growing adoption of digital financial services. Latin America and the Middle East & Africa, while currently smaller markets, also present significant growth opportunities due to improving economic conditions and rising investor interest.

Asset Class Analysis

The AUM market is segmented by asset class, including equities, fixed income, real estate, alternatives, cash and cash equivalents, and others. Equities represent a substantial portion of the AUM market, driven by their potential for high returns and the general investor optimism towards stock markets. The increasing global stock market capitalization and the introduction of innovative equity investment products have further boosted the growth of this segment. Additionally, the rising participation of retail investors in stock markets, facilitated by digital trading platforms, has significantly contributed to the expansion of equity assets under management.

Fixed income assets, such as bonds and other debt instruments, form another crucial segment of the AUM market. These investments are typically favored for their relatively stable returns and lower risk compared to equities. The demand for fixed income assets is particularly strong among institutional investors, such as pension funds and insurance companies, which seek to match their long-term liabilities with stable income streams. Moreover, the current low-interest-rate environment in many developed economies has led investors to seek yield in fixed income securities of emergin

Stock Fund Sales Market Outlook

The global stock fund sales market is projected to witness substantial growth, expanding from an estimated USD 20 trillion in 2023 to approximately USD 35 trillion by 2032, growing at a compound annual growth rate (CAGR) of 6%. This robust market size increase is driven by several key factors, including rising disposable incomes, growing awareness of investment opportunities, and the increasing popularity of diversified investment portfolios. The growth in the stock fund sales market is underpinned by the increasing number of retail and institutional investors seeking to capitalize on the benefits of stock funds as a vehicle for wealth accumulation and risk management.

A significant growth factor in the stock fund sales market is the proliferation of financial literacy programs and investment education. As governments and financial institutions worldwide invest in educating the masses about the importance of saving and investing, more individuals are becoming aware of stock funds as a viable and lucrative investment option. This educational push has led to an upsurge in the number of retail investors entering the market, thereby driving demand for various types of stock funds. Additionally, the ease of access to information through the internet and social media platforms has further facilitated this growth, enabling potential investors to make more informed decisions.

Another driving factor is the technological advancements in financial services, especially in the realm of online trading and investment platforms. The advent of robo-advisors and automated trading systems has made it easier for individuals to invest in stock funds with little to no manual intervention. These platforms provide personalized investment advice and portfolio management services, which have democratized access to sophisticated investment strategies previously available only to high-net-worth individuals. The convenience, lower fees, and increased transparency offered by these technologies have significantly contributed to the growth of the stock fund sales market.

Moreover, the increasing globalization of financial markets has played a crucial role in the expansion of the stock fund sales market. With the removal of barriers to capital flows across borders, investors now have greater access to international stock funds. This trend has been particularly pronounced in emerging markets, where economic growth rates are higher, and investment opportunities are abundant. As a result, there has been a notable increase in the demand for global and regional stock funds, further propelling market growth. Additionally, regulatory reforms in various countries aimed at protecting investors and ensuring market stability have boosted investor confidence, thereby encouraging more investment in stock funds.

From a regional perspective, North America continues to dominate the stock fund sales market, accounting for a significant share of the global market. The region's well-developed financial infrastructure, high levels of disposable income, and a strong culture of investment are key factors driving this dominance. Additionally, the presence of major financial institutions and asset management companies in North America supports the growth of the stock fund market. However, the Asia Pacific region is expected to witness the fastest growth during the forecast period, driven by rapid economic development, increasing financial literacy, and a burgeoning middle class with rising disposable incomes. The growing penetration of digital financial services in countries such as China and India is also a significant contributor to the region's growth.

Fund Type Analysis

The stock fund sales market can be segmented by fund type, including equity funds, bond funds, money market funds, hybrid funds, and others. Equity funds are among the most popular types of stock funds, attracting a significant portion of investor capital. These funds invest primarily in stocks and aim to generate high returns by capitalizing on the growth potential of companies. The appeal of equity funds lies in their potential for higher returns compared to other types of investments, albeit with a higher level of risk. Factors such as market volatility, economic conditions, and company performance play crucial roles in determining the success of equity funds. The increasing awareness of the long-term benefits of equity investments is driving the demand for these funds.

Bond funds, which invest in various types of bonds, are another important segment within the stock fund sales market. These funds are generally considered safer t

The largest number of people in the United Kingdom participating in the investment market came from Gen Z. Silent generation accounted for the second largest number of investors in the UK with over ** percent having invested in financial securities.

Dhaka Stock Exchange (DSE) Historical Stock Prices (2000-2025)

Dataset Overview:

This dataset provides a comprehensive historical record of stock prices from the Dhaka Stock Exchange (DSE), the primary stock exchange of Bangladesh. Spanning from January 1, 2000, to February 26, 2025, it offers a detailed look into the daily trading activity of 464 unique stocks.

Key Features:

• Date: The trading date (YYYY-MM-DD format).
• Script (Stock Name): The name or ticker symbol of the listed company.
• Open: The opening price of the stock on the given trading day.
• High: The highest price reached by the stock during the trading day.
• Low: The lowest price reached by the stock during the trading day.
• Close: The closing price of the stock on the given trading day.
• Volume: The total number of shares traded for the stock on the given trading day.

Data Characteristics:

• Time Span: January 1, 2000, to February 26, 2025.
• Number of Unique Stocks: 464
• Frequency: Daily
• Accuracy: Clean and accurate data, suitable for reliable analysis.

Potential Uses:

• Financial Analysis: Analyze stock trends, volatility, and performance over time.
• Machine Learning: Develop predictive models for stock price forecasting.
• Economic Research: Study the impact of economic events on the Bangladeshi stock market.
• Investment Strategies: Backtest trading strategies and identify potential investment opportunities.
• Educational Purposes: Learn about stock market dynamics and data analysis in finance.

Acknowledgements:

This dataset was meticulously compiled and cleaned to provide a valuable resource for researchers, analysts, and investors interested in the Dhaka Stock Exchange.

Note:

While efforts have been made to ensure the accuracy of the data, users are advised to conduct their own due diligence and validation before making any investment decisions based on this dataset.

This description highlights the key aspects of your dataset, its potential uses, and its reliability. Feel free to adjust it further based on any specific details or insights you want to emphasize!

Name: Characterization of investments profiles on the energy transition for european citizens

Summary: The dataset contains: (1) surveyee consent form for the study, (2) different scenarios about the energy transition, (3) determinant factors about those scenarios, (4) socioeconomic description of the surveyee, (5) investment decisions, (6) and household characterization/description.

License: cc-BY-SA

Acknowledge: These data have been collected in the framework of the WHY project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 891943.

Disclaimer: The sole responsibility for the content of this publication lies with the authors. It does not necessarily reflect the opinion of the Executive Agency for Small and Medium-sized Enterprises (EASME) or the European commission (Ec). EASME or the Ec are not responsible for any use that may be made of the information contained therein.

Collection Date: 22/07/2022

Publication Date: 15/10/2023

DOI: 10.5281/zenodo.4455198

Other repositories:

Author: University of Deusto

Objective of collection: This data was originally collected to analyze quantitatively the decisions of everyday people in relation to their energy consumption and their reactions to specific political interventions.

Description: The dataset contains a ODS spreadsheet file containing data collected from a survey about energy consumption investments. The fields that can be found for each entry are (1) Different scenarios about the energy transition and reactions to those scenarios, (money spent on energy investments, decisions about scenarios, actions taken under a blackout, etc.) (2) Determinant factors about the chosen scenarios in the previous question, which include different choices that could affect your decision about a scenario (3) socioeconomic information about the user (age, country of residence, studies), (4) estimation of the prices of various technologies related to the energy transition and (5) descriptive statistics about the household living situation (gender of user, people living in household, yearly rent, average savings per month, type of house, size of house) and also includes questions about climate change expertise. Next you can found a description of each field in the dataset

Section 1 - Scenarios for energy transition.

ID90. Rank in order of priority, from top to bottom, in which scenario you will be willing to live or to contribute/invest to make it possible.

ID36, ID38, ID43, ID44, ID72. Percentage of money people are willing to spend/save out of their income per scenario

ID191, ID192.. Amount of money people would spend based on an assumed case.

ID191, ID192. Priority service provision in case of Intermittent energy service. Rating energy services from 0 to 10 stars, where 0 stars means it is extremely low priority for you and 10 stars means it is absolutely necessary for you.

[ID325, ID326, ID327, ID328, ID329, ID330, ID331, ID332, ID333, ID334, ID335, ID336, ID337, ID338, ID339, ID340, ID341, ID133, ID242]. Priority service provision in case of Intermittent energy service. Rating energy services from 0 to 10 stars, where 0 stars means it is extremely low priority and 10 stars means it is absolutely necessary.

[ID251, ID256, ID257, ID292, ID293, ID294, ID295, ID296, ID297, ID298, ID299, ID301, ID302, ID303, ID304, ID305, ID306, ID250, ID251]. Priority service provision in case of full black-outs. Rating energy services from 0 to 10 stars, where 0 stars means it is extremely low priority and 10 stars means it is absolutely necessary.

[ID141, ID5, ID147]. Used for statements that best represent survey responder

Section 2 - Determinants (factors). Questions used to rate (from 0 to 100) factors that may influence the decision-making process contributing to make an ideal scenario possible.

ID100 Risk profile

ID101 Added value

ID102 Self-Satisfaction

ID103 Technical Fit

ID104 Own competence

ID105 Knowledge

ID106 cost-Efficiency

ID107 Safety

ID108 Trust

ID109 Autarky

ID110 Legal

ID111 climate protection

ID112 Wellbeing

ID113 Coziness

ID114 Rights and Duties

ID115 Peer-Pressure

ID116 Socialising

ID117 Support

ID118 Agreement

ID119 Brag

ID120 Fun

ID121 Novelty

ID122 Trends

ID123 Authority

ID124 Own Significance

ID125 Poseur

ID2 Frugality

ID3 Environmental concerns

ID31 Adherence

ID52 Commitment

ID97 Profits

ID99 Credit Score

Section 3 - “Socio-economic” description. Questions about the socio-economic information of the survey respondents for data stratification. The indentation represents the dependency of questions and whether this data was asked

ID164 Understanding of questions

ID300 Country of residence

ID137 Age

ID178 Highest level of education

ID136 Willingness to provide data on the investment decision (respond apply for -Investment decision section)

Section 4 - Investment decision. Questions about specific prices of potential purchases-decisions related to four scenarios (respondent's lifestyle)

Appliances

ID42 Affordable cost of a Regular refrigerator

ID45 Energy efficient refrigerator costs

ID50 Willingness to purchase an energy efficient refrigerator

ID65 Why no

ID66 affordable cost of an energy efficient option

ID67 Years to amortize an efficient option

Insulation

ID47 Affordable cost of updating to a state of the art insulation on the facade

ID56 Willingness for paying/invest

ID74 Why no?

ID20 affordable cost of an energy efficient option

ID34 Years to amortize an energy efficient option

Energy Generation

ID68 Affordable cost of a solar photovoltaic system

ID76 Willingness for paying/invest

ID84 Why no?

ID132 Affordable cost of a photovoltaic system

ID138 Years that amortize a photovoltaic system

Energy Storage

ID142 Affordable cost of an energy storage system

ID146 Willingness for paying/invest

ID181 Why no?

ID182 Affordable cost of an energy storage system

ID183 Years that amortize an energy storage systems

Heating

ID140 Affordable cost of a gas boiler

ID209 Affordable cost of an energy efficient heating system

ID217 Willingness for paying/invest

ID238 Why no?

ID239 Affordable cost of a energy efficient option

ID241 Years that amortize a heat pumps

Mobility

ID41 Average kilometers traveled a typical day

ID51 Usual travel option

ID264 Affordable cost of a diesel or gasoline mid-range brand new car

ID265 Affordable cost of a mid-range brand new electric car

ID281 Willingness to buy an electric car

ID289 Why no?

ID290 Affordable price of an electric car

ID291 Years that amortize an electric car

Section 5 - Household characterization

ID127 Selecting an asked value

ID189 Type of living area

ID202 Gender identity

ID1 Those living in the house

ID32 Number of inhabitants

ID220 Average neat yearly income

ID229 Average monthly saving

ID240 Type of housing

ID249 Owner / co-owner

ID255 Usable area of the property (m²)

ID263 Insulation level

ID270 Climate zone

ID86 Level of self-awareness about climate change. On scale of 0-10, where 0 is “climate change does not exist” and 10 is “I am a climate change expert/activist”

ID87 Level of awareness of climate change among your peers or relatives, On a scale of 0-10, where 0 is “climate change does not exist” and 10 is “They are climate change experts/activists”

ID88 Level of self-awareness about energy transition. On a scale of 0-10, where 0 is “It is the first time I hear about it” and 10 is “I am an expert or activist”

ID89 Level of awareness of energy transition among your peers or relatives On a scale of 0-10, where 0 is “It is the first time they hear about it” and 10 is “They are experts or activists”

ID190 feedback about survey

5 star: ⭐⭐⭐

Preprocessing steps: anonymization, data fusion, imputation of gaps.

Reuse: NA

Update policy: No more updates are planned

Ethics and legal aspects: Spanish electric cooperative data contains the CUPS (Meter Point Administration Number), which is personal data. A pre-processing step has been carried out to substitute the CUPS by a random value hash.

Technical aspects:

Other:

Shark Tank India Data set.

Shark Tank India - Season 1 to season 4 information, with 80 fields/columns and 630+ records.

All seasons/episodes of 🦈 SHARKTANK INDIA 🇮🇳 were broadcasted on SonyLiv OTT/Sony TV.

Here is the data dictionary for (Indian) Shark Tank season's dataset.

• Season Number - Season number
• Startup Name - Company name or product name
• Episode Number - Episode number within the season
• Pitch Number - Overall pitch number
• Season Start - Season first aired date
• Season End - Season last aired date
• Original Air Date - Episode original/first aired date, on OTT/TV
• Episode Title - Episode title in SonyLiv
• Anchor - Name of the episode presenter/host
• Industry - Industry name or type
• Business Description - Business Description
• Company Website - Company Website URL
• Started in - Year in which startup was started/incorporated
• Number of Presenters - Number of presenters
• Male Presenters - Number of male presenters
• Female Presenters - Number of female presenters
• Transgender Presenters - Number of transgender/LGBTQ presenters
• Couple Presenters - Are presenters wife/husband ? 1-yes, 0-no
• Pitchers Average Age - All pitchers average age, <30 young, 30-50 middle, >50 old
• Pitchers City - Presenter's town/city or place where company head office exists
• Pitchers State - Indian state pitcher hails from or state where company head office exists
• Yearly Revenue - Yearly revenue, in lakhs INR, -1 means negative revenue, 0 means pre-revenue
• Monthly Sales - Total monthly sales, in lakhs
• Gross Margin - Gross margin/profit of company, in percentages
• Net Margin - Net margin/profit of company, in percentages
• EBITDA - Earnings Before Interest, Taxes, Depreciation, and Amortization
• Cash Burn - In loss in current year; burning/paying money from their pocket (yes/no)
• SKUs - Stock Keeping Units or number of varieties, at the time of pitch
• Has Patents - Pitcher has Patents/Intellectual property (filed/granted), at the time of pitch
• Bootstrapped - Startup is bootstrapped or not (yes/no)
• Part of Match off - Competition between two similar brands, pitched at same time
• Original Ask Amount - Original Ask Amount, in lakhs INR
• Original Offered Equity - Original Offered Equity, in percentages
• Valuation Requested - Valuation Requested, in lakhs INR
• Received Offer - Received offer or not, 1-received, 0-not received
• Accepted Offer - Accepted offer or not, 1-accepted, 0-rejected
• Total Deal Amount - Total Deal Amount, in lakhs INR
• Total Deal Equity - Total Deal Equity, in percentages
• Total Deal Debt - Total Deal debt/loan amount, in lakhs INR
• Debt Interest - Debt interest rate, in percentages
• Deal Valuation - Deal Valuation, in lakhs INR
• Number of sharks in deal - Number of sharks involved in deal
• Deal has conditions - Deal has conditions or not? (yes or no)
• Royalty Percentage - Royalty percentage, if it's royalty deal
• Royalty Recouped Amount - Royalty recouped amount, if it's royalty deal, in lakhs
• Advisory Shares Equity - Deal with Advisory shares or equity, in percentages
• Namita Investment Amount - Namita Investment Amount, in lakhs INR
• Namita Investment Equity - Namita Investment Equity, in percentages
• Namita Debt Amount - Namita Debt Amount, in lakhs INR
• Vineeta Investment Amount - Vineeta Investment Amount, in lakhs INR
• Vineeta Investment Equity - Vineeta Investment Equity, in percentages
• Vineeta Debt Amount - Vineeta Debt Amount, in lakhs INR
• Anupam Investment Amount - Anupam Investment Amount, in lakhs INR
• Anupam Investment Equity - Anupam Investment Equity, in percentages
• Anupam Debt Amount - Anupam Debt Amount, in lakhs INR
• Aman Investment Amount - Aman Investment Amount, in lakhs INR
• Aman Investment Equity - Aman Investment Equity, in percentages
• Aman Debt Amount - Aman Debt Amount, in lakhs INR
• Peyush Investment Amount - Peyush Investment Amount, in lakhs INR
• Peyush Investment Equity - Peyush Investment Equity, in percentages
• Peyush Debt Amount - Peyush Debt Amount, in lakhs INR
• Ritesh Investment Amount - Ritesh Investment Amount, in lakhs INR
• Ritesh Investment Equity - Ritesh Investment Equity, in percentages
• Ritesh Debt Amount - Ritesh Debt Amount, in lakhs INR
• Amit Investment Amount - Amit Investment Amount, in lakhs INR
• Amit Investment Equity - Amit Investment Equity, in percentages
• Amit Debt Amount - Amit Debt Amount, in lakhs INR
• Guest Investment Amount - Guest Investment Amount, in lakhs INR
• Guest Investment Equity - Guest Investment Equity, in percentages
• Guest Debt Amount - Guest Debt Amount, in lakhs INR
• Invested Guest Name - Name of the guest(s) who invested in deal
• All Guest Names - Name of all guests, who are present in episode
• Namita Present - Whether Namita present in episode or not
• Vineeta Present - Whether Vineeta present in episode or not
• Anupam ...

This dataset is about books. It has 2 rows and is filtered where the book is Investing in People : The Economics of Population Quality. It features 7 columns including author, publication date, language, and book publisher.

This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.

This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.

Abstract

Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.

By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

Geographic coverage

Sample excludes the Federal Dependencies because of remoteness and difficulty of access, as well as some additional areas because of security concerns.The excluded areas represent about 5% of the population.

Analysis unit

Individual

Universe

The target population is the civilian, non-institutionalized population 15 years and above.

Kind of data

Observation data/ratings [obs]

Sampling procedure

The indicators in the 2017 Global Findex database are drawn from survey data covering almost 150,000 people in 144 economies-representing more than 97 percent of the world's population (see Table A.1 of the Global Findex Database 2017 Report). The survey was carried out over the 2017 calendar year by Gallup, Inc., as part of its Gallup World Poll, which since 2005 has annually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 150 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. Interview procedure Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or where this is the customary methodology. In most economies the fieldwork is completed in two to four weeks.

In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used.

Respondents are randomly selected within the selected households. Each eligible household member is listed and the handheld survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

In economies where telephone interviewing is employed, random digit dialing or a nationally representative list of phone numbers is used. In most economies where cell phone penetration is high, a dual sampling frame is used. Random selection of respondents is achieved by using either the latest birthday or household enumeration method. At least three attempts are made to reach a person in each household, spread over different days and times of day.

The sample size was 1000.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup Inc. also provided valuable input. The questionnaire was piloted in multiple countries, using focus groups, cognitive interviews, and field testing. The questionnaire is available in more than 140 languages upon request.

Questions on cash on delivery, saving using an informal savings club or person outside the family, domestic remittances, and agricultural payments are only asked in developing economies and few other selected countries. The question on mobile money accounts was only asked in economies that were part of the Mobile Money for the Unbanked (MMU) database of the GSMA at the time the interviews were being held.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar, and Jake Hess. 2018. The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution. Washington, DC: World Bank

How to optimally allocate time, energy and investment in an effort to maximize one's reproductive success is a fundamental problem faced by all organisms. This effort is complicated when the production of each additional offspring dilutes the total resources available for parental investment. Although a quantity–quality trade-off between producing and investing in offspring has long been assumed in evolutionary biology, testing it directly in humans is difficult, partly owing to the long generation time of our species. Using data from an Icelandic genealogy (Íslendingabók) over two centuries, I address this issue and analyse the quantity–quality trade-off in humans. I demonstrate that the primary impact of parents on the fitness of their children is the result of resources and or investment, but not genes. This effect changes significantly across time, in response to environmental conditions. Overall, increasing reproduction has negative fitness consequences on offspring, such that each additional sibling reduces an individual's average lifespan and lifetime reproductive success. This analysis provides insights into the evolutionary conflict between producing and investing in children while also shedding light on some of the causes of the demographic transition.

Denmark Foreign Direct Investment Income: Inward: Total: Lao People'S Democratic Republic data was reported at 0.000 DKK mn in 2023. This stayed constant from the previous number of 0.000 DKK mn for 2022. Denmark Foreign Direct Investment Income: Inward: Total: Lao People'S Democratic Republic data is updated yearly, averaging 0.000 DKK mn from Dec 2020 (Median) to 2023, with 4 observations. The data reached an all-time high of 0.000 DKK mn in 2023 and a record low of 0.000 DKK mn in 2023. Denmark Foreign Direct Investment Income: Inward: Total: Lao People'S Democratic Republic data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Denmark – Table DK.OECD.FDI: Foreign Direct Investment Income: by Region and Country: OECD Member: Annual. Reverse investment:Reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) is treated as portfolio investment. Netting of reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt transactions and positions between fellow enterprises: directional basis according to the residency of the ultimate controlling parent (extended directional principle). FDI transactions and positions by partner country and/or by industry are available excluding and including resident Special Purpose Entities (SPEs). The dataset 'FDI statistics by parner country and by industry - Summary' contains series excluding resident SPEs only. Valuation method used for listed inward and outward equity positions: Market value, Own funds at book value. Valuation method used for unlisted inward and outward equity positions: Own funds at book value. Valuation method used for inward and outward debt positions: Market value, Nominal value.; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the immediate counterpart country. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Direct Influence/Indirect Control (DIIC) method. Debt between fellow enterprises are completely covered. Collective investment institutions are not covered as direct investment enterprises. Non-profit institutions serving households are covered as direct investors. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the resident direct investment enterprise. Outward FDI positions are allocated according to the activity of the resident direct investment enterprise. Statistical unit:Enterprise and Local Enterprise Group combined. Respondents have the opportunity to choose between reporting for one enterprise only or reporting for several enterprises within the same group