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- Herausgeber: John Wiley & Sons
- Kategorie: Fachliteratur
- Sprache: Englisch
An insightful and practical guide to beating the markets
In the newly revised third edition of The Only Three Questions That Still Count: Investing By Knowing What Others Don't, renowned investor Ken Fisher delivers an innovative and insightful strategy you can use in your own life to understand and profit from the markets. He offers updated info on how to navigate an increasingly interconnected world, showing investors can improve their odds of success by answering just three questions using only publicly available information.
The author provides a practical framework you can apply immediately—and in the rest of your investing career—to boost your chances of outsized returns. You'll also find:
- More than 100 visuals illustrating the straightforward investing concepts found within
- Strategies to help you challenge yourself, and your preconceived notions, to improve your investing returns
- Updated techniques and strategies that assist retail investors in developing innovative ways to beat the market
Perfect for professional and individual investors, The Only Three Questions That Still Count is also an invaluable resource for anyone with an interest in the markets and investing behavior.
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Veröffentlichungsjahr: 2025
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Table of Contents
Cover
Table of Contents
Title Page
Copyright
PREFACE
Who Am I to Tell You Something That Counts?
Investing Isn't a Craft
Because It Isn't a Craft …
It's All Latin to Me—Starting to Think Like a Scientist
The Only Three Questions That Count
ACKNOWLEDGMENTS
1 QUESTION ONE: WHAT DO YOU BELIEVE THAT IS ACTUALLY FALSE?
If You Knew It Was Wrong, You Wouldn't Believe It
The Mythological Correlation
Always Look at It Differently
When You Are Really, Really Wrong
2 QUESTION TWO: WHAT CAN YOU FATHOM THAT OTHERS FIND UNFATHOMABLE?
Fathoming the Unfathomable
Ignore the Rock in the Bushes
Discounting the Media Machine and Advanced Fad Avoidance
The Shocking Truth About Yield Curves
What the Yield Curve Is Trying to Tell You
The Presidential Term Cycle
3 QUESTION THREE: WHAT THE HECK IS MY BRAIN DOING TO BLINDSIDE ME NOW?
It Isn't Your Fault—Blame Evolution
Cracking the Stone Age Code—Pride and Regret
The Great Humiliator's Favorite Tricks
Get Your Head Out of the Cave
4 CAPITAL MARKETS TECHNOLOGY
Building and Putting Capital Markets Technology into Practice
It's Good While It Lasts
Forecast with Accuracy, Not Like a Professional
Better Living Through Global Benchmarking
5 WHEN THERE'S NO THERE THERE!
Johns Hopkins, My Grampa, Life Lessons, and Pulling a Gertrude
In the Center Ring—Oil Versus Stocks
Sell in May Because the January Effect Will Dampen Your Santa Claus Rally Unless There Is a Witching Effect
6 NO, IT'S JUST THE OPPOSITE
When You Are Wrong—Really, Really, Really Wrong
Multiplier Effects and the Heroin‐Addicted iPhone Borrower
Let’s Trade This Deficit for That One
The New Gold Standard
7 SHOCKING BUT TRUE
Supply and Demand … and That's It
Weak Dollar, Strong Dollar—What Does It Matter?
8 THE GREAT HUMILIATOR AND YOUR STONE AGE BRAIN
That Predictable Market
Anatomy of a Bubble
Some Basic Bear Rules
What Causes a Bear Market?
9 PUTTING IT ALL TOGETHER
Stick with Your Strategy and Stick It to TGH
Four Rules That Count
Finally! How to Pick Stocks That Only Win
When the Heck Do You Sell?
CONCLUSION:Time to Say Goodbye
Transformationalism
APPENDIX A: Causal Correlations and the Correlation Coefficient
APPENDIX B: News You Can't Use
APPENDIX C: Greater Fools
APPENDIX D: Annualized Versus Average
APPENDIX E: The Wizard of Oz and an Oz of Gold
APPENDIX F: 1980 Revisited
APPENDIX G: Why 2023 Will Be Like 1967's “Summer of Love” for the Stock Market
APPENDIX H: Popular but Problematic
Stop Losses? More Like Stop Gains
Dollar‐Cost Averaging—Higher Fees, Lower Returns
APPENDIX I: Covered Calls—Covering What?
ABOUT THE AUTHORS
INDEX
End User License Agreement
List of Tables
Chapter 1
Table 1.1 What Is an Earnings Yield?
Table 1.2 Stock Returns Following Budget Balance Extremes
Chapter 2
Table 2.1 Presidential Term Anomaly
Table 2.2 Incumbents Uninhibited
Chapter 3
Table 3.1 The January Ineffect
Chapter 4
Table 4.1 Data Sources
Table 4.2 Leadership Keeps Shifting—Top Five Performing Stock Marke...
Chapter 5
Table 5.1 Sell in May and Go Away?
Table 5.2 S&P 500 Average Monthly Returns
Chapter 6
Table 6.1 Aggregate Hard Asset Balance Sheet of the United States...
Chapter 7
Table 7.1 Stock Market Returns Following Bear Markets
Table 7.2 The Dollar and Stocks
Chapter 8
Table 8.1 Average Returns Aren't Normal. Normal Returns Are Extreme...
Table 8.2 Average Returns Aren't Normal. Normal Returns Are Extreme...
Table 8.3 The Making of Two Bubbles
Table 8.4 Internet Burn Rates
Table 8.5 Never a Dull Moment
List of Illustrations
Chapter 1
Figure 1.1 Relationship Between P/E Ratios at the Beginning of a Y...
Figure 1.2 Relationship Between Annualized (Overlapping) One‐Year...
Figure 1.3 153 Years of Historical P/E Ratios and Stock Market Ret...
Figure 1.4 US 10‐Year Bond Yield Versus Earnings Yield.
Figure 1.5 Budget Deficits Are Good for Stocks.
Chapter 2
Figure 2.1 The Fed Doesn't Dictate Long Rates.
Figure 2.2 Hypothetical Yield Curve.
Figure 2.3 Fed Funds and the S&P 500.
Figure 2.4 Global Yield Curve, December 2024.
Figure 2.5 Global Yield Spread.
Figure 2.6 No Style Is Best for All Time.
Figure 2.7 Global Growth and Value Performance Relative to Global...
Chapter 3
Figure 3.1 Net New Cash Flow in Stock Mutual Funds.
Figure 3.2 Don't Hold Your Breath.
Figure 3.3 The Opportunity Cost of Holding On.
Chapter 4
Figure 4.1 Annual Market Forecast Surveys.
Figure 4.2 Benchmark and Time Horizon. Note: For illustrative pur...
Chapter 5
Figure 5.1 US Oil Production Gushes Past Peak Fears.
Figure 5.2 US Energy Intensity.
Figure 5.3 High Oil Prices Hurt Stocks. Do They Really?
Figure 5.4 Oil Versus S&P 500: One‐Year Monthly Rolling Correlatio...
Figure 5.5 Oil Versus S&P 500: Five‐Year Monthly Rolling R‐Squared...
Figure 5.6 Oil Prices and International Stocks.
Chapter 6
Figure 6.1 Budget Deficits Are Good for Stocks—Globally.
Figure 6.2 US Net Federal Debt as a Percent of GDP.
Figure 6.3 UK Net Public Debt as a Percent of GDP.
Figure 6.4 Trade Balances as a Percent of GDP.
Figure 6.5 Price of Gold and the S&P 500.
Figure 6.6 Growth of $1 in US Stocks, Bonds and Gold.
Figure 6.7 Global Long Bonds.
Figure 6.8 US 10‐Year Treasury Yield.
Chapter 7
Figure 7.1 Trade Deficits Don't Doom the Dollar.
Figure 7.2 A Weak Currency Doesn't Mean a Weak Stock Market: US....
Figure 7.3 A Weak Currency Doesn't Mean a Weak Stock Market: Globa...
Figure 7.4 Global Yield Curves, January 1, 2004.
Figure 7.5 Global Yield Curves, January 1, 2005.
Chapter 8
Figure 8.1 The Differing Fortunes of Pam and Pete.
Figure 8.2 The Sentiment Bell Curve Shifts to the Right (S&P 500 F...
Figure 8.3 Bull Markets Die with a Whimper, Not a Bang.
Figure 8.4 The Two‐Thirds, One‐Third Rule.
Figure 8.5 Every Bear Market Is Followed by a Bull Market.
Figure 8.6 The 2% Rule.
Figure 8.7 A Shallow Bear Market.
Figure 8.8 Have No Fear: The Market Doesn't.
Figure 8.9 Regional Conflict Doesn't Knock Stocks
Chapter 9
Figure 9.1 Pharma and Tech Correlation Wiggles.
Figure 9.2 Tech and Pharma Divergence.
Figure 9.3 Portfolio Engineering Funnel.
10
Figure I.1 Covered Call Possible Payout.
Figure I.2 Covered Calls and Naked Puts.
Guide
Cover
Table of Contents
Title Page
Copyright
PREFACE
ACKNOWLEDGMENTS
Begin Reading
CONCLUSION: Time to Say Goodbye
APPENDIX A: Causal Correlations and the Correlation Coefficient
APPENDIX B: News You Can't Use
APPENDIX C: Greater Fools
APPENDIX D: Annualized Versus Average
APPENDIX E: The Wizard of Oz and an Oz of Gold
APPENDIX F: 1980 Revisited
APPENDIX G: Why 2023 Will Be Like 1967's “Summer of Love” for the Stock Market
APPENDIX H: Popular but Problematic
APPENDIX I: Covered Calls—Covering What?
ABOUT THE AUTHORS
INDEX
END USER LICENSE AGREEMENT
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The Only Three Questions That Still Count
Investing by Knowing What Others Don't
Third Edition
KEN FISHER WITH LARA HOFFMANS, ELISABETH DELLINGER, AND TODD BLIMAN
Copyright © 2026 by Fisher Investments. All rights reserved.
Published by John Wiley & Sons, Inc., Hoboken, New Jersey.Published simultaneously in Canada.
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ISBN 9781394318834 (Cloth)ISBN 9781394318865 (ePub)ISBN 9781394318858 (ePDF)
COVER DESIGN: PAUL MCCARTHY
PREFACE
Who Am I to Tell You Something That Counts?
Who am I to tell you anything, much less anything that counts? Or that there are only three questions that count and I know what they are? Why should you bother reading any of this? Why listen to me at all?
As I revisit this book for its third edition—a fact that amazes me to this day—I'm celebrating over half a century in the investment industry. I'm the founder, Executive Chairman, and co‐CIO of my firm, Fisher Investments. When I last updated this book, we were already among the world's largest independent discretionary money management firms. We've only grown since. My firm now stewards the portfolios of more than 100,000 American families—plus thousands in the UK, eurozone, Sweden, Norway, Denmark, Canada, Australia, New Zealand, and Saudi Arabia. Beyond high‐net‐worth individuals, we manage portfolios for an impressive roster of institutions—major corporate and public pension plans, sovereign states, endowments, and foundations—spanning the globe. In all, we manage more than $290 billion for our clients.
I wrote Forbes's “Portfolio Strategy” column from 1984 through 2016, a 32½ year run that made me the longest continuously running columnist in Forbes's long history. Now I write regular, monthly columns in 25 publications worldwide, including the New York Post, Britain's Daily Telegraph, Canada's Globe & Mail, Germany's Focus Money, Spain's elEconomista, Japan's Diamond Weekly, Saudi Arabia's Al Eqtisadiah, and more. I've written 11 books, including four New York Times bestsellers. Along the way, and without really aiming at it, I made the Forbes 400 list of richest Americans.
That's a lot for one lifetime and one professional career. But I'm here to tell you the prime cumulative lesson of my long career is when it comes to investing: There are only three questions that count. And my view on that hasn't changed since I first penned this book. In updating it, my belief in this statement only grew.
In reality, there really is only one question that counts. Or, at least, only one question that really counts. But I don't know how to express that one question in a way you can easily use for everyday investing decisions. If broken down into three subparts, I know how.
And what is that only question that counts? Finance theory is quite clear: The only rational basis for making an investment decision is if you believe somehow, some way, you know something others don't know. The only question that counts is: What do you know that others don't?
Most people don't know anything others don't. Most folks don't think they're supposed to know something others don't. We'll see why. But saying you must know something others don't isn't at all novel. Pretty much everyone who took a basic college investment class learned this, although most people conveniently forgot.
Without answering the question—what do you know that others don't—investing with an aim to do as well or better than the market is futile. I'll say that another way. Markets are pretty efficient at incorporating all currently known information into today's prices. There is nothing new about that statement. It's an established pillar of finance theory and has been repeatedly verified over the decades. If you make market decisions based on the same information others have (or have access to), you will likely do worse than you would have in just sitting passively and taking no action at all. If you try to outguess where the market will go or what sectors will lead and lag or what stock to buy based on what you read online, saw on social media, or chatter about with your friends and peers—no matter how smart or well‐trained you are—you will sometimes be right or lucky or both, but more often be wrong and overall do worse than had you made no trades or transactions at all. Luck, like hope, isn't a strategy. Investing on what everyone knows or sees or chatters about is a strategy for reaping poor investing results.
Perhaps you hate hearing that. But I already told you I didn't know how to express that truism as a single question in a way useful to you. What I can do is show you how to know things other people don't know.
Polling for Perfect Truth
Why is knowing something others don't so important? Financial markets are “discounters” of widely known information—all widely known or discussed information is reflected in securities prices faster than we can say “buy.”
Envision if someone could build an actually accurate poll of all the world's investors. (Yes, yes, I know political polls have proven to have huge blind spots in recent years—use your imagination.) It would include every possible type in just the right proportions. Institutional and retail. Growth and value fans. Small and big cap. Foreign and domestic. FX traders and cryptocurrency fanatics. Meme stock fad‐chasers and penny stock dreamers. Government bond, corporate bond, you name it. Whatever imaginable. Suppose the pollsters polled the sample and the consensus view was the market would rise next month—big time. Could it?
No.
If everyone tended to agree the market would rise next month, anyone with any buying power and a clear mind would buy before then. The market might rise before next month, but only a fool would wait for next month to buy. Hence, next month there would be no subsequent buying power to drive stocks up. It could fall. It could stay flat. But it couldn't rise much. This is an oversimplification, but it's a useful illustration of how whatever we agree on has already been priced into sufficiently liquid markets by the time we can articulate it, and, therefore, it can't occur. Since investors tend to be avid information seekers, the information they have access to has already been reflected in markets via the decisions they made. Think about how quickly a stock's price moves after it releases earnings. By the time you have even skimmed the results and formed a loose opinion, preprogrammed algorithms have traded on that same conclusion. The instant information appears, it is priced.
So it isn't what we all anticipate that moves markets most. It is surprises. The thing few previously fathomed.
Said differently: You may be smarter, wiser, or better trained than the next investor, but finance theory says that isn't enough. No matter how wise you think you are, it's foolhardy to think being smarter or better trained is enough to beat others based on commonly available news and information. And this book's aim is to show how to find things you can know that others can't.
Investing by Knowing What Others Don't
Investing is a difficult, lifetime pursuit. Just knowing the questions isn't enough. You must know what the questions really mean and how to use them. And then you must actually put them to use diligently. Over and over again! The Three Questions don't constitute a craft or a simple “Three Steps to Riches” list. It isn't some Investing Made Easy to‐do list for beating the market. If there were such a thing, I wouldn't be writing this book. You wouldn't read it. Instead, I would put it in a single column and you would glean all you needed to know from it. From there, you would go off and promptly become unimaginably wealthy, perhaps buying your own football team or tropical island. No, it isn't Investing Made Easy. Instead, it's Investing by Knowing What Others Don't.
If you can learn how to use the Three Questions, you can learn to start making better investing decisions. And that should give you an edge over your fellow investors.
Let's think about them. Your fellow investors.
Investing Isn't a Craft
You know some folks are clueless. You don't fear competing with them. But how will you compete with serious professionals who've had serious training, are seriously smart, and have scads of experience? The good news is, in my observation, even most professionals don't have much better long‐term results than average amateur investors. Why? Because, despite being taught they must know something others don't, they forget or ignore it. They fail to get that in their bones.
Typical investors cling to the false premise investing is a craft, like carpentry or doctoring. They don't treat investing like a scientific query session, which is what I'll teach you to do. Instead, consider how they approach it. Maybe they have a few favorite information sources—CNBC, a few news outlets, some blogs, YouTube feeds, and/or a newsletter from their guru du jour. Maybe they have software tracking price patterns. They may have specific rules they adhere to—momentum investing, buy the dips, buy on bad news. They look for clues or signals to buy or sell. They may wait for the S&P 500 and Nasdaq to correspondingly reach certain levels and then they buy or sell or just generally panic. They clock 90‐day moving averages and monitor the VIX (the S&P 500 volatility index) or some other supposedly predictive market indicator. (The VIX is a statistically provable worthless forecaster, by the way—but many people use it every day, applying a wasteful mythology losing more money than it makes.) They believe investing is a craft‐like skill they can hone with practice. They believe master craftsmen must be better investors.
Investors categorize themselves and develop craft skills accordingly. The wannabe value investor develops a slightly different tool kit than the wannabe growth investor. Ditto for small‐cap fans versus big‐cap. Or foreign versus domestic. This works perfectly in carpentry. Anyone can learn basic carpentry, though some people are more naturally gifted than others. It works well for doctoring, if you're smart enough. It works for most sports, which are craft‐based. Again, some folks are naturally better at some sports than others. Accounting, dentistry, lawyering, engineering, and much more—all learnable crafts, though requiring varying degrees of time commitment and physical or mental prowess.
We know learning a craft is possible because there are countless people who perform craft‐based functions after adequate training and apprenticeship (necessary to craft) in high quantities within acceptable and predictable bandwidths. The ability to train an accountant to do an audit in an acceptable manner is a perfect reflection of craftsmanship. But few folks beat the market, amateur or professional. Darned few! So learning a craft obviously isn't enough to do it. Craftsmanship isn't sufficient to the task of beating markets.
Finance theory says it shouldn't be—craft won't help you—because you're supposed to know something others don't. That may excuse an amateur from failing to beat the market, but what about the pros? At a minimum, there are educational licensing requirements professionals must pass to legally advise clients. University students and doctoral candidates in investment finance spend years studying markets. They learn to analyze corporate balance sheets. They learn to calculate risk and expected return, but with widely known analytical tools like Sharpe ratios and R‐squared and CAPM. And with all of this, they still can't beat the market any more often than those without a PhD.
Quite wisely, after years of study, some young wannabe professionals commit to apprenticeship by laboring under another established investor. At the knee of their chosen master, they generally learn a craft the same way a blacksmith apprenticed years ago. Some became generalists and others were specialists who made only weapons like swords and spears, while others made livery gear and plowshares. And today, you name the investing style, there are adherents, apostolic in their allegiance to the school they apprenticed in. Armed with degrees, certifications and apprenticeships, professional investors embark into the world, and still they overwhelmingly lag markets.
They most commonly start where entry is easiest, the way I did decades ago, rendering advice to individuals. These are your stockbrokers, financial planners, and insurance and annuity salespeople. Some provide forecasts and prescriptions of their own, but those working for the big‐name firms generally kowtow to the firm's forecasts. This makes sense for the firm since it's the only way these larger institutions can maintain a semblance of control over their huge employee bases. Big firms hire a few folks with extremely prestigious schooling and extensive professional training who look and sound good for a role like chief economist or chief market strategist—whose main responsibility is forecasting. Industry analysts then forecast in their own individual realms of experience and training. Clients of said illustrious firms, both private and institutional, get the benefit of not only their individual broker's schooling and experience, but also that of the learned, tenured bigwigs who think bigger and wig out well when needed.
So why, with all the knowledge, expertise, and battle scars out there, do vastly more professional investors lag markets than beat them? These are smart people. A lot of them are very smart. Smarter than me for sure. You're probably pretty smart, too. Aren't you? You might be much smarter than me, too. But that won't make any difference on whether you can do better than me as an investor. Smarts and training are good—nothing wrong with them. A PhD is good. But they aren't enough. And they aren't necessary. You must know something others don't and then—with that extra something—you can do better than people who are smarter than you are.
Because It Isn't a Craft …
The answer to improving your error rate isn't in perfecting a craft but in knowing something others don't.
More academic study won't do it. The most learned finance PhD knows free markets are at least pretty efficient (although they do disagree about exactly how efficient). Passing tests like the Series 6, 7, 65—or the CFA or a CIMA certification won't do it. Don't get me wrong. Those things are fine. I'm not casting aspersions. But they involve the study of information millions of other folks have. The media broadcasts them globally. It all hypes what is known and therefore priced. And if they knew something everyone else didn't and told you via the media, instantly everyone else would know it. The new information probably would be priced almost instantly. Now worthless! (I'll show you how to measure an exception to this later.)
You can study technical investing and buy software identifying price movement patterns. It won't help! You can study fundamental investing and vow to buy only when P/Es are at a certain level and sell at yet another level. Won't help! You can hire someone to do it for you who has the most designation letters after his or her name. But you won't beat the market over the long term if you treat investing like a craft.
Well, that isn't quite true. If enough people try all this stuff, some very few will get there simply by dumb luck. In the same way, if enough folks line up to flip coins, you will find someone who gets 50 heads in a row; but that is a fluke. And it likely isn't you. Nor is it the basis for investing or beating markets. And you can count on that.
If investing were a craft, some type of craft (or even some combination of crafts) would have demonstrated market superiority. Someone somewhere would have figured out the right combination to keep beating markets. The right formula, no matter how complicated!
If it were a craft in the very long term, there would be a clear sense a specific craft had generated an army of disciples who did better over the very long term than conflicting approaches. But there is no evidence of this. If investing were a craft, the decades wouldn't have sired thousands of investment books teaching largely contradicting craft—with gurus, pundits, and seminars touting conflicting strategies. There would be a few differing strategies at most. There would be repeatability and consistency. Investing would be learnable like woodworking, masonry, or medicine. Others could teach you. You could pass the skill on with efficacy. There wouldn't be so much failure. And you wouldn't have bought this book because anything I could say would be passé.
It's All Latin to Me—Starting to Think Like a Scientist
When I was a kid, if you wanted to be a scientist, they made you take Latin or Greek. I was a good student generally and took Latin, not because I wanted to be a scientist—I didn't—but because I couldn't figure out the benefit of my other options, Spanish or French. Since no one speaks Latin, I forgot almost everything immediately thereafter except the life lessons in which Latin abounds—like Caesar distinguishing himself by leading from the front of his troops, not the rear as most generals did (and do). It's maybe the most important single lesson of leadership. (One I write about more in my 2008 book, The Ten Roads to Riches.)
Another lesson: The word science derives from the Latin scio—to know, understand, to know how to do. Any scientist will tell you science isn't a craft; rather, it's a never‐ending query session aimed at knowing. Scientists didn't wake up one day and decide to create an equation demonstrating the force exerted on all earthly objects. Instead, Newton first asked a simple question, like, “What the heck makes stuff fall down?” Galileo wasn't excommunicated for agreeing with Aristotle. He asked, “What if stars don't work like everyone says? Wouldn't that be nuts?”
Most of us would see the best scientists of all time, if we could meet them face‐to‐face, as maybe nuts. My friend Stephen Sillett, today's leading redwood scientist, changed the way scientists think about old‐growth redwoods and trees in general by shooting arrows with fishing lines tied to them over the tops of 350‐foot‐tall giants, tying on a firmer line and free‐climbing to the tops. He found life forms and structures up there no one knew existed. Dangling off those ropes 350 feet from terra firma is nuts. Nuts! But he asked the questions: What if there is stuff in the very tops of standing trees that isn't there when you cut them down? And if there is, would it tell you anything about the trees? In the process, he discovered much no one had ever known existed.
Why am I telling you this? Because most of what there is to know about investing doesn't exist yet. Only scientific inquiry and discovery can reveal it. It isn't in a book and isn't finite. We just don't know it yet. We know more now about how capital markets work than we did 50 years ago but little compared to what we can know in 10, 30, and 50 years. That is why I keep updating this book as I accumulate new knowledge! Contrary to what the pundits and professionals will have you believe, the study of capital markets is both an art and a science—one in which theories and formulas continually evolve and are added and adjusted. We are at the beginning of a process of inquiry and discovery, not the end. Its scientific aspect is very much in its infancy.
Scientific inquiry offers opportunities ahead as we steadily learn more about how markets work than we ever imagined we could know previously. What's more, anyone can learn things now that no one knows … but in a few decades will be general knowledge. Building new knowledge of how capital markets work is everyone's job, whether you accept that or not. You're part of it, like it or not. By knowingly embracing it, you can know things others don't—things finance professors don't know yet. You needn't be a finance professor or have any kind of finance background to do it. To know things others don't, you just need to think like a scientist. Think freshly. Be curious. Be open.
As a scientist, you should approach investing not with a rule set but with an open, inquisitive mind. Like any good scientist, you must learn to ask questions. Your questions will help develop hypotheses you can test for efficacy. In the course of your scientific inquiry, if you don't get good answers to your questions, it's better to be passive than make an actionable mistake. But merely asking questions won't, by itself, help you beat the markets. The questions must be the right ones leading to actionable information.
Since 2023 and through this third edition's publication, the big thing in our cultural discourse about the economic future and so‐called information seems to be AI. I'll not waste your time refreshing you on any of that. But, think about it briefly. This book, as it is revised, says little about AI. Why? Because you have to know something others don't. And AI, which is wonderful, doesn't know anything others don't. Wonderful programs exist to which you can ask questions and get answers. And I love that. But whether ChatGPT, Google Assistant, Copilot, Gemini, Character AI, or one I use a lot, Perplexity, they all can do nothing more than tell you what is already known.
That is great! When you're asking questions, you don't want to waste time wondering if everyone already can know the answers. Why? Because if they can, too many already do to give you an edge in the stock market with the answer to that question. I love AI. Maybe someday it will be creative and scientific. But it isn't now, just generative based on aggregating and making coherent what is already known. That is great. But it isn't enough to help you do a better job investing than average. It doesn't change the stock market or capital markets in total. And the only way to beat the market is to base transactions solely on knowing something others don't. Doing that means asking questions that take you there. If you ask the only three questions that still count of AI systems, which is an illuminating thing to do, you get back not much more than gobbledygook. Why? The three questions go beyond what is known and lead you into the unknown. The three questions, unlike AI, take you back to the future. And that is what you need. Hence, this book says almost nothing in any regard about AI.
So, what are the right questions?
The Only Three Questions That Count
First, we need a question helping us where we see wrongly. Then we need one helping us where we don't see at all. Third, we need one helping us sense reality when our eyes and intuition aren't at all the correct tools.
For our first question, we must identify our own wrongness. The question is: What do I believe that is actually false? Note: What you believe is probably believed by most people. In Chapter 1, I'll cover this question in detail. But if you and I think something is true, then most people probably do. If most people do, we can predict how they will act and think, and we can learn to outflank these beliefs at times because the market will discount them and their false truths.
Suppose you believe factor X causes result Y. Most people do, and we can verify most people believe it. Then when you see X happen, you know people will presume Y follows. But suppose you can prove in reality X doesn't cause Y at all. Now you have actionable information. You can position against Y happening while everyone else expects it. You can beat the crowd because you know something others don't. I'll show you how to do this.
Second question: What can I fathom that others find unfathomable? Here we need a process of inquiry allowing us to contemplate things most people assume simply can't be contemplated at all. Or never even considered thinking about! It's what made Edison and Einstein so successful but weird. They could think about how to think about the unthinkable. Think how unthinkable that is. Almost heretical! It's amazingly easier to do than most people assume, and it's a trainable skill. I'll show you how to do that in Chapter 2. Intuitively you know if no one knows what causes a particular result—let's call it result Q—and we can prove factor Z causes Q, then every time we see Z, we can position for Q to follow more often than not. We know something others don't!
Finally, our third question: What the heck is my brain doing to mislead and misguide me now? To blindside me? Another way to ask this is: How can I outthink my brain, which normally doesn't let me think too well about markets? This is the realm of behavioral psychology. One thing you can come to know no one else can is how your individual brain works—what it does well in relation to markets, what it does badly, and how to reprogram yourself not to use your brain in the ways it works worst for markets.
Few investors have spent any material time trying to understand how their own brains work. Most focus on craft, not internal deficiency. (Note: A craftsman wouldn't think about that at all. No need.) You can learn how your brain works against you, giving you something almost unique since your brain is partly like other people's and partly yours uniquely. Chapter 3 covers this topic in very simple lessons.
From there on, the rest of the book is simply about putting the Three Questions to work in various ways. We look at how to use the Three Questions to think about the overall market, different parts of the market, and even individual stocks. We'll apply them to interest rates and currencies. We look at lots of things I've figured out over the years using the Three Questions. We also address areas I haven't figured out because there is still a lot of potential figuring to do. Maybe you're the person who figures these things out in the years ahead. We won't be able to cover everything, everywhere—nor is there a need for that.
I will make a lot of statements of fact you won't have heard before or think sound simply wrong, nuts, and crazy. I've come to those conclusions using the Three Questions, and I'll show you how in each case. You can still disagree with me. That's okay. But if you learn how to use the Three Questions and want to explore any area, including these, you can do it on your own later. Forever! You can use the Three Questions to show me where I was wrong and messed up. I'd be delighted, and you should feel free to write me to show me evidence, using the Three Questions, where I'm wrong.
There are endless opportunities to discover new things in terms of what we don't know. You don't need to know everything. You need to know some things others don't know. The Three Questions can empower you to know things others don't for the rest of your life.
This third edition updates many of the charts, examples, and much of the text for the events transpiring between the second edition in 2011 and early 2025, as I write. I left a few charts alone because they were fine examples of the point I made. I also replaced a few because in the intervening years, I've found a better way to make the same point. I also added commentary and a few new graphs in places. And I added some reflections on my earlier thinking, too.
Also, there's that old saying, “If I had more time, I'd write you a shorter letter.” In updating this third edition, I've pared back in places—but added in others. Maybe in the fourth I'll actually get the time to make this shorter. Then again, maybe I'll have discovered a mystical fourth question that really reveals the easy path to knowing what others don't. You never know.
What amazed me most in reading this was how much the basic framework of the Three Questions hasn't changed. And that's the idea. Over time, you get more knowledge, more data. Something that once worked doesn't anymore. Something that didn't work at all becomes more relevant. The world moves and changes and is dynamic, but the basic process of a disciplined scientific method shouldn't change. That is why these are the Three Questions that still count, even nearly 20 years after the first edition went to print.
Ken Fisher
Dallas, Texas
ACKNOWLEDGMENTS
I've always loved old investment books. But by now, having updated numerous of my own works, I understand people want things refreshed. And I see value in telling readers that not only did this process hold before—it still does now.
Maybe that is even more important today, given how tumultuous the 14 years between the second edition and today were. I won't recount all the events you already know make this time period so different. COVID and the lockdowns alone are historically important. But the investment world has also radically shifted. Trading costs are way down. Market access for individuals is easier than ever. More and more, pundits and regular people alike convince themselves data are the answer to beating markets and investing successfully. They still think like this is a craft. It still isn't.
Ergo, the three questions in this book aren't just those that still count. I would argue they count more now than ever before.
I have many to thank for this book becoming a reality in the first, second, and third editions.
First, I must thank Lara Hoffmans, whose work was unparalleled in drafting the original version nearly two decades ago—and the second edition five years later. Her work built a foundation that made this update worthwhile. Thanks are also due to Jennifer Chou for her assistance with data in the original version.
For this third edition, a hearty thanks to both Elisabeth Dellinger and Todd Bliman. These two collaborated on a difficult project with a tight turnaround to write the updated text that drives much of this new edition … on top of performing their day‐to‐day functions in Fisher Investments' Research Department.
Data updates for this third edition were the handiwork of Fisher Investments Research Specialists Jimmy Morris and Chris Lawrence, as well as Analyst Matt Schott. Their diligence, attention to detail, and ability to change direction swiftly are greatly appreciated.
Fisher Investments' Investment Policy Committee members Aaron Anderson, William Glaser, Michael Hanson, and Jeff Silk join me in making portfolio decisions for my firm's clients. They didn't contribute to the book, but they certainly contribute to my views of the market. CEO Damian Ornani runs the day‐to‐day business of my firm—which couldn't be successful without the combined efforts of those five fine gentlemen.
Many thanks also to my excellent team at John Wiley & Sons, managing editor Stacey Rivera, and the rest of the team: Shridhar Viswanathan, Kim Wimpsett and Sophia Ho. And thank you to Jeff Herman, my excellent agent, who led me to John Wiley & Sons.
Finally, I must thank my wife, Sherrilyn—whose immense patience and love through the years have made our life's work possible.
1QUESTION ONE: WHAT DO YOU BELIEVE THAT IS ACTUALLY FALSE?
If You Knew It Was Wrong, You Wouldn't Believe It
It's safe to assume if you knew something was wrong, you wouldn't believe it in the first place. But in a world where so much of industry‐applied craft has morphed into long‐held mythologies, much of what everyone believes is false. This isn't any different from long ago, when humanity believed the world was flat and bleeding someone with leeches treated what ailed them.
Don't beat yourself up if you fall prey to false mythologies. Pretty much everyone has and does. Accept that, and you can begin gaming everyone else with greater success.
If sorting false mythology from fact were trivial, there wouldn't be so many false truths. While this isn't trivial, it isn't impossible. But it does require being skeptical about all your prior beliefs—something most humans dislike. Most humans hate self‐questioning and prefer spending time convincing themselves (and others) their beliefs are right. Effectively, you can't trust any conclusion you thought you knew.
To think through false mythologies, we must first ask: Why do so many people believe things that are false? And why do false truths persist—passed down the decades as if they were fact? It comes back to the same point: People persist in believing things that are wrong because, individually, people rarely investigate their own beliefs, particularly when what they believe makes sense intuitively—even more so when those around them nod along.
As a society, we are often encouraged to challenge someone else's views, as in, “I know those @&%$#! (insert either Republicans or Democrats as you choose) are full of phony views!” But we aren't trained to challenge ourselves or to question the basic nature of the universe the way an Einstein, Edison, or Newton would. Our instinct is to accept wisdom passed to us by former generations, smarter people, or both. These beliefs don't require investigation because we believe certain truths are beyond our ability to challenge. Often, that's right. I mean, if “they” can't figure it out, how can I?
Medicine is a good example. We are correctly conditioned to go to the doctor, describe symptoms, hear a diagnosis, and accept a prescription. Generally, that is good conditioning because medicine is an example of science and craft operating largely in parallel harmony. Not perfectly, because there are certainly plenty of myths among doctors—but generally because over time science modifies the craft and the craft improves. Because there are so many life examples where our conditioning serves us well, we're blind to the few areas, like capital markets, where it doesn't.
There are myriad beliefs you likely share with other investors. These beliefs have been built into decades of literature and are among the first things people learn when they start investing. They have been accepted by the biggest names around us. Who are you to question and challenge them?
Exactly the right person!
For example, investors categorically believe when the stock market has a high price‐to‐earnings ratio (P/E), it's riskier and has less upside than when it has a low P/E. Think about it casually, and it probably makes sense. A high P/E means a stock price (or even the whole market) is high—way high—compared to earnings. Get too far out on that scale, and it would seem a high P/E means a stock is vastly overpriced … destined to fall. This belief is so widely held by so many people, seems so logical, and has been a basic tenet of investing for so long that proposing it's false will be met with overwhelming rejection, ridicule, and perhaps suggestions you're morally deficient somehow.
Yet I proved statistically more than 25 years ago the P/E, no matter its level, by itself tells you nothing about market risk or return. Statistics aside, delving heavily into theory (as we do later) teaches the P/E shouldn't tell you anything about risk or return anyway. But tell that to people, including the overwhelming bulk of people who have been trained and should know better, and they will think you're crazy—a real wack job.
The cool part comes after we accept the truth that P/Es by themselves tell you nothing about future returns—when people are freaking out, fearfully fretting over the market P/E being too high, we can play off that. Being bullish on the freakout worked time and again through the long 2010s bull market—and right into the postpandemic era. It doesn't always work because something else can knock the market down (we cover how to better see that later), but it will work much more often than not. In the same way, if the market's P/E is low and we can sense people are optimistic because of it, we might play against them also. Now, being a rote contrarian for contrarian's sake is also wrongheaded, as my 2015 book, Beat the Crowd, details. The key is understanding and seeking truth instead of the mythology. This is basic to the scientific approach.
Many false mythologies—like the P/E one—are accepted widely by the best and brightest minds and passed to the investing public through all forms of media. They don't inspire questioning from anyone. We have faith in them, like the pious do religious teachings, and they require no further proof. Holy! Sacred! No one questions these beliefs. No one offers dissenting analysis. If you do, you're a heathen. And because there is no dissenting opinion, society feels no need to see proof of these alleged investing truisms with statistically valid data. Myths live on.
How can so few demand hard evidence to support generally accepted investing wisdom? Why do investment decisions not get the scrutiny that car mechanics do? We should be at least as skeptical, if not more so, of the financial industry's pronouncements. To change the success (or lack thereof) you've had so far with investing, be skeptical. Be a cynic. Be the one to point out the emperor wears no clothes. Look around and assess what you and your fellow investors accept as truth. But the most important person to be skeptical of is yourself.
Long ago as I read or listened to media, I'd note things I believed were false and run off to do independent checking to prove my point. (People love to prove they're right.) I'd gather data and do statistical analysis to prove they were wrong and I was right; and I could prove I was right to my satisfaction pretty often. (It's amazing how often people can prove they're right to their own satisfaction—the plaintiff, judge, jury, and executioner all in one.) But later I saw the error in my ways. I should have sought assertions I believed were true … and checked to see if they weren't really false.
Why?
If I believe the assertion is true, then probably so do many others, if not the overwhelming bulk of investors. Maybe everyone. And if we're all wrong, there's real power. If I can prove I'm wrong and most everyone else is also wrong, then I find useful information. I can bet against everyone knowingly. I’ve got one provable form of knowing something others don't—something efficient markets haven't pre‐priced.
Suppose I believe factor X causes result Y. If I believe it, probably most other folks do, too. But if I'm wrong, most everyone else is wrong. When X happens, people will move to position for Y happening. Suppose I can learn X doesn't cause Y. That means something else is causing Y. That means after X happens, Y happens sometimes, but it's purely random to X's existence. Now when X happens, people will still move to position for Y happening, but I can position for Y not happening, and I'll be right more often than I'm wrong. (If I can figure out what actually causes Y, I can take a big step further, but we don't cover that step until Chapter 2 and Question Two.)
With our P/E notion, we can see one such perfect example. Say the market's P/E goes up—a lot. Normal investors notice and conclude risk has risen and future return is lower and position for the market sagging. Sometimes stocks won't do well, but more often than not stocks will be just peachy because the P/E by itself tells you nothing about market risk and direction.
When I see a high‐P/E market and fear of it, I can position for the market rising. Sometimes, like in 2000 or 2022, it won't work. But more often, like in 1996, 1997, 1998, 1999, 2003, 2009, most of the later 2010s, 2021, 2023, and 2024, it will. I don't expect you to believe the P/E thing right now. Right now, I expect you to believe the traditional mythology about P/Es and not even be very interested in challenging it. (We get to that later in detail.) For now, just accept in your bones if you can learn an accepted mythology is actually false, you can position against it and win more often than lose.
Using Question One
A good way to think about successful investing is it's two‐thirds not making mistakes and one‐third doing something right. Hippocrates is frequently credited with the phrase, “First, do no harm,” and it's a good investment principle.
To first do no harm, think about what you believe and ask yourself whether it's correct and factually accurate. Go crazy. Question everything you think you know. Most people hate doing this, which gives you a real advantage over them. As stated in this chapter's title, this is the first question: What do you believe that is actually false?
Asking Question One helps only if you are honest with yourself. Many people, particularly in investing, are constitutionally incapable of contemplating they're ever wrong. They will tell you they do well and likely hoodwink themselves into believing it—but they don't. And they never subject themselves to reliable independent analysis. Accept this truth: You and the pundits and professionals from whom you glean information can be and probably are wrong about many basic beliefs. Me too!
Have you ever presented such a question to yourself about capital markets? Asking if what you believe is actually wrong requires introspection. As humans, we're hardwired to be overconfident. This is hardly a new development. Behavioralists argue our Stone Age ancestors had to be overconfident to hunt giant beasts each day armed merely with stone‐tipped sticks. If they practiced introspection and came to the rational conclusion that tossing a flint‐tipped branch at a buffalo was utter lunacy, they, their families and their communities would have starved. Overconfidence—the belief you can do something successfully when rationality would argue otherwise—is basic to human success in most fields and necessary to our successful evolution as a species. However, it hurts tremendously when it comes to capital markets. (More on this in Chapter 3.)
Just so, investors are loath to question generally accepted knowledge. If we started doing it, we might soon realize the market exists solely to humiliate us as much as it can for as long as it can for as many dollars as it can. Hence, I refer to the market by its proper name, “The Great Humiliator” (TGH for short). I've come to accept my goal is to interact with TGH without getting humiliated too much.
TGH is an equal‐opportunity humiliator. It doesn't care if you're rich or poor, black or white, tall or short, male or female, amateur or an Olympian. It wants to humiliate everyone—me and you, too. To be frank, I think it wants to humiliate me more than you. You're fun to humiliate, but if you're fun, I'm more fun. I'm (probably) a more public figure than you and therefore a bigger TGH target. Think how much TGH would love to humiliate Warren Buffett! The bigger you are, the more TGH wants you. But in reality, TGH wants to get everyone and does a pretty good job at getting them all eventually. It can't be sated!
How do you, personally, give TGH the most fun? By acting on the same information everyone else has. How do you spoil the fun for TGH? By restricting actions to things you think you actually know that others don't.
Practice using Question One the same way I should have—by scanning the media for assertions you believe. Make a list of them. They can be about single stocks, whole markets, currencies. Anything. Make a list of anything influencing your decisions, whether on single stocks, asset allocation, anything.
Make note of decisions you've made not supported by data or any other information. Underneath there somewhere is something you believe—right or wrong. Be particularly wary of making a decision simply because of something you know others agree with. Highlight, underline, and asterisk decisions prompted by or based on common investor catechism. Ask what evidence you saw supporting these beliefs. Is there any? For most investors, there isn't much.
Common Myths You Believe In, Too
For example, you may hold a stock with a high P/E ratio. You believe a high P/E signals an overvalued stock, so you decide to dump the stock and buy one with a lower P/E. It's a fairly rational decision you may have made countless times before, and one many people would agree is rational.
But are high P/Es bad for single stocks or the market? Have you personally checked the data? If you have asked the question, where did you find the answer? Did you look at the numbers, or did conventional wisdom or some big‐name guru say so?
Take another scenario. You hold a stock that does well in rising markets but badly in falling ones—a typical, highly volatile stock. However, you know the US federal government is running a growing budget deficit—not only a deficit, but a historically high deficit like 2024's whopping $1.83 trillion shortfall … one that “can't go on forever.”1 You know federal budget deficits left unchecked are “bad for the economy” and hence “bad for the stock market.” All that debt caused by the deficit must be paid back by future generations, and the market will reflect that sooner or later, right? The burden of the deficit has long‐term rippling implications, holding down growth and earnings. The deficit has grown to such a size you know a bear market looms eventually. In that environment, your highly volatile stock would do badly. So you sell.
