Trading & Investing Quotes

Warren Buffett’s quote highlights a key principle of successful investing: patience.

The stock market is inherently volatile, with prices fluctuating constantly.

Impatient investors often react emotionally to these swings, buying high in moments of excitement and selling low in fear. This emotional decision-making leads to losses.

Patient investors, on the other hand, understand that market fluctuations are normal.

They focus on the long-term potential of their investments, holding onto them through temporary downturns.

This allows them to ride out the volatility and ultimately profit from the overall upward trend of the market.

Essentially, impatient investors lose money by trying to time the market, while patient investors win by giving their investments time to grow.

“Risk comes from not knowing what you’re doing.” – Warren Buffett 

This highlights the importance of knowledge and research in investing.

Investors who don’t understand their investments expose themselves to greater risks, while informed traders can make more calculated, confident decisions.

“The market can stay irrational longer than you can stay solvent.” – John Maynard Keynes 

This warns that market trends can defy logic for extended periods.

Betting on a quick return to fundamentals can lead to losses if irrationality persists.

In the end, the price of something is just the amount spent on it divided by the quantity, not necessarily its notional equilibrium value, which is a longer-term consideration (and is subjective).

“Time in the market beats timing the market.” – Unknown 

This quote emphasizes that staying invested over the long term is often more profitable than trying to time market ups and downs, which can be unpredictable and lead to missed opportunities.

“Buy when there’s blood in the streets.” – Baron Rothschild 

This encourages a contrarian approach.

It suggests buying during widespread fear or market crashes, as those are often the best times to find undervalued investments.

In terms of modern finance parlance, risk premiums generally expand when prices fall and compress when they rise.

“Compound interest is the eighth wonder of the world.” – Albert Einstein 

Einstein’s quote underscores the power of compounding, where reinvesting earnings leads to exponential growth over time, especially in long-term investments.

“An investment in knowledge pays the best interest.” – Benjamin Franklin 

Franklin suggests that continuous learning, particularly about investing, is one of the most valuable investments a person can make, yielding substantial long-term returns.

“Price is what you pay, value is what you get.” – Warren Buffett

This quote distinguishes between the price of an asset and its true value.

Investors should focus on understanding the underlying value of what they’re buying rather than simply looking at the current price, which might not reflect the asset’s true worth.

“Wide diversification is only required when investors do not understand what they are doing.” – Warren Buffett

Buffett suggests that excessive diversification is a crutch for investors who lack confidence in their investments.

Instead, he advocates for focused investing in a few well-understood assets.

It, of course, depends on one’s knowledge.

Those active in their approach will tend to be more concentrated, while those who are passive will tend to diversify more.

“In investing, what is comfortable is rarely profitable.” – Robert Arnott

Arnott highlights that successful investing often involves stepping out of one’s comfort zone.

The most rewarding investments may be found in areas where others are unwilling to look due to fear or uncertainty.

“Know what you own, and know why you own it.” – Peter Lynch

This stresses the importance of understanding your investments.

Blindly holding assets without knowing their value or potential can lead to poor decision-making, especially during market volatility.

“The stock market is filled with individuals who know the price of everything, but the value of nothing.” – Philip Fisher

Fisher’s quote reinforces the importance of focusing on intrinsic value rather than the day-to-day price movements.

Many investors get caught up in short-term prices without understanding the long-term potential of the underlying asset.

“Diversification is protection against ignorance.” – Warren Buffett

Buffett argues that diversification is often a way to reduce risk when an investor lacks deep knowledge about specific assets.

Especially those from Buffett’s time where trading wasn’t so computerized, they tend to focus on fewer stocks and know them well rather than spreading their investments too thin.

“Cut your losses and let your winners run.” – Jesse Livermore

This advice from legendary trader Jesse Livermore underscores the importance of controlling risk by quickly exiting losing positions while holding onto profitable ones.

Cutting losses early – when you realize that something was genuinely a bad decision – prevents small setbacks from becoming large ones, while riding winners maximizes potential gains.

It’s a fundamental principle in both trading and investing that emphasizes disciplined decision-making.

“The trend is your friend, until the end when it bends.” – Ed Seykota

Ed Seykota was a pioneer of systematic trading.

Here he highlights the importance of following market trends rather than fighting them.

Trend-following strategies try to profit from sustained price movements, but they also carry risks when trends reverse.

Successful traders know when to stick with the trend and when to exit when the trade meets its goals.

“Markets are never wrong, opinions often are.” – Jesse Livermore

This quote reflects the humility necessary in trading and investing.

It warns against becoming too attached to personal predictions, which can lead to stubbornness and losses.

The market reflects collective behavior, and traders must respect its signals rather than sticking to rigid opinions.

“Far more money has been lost by investors preparing for corrections, or trying to anticipate corrections, than has been lost in corrections themselves.” – Peter Lynch

Peter Lynch’s quote cautions against market timing and the fear of downturns.

Many investors panic and exit the market prematurely.

In turn, they miss out on the recovery and growth that often follow corrections.

This highlights the value of long-term investing, where staying the course often yields better results than attempting to predict every market fluctuation.

“Bull markets are born on pessimism, grow on skepticism, mature on optimism, and die on euphoria.” – Sir John Templeton

Templeton’s quote offers a framework for understanding market cycles.

Successful investors recognize the signs of each phase and may adjust their strategies accordingly.

Pessimism often presents buying opportunities, while euphoria signals potential market peaks, leading to caution.

“Do not put all your eggs in one basket.” – Andrew Carnegie

Carnegie’s well-known quote speaks to the principle of diversification in investing.

Spreading investments across different assets reduces risk, as a failure in one doesn’t jeopardize the entire portfolio.

It’s a fundamental strategy for risk management and protection against market volatility.

“You make most of your money in a bear market; you just don’t realize it at the time.” – Shelby Cullom Davis

Davis’s quote emphasizes the long-term perspective.

Bear markets are challenging, but often present opportunities to buy quality investments at discounted prices.

Although these purchases may not immediately show returns, the recovery phase of the market typically rewards patient investors.

Alternatively, you might think of bear markets where you learn many lessons on how to develop more robust portfolios.

“Amateurs think about how much money they can make. Professionals think about how much money they could lose.” – Jack Schwager

This quote captures the essence of risk management.

Amateur traders tend to focus solely on potential profits, while professionals are equally concerned with minimizing losses.

In general, professional traders are always thinking about the balance between reward and risk and not overly focused on playing offense.

“If you go to Minnesota in January, you should know that it’s gonna be cold. You don’t panic when the thermometer falls below zero.” – Peter Lynch

He’s drawing a parallel between the expected cold weather in Minnesota in January and the expected declines that occur in the stock market.

Just as Minnesotans are prepared for the cold, investors should expect and be prepared for market downturns.

They’re a normal part of the market cycle, and panicking during these times can lead to poor decisions.

“The market is essentially designed to cause traders to do the wrong thing at the wrong time. The market turns our cognitive tools and psychological quirks against us, making us our own enemy in the marketplace. It is not so much that the market is against us; it is that the market sets us against ourselves.” – Adam H. Grimes

This quote captures the psychological challenges of trading and investing.

It suggests that financial markets inherently work in a way that often leads traders to make poor decisions.

The market doesn’t actively work against us. Rather, it creates conditions that exploit our natural cognitive biases and psychological tendencies, leading us to become our own worst enemy.

Human psychology has evolved to make quick judgments, often based on emotion and instinct (e.g., heuristics) – traits that, while useful in everyday life, can be detrimental in trading.

For example, cognitive biases like loss aversion make people fear losses more than they value equivalent gains, often leading traders to hold onto losing positions too long, hoping for a rebound.

Similarly, recency bias – where recent events are weighted more heavily than long-term trends – can lead traders to believe a trend will continue just because it has been present in the short term, leading to irrational trading decisions.

Traders also tend to buy when prices go up (out of excitement or fear of missing out, thinking they’re good rather than more expensive) and get spooked and sell when things go down (when they’re getting cheaper).

So, they do basically the opposite of what they should be doing.

We covered in a separate article how the best traders tend to be the ones that forgot about their accounts or passed away.

Grimes’ insight is particularly relevant in volatile or uncertain markets, where price movements can seem irrational or unpredictable.

Such environments trigger emotions like fear and greed, which can cloud judgment and lead to impulsive actions.

To counteract these tendencies, Grimes’ message implies that traders have to cultivate self-awareness, discipline, and some sort of systematic approach that tempers emotional responses.

“Whenever I make an investment decision, I observe myself making it and think about the criteria I used. I ask myself how I would handle another one of those situations and write down my principles for doing so. Then I turn them into algorithms. I am now doing the same for management and I have gotten in the habit of doing it for all my decisions.” – Ray Dalio

Dalio emphasizes a structured approach to decision-making in this quote.

He describes how he observes his own thought process when making investment decisions, analyzing the criteria he considers and the steps he takes.

This helps him understand the reasoning behind his choices, which enables him to identify patterns and principles that guide his actions.

Whenever we make a decision there’s something going on in our heads that’s causing us to make these decisions.

So why not write down the criteria and stress-test it to make it’s good?

Accordingly, he aims to codify his thought process into clear principles. 

From documenting these principles, he creates a foundation for handling similar situations in the future.

This method of turning principles into algorithms helps with much better consistency and objectivity in his decision-making.

Dalio then applies this practice not only to investment but to management and all areas of his life, looking to make his decision-making as systematic and reliable as possible.

Overall, from formalizing his thinking into principles (decision-making criteria) and then algorithms (where possible), Dalio builds a framework that allows him (and others) to benefit from his experience, making his decision-making process more transparent, systematic (i.e., replicable), and efficient.

“The greatest mistake of the individual investor is to think that a market that did well is a good market rather than a more expensive one.” – Ray Dalio

Dalio highlights a common pitfall among individual investors: mistaking past market performance as an indicator of future value. 

When a market performs well, investors often assume it’s inherently “good,” leading them to invest more heavily. 

However, Dalio warns that a strong-performing market is usually more expensive, meaning assets are pricier, which reduces potential returns. 

Instead of viewing a successful market as safe, investors should consider its current valuation and future potential. 

Future returns are often dependent on the current pricing.

This perspective encourages critical analysis over emotional decision-making and avoiding costly mistakes tied to past performance alone.

“All investments compete and it’s not easy to tell whether one investment is better than the other. Because if people could do that life would be easy and everybody would make a ton of money, and this is a competitive game that’s very difficult to compete in.” – Ray Dalio

Dalio emphasizes the inherent challenge in choosing between investments/trades, emphasizing that all of them are in constant competition for capital.

Determining which investment is superior isn’t straightforward.

If it were, investing would be simple, and everyone would profit effortlessly.

The competitive nature of trading and investing stems from the complexity and unpredictability of markets.

Traders and investors have to constantly assess risk, return, and timing, and rarely with perfect information.

This competitive “game” is difficult precisely because markets are influenced by countless variables – economic trends, company performance, global events – with all sorts of variance associated with them.

Every trader is trying to gain an edge, and success requires a blend of strategy, skill, and luck.

Dalio’s insight highlights that achieving significant returns isn’t just about picking good trades or investments; it’s about understanding the competition and the complexity of markets.

The upshot is that most should have the bulk of their capital in passive, diversified strategies for best results.

“But when I mean financial engineering, I don’t mean go into an optimizer and throw things around and see what spits out. I mean understanding the parts and how to put those parts together.” – Ray Dalio

Ray Dalio emphasizes a thoughtful approach to “financial engineering,” contrasting it with a more superficial, formula-driven method.

When he talks about financial engineering, he doesn’t mean merely using optimization software to experiment randomly with different variables or backtesting the recent past until a desirable outcome appears.

Instead, he advocates for a deep, fundamental understanding of the elements involved in financial decisions and how they interact.

Dalio’s approach requires comprehending the specific characteristics, risks, intrinsic correlations, and behaviors of individual investment assets or strategies.

He encourages investors to consider how different financial parts – such as stocks, bonds, commodities, and cash – work in relation to one another, rather than simply relying on software to generate portfolios without deeper insight.

This level of understanding enables traders and investors to build a cohesive, balanced strategy based on knowledge rather than luck or suboptimal, generic optimization.

Knowing how different assets respond to various economic environments, they can engineer a portfolio that withstands different market scenarios.

Dalio’s perspective emphasizes strategic design over trial-and-error experimentation, looking for purpose and resilience in financial planning.

In his view, successful financial engineering relies on insight and intentionality, not just on algorithms or formulas without the deep understanding.

AI Trading & Investing Quotes

“Let’s suppose you have a coin that is 70/30 heads. Well, if you get to bet heads, you are going to win 7 times out of 10. Three times out ten you are going to lose, and that’s bad luck. So you need a measure of good luck to avoid a long run of tails when you have a 70/30 coin that’s heads. At a certain point the luck evens out. Of course there’s luck in our business, but so far we’ve had a nice edge.” – Jim Simons

This is a good quote that talks about the variance involved in markets and how it takes not only an edge but a large enough sample size to realize it. (Related: How Long to Test a Trading Strategy)

It uses the analogy of a biased coin to illustrate the role of luck and edge in trading. 

Even with a statistical advantage (like a coin biased towards heads), there will be periods of losses due to random fluctuations. 

Managing risk and surviving these drawdowns is important to realizing the long-term benefits of the edge. 

The quote acknowledges the presence of luck, but emphasizes the importance of having a strategy that provides a consistent advantage over time. 

This highlights the need for both statistical analysis and sound risk management to navigate the inevitable ups and downs of the market.

“No model is correct; pick the one that’s useful.” – Emanuel Derman (former Goldman Sachs quant, author of “Models.Behaving.Badly”)

Derman, a physicist-turned-quant, points out the limitations of financial models. 

He argues that models are simplified representations of a complex reality, not perfect replicas. 

No model can fully capture all the variables, nuances and unpredictability of markets. 

Instead of seeking an ideal model, traders and investors have to focus on finding models that are useful – those that provide insights, identify opportunities, and manage risks, even if they aren’t entirely accurate (which it’s virtually impossible to be). 

This pragmatic approach acknowledges that all models have flaws, and the key is to select and use them effectively in light of your particular goals, understanding their strengths and weaknesses in a nuanced way.

“We don’t start with models. We start with data. We don’t have any preconceived notions. We look for things that can be replicated thousands of times.” – Jim Simons

Rather than parametric theoretical models onto the market, Simons and his team at RenTech began by analyzing large amounts of data (terabytes per day), searching for patterns and signals. 

They avoid preconceived ideas or biases, letting the computer models guide their strategy development. 

The emphasis on replicability is important: they seek patterns that occur consistently, indicating a strong relationship rather than a random fluke. 

This is important in trading. You don’t want your strategy to be highly tactical and dependent on spotting things that are likely to never repeat themselves. Or at least not repeat themselves consistently.

This approach is central to their success in identifying subtle market inefficiencies.

“Patterns of price movement are not random. However, they’re close enough to random so that getting some excess, some edge out of it, is not easy and not so obvious.” – Jim Simons

While markets may exhibit some predictable patterns, they are often obscured by noise and randomness. 

There are all sorts of different buyers and sellers, of all types of sizes, with many different types of motivations for doing what they’re doing.

Extracting a consistent advantage (“edge”) requires sophisticated techniques to identify these subtle signals. 

It’s not a simple task, as markets are complex adaptive systems influenced by countless factors. 

“There’s no such thing as the goose that lays the golden egg forever.” – Jim Simons

This quote is a reminder that no trading strategy or investment approach works indefinitely outside the obvious – e.g., holding a diversified portfolio of stocks and bonds over long periods of time. 

Successful traders, investors, and business people have to be adaptable, constantly refining their models, and searching for new opportunities as markets evolve.

“The most painful lesson that was repeatedly hammered home is that you can never be sure of anything: There are always risks out there that can hurt you badly, even in the seemingly safest bets, so it’s always best to assume you’re missing something.”  – Ray Dalio

Dalio emphasizes the importance of humility and recognizing the inherent unknowns in markets. 

Even when things seem safe, hidden risks can exist. 

There’s what we know – which isn’t much compared to what’s already discounted in the price. There’s what we know we don’t know. And there’s what we don’t know that we don’t even know that we don’t know.

Amateur traders have a tendency to be far too certain.

Those with more expertise have a better understanding of what they don’t know and can’t know.

So, there’s always the need for continuous learning, critical thinking, and a healthy dose of skepticism to avoid complacency and potential losses.

“Investment systems built on machine learning that is not accompanied by deep understanding are dangerous because when some decision rule is widely believed, it becomes widely used, which affects the price. In other words, the value of a widely known insight disappears over time.”  – Ray Dalio

Dalio cautions against blindly relying on machine learning models in trading. 

Here’s why:

• Overcrowding – When a profitable pattern is discovered, many people exploit it. This pushes prices up (for buying) or down (for selling), eroding the original advantage.
• Self-Defeating Prophecy – The strategy works because it’s not widely known. As it gains popularity, the market adjusts, and the edge vanishes.
• Black Swans – Models are trained on past data – though the algorithms are not necessarily derived that way. Unexpected events (like a pandemic) can cause markets to behave in ways the model never anticipated. It ultimately can’t react to something that’s not accounted for in the system.

Essentially, widely known things get priced in, becoming useless as a source of outperformance. 

True, lasting success requires deep understanding of why something works, allowing you to adapt when the rules of the game change.

“Widely adopted strategies based solely on data patterns often lose their edge as they become crowded trades.” – Ray Dalio 

The market adapts, eroding the initial advantage. 

It requires understanding the underlying drivers behind the patterns.

“We would need to make sense of the formulas the computer produces, of course, to make sure that they are not data-mined gibberish, by which I mean based on correlations that are not causal in any way.”  – Ray Dalio

This quote stresses the importance of human oversight in algorithmic trading. 

Machine learning can identify correlations in data, but it can struggle with causation. 

Humans must analyze the output, so the model’s logic is sound and not based on spurious relationships.

“Of course, given our brain’s limited capacity and processing speed, it could take us forever to achieve a rich understanding of all the variables.”  – Ray Dalio

Dalio acknowledges the limitations of human cognition. 

The sheer volume and complexity of market data can overwhelm our ability to process it effectively. 

We simply can’t process the enormous amount of information fast, accurately, and less emotionally than a well-programmed computer can.

This underscores the need for tools and systems to augment our understanding, but not replace our critical judgment.