9 Money Mistakes To Avoid To Protect Your Finances and Save Over Time

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Generosity is good—but what if it starts to sabotage your savings? You might be spending out of habit or social pressure without realizing how much it’s costing you. “One of the first things I tell people who consider working with me is that I’m not the fun police,” says Erik Scudder, a certified financial planner and founder of Trailhead Financial in Fairfax, Virginia. He has prospective clients fill out an expense worksheet. The task isn’t about telling them what not to do, he says, but to see how they’re spending money………Continue reading…

By: Sara Clarke

Source: Investopedia

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Critics:

Financial literacy in personal financial planning can be defined as objectively measured Financial Literacy and Subjectively measured financial literacy. Objectively measured literacy is mainly about the numerical understanding of facts like compound growth rate, portfolio investment, diversification benefits, and the impact of inflations on financial decisions.

Objective financial literacy has been measured with five 5-item tests, which we call the big five, that include questions related to interest rates, saving accounts, and inflation. Out of 5 questions, people who tend to answer three questions correctly counted as low financial literacy.

Subjective financial literacy is more of the self-perception of individuals about their financial literacy. Luradi and Mitchell (2014) identified that people rate their subjective financial literacy higher than objective financial literacy because of their behavioral biases when judging their financial knowledge subjectively. People often misestimate their financial knowledge.

Some financial literacy researchers have raised questions about the political character of financial literacy education, arguing that it justifies the shifting of greater financial risk (e.g. tuition fees, pensions, health care costs, etc.) to individuals from corporations and governments. Many of these researchers argue for a financial literacy education that is more critically oriented and broader in focus:

An education that helps individuals better understand systemic injustice and social exclusion, rather than one that understands financial failure as an individual problem and the character of financial risk as apolitical. Many researchers work within social justice, critical pedagogy, feminist and critical race theory paradigms.

The Journal of Financial Literacy and Wellbeing, published by Cambridge University Press, is a open-access academic journal established in April 2023. It publishes rigorous research on financial literacy and financial well-being. It aims to inform public policies as public, private and civil society strategies and activities, with the ultimate objective of improving the financial literacy, resilience, and well-being of individuals and micro and small entrepreneurs. 

This journal covers the topics including financial knowledge, financial attitudes and skills. This journal also includes research on related fields like financial well being. Accounting literacy refers to the ability to read and analyse financial statements of the company or individuals and understand the impact of financial decisions, This can be helpful for the investors, managers and individuals.

Accounting literacy can be combined with financial planning, tax planning and understanding the financial health of the company. Academic researchers have explored the relationship between financial literacy and accounting literacy. Roman L. Weil defines financial literacy as “the ability to understand the important accounting judgments management makes, why management makes them, and how management can use those judgments to manipulate financial statements”.

The 1999 Blue Ribbon Committee on Improving the Effectiveness of Corporate Audit Committees recommended that publicly traded companies have at least three members with “a certain basic ‘financial literacy’. Such ‘literacy’ signifies the ability to read and understand fundamental financial statements, including a company’s balance sheet, income statement and cash flow statement.”

Digital financial literacy is all about the combination of Fintech and financial literacy. Digital Financial Literacy (DFL) combines objective financial literacy with the skills and ability of individuals to use digital devices to make financial decisions. There is a need for digital financial literacy across all consumers because of increasing fraud victimization due to digitalization, which prone individuals to misinformed financial decisions.

An international OECD study was published in late 2005 analysing financial literacy surveys in OECD countries. A selection of findings included:

• In Australia, 67 percent of respondents indicated that they understood the concept of compound interest, yet when asked to solve a problem using the concept, only 28% had a good understanding.
• A British survey found that consumers do not actively seek out financial information. The information they receive is acquired by chance, for example, by picking up a pamphlet at a bank or having a chance talk with a bank employee.
• A Canadian survey found that respondents considered choosing the right investments more stressful than going to the dentist.
• A survey of Korean high-school students showed that they had failing scores—that is, they answered fewer than 60 percent of the questions correctly—on tests designed to measure their ability to choose and manage a credit card, their knowledge about saving and investing for retirement, and their awareness of risk and the importance of insuring against it.
• A survey in the US found that four out of ten American workers need to be saving for retirement.

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

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Artificial intelligence (AI) is shaking up the way we invest our money. Gone are the days when complex tools were reserved for the wealthy or financial institutions. AI-powered robo-advisers, such as Betterment and Vanguard in the US, and finance app Revolut in Europe, are now democratising investment. These tools are making professional financial insight and portfolio management available to everyone. But although there are plenty of advantages to using robo-advisers, there are downsides too.……..Story continues…

By: Laurence Jones & Heather He

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.

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Venus Is Losing Water Faster Than Previously Thought

How Cognitive Biases Can Negatively Affect Your Investment Decisions

The most significant foundational theories of modern finance, Modern Portfolio Theory and the Efficient Market Hypothesis, have an important assumption in common. In fact, academic research in finance and economics, as well as in many other social sciences, is based on the rational actor theory, which posits that people evaluate all information and options available to choose the one that maximizes benefits and minimizes costs. It wouldn’t make sense to do otherwise, would it? But real life rarely mirrors theory, and in real life investors aren’t rational……..…Continue reading….

By: Motley Fool Asset Management

Source: Motley Fool

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Critics: 

Many social institutions rely on individuals to make rational judgments. Across management, finance, medicine, and law, the most recurrent bias is overconfidence, though anchoring and framing also play substantial roles. While research in finance often uses large-scale data, studies in medicine and law frequently rely on vignette-based designs. Berthet highlights the lack of ecological validity in many studies and the need for deeper exploration of individual differences in susceptibility to bias.

The securities regulation regime largely assumes that all investors act as perfectly rational persons. In truth, actual investors face cognitive limitations from biases, heuristics, and framing effects. In some academic disciplines, the study of bias is very popular. For instance, bias is a wide spread and well studied phenomenon because most decisions that concern the minds and hearts of entrepreneurs are computationally intractable.

In law enforcement and legal decision-making, confirmation bias and related errors frequently influence investigative decisions and evidence evaluation. Structured intervention strategies, such as accountability measures and checklists, show some promise in reducing bias during case evaluations. A fair jury trial, for example, requires that the jury ignore irrelevant features of the case, weigh the relevant features appropriately, consider different possibilities open-mindedly and resist fallacies such as appeal to emotion.

The various biases demonstrated in these psychological experiments suggest that people will frequently fail to do all these things. However, they fail to do so in systematic, directional ways that are predictable. Cognitive biases can create other issues that arise in everyday life. Study participants who ate more unhealthy snack food tended to have less inhibitory control and more reliance on approach bias.

Cognitive biases could be linked to various eating disorders and how people view their bodies and their body image. Cognitive biases can be used in destructive ways. Some believe that there are people in authority who use cognitive biases and heuristics in order to manipulate others so that they can reach their end goals. Some medications and other health care treatments rely on cognitive biases in order to persuade others who are susceptible to cognitive biases to use their products.

Many see this as taking advantage of one’s natural struggle of judgement and decision-making. They also believe that it is the government’s responsibility to regulate these misleading ads. Cognitive biases also seem to play a role in property sale price and value. Participants in the experiment were shown a residential property. Afterwards, they were shown another property that was completely unrelated to the first property. They were asked to say what they believed the value and the sale price of the second property would be.

They found that showing the participants an unrelated property did have an effect on how they valued the second property. Cognitive biases can be used in non-destructive ways. In team science and collective problem-solving, the superiority bias can be beneficial. It leads to a diversity of solutions within a group, especially in complex problems, by preventing premature consensus on suboptimal solutions.

This example demonstrates how a cognitive bias, typically seen as a hindrance, can enhance collective decision-making by encouraging a wider exploration of possibilities. Cognitive biases are interlinked with collective illusions, a phenomenon where a group of people mistakenly believe that their views and preferences are shared by the majority, when in reality, they are not. These illusions often arise from various cognitive biases that misrepresent our perception of social norms and influence how we assess the beliefs of others.

Cognitive biases also influence the spread of misinformation, particularly in digital environments. Lazer, Baum, and Grinberg (2018) analyzed over 16,000 false news stories shared by millions of Twitter users during the 2016 U.S. election and found that false information spread significantly faster than accurate news. This occurs partly because misinformation aligns with existing beliefs and triggers emotional reactions, both of which are linked to confirmation and availability biases.

These findings illustrate how cognitive biases can distort public understanding and contribute to the rapid dissemination of false narratives. The content and direction of cognitive biases are not “arbitrary”. Debiasing is the reduction of biases in judgment and decision-making through incentives, nudges, and training. Cognitive bias mitigation and cognitive bias modification are forms of debiasing specifically applicable to cognitive biases and their effects.

One debiasing technique aims to decrease biases by encouraging individuals to use controlled processing compared to automatic processing. Because they cause systematic errors, cognitive biases cannot be compensated for using a wisdom of the crowd technique of averaging answers from several people. Reference class forecasting is a method for systematically debiasing estimates and decisions, based on what Daniel Kahneman has dubbed the outside view.

Cognitive bias modification (CBM) refers to the process of modifying cognitive biases in healthy people and also refers to a growing area of psychological (non-pharmaceutical) therapies for anxiety, depression and addiction called cognitive bias modification therapy (CBMT). CBMT is sub-group of therapies within a growing area of psychological therapies based on modifying cognitive processes with or without accompanying medication and talk therapy, sometimes referred to as applied cognitive processing therapies (ACPT).

Although cognitive bias modification can refer to modifying cognitive processes in healthy individuals, CBMT is a growing area of evidence-based psychological therapy, in which cognitive processes are modified to relieve suffering from serious depression, anxiety, and addiction. CBMT techniques are technology-assisted therapies that are delivered via a computer with or without clinician support.

CBM combines evidence and theory from the cognitive model of anxiety, cognitive neuroscience, and attentional models. Even one-shot training interventions, such as educational videos and debiasing games that taught mitigating strategies, significantly reduced the commission of several cognitive biases. Cognitive bias modification has also been used to help those with obsessive-compulsive beliefs and obsessive-compulsive disorder. This therapy has shown that it decreases the obsessive-compulsive beliefs and behaviors.

In relation to reducing the fundamental attribution error, monetary incentives and informing participants they will be held accountable for their attributions have been linked to the increase of accurate attributions. Individual differences in cognitive bias have also been linked to varying levels of cognitive abilities and functions. The Cognitive Reflection Test (CRT) has been used to help understand the connection between cognitive biases and cognitive ability.

There have been inconclusive results when using the Cognitive Reflection Test to understand ability. However, there does seem to be a correlation; those who gain a higher score on the Cognitive Reflection Test, have higher cognitive ability and rational-thinking skills. This in turn helps predict the performance on cognitive bias and heuristic tests. Those with higher CRT scores tend to be able to answer more correctly on different heuristic and cognitive bias tests and tasks.

Age is another individual difference that has an effect on one’s ability to be susceptible to cognitive bias. Older individuals tend to be more susceptible to cognitive biases and have less cognitive flexibility. However, older individuals were able to decrease their susceptibility to cognitive biases throughout ongoing trials. These experiments had both young and older adults complete a framing task. Younger adults had more cognitive flexibility than older adults. Cognitive flexibility is linked to helping overcome pre-existing biases.

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