Showing posts with label investing. Show all posts
Showing posts with label investing. Show all posts

Sunday, November 1, 2026

Coinbase Q3 Net Income Jumps 66% As Prediction Markets Gain Traction

Coinbase Coinbase Global, Inc.COIN-10.62% reported a sharp jump in third-quarter net income to $719 million, as its expanding prediction markets and derivatives businesses helped offset weaker spot trading activity, analysts said. According to the exchange’s earnings report released Thursday, the company generated $1.22 billion in total revenue, broadly flat from the previous quarter but down 35% year over year.The company’s net income rose 66% year on year to $719 million from $433 million in the same period last year……..Continue reading…

By: Timmy Shen

Source:  The Block

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Critics:

The process of creating tokenized assets involves several steps—defining the token type (fungible or non-fungible), selecting the blockchain to issue the tokens on, selecting a third-party auditor to verify off-chain assets, issuing the assets, and more.Tokenization lets you digitally represent asset ownership for any tangible or intangible asset — stocks or bonds, cash or cryptocurrency, data sets or loyalty points — on a blockchain.

Once your asset is represented by a token, you can quickly and cost-effectively transfer or trade it, use it as collateral and more. Tokenization of real-world assets refers to the process of converting real-world or traditional assets—such as equities, bonds, real estate, or commodities—into digital tokens on a blockchain platform. WisdomTree is an early adopter of tokenizing traditional assets like mutual funds, bonds, and gold.

Tokenization replaces a sensitive data element, for example, a bank account number, with a non-sensitive substitute, known as a token. The token is a randomized data string that has no essential or exploitable value or meaning. In Python, tokenization in NLP can be accomplished using various libraries such as NLTK, SpaCy, or the tokenization module in the Transformers library.

These libraries offer functions to split text into tokens, such as words or subwords, based on different rules and language-specific considerations. Another risk associated with tokenization is the lack of regulatory framework. Since the technology is still relatively new, many governments have yet to establish clear regulations around tokenization, leaving investors and businesses open to legal risks.

Banks are drawn to blockchain technology for its ability to “tokenize” traditional assets like stocks and Treasury bills, making trading them faster and cheaper. Tokenization is the process of creating a digital representation of a real thing. Tokenization can be used to protect sensitive data or to efficiently process large amounts of data. A terracotta soldier figurine emerging from a digital tablet.

What are tokenised funds and how do they differ to traditional funds? A tokenised fund, which may also be known as a digital fund or a BTF (blockchain-traded fund) is one where shares or units in the fund, or a feeder fund for it, are digitally represented and can be traded and recorded on a distributed ledger. By 2030, tokenization in private markets could reach nearly USD4 trillion in value, an 80x growth rate, according to a Citi forecast.

Another report from asset manager Alliance Bernstein estimates that up to 2% of the global money supply could be tokenized over the next five years. Moving forward, our strategy includes securing digital payment licences in Taiwan, Dubai and Abu Dhabi,” he added. Founded in 2017, Tokenize has operations in key Asian markets including Singapore, Malaysia and Vietnam, serving both individual and institutional investors.

Asset tokenization presents a solution by digitizing assets and enabling fractional ownership, thereby increasing liquidity and accessibility. Through tokenization, assets become divisible into millions or billions of tokens, facilitating trading on accessible exchanges without intermediaries. Already industries including healthcare, real estate and legal services are using a form of tokenization to safeguard their data.

In the future network tokens may also be able to incorporate identification and payment data to create a seamless and more personalized experience for customers. Turning these assets into digital tokens makes them more easily divisible, allowing for fractional ownership that enables more people to invest, which can in turn make the markets for those assets more liquid.

Tokenizers may treat numbers inconsistently, breaking them down into separate tokens or keeping them as part of a token. Challenge: Inconsistent tokenization of numbers can impact the interpretation of numerical information, especially in tasks involving mathematical or quantitative analysis. Existing legal systems may not recognize tokenized asset ownership or digital ownership rights, potentially leading to problems with enforcing ownership or transferring rights.

As the technology matures and regulatory frameworks evolve, we can expect to see more tokenization migrating to public blockchains and a new wave of innovation. However, at least for the near future, the majority of institutional tokenization will take place on closed, permissioned networks. Blockchain-based tokenization streamlines the process of issuing, transferring and settling asset ownership, reducing administrative overhead and eliminating intermediaries.

This efficiency can lead to lower transaction costs and faster settlement times compared to traditional methods. The benefits of tokenization are a better experience and greater safety and security. Because fraud risk is lower with tokenized transactions, approval rates are higher, which means a lesser chance of your bank declining a transaction.

 The most common way of forming tokens is based on space. Assuming space as a delimiter, the tokenization of the sentence results in 3 tokens – Never-give-up. As each token is a word, it becomes an example of Word tokenization. Tokenization, the process of converting an asset or the ownership rights of an asset to a digital form using blockchain technology, has gained significant traction throughout the financial services industry.

Investors suggest they may allocate 7% to 9% of their entire portfolio to tokenized assets by 2027.

Saturday, October 31, 2026

Robo Advisers Are Here The Pros And Cons of Using AI In Investing

By: &

Source: TheConversation

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Critics:

Investors can use AI to efficiently sort through U.S.stock market datato identify investments matching their criteria. Stock screeners allow investors to filter stocks on fundamental and technical data points. These criteria could include market capitalization, trading volume, accounting ratios or moving averages. Some of the top benefits of AI for investing include:

  • Personalization of strategies.
  • Cost reduction.
  • Automation of routine tasks.
  • Real-time monitoring.
  • Risk management.
  • Predictive analytics.
  • Enhanced data analysis.
  • Improved decision-making.

Many top AI stocks have been outperforming the S&P 500 and continue to draw investors. Artificial intelligence tailwinds remain strong as AI-fueled corporations continue to post strong earnings. But investors should diversify their portfolios so they aren’t overexposed to a single stock or industry. With Machine Learning, Natural Language Processing, and other advanced algorithms, AI can help investors optimise their investment strategy, recommend efficient portfolio allocation, manage risk, and much more by offering personalised insights.

Using AI to trade stocks is legal. However, financial institutions must remain compliant with any regulations when relying on AI-based trading, and individuals may want to keep in mind the potential risks of AI trading tools. If you want to start investing in AI, there are two main paths: selecting individual stocks or opting for AI ETFs (exchange-traded funds). Whether you’re starting fresh or looking to deepen your investment, exploring these avenues can align you with the future of technology.

Elon Musk founded xAI in 2023 to develop large language models and artificial intelligence products as an alternative to AI tools created by OpenAI, Microsoft and Google. Facebook-parent Meta is among the top AI stocks to watch. Meta stock has gained 62% in 2024. Meanwhile, Nvidia and Arista Networks (ANET) are squaring off in the AI Ethernet networking market. Also, Arista stock has gained 67% in 2024.

29.5% of Warren Buffett’s $305.7 Billion Portfolio Is Invested in 2 Artificial Intelligence (AI) Stocks. Warren Buffett has steered the Berkshire Hathaway investment company to market-beating returns since 1965. By processing vast quantities of data, including market data, financial reports and news, AI can uncover insights that assist investor decision making. Through pattern recognition and trend analysis, AI helps investors to find new opportunities and make better investment decisions.

Existing research has shown that AI systems can make more accurate predictions of earnings changes and generate more profitable trading strategies compared to human analysts. Powerful AI algorithms transform how corporate and investment banks navigate complexities, enabling forward-looking organizations to enhance their competitive edge in a rapidly evolving industry. Here are some of the most high-impact use cases of AI in investment banking.

Even in long-term trading, where strategy plays a bigger role, AI’s current capabilities are limited. Human traders still have the upper hand when it comes to deeper understanding of market trends and ability to make informed predictions. For beginners, Stock Rover, Trade Ideas, and Alpaca are great choices. These tools are easy to use and offer features like stock analysis, commission-free trading, and AI-generated trade suggestions, making them perfect for new traders looking to get started.

Artificial Intelligence (AI) cannot reliably predict which stock will go up today. While AI has made significant advancements in various fields, it currently lacks the ability to consistently and accurately predict individual stock prices. Individual AI stocks can potentially offer high returns, but require taking on a lot of risk, upfront expense and research work. Another option is to invest in AI stocks via pooled exchange-traded funds that focus on AI.

NVDA is the best-performing AI stock over the past year. Earnings per share, or EPS, had a big leap higher in 2023, and analysts project strong EPS growth going forward. It has the highest forecasted 5-year EPS growth on the list. You can make money with AI trading but it requires significant research, data, and coding skills. Strategies involve using AI to scan news, process earnings reports, identify trends/patterns, and make quantitative models for entries, exits and position sizing. Thorough backtesting is critical before going live.

One way to make money with AI bots is by developing and selling trading bots or investment advisory bots. These bots can be programmed to monitor market trends, technical indicators, news events, and other relevant data to generate buy/sell signals or investment recommendations.Investing in professionally managed ETFs or mutual funds that hold shares in AI companies allows you to leave it to a fund’s professional managers to research and pick suitable AI companies. Through an ETF, you own a share of a portfolio of multiple AI stocks within a single investment.

Why it’s time for law firms to start investing in generative AIRaconteur 19:47 Mon, 29 Apr
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History Says The Nasdaq Will Soar: 2 Brilliant IPO Stocks To Buy Before 2026, According To Wall Street

Image source: Getty Images.

The Nasdaq Composite (^IXIC-2.86%) crashed earlier this year when white House shocked Wall Street with sweeping tariffs. But the index promptly bounced back into a new bull market and has since advanced 50%. However, history says the Nasdaq is headed much higher in the coming years. It has returned an average of 281% during bull markets since 1990. Most Wall Street analysts see CoreWeave (CRWV-9.66%) and ServiceTitan (TTAN+4.37%) as undervalued. Both companies completed initial public offerings (IPOs) in the past year………Continue reading….

By: Trevor Jennewine

Source: The Motley Fool

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Critics:

The stock market is one of the most important ways for companies to raise money, along with debt markets which are generally more imposing but do not trade publicly. This allows businesses to be publicly traded, and raise additional financial capital for expansion by selling shares of ownership of the company in a public market.

The liquidity that an exchange affords the investors enables their holders to quickly and easily sell securities. This is an attractive feature of investing in stocks, compared to other less liquid investments such as property and other immoveable assets. History has shown that the price of stocks and other assets is an important part of the dynamics of economic activity, and can influence or be an indicator of social mood.

Therefore, central banks tend to keep an eye on the control and behavior of the stock market and, in general, on the smooth operation of financial system functions. Financial stability is the raison d’être of central banks. Exchanges also act as the clearinghouse for each transaction, meaning that they collect and deliver the shares, and guarantee payment to the seller of a security.

This eliminates the risk to an individual buyer or seller that the counterparty could default on the transaction. The smooth functioning of all these activities facilitates economic growth in that lower costs and enterprise risks promote the production of goods and services as well as possibly employment. In this way the financial system is assumed to contribute to increased prosperity, although some controversy exists as to whether the optimal financial system is bank-based or market-based.

Recent events such as the Global Financial Crisis have prompted a heightened degree of scrutiny of the impact of the structure of stock markets (called market microstructure), in particular to the stability of the financial system and the transmission of systemic risk. A transformation is the move to electronic trading to replace human trading of listed securities.

Changes in stock prices are mostly caused by external factors such as socioeconomic conditions, inflation, exchange rates. Intellectual capital does not affect a company stock’s current earnings. Intellectual capital contributes to a stock’s return growth. The efficient-market hypothesis (EMH) is a hypothesis in financial economics that states that asset prices reflect all available information at the current time.

The ‘hard’ efficient-market hypothesis does not explain the cause of events such as the crash in 1987, when the Dow Jones Industrial Average plummeted 22.6 percent—the largest-ever one-day fall in the United States. This event demonstrated that share prices can fall dramatically even though no generally agreed upon definite cause has been found: a thorough search failed to detect any ‘reasonable’ development that might have accounted for the crash.

It seems also to be true more generally that many price movements (beyond those which are predicted to occur ‘randomly’) are not occasioned by new information; a study of the fifty largest one-day share price movements in the United States in the post-war period seems to confirm this. A ‘soft’ EMH has emerged which does not require that prices remain at or near equilibrium, but only that market participants cannot systematically profit from any momentary ‘market anomaly‘.

Psychological research has demonstrated that people are predisposed to ‘seeing’ patterns, and often will perceive a pattern in what is, in fact, just noise, e.g. seeing familiar shapes in clouds or ink blots. In the present context, this means that a succession of good news items about a company may lead investors to overreact positively, driving the price up. A period of good returns also boosts the investors’ self-confidence, reducing their (psychological) risk threshold.

Another phenomenon—also from psychology—that works against an objective assessment is group thinking. As social animals, it is not easy to stick to an opinion that differs markedly from that of a majority of the group. An example with which one may be familiar is the reluctance to enter a restaurant that is empty; people generally prefer to have their opinion validated by those of others in the group.

In one paper the authors draw an analogy with gambling. In normal times the market behaves like a game of roulette; the probabilities are known and largely independent of the investment decisions of the different players. In times of market stress, however, the game becomes more like poker (herding behavior takes over). The players now must give heavy weight to the psychology of other investors and how they are likely to react psychologically.

Stock markets play an essential role in growing industries that ultimately affect the economy through transferring available funds from units that have excess funds (savings) to those who are suffering from funds deficit (borrowings) (Padhi and Naik, 2012). In other words, capital markets facilitate funds movement between the above-mentioned units. This process leads to the enhancement of available financial resources which in turn affects the economic growth positively.

Economic and financial theories argue that stock prices are affected by macroeconomic trends. Macroeconomic trends include such as changes in GDP, unemployment rates, national income, price indices, output, consumption, unemployment, inflation, saving, investment, energy, international trade, immigration, productivity, aging populations, innovations, international finance.

Increasing corporate profit, increasing profit margins, higher concentration of business, lower company income, less vigorous activity, less progress, lower investment rates, lower productivity growth, less employee share of corporate revenues, decreasing Worker to Beneficiary ratio (year 1960 5:1, year 2009 3:1, year 2030 2.2:1), increasing female to male ratio college graduates.

Therefore, the stock market may be swayed in either direction by press releases, rumors, euphoria and mass panic. Over the short-term, stocks and other securities can be battered or bought by any number of fast market-changing events, making the stock market behavior difficult to predict. Emotions can drive prices up and down, people are generally not as rational as they think, and the reasons for buying and selling are generally accepted.

Behaviorists argue that investors often behave irrationally when making investment decisions thereby incorrectly pricing securities, which causes market inefficiencies, which, in turn, are opportunities to make money.However, the whole notion of EMH is that these non-rational reactions to information cancel out, leaving the prices of stocks rationally determined.

London close: Stocks mixed after ECB rate cut ShareCast 21:41

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