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Yousef Haddad

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Yousef Haddad writes for ICN.live about global markets, cross-border payments, and digital custody and has authored market coverage for Arab News Tech, and other regional publications. Known for clarity and precision, he trained in Broadcast Journalism and Media Communication at a leading Arab University. His passion for biking is very well known inside of the company. He has a huge collection of bikes.
8 Money Principles now

The psychology of money decides more about a person’s finances than their salary ever will. Two people can earn the same and land in different places because the beliefs steering their choices differ. Financial psychologists have studied these patterns for decades. Some form in childhood. Others come from fear wired into the brain across thousands of years. The eight principles below pull from that research and from hard practice. Each names a habit that keeps people broke and the shift that turns it around. The last principle points to three books that go deeper than any short summary can. Read to the end for those.

Money scripts run before a person notices them

Every financial choice runs through a script most people never wrote. Researchers sort these subconscious beliefs into four money scripts. The first, money avoidance, treats wealth as something dirty, so a person undercharges and feels guilt about earning. Worship flips that, treating cash as the cure for every problem, so the chase never ends. Status ties self-worth to net worth, which pushes overspending to keep up appearances. Last comes vigilance, steady saving next to steady worry, even with plenty in the bank. Most people carry a blend, with one script leading. Each forms in childhood, often before a kid can define money at all. A child who hears that rich people are greedy stores that line and acts on it decades later. In the psychology of money, spotting the dominant script is step one, because a belief nobody can see keeps steering the wheel without any resistance.

Self-image sets a wealth ceiling

Limiting beliefs about money set a ceiling on income that ability alone cannot break. A person who sees themselves as a $100,000 earner tends to defend that number without meaning to. Earn more, and lifestyle rises to swallow the extra. Fall short, and effort climbs until the familiar level returns. A $200,000 opening slips past anyone still picturing a $50,000 version of themselves. The cap sits in the self-image, not the market.

The psychology of money treats this ceiling as a belief, not a fact. Changing it starts with one honest sentence. Write down the current financial identity, whether that is overspender, chronic saver, or someone scraping by. Beside it, write a truer target, such as a person who builds and manages wealth with ease. Read both before each money decision. As the self-image widens, income tends to move with it. The shift is slow, and it holds.

Assets pay their owner; liabilities charge them

Robert Kiyosaki reduced wealth to one test in Rich Dad Poor Dad. An asset puts money in a pocket. A liability pulls money out. The wealthy stack assets. Middle-class buyers collect liabilities and file them under assets by mistake. A car loses value the moment it leaves the lot, then bills its owner for fuel, insurance, and repairs. Living in a home brings a mortgage, taxes, and upkeep with nothing coming back. A rental property pays every month. Skill courses pay back through higher earnings later. Judging assets vs liabilities before each purchase is where a working money mindset begins. Idle cash carries a quiet cost too. Money parked in a low-rate account loses ground to rising prices year after year. Even savings, left to sit, can slide toward the liability column. The question that reorders spending is short: will this pay back, or drain over time?

A scarcity mindset makes decisions worse

A scarcity mindset does more than sour the mood. When money feels finite, mental bandwidth shrinks and judgment drops. The brain fixes on the next bill and loses the long view. That wiring made sense long ago, when food supplies could run out. Money works differently. It is created every day, and the supply is not fixed. An abundance mindset asks a sharper question. Instead of how to protect what exists, it asks how to create more. That single reframe moves a person from defense to offense. Fear says wait. Possibility says invest. The switch does not come naturally, since humans lean toward caution by default. Training helps. Each time the mind reaches for I cannot afford this, the stronger move is to ask how the thing could be afforded at all. Small reframes, repeated, widen what feels possible.

Every loss can work as tuition

Loss aversion keeps more people poor than bad luck does. Daniel Kahneman and Amos Tversky measured it in 1979, and the finding still holds. Losing $100 hurts about twice as much as gaining $100 feels good. Kahneman later won the 2002 Nobel Prize in economics for the wider work. That imbalance explains a lot of stuck lives. People grip losing stocks and pray for a rebound instead of cutting the loss. Some sit in dead-end jobs because quitting feels like defeat. Others skip raises and dodge investing, since the fear of losing beats the pull of gaining. The cost can be steep.

A person might stay in a draining job two years too long, losing income, energy, and health, all to avoid the feeling of a loss. One fix reframes the setback. A failed venture becomes tuition for a lesson that pays later. Once the loss reads as a receipt for learning, it stops running the show.

Time matters more than money saved

Money multiplies. Time does not. That gap is why saving every dollar can quietly cost a fortune. Consider a worker worth $100 an hour. Two hours spent cleaning to avoid a $50 fee does not save $50. It burns $150, once the lost earning time is counted. Wealthy people run the math the other way. They hire help, buy back hours, and steer that time toward work worth far more. The habit does not require millions to start. Hiring a first assistant early frees a founder to chase revenue instead of chores. The rule scales down as much as up. Someone earning $60,000 a year works out to about $30 an hour, so low-value chores are worth handing off. Anyone can find the number. Divide annual income by roughly 2,000 working hours, and the rate appears. From there, the test is simple. Any task worth less than that rate belongs to someone else.

A new money mindset gets written down first

A money mindset does not change by wishing. It changes on paper, through a small daily act. The method is plain. Write the earliest money memory, then note what parents said and did with cash. That memory usually holds the original script. Once it sits in plain view, a new line can replace it, such as money is a tool for freedom and for helping more people. The same trick works for identity and for spending. List the last ten purchases, then mark each one as an asset or liability with full honesty. Patterns show up fast. Reading these notes before decisions retrains the reflex over weeks, not minutes. The point is not a burst of motivation. Repetition rewires the default, so the calm choice starts to feel normal. Behavior follows the script it is fed, so a better script pays off in time.

The three books worth reading on the psychology of money

Short summaries can point the way, but three books map the whole field. The Psychology of Money by Morgan Housel, published in 2020, sits at the top. It runs on 19 short stories and one core claim: that behavior beats intelligence when it comes to wealth. The book has sold more than 10 million copies worldwide. Thinking, Fast and Slow by Daniel Kahneman comes next. Kahneman, the Nobel laureate behind loss aversion, lays out the two mental systems that drive every money call, one fast and emotional, the other slow and deliberate.

The third pick is Your Money and Your Brain by Jason Zweig, from 2007. Zweig ties neuroscience to investing and shows why the brain chases risk and panics at the wrong moments. None of the three sells a slogan. Each leans on evidence, from Nobel-winning research to market history. Together, they cover the beliefs, the biases, and the brain chemistry behind spending and saving. The psychology of money makes far more sense after reading all three. One honest read can shift the next decision more than any raise.

China moves against Hormuz's oil price shocks

China moves against Hormuz’s oil price shocks by leaning on a growing electric taxi fleet. Across big cities, you now see more riders picking cabs over their own petrol cars. People took 3.05 billion trips in May, a 6% rise since the Iran war. Fares keep falling even while pump prices climb steadily across the whole country right now. A wave of new drivers and cheap electric cars pushes those low prices even lower. Many workers chase ride-hailing jobs in a slow economy, so competition among drivers grows. Cheaper fares then pull in more riders who want to skip their rising petrol bills.

Li, a 36-year-old Beijing driver, says fares fell 10% to 15% in six months. He told Reuters at a charging station how tough the competition now feels for drivers. Yang, a 45-year-old car owner, now prefers a taxi when petrol prices run high. She skips parking hunts and fuel costs on trips too far to reach by bike. Social media posts since March show riders swapping their own cars for cheaper cab trips. This small daily choice, repeated millions of times, reshapes national fuel demand quite fast.

China moves against Hormuz’s oil price shocks with a cleaner fleet

About half of China’s 1.3 million taxi fleet already runs on electric power today. In major cities, China’s electric taxis reach nearly the entire working fleet on the road. Didi added 2 million more electric or hybrid cars to its fleet last year. Its non-fossil fleet now totals 8 million cars, with EVs doing 75% of mileage. You can see the clear payoff in the national fuel numbers from May this year. China burned 10% less gasoline and 14% less diesel than the same month last year. Road freight still rose 2%, and holiday travel hit an all-time high in May.

As fuel prices have gone up, people are driving their own petrol cars less, said Daizong Liu. He leads East Asia work at the Institute for Transportation and Development Policy in China. Overall travel demand keeps rising, so more trips shift to taxis and the subway. Subway ridership also climbs as many commuters trim spending on their own petrol cars. Each cheap electric trip shows how China moves against Hormuz’s oil price shocks in practice.

Strait of Hormuz oil pressure meets a shifting travel habit

This shift helps explain how China’s oil imports fell 41% in June from last year. Beijing managed this steep drop without heavily draining its own large strategic oil reserves. Freed cargoes then eased a tight global market and kept oil prices in check. An oil price shock hits importers hardest when they cannot swap fuel for power. Analysts read the EV ride-hailing China trend as a real national energy defense right now. Greenpeace expects 90% of taxi and rideshare mileage to run on electricity by 2035.

From my standpoint, this dual trend reshapes how markets should price China’s oil demand. J.P. Morgan says the conflict left China less dependent on oil than markets assumed. You should watch this pattern as fuel prices settle back toward pre-war levels again. China moves against Hormuz’s oil price shocks in a way few big importers can match.

Muse Spark artificial intelligence model

Muse Spark artificial intelligence model now carries a price tag, and developers must pay for access. Meta released the upgraded version on Thursday, opening a public preview to United States developers. The company charges $1.25 per million input tokens and $4.25 per million output tokens. Every new account receives twenty dollars in free credits before pay-as-you-go billing starts. You can read this move as Meta finally selling access instead of giving models away.

Alexandr Wang leads the effort, and he calls the pricing aggressive next to rival lab offerings. His team built the model to handle coding work and long chains of agent tasks. Meta Superintelligence Labs trained it on real-world software problems across large enterprise code bases. Wang told CNBC the update marks the best coding and agent performance Meta has shipped. Rivals now face a cheaper option built by a company with enormous computing capacity.

The Meta Model API sits at the center of this shift toward paid developer access. Developers sign up through a portal, test prompts, compare outputs, and prototype their own integrations. Meta limits access to its own properties for now, skipping third-party marketplaces like OpenRouter. Some early partners already hold API keys, and new users enter a waitlist for entry. Replit, Cline, and Box rank among the first companies building on the new system.

Muse Spark artificial intelligence model sets a new price floor

Muse Spark 1.1 pricing lands below Anthropic’s Claude Sonnet 4.6 on both input and output. The rate still runs above cheaper tiers such as GPT 5 mini and Claude Haiku 4.5. Zuckerberg framed the cost as one of the lowest available to developers right now. In my assessment, price alone will not decide which lab wins the coding market. Quality, reliability, and developer trust matter as much as the number on the invoice.

Meta claims strong benchmark results, including wins over Google’s Gemini 3.1 Pro in some areas. The AI coding model handles bug diagnosis, feature builds, and large-scale code migrations. It supports a context window of one million tokens for long-running technical sessions. Engineers can run it as a lead agent or as a subagent inside larger systems. Mark Zuckerberg said, “Muse Spark 1.1 is strongest at agentic performance, tool use, and computer use.”

Wall Street keeps pressing Mark Zuckerberg for returns on enormous artificial intelligence spending commitments. The company spends like its hyperscaler peers, yet it owns no cloud infrastructure business. Meta plans to launch one, and paid model access opens a second revenue line. Earlier Llama releases went to the open source community without any charge to users. Wang says an open source variant remains in development, though he gave no release date.

What Muse Spark artificial intelligence model means for your stack

Muse Spark artificial intelligence model gives you another vendor inside a crowded developer market. Meta trained the release to work with popular agent harnesses developers already run daily. Wang points to health research as one use case, from web searches to academic papers. Your team should test output quality against cost before moving any production workload over. Meta faces a hard climb, and the Muse Spark artificial intelligence model carries heavy expectations. Developers now decide whether the Muse Spark artificial intelligence model earns a permanent slot.