What Is The House Money Effect? The House Money Effect In A Nutshell

The house money effect was first described by researchers Richard Thaler and Eric Johnson in a 1990 study entitled Gambling with the House Money and Trying to Break Even: The Effects of Prior Outcomes on Risky Choice. The house money effect is a cognitive bias where investors take higher risks on reinvested capital than they would on an initial investment.

Definition of House Money EffectThe House Money Effect is a psychological phenomenon observed in decision-making and risk-taking behaviors. It refers to the tendency of individuals to take greater risks with money or assets that they perceive as “house money” or winnings from prior activities, as opposed to their own hard-earned money. The term originates from the world of gambling, where players are more likely to place riskier bets with their winnings (house money) rather than their initial stake. In broader contexts, the House Money Effect can influence financial investments, business decisions, and everyday choices. It suggests that people tend to be less risk-averse when they perceive the funds as “extra” or not part of their baseline assets. Recognizing this effect is important in understanding how individuals and organizations approach risk and financial decisions.
Key ConceptsSeveral key concepts define the House Money Effect:
Perceived OwnershipThe House Money Effect is driven by the perception of ownership over the money or assets in question. When individuals perceive the funds as “extra” or not part of their original investment, they are more willing to take risks with those funds. Perceived ownership influences risk-taking behavior.
Risk ToleranceRisk tolerance refers to an individual’s willingness and comfort level with taking risks. The House Money Effect can lead to an increased risk tolerance when dealing with perceived winnings or “house money.” People may take risks they wouldn’t with their own savings or initial capital. Risk tolerance is influenced by the House Money Effect.
Behavioral EconomicsThe House Money Effect is a concept rooted in behavioral economics, a field that studies how psychological factors and biases influence economic decisions. It illustrates how non-rational factors can impact financial choices. Behavioral economics highlights the role of psychology in economic decision-making.
Contextual InfluenceContext plays a significant role in the House Money Effect. The decision to perceive funds as “house money” is influenced by the context in which the funds were acquired. This can include gambling winnings, investment gains, or unexpected windfalls. Contextual influence shapes the House Money Effect.
CharacteristicsThe House Money Effect exhibits the following characteristics:
Context DependencyThe House Money Effect is context-dependent, meaning it varies based on the specific circumstances and how individuals perceive their financial situation. It is more likely to be observed when individuals view the funds as “extra” or separate from their core financial resources. Context dependency is a defining characteristic of the House Money Effect.
Risk PerceptionThe effect directly impacts risk perception. When individuals perceive funds as house money, they tend to underestimate the potential risks associated with decisions involving those funds. This can lead to riskier choices. Risk perception is influenced by the House Money Effect.
Impact on Decision-MakingThe House Money Effect can influence various decision-making scenarios, including investments, spending, and entrepreneurial ventures. It often leads to more daring choices and a willingness to take on risks that might be avoided with personal savings or initial capital. Impact on decision-making can have financial consequences.
Psychological BiasThe House Money Effect is considered a psychological bias that affects how individuals assess and approach financial situations. It underscores the role of cognitive biases in financial decision-making. Psychological bias is central to the House Money Effect.
Revenue ModelsThe House Money Effect itself does not generate revenue; instead, it can influence financial decisions that may impact revenue in various ways:
Investment DecisionsIn investment scenarios, individuals who perceive gains as “house money” may be more willing to invest in riskier assets or make speculative decisions. While this can lead to potential gains, it also carries higher risks that could affect investment returns.
Business VenturesEntrepreneurs or business owners may be more inclined to undertake riskier business ventures or expand their operations when they view additional funds as “house money.” This can lead to opportunities for revenue growth, but it also exposes the business to increased risks.
Consumer SpendingConsumers who perceive their surplus funds as “extra” may engage in higher levels of discretionary spending or luxury purchases, potentially boosting revenue for businesses catering to such spending patterns.
Asset AllocationIn the context of asset management, individuals managing portfolios may allocate perceived winnings or “house money” differently than their core investments. This can impact the overall performance of the portfolio and, consequently, investment returns.
AdvantagesWhile the House Money Effect is not inherently advantageous or disadvantageous, understanding its implications can offer several advantages:
Risk AwarenessRecognizing the House Money Effect increases awareness of how psychological biases can influence financial decisions. This awareness can lead to more informed and balanced risk-taking behavior.
Better Decision-MakingUnderstanding the House Money Effect allows individuals and organizations to make more deliberate and rational choices when dealing with perceived winnings or additional funds. It can lead to improved financial decision-making.
Mitigating RisksOrganizations and investors can take steps to mitigate the potential risks associated with the House Money Effect by incorporating risk management strategies and diversification into their decision-making processes. This can help protect against excessive risk-taking.
Financial PlanningIncorporating the House Money Effect into financial planning can result in more balanced and realistic financial goals and strategies. It helps individuals and organizations account for potential biases in their financial plans.

Understanding the house money effect

In the paper, Thaler and Johnson ask the reader to consider a scenario where they were attending a convention in Las Vegas. While passing the slot machines in a casino one night, they place a quarter in one slot machine and win $100. 

The pair then asks the reader to consider how their gambling behavior might be affected for the rest of the evening. In other words, would they be tempted to make a few more serious wages – even if they usually refrained from the practice? The answer, in most cases, is yes. The individual would continue to place bets in the casino with house money.

Today, the house money effect is more commonly associated with investors. The effect suggests some investors tend to enter into positions with higher risk if they have already made a profit from the initial investment. Windfall trades may also induce the house money effect. When an investor triples their money in four months, for example, they may bet it all on another risky trade instead of taking profit or investing more conservatively.

Why does the house money effect occur?

The house money effect occurs because of the distinction investors make between their own capital in the form of wages or savings and the capital gains made on an investment.

In simple terms, the house money effect describes a tendency for the investor to take on more risk with money obtained easily or unexpectedly. Capital earned through employment or other means is not invested in the same way since the capital itself is harder to “earn”.

To demonstrate the attraction of easy-won gains, Thaler and Johnson conducted a study with two groups. The first group was told they’d won $30 and could take part in a coin toss to gamble a portion of their winnings. Heads would reduce the winnings to $21 and tails would increase them to $39. The second group was given a more simple proposition: they could either accept the $30 or toss the coin under identical terms to the first group.

While the expected value for each group was the same, the members of the group who were told they’d won the money were more likely to take the coin toss and risk losing their money. The second group, whose money was not associated with gambling, was much more conservative and decided to cash out their $30.

Examples of the House Money Effect:

  • Stock Market Investment: An investor, let’s call her Sarah, buys shares of a tech company and sees a significant increase in the stock price, resulting in a sizable profit. Sarah experiences the house money effect and becomes more willing to take higher risks with her profits. Instead of cashing out some of her gains or diversifying her portfolio, she decides to reinvest a large portion of her profits into riskier stocks or speculative assets.
  • Cryptocurrency Trading: John invests a small amount in a cryptocurrency and sees its value skyrocket within a short period. He experiences the house money effect and becomes overconfident in his trading abilities. John decides to invest more significant amounts in other cryptocurrencies without conducting thorough research or understanding the potential risks involved. His decision is influenced by the profits he made earlier, leading to higher-risk trades.
  • Real Estate Investment: Mary invests in a rental property, and over time, its value appreciates substantially. As a result of the house money effect, she decides to take out a home equity loan against the property to fund another investment. This decision exposes her to higher financial risks, as she is leveraging her property’s gains to make additional investments.
  • Startup Funding: Jack is an angel investor who invested in a startup during its early stages. The startup achieves significant success and receives a large funding round from a venture capital firm. Encouraged by the success of the startup, Jack decides to invest more money in riskier early-stage startups without conducting thorough due diligence. He believes that his initial success with the first startup makes him more capable of identifying successful ventures.
  • Gambling Behavior: The house money effect is well-documented in the context of gambling. For example, in a casino, a gambler wins a substantial amount of money early in the night while playing blackjack. Experiencing the house money effect, the gambler becomes more willing to place larger bets on riskier games or bets, believing that they are playing with “house money” and can afford to take bigger risks.
  • Business Expansion: A successful small business owner decides to expand their operations after a particularly profitable quarter. They open multiple new locations without conducting thorough market research or financial analysis. The business owner is influenced by the house money effect, believing that their past success guarantees future success in the expansion.

Key takeaways:

  • The house money effect is a cognitive bias where investors take higher risks on reinvested capital than they would on an initial investment.
  • The house money effect was first described by researchers Richard Thaler and Eric Johnson in 1990. They described the effect in the context of a gambler in Las Vegas, who becomes more inclined to bet with house money after winning $100 on a slot machine.
  • The house money effect occurs because of the distinction investors make between their own capital in the form of wages or savings and the capital gains made on an investment. Capital gains are considered more easily attained, so the investor is comfortable taking on more risk when investing them.

Key Highlights

  • Definition of the House Money Effect: The house money effect is a cognitive bias in which investors are more likely to take higher risks with profits or gains from previous investments (reinvested capital) than they would with their initial investment. This effect is named after the idea that individuals may treat gains as if they were “house money” in a casino.
  • Origin of the Term: The house money effect was first described in a 1990 study by Richard Thaler and Eric Johnson titled “Gambling with the House Money and Trying to Break Even: The Effects of Prior Outcomes on Risky Choice.” The study used the context of gambling to illustrate the phenomenon.
  • Behavioral Explanation: The house money effect suggests that individuals are more willing to take risks with gains that were obtained easily or unexpectedly (such as from investments) compared to money that they had to work harder to earn. The perceived separation between the initial investment and the subsequent gains influences their risk-taking behavior.
  • Investment Behavior and Windfall Trades: The house money effect is often observed among investors. It leads to scenarios where investors take on higher risks with their profits or windfall gains instead of cashing out or diversifying their investments. This behavior may lead to risky decisions and overconfidence.
  • Demonstrating the Effect: Thaler and Johnson conducted a study to demonstrate the house money effect. They offered participants the opportunity to gamble with money they had just won and found that participants were more likely to take risks with the “house money” than with their own earned money.
  • Examples of the House Money Effect:
    • Stock Market: Investors reinvest profits from successful trades into riskier assets.
    • Cryptocurrency: Traders make higher-risk investments after experiencing significant gains in the market.
    • Real Estate: Property owners leverage property gains for additional investments.
    • Startup Funding: Early success leads to riskier investments in startups.
    • Gambling: Gamblers place larger bets after early wins.
    • Business Expansion: Business owners expand without thorough analysis after profitable periods.

Connected Thinking Frameworks

Convergent vs. Divergent Thinking

Convergent thinking occurs when the solution to a problem can be found by applying established rules and logical reasoning. Whereas divergent thinking is an unstructured problem-solving method where participants are encouraged to develop many innovative ideas or solutions to a given problem. Where convergent thinking might work for larger, mature organizations where divergent thinking is more suited for startups and innovative companies.

Critical Thinking

Critical thinking involves analyzing observations, facts, evidence, and arguments to form a judgment about what someone reads, hears, says, or writes.


The concept of cognitive biases was introduced and popularized by the work of Amos Tversky and Daniel Kahneman in 1972. Biases are seen as systematic errors and flaws that make humans deviate from the standards of rationality, thus making us inept at making good decisions under uncertainty.

Second-Order Thinking

Second-order thinking is a means of assessing the implications of our decisions by considering future consequences. Second-order thinking is a mental model that considers all future possibilities. It encourages individuals to think outside of the box so that they can prepare for every and eventuality. It also discourages the tendency for individuals to default to the most obvious choice.

Lateral Thinking

Lateral thinking is a business strategy that involves approaching a problem from a different direction. The strategy attempts to remove traditionally formulaic and routine approaches to problem-solving by advocating creative thinking, therefore finding unconventional ways to solve a known problem. This sort of non-linear approach to problem-solving, can at times, create a big impact.

Bounded Rationality

Bounded rationality is a concept attributed to Herbert Simon, an economist and political scientist interested in decision-making and how we make decisions in the real world. In fact, he believed that rather than optimizing (which was the mainstream view in the past decades) humans follow what he called satisficing.

Dunning-Kruger Effect

The Dunning-Kruger effect describes a cognitive bias where people with low ability in a task overestimate their ability to perform that task well. Consumers or businesses that do not possess the requisite knowledge make bad decisions. What’s more, knowledge gaps prevent the person or business from seeing their mistakes.

Occam’s Razor

Occam’s Razor states that one should not increase (beyond reason) the number of entities required to explain anything. All things being equal, the simplest solution is often the best one. The principle is attributed to 14th-century English theologian William of Ockham.

Lindy Effect

The Lindy Effect is a theory about the ageing of non-perishable things, like technology or ideas. Popularized by author Nicholas Nassim Taleb, the Lindy Effect states that non-perishable things like technology age – linearly – in reverse. Therefore, the older an idea or a technology, the same will be its life expectancy.


Antifragility was first coined as a term by author, and options trader Nassim Nicholas Taleb. Antifragility is a characteristic of systems that thrive as a result of stressors, volatility, and randomness. Therefore, Antifragile is the opposite of fragile. Where a fragile thing breaks up to volatility; a robust thing resists volatility. An antifragile thing gets stronger from volatility (provided the level of stressors and randomness doesn’t pass a certain threshold).

Systems Thinking

Systems thinking is a holistic means of investigating the factors and interactions that could contribute to a potential outcome. It is about thinking non-linearly, and understanding the second-order consequences of actions and input into the system.

Vertical Thinking

Vertical thinking, on the other hand, is a problem-solving approach that favors a selective, analytical, structured, and sequential mindset. The focus of vertical thinking is to arrive at a reasoned, defined solution.

Maslow’s Hammer

Maslow’s Hammer, otherwise known as the law of the instrument or the Einstellung effect, is a cognitive bias causing an over-reliance on a familiar tool. This can be expressed as the tendency to overuse a known tool (perhaps a hammer) to solve issues that might require a different tool. This problem is persistent in the business world where perhaps known tools or frameworks might be used in the wrong context (like business plans used as planning tools instead of only investors’ pitches).

Peter Principle

The Peter Principle was first described by Canadian sociologist Lawrence J. Peter in his 1969 book The Peter Principle. The Peter Principle states that people are continually promoted within an organization until they reach their level of incompetence.

Straw Man Fallacy

The straw man fallacy describes an argument that misrepresents an opponent’s stance to make rebuttal more convenient. The straw man fallacy is a type of informal logical fallacy, defined as a flaw in the structure of an argument that renders it invalid.

Streisand Effect

The Streisand Effect is a paradoxical phenomenon where the act of suppressing information to reduce visibility causes it to become more visible. In 2003, Streisand attempted to suppress aerial photographs of her Californian home by suing photographer Kenneth Adelman for an invasion of privacy. Adelman, who Streisand assumed was paparazzi, was instead taking photographs to document and study coastal erosion. In her quest for more privacy, Streisand’s efforts had the opposite effect.


As highlighted by German psychologist Gerd Gigerenzer in the paper “Heuristic Decision Making,” the term heuristic is of Greek origin, meaning “serving to find out or discover.” More precisely, a heuristic is a fast and accurate way to make decisions in the real world, which is driven by uncertainty.

Recognition Heuristic

The recognition heuristic is a psychological model of judgment and decision making. It is part of a suite of simple and economical heuristics proposed by psychologists Daniel Goldstein and Gerd Gigerenzer. The recognition heuristic argues that inferences are made about an object based on whether it is recognized or not.

Representativeness Heuristic

The representativeness heuristic was first described by psychologists Daniel Kahneman and Amos Tversky. The representativeness heuristic judges the probability of an event according to the degree to which that event resembles a broader class. When queried, most will choose the first option because the description of John matches the stereotype we may hold for an archaeologist.

Take-The-Best Heuristic

The take-the-best heuristic is a decision-making shortcut that helps an individual choose between several alternatives. The take-the-best (TTB) heuristic decides between two or more alternatives based on a single good attribute, otherwise known as a cue. In the process, less desirable attributes are ignored.

Bundling Bias

The bundling bias is a cognitive bias in e-commerce where a consumer tends not to use all of the products bought as a group, or bundle. Bundling occurs when individual products or services are sold together as a bundle. Common examples are tickets and experiences. The bundling bias dictates that consumers are less likely to use each item in the bundle. This means that the value of the bundle and indeed the value of each item in the bundle is decreased.

Barnum Effect

The Barnum Effect is a cognitive bias where individuals believe that generic information – which applies to most people – is specifically tailored for themselves.

First-Principles Thinking

First-principles thinking – sometimes called reasoning from first principles – is used to reverse-engineer complex problems and encourage creativity. It involves breaking down problems into basic elements and reassembling them from the ground up. Elon Musk is among the strongest proponents of this way of thinking.

Ladder Of Inference

The ladder of inference is a conscious or subconscious thinking process where an individual moves from a fact to a decision or action. The ladder of inference was created by academic Chris Argyris to illustrate how people form and then use mental models to make decisions.

Goodhart’s Law

Goodhart’s Law is named after British monetary policy theorist and economist Charles Goodhart. Speaking at a conference in Sydney in 1975, Goodhart said that “any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes.” Goodhart’s Law states that when a measure becomes a target, it ceases to be a good measure.

Six Thinking Hats Model

The Six Thinking Hats model was created by psychologist Edward de Bono in 1986, who noted that personality type was a key driver of how people approached problem-solving. For example, optimists view situations differently from pessimists. Analytical individuals may generate ideas that a more emotional person would not, and vice versa.

Mandela Effect

The Mandela effect is a phenomenon where a large group of people remembers an event differently from how it occurred. The Mandela effect was first described in relation to Fiona Broome, who believed that former South African President Nelson Mandela died in prison during the 1980s. While Mandela was released from prison in 1990 and died 23 years later, Broome remembered news coverage of his death in prison and even a speech from his widow. Of course, neither event occurred in reality. But Broome was later to discover that she was not the only one with the same recollection of events.

Crowding-Out Effect

The crowding-out effect occurs when public sector spending reduces spending in the private sector.

Bandwagon Effect

The bandwagon effect tells us that the more a belief or idea has been adopted by more people within a group, the more the individual adoption of that idea might increase within the same group. This is the psychological effect that leads to herd mentality. What in marketing can be associated with social proof.

Moore’s Law

Moore’s law states that the number of transistors on a microchip doubles approximately every two years. This observation was made by Intel co-founder Gordon Moore in 1965 and it become a guiding principle for the semiconductor industry and has had far-reaching implications for technology as a whole.

Disruptive Innovation

Disruptive innovation as a term was first described by Clayton M. Christensen, an American academic and business consultant whom The Economist called “the most influential management thinker of his time.” Disruptive innovation describes the process by which a product or service takes hold at the bottom of a market and eventually displaces established competitors, products, firms, or alliances.

Value Migration

Value migration was first described by author Adrian Slywotzky in his 1996 book Value Migration – How to Think Several Moves Ahead of the Competition. Value migration is the transferal of value-creating forces from outdated business models to something better able to satisfy consumer demands.

Bye-Now Effect

The bye-now effect describes the tendency for consumers to think of the word “buy” when they read the word “bye”. In a study that tracked diners at a name-your-own-price restaurant, each diner was asked to read one of two phrases before ordering their meal. The first phrase, “so long”, resulted in diners paying an average of $32 per meal. But when diners recited the phrase “bye bye” before ordering, the average price per meal rose to $45.


Groupthink occurs when well-intentioned individuals make non-optimal or irrational decisions based on a belief that dissent is impossible or on a motivation to conform. Groupthink occurs when members of a group reach a consensus without critical reasoning or evaluation of the alternatives and their consequences.


A stereotype is a fixed and over-generalized belief about a particular group or class of people. These beliefs are based on the false assumption that certain characteristics are common to every individual residing in that group. Many stereotypes have a long and sometimes controversial history and are a direct consequence of various political, social, or economic events. Stereotyping is the process of making assumptions about a person or group of people based on various attributes, including gender, race, religion, or physical traits.

Murphy’s Law

Murphy’s Law states that if anything can go wrong, it will go wrong. Murphy’s Law was named after aerospace engineer Edward A. Murphy. During his time working at Edwards Air Force Base in 1949, Murphy cursed a technician who had improperly wired an electrical component and said, “If there is any way to do it wrong, he’ll find it.”

Law of Unintended Consequences

The law of unintended consequences was first mentioned by British philosopher John Locke when writing to parliament about the unintended effects of interest rate rises. However, it was popularized in 1936 by American sociologist Robert K. Merton who looked at unexpected, unanticipated, and unintended consequences and their impact on society.

Fundamental Attribution Error

Fundamental attribution error is a bias people display when judging the behavior of others. The tendency is to over-emphasize personal characteristics and under-emphasize environmental and situational factors.

Outcome Bias

Outcome bias describes a tendency to evaluate a decision based on its outcome and not on the process by which the decision was reached. In other words, the quality of a decision is only determined once the outcome is known. Outcome bias occurs when a decision is based on the outcome of previous events without regard for how those events developed.

Hindsight Bias

Hindsight bias is the tendency for people to perceive past events as more predictable than they actually were. The result of a presidential election, for example, seems more obvious when the winner is announced. The same can also be said for the avid sports fan who predicted the correct outcome of a match regardless of whether their team won or lost. Hindsight bias, therefore, is the tendency for an individual to convince themselves that they accurately predicted an event before it happened.

Read Next: BiasesBounded RationalityMandela EffectDunning-Kruger EffectLindy EffectCrowding Out EffectBandwagon Effect.

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