Chapter 34: What We Know & Don’t Know About Finance

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Welcome back to the Deep Dive.

Our mission today is to give you a really powerful shortcut to understanding the very foundation of corporate finance.

We're going to dive deep into the absolute essentials,

you know, the settled knowledge, and then right after that, we're turning our attention to the cutting edge mysteries, the things that keep CEOs and, well, finance professors up at night.

We are, yeah.

We're essentially cracking open the final chapter of a major textbook, really.

We're looking at the difference between what's considered foundational, what you can act on, what our source calls the seven most important ideas in finance, and then the really challenging high stakes questions that are still wide open, the ten unsolved problems.

And this is such a crucial distinction for anyone learning this stuff, whether you're, I don't know, prepping for a big strategic decision, or just trying to get your head around the field.

It is.

Finance is not a solved discipline with a fixed set of answers.

It's an incredibly dynamic, evolving field where these core principles, they just keep meeting brand new mysteries.

That's so true.

And if you only master the foundational tools, you can still be completely blindsided by what's happening at frontiers of the unknown.

Understanding the bedrock principles lets you make consistent rational choices that maximize value.

But knowing the unanswered questions, that shows you exactly where the true innovation is, where massive potential value creation or systemic failure is going to happen.

It highlights where the real risk is in the future.

So we're going to give you the essential toolkit you need to make sound financial decisions today.

And then we're going to walk you right up to the frontiers, the place where the next generation of financial insight and strategic advantage is going to be discovered.

Let's do it.

Okay, let's unpack this and start with the foundation.

Yeah.

The seven ideas we absolutely know to be true.

Let's start there.

So the first three concepts are really about assigning value, dealing with time,

and quantifying risk.

Let's begin with the undisputed champion of financial decision making, net present value, or NPV.

This is the decision rule.

It really is.

An NPV is, you know, it's deceptively simple in what it's trying to do.

Is the project worth more than it costs?

That's it.

That's the question.

If the net present value is positive, the project adds value to the firm.

You should do it.

If it's zero or negative, management should just walk away.

But the rigor required to get to that simple decision,

well, it's immense.

And the core of that rigor, it lies in how we figure out the true value of those future cash flows, right?

It's not just guesswork or, you know, speculating about whether the cash flows seem big enough.

No, not at all.

It's an exercise in comparative market pricing.

Okay, break that down.

When we calculate NPV, we are fundamentally asking what the project's future cash flows would be worth if a claim on them were offered separately to investors and traded in the capital markets.

Ah, so you're valuing this unique new thing based on how the market already prices existing similar things.

Precisely.

You're valuing a prospective asset based on how the market price is comparable traded assets.

I remember the textbook analogy for this, which I love, is that investment bankers are basically just secondhand cash flow dealers.

That's a great way to put it.

You're not trying to determine some intrinsic value in a vacuum.

You're comparing it to the price of established assets in a very real, very competitive market.

And that's why the concept of the opportunity cost of capital is so fundamental.

It's everything.

We calculate NPV by discounting those expected future cash flows at this opportunity cost.

In practice, that's defined as the expected rate of return offered by securities that carry the same degree of risk as the project we're looking at.

So if my new factory project has, say, the same risk profile as a portfolio of publicly traded energy stocks,

the opportunity cost of capital for my factory is a return I could have gotten from that energy stock portfolio.

It's the opportunity I'm giving up to invest in my factory.

You've hit the nail on the head.

The intuition is that in well -functioning markets, assets with equivalent risk get priced to offer the same expected return.

So by using that rate, the market required rate, as our discount rate, we are effectively calculating the price at which investors could invest in your project and earn exactly that market required rate.

And if the project delivers more than that, then it's a bargain.

It has a positive NPV.

And this NPV rule has huge implications for how companies are run.

For corporate governance, it solves the problem of having all these diverse shareholders.

Yes, it standardizes the instruction to management.

Imagine you have thousands of individual shareholders.

They have different wealth levels, different time horizons, totally different attitudes toward risk.

You could never satisfy them all individually.

It'd be impossible.

But the NPV rule provides that single simple unifying metric.

Exactly.

It allows this dispersed ownership to work by letting shareholders delegate to management with one crystal clear instruction,

maximize net present value.

Because if you do that, you're making every single shareholder wealthier.

It aligns everyone's interests.

Okay, moving on to idea number two.

We need a way to quantify that risk we just talked about to figure out the opportunity cost.

And this brings us to the capital asset pricing model,

or CAPM.

Right.

And for all its flaws, and believe me, we will get to those later, the enduring power of CAPM is that it offers a manageable, systematic and intuitive way to think about the required return on a risky investment.

Its great attraction is its core logic, which is it's simple and highly likely to survive in whatever future more complex theories come along.

And that core logic forces us to make crucial distinction, the one that separates, I think, financial professionals from amateur investors.

Yeah, the distinction between two kinds of risk.

Yes.

The first type is diversifiable risk, sometimes called specific or unique risk.

This is the risk of things specific to a single company, a factory fire, a new competitor, a strike, things you can get away from.

Exactly.

Because an investor can easily eliminate this risk by holding a well diversified portfolio, just by holding many different stocks, they don't require any extra compensation for bearing it.

So the market doesn't pay you for taking risks you don't have to take.

Precisely.

Which brings us to the second type, non -diversifiable,

or market risk.

This is the risk you can't eliminate because it tracks macroeconomic factors that affect pretty much all assets at the same time.

Like recessions, interest rate shifts,

major geopolitical events.

All of that.

And the brilliant simplicity of CAPM is that it measures this non -diversifiable risk using a single variable, beta.

Beta.

It just tracks the sensitivity of an investment's value to changes in the overall market, right?

Right.

We often use a broad market index as a proxy.

If a stock's beta is 1 .5, it means that for every 1 % move in the market, that stock tends to move 1 .5%.

A beta of 0 .5, it moves less.

So the required return on an asset goes up in a straight line with its beta and only its beta.

Because people only care about the risk they absolutely cannot eliminate.

It simplifies this whole chaotic world of risk down to one measurable, compensable number.

Now, we have to admit, the model has some strong assumptions, and estimating a reliable beta for a new, unlisted project can be really challenging.

But the foundational concept, that distinction between diversifiable and non -diversifiable risk, that is what makes CAPM an indispensable core idea.

Okay, so the third foundational principle.

This one deals with aggregation and is, well, it's sometimes the quietest but most important idea we have.

Value additivity and the law of the conservation of value.

Stated simply, it's that the value of the whole must equal the sum of the values of the part.

Which seems like just basic arithmetic.

It does, but it's the principle that lets us even use the NPV formula in the first place.

When we appraise a project, we assume that the present value of the entire project is just the sum of the present values of cash flow one plus cash flow two and so on.

We break the project down into these time slices, discount each slice, and then just assume they all add up neatly.

And the formula for that PV project plus PVC2 plus dots PVC2 only works because we believe in this law.

And the practical implications for corporate strategy are huge.

Enormous.

Take mergers and acquisitions.

The law of conservation of value states you cannot increase the total value of a firm just by combining two companies solely for diversification benefits.

So if company A and company B merge, their combined value should just be VA plus VB.

Right.

And if the market values the new combined company at more than that sum, that difference is what we call synergy.

And that synergy has to come from something real.

It has to come from an increase in the total combined cash flow.

Maybe cost savings, better marketing, shared tech.

If the merger only offers diversification like smoothing out earnings, the total value of the firm doesn't increase.

Because shareholders could get that same benefit much more cheaply just by buying shares in both companies individually.

Exactly.

The law protects us from believing in financial alchemy.

Okay.

So with those foundational valuation tools in place, let's shift to how markets operate and how managers should think about their companies.

Idea number four,

the efficient capital markets hypothesis or ECM.

This is a highly competitive view of the world.

The hypothesis states that security prices accurately reflect available information and respond rapidly to new information as soon as it's available.

In short,

competition among smart, motivated investors is relentless and brutal.

There's no such thing as an easily exploitable bargain.

No free lunch.

No free lunch.

And to structure this idea, researchers break efficiency down into three forms based on what kind of information is in the price.

The first is the weak form.

Right.

That posits that prices reflect all information contained in past prices.

This is where the famous random walk theory comes from.

You can't earn superior returns by looking at historical stock charts because all that past data is already baked into today's price.

Then you have the semi -strong form, which is much stricter.

Much stricter.

It says prices reflect all publicly available information.

If a company releases an earnings report or a big geopolitical event happens, the price adjusts almost instantaneously.

If you read it in the Wall Street Journal, it's already too late to profit from it.

It's too late.

And the final most stringent form is the strong form.

This holds that prices reflect all acquirable information, even private and insider information.

Which of course can't be true in the real world.

No, the very existence of insider trading laws and the fact that people go to jail for it proves the strong form is functionally impossible.

So what's the empirical reality of the weak and semi -strong forms?

It's pretty fascinating.

It is.

Since large scale testing began back in the 70s, researchers have found dozens of statistically significant anomalies.

Places where prices seem to move in ways that are inconsistent with pure efficiency.

But, and this is the crucial caveat for you listening.

Yes.

Statistical significance rarely translates into easy money for real investors.

Anomalies might exist, but they're often too small, too fleeting, or require too much in transaction costs to actually exploit.

Superior returns are elusive.

Extremely elusive.

We see it in the mutual fund industry.

A few managers might generate small superior returns for a few years, but it rarely lasts.

The widespread agreement among experts is still that beating the market consistently over the long term is incredibly difficult.

Okay.

Idea number five.

This tackles the question of corporate funding.

Capital structure theory, which is really defined by the famous 1958 work of Modigliani and Miller or M.

This theory is really just a logical extension of value additivity.

If the value of the firm's cash flows adds up, then M .M.

argued that changing how you divide those cash flows between your equity holders and your debt holders, it shouldn't affect the total value of the firm.

And this gave us M .M.

proposition one.

Right.

In a perfect world, a world with no taxes, no transaction costs, no financial distress changes in capital structure do not affect overall firm value.

The total cash flow generated by the firm's assets is the same no matter who you pay it to.

Exactly.

It's the famous analogy.

The value of the whole pie does not depend on how it is sliced.

Now, critics often say, well, that's just an impractical fantasy.

Right.

But they miss the genius of it.

By showing what happens in a perfect world, the proposition tells us exactly where to look for the reasons why capital structure does matter in the real world.

You look for the market imperfections they assumed away.

Precisely.

And those imperfections are what drive the modern debate.

The most obvious one is taxes.

Sure.

Interest payments on debt are tax deductible.

So debt provides a corporate interest tax shield, which is a clear financial benefit that adds value.

But that benefit is immediately balanced by the cost of having high debt.

Right.

The potential for costly financial distress, that includes bankruptcy costs, but also the indirect costs, distracting management, losing good employees, upsetting customers.

So the goal of capital structure decisions then becomes finding that optimal balance between the tax benefits of debt and the costs of potential financial distress.

Exactly.

And there's also a governance angle M .M.

didn't cover.

High debt can spur managers to work harder, run a tighter ship because they have less of a cushion.

M .M.'s insight the entire debate.

Okay.

The sixth core idea.

This is essential for modern risk management and strategy.

Option theory.

In finance, an option refers specifically to the opportunity to trade in the future on terms like price and date that are fixed today.

And this concept is so powerful because smart managers recognize the value of flexibility.

It's often worth paying something today for the right, but not the obligation to do something tomorrow.

That flexibility is a valuable asset in itself.

And the revolution here was the Black -Scholes formula.

Before this, experts knew the variables that mattered.

Exercise price, date, risk of the underlying asset, interest rates, but they didn't know how to quantify them precisely.

Black and Scholes gave them the usable quantifiable formula that allowed options to be priced consistently.

Now that formula was for simple call and put options on exchanges.

It doesn't apply directly to the complicated real options we see in corporate finance.

Like the option to expand a factory if demand is high or abandon a project if it fails.

Exactly.

However, and this is the key takeaway, the core underlying ideas still apply.

Even when you're valuing these complicated real options,

fundamental concepts like the risk -neutral valuation method still work.

Let's clarify that one because it's pretty technical.

What does risk -neutral valuation mean in practice?

It's one of the most elegant breakthroughs in finance.

In simple terms, it means we can pretend that all investors are indifferent to risk, that they require no risk premium, and the math of the Black -Scholes model still works.

How is that possible?

We know investors aren't indifferent to risk.

Because the relative price of the option to the underlying asset is independent of risk preferences.

If there was a difference between the price in a risk -neutral world and the real world, an arbitrage opportunity would open up.

And the market would close it.

Instantly.

So while valuing complex real options might take more number crunching, it requires no extra concepts beyond that Black -Scholes framework.

The foundational idea is the same.

And finally, we get to our seventh core idea, the one that deals with the human element, agency theory and conflicts of interest.

The modern corporation is a massive team effort, right?

You've got managers, employees, shareholders, bondholders,

all with overlapping but sometimes conflicting interests.

And agency theory is all about those conflicts.

Right.

And the mechanisms firms use to deal with them.

The most famous conflict is the manager -shareholder conflict.

The principals and the agents.

Exactly.

The shareholders, the principals, want managers to maximize firm value.

But in big corporations with dispersed ownership,

no single shareholder has enough power or incentive to really monitor the management team effectively.

Which leads to classic agency costs, managers slacking off, taking perks, corporate jets, lavish offices, what we call private benefits of control, or pursuing huge risky projects that boost their personal reputation, even if they have a negative NPV for the firm.

So how does finance try to solve this?

Well, the solutions are all about aligning incentives.

First, you tie management compensation directly to long -term stock performance.

Second, the ultimate external check is the threat of a takeover target and those managers get turfed out.

And the conflict doesn't stop there.

There are also issues between shareholders and bondholders.

Yes, a classic one.

Especially when a firm is in financial distress.

Shareholders, who control the decisions, might take actions that benefit themselves at the expense of the debt holders.

Like taking on a super risky bet the farm project.

Exactly.

If it succeeds, shareholders get all the upside.

If it fails, the bondholders bear the loss.

And these issues are anticipated and mitigated through contracts.

Absolutely.

Loan agreements have protective covenants, provisions designed to minimize those conflicts before they blow up.

So these seven ideas, NPV, CAPM, efficient markets, value additivity, MM capital structure, option theory, and agency theory, that's the essential toolkit.

Okay, so that's the playbook.

That is the reliable compass for daily financial decisions.

But here's where it gets really interesting.

The edges of the map.

If the last section was the foundation, this is the blueprint for the next 30 years of research.

We are moving from the established rules to the highest stakes gaps in our knowledge.

These are the 10 unsolved problems.

They're ripe for research and they have immense implications for strategy and global economic stability.

Problem number one takes us right back to the start.

What determines project risk and present value?

We know how to calculate a positive NPV once we have the numbers.

But the question that truly separates great management from the rest is, how do we find a positive NPV project in the first place?

If competition is so tough, like the efficient market hypothesis says, how do we consistently find opportunities that generate value?

Right.

When a project has a positive NPV, the firm is earning what we call economic rents returns above and beyond the cost of capital.

Are these just windfalls or can you plan for them?

What's the source?

Exactly.

Is it superior technology, a protected regulatory position, an unbeatable brand,

unique operational efficiency, and critically, how long will they last before competition inevitably erodes them?

We have clues, but no general theory.

And tied to finding the NPV is assessing the risk.

We need a project beta, but getting that for a real asset, not a traded stock, is just incredibly difficult.

We lack a general repeatable procedure for it.

We have clues, sure differences in operating leverage, how cash flows respond to the national economy.

But ultimately, assessing project risk remains, as the source text admits, largely a seat of the pants matter.

Which introduces a huge amount of subjective judgment into the core decision rule.

A huge amount.

Okay.

Problem number two goes right to the heart of CAPM.

Risk and return.

What have we missed?

Yeah, despite the conceptual power of beta, the statistical problems just won't go away.

Empirical tests consistently show that average returns from low beta stocks seem too high, and from high beta stocks, too low compared to what CAPM predicts.

Which could be a testing issue, I suppose.

It could be.

Maybe beta changes over time in ways we don't capture.

But the anomaly is stubbornly present.

And this leads us to the famous anomalies discovered by Fama and French.

They show that expected returns seem to relate not just to beta, but also to two other factors.

Firm size and the ratio of book value to market value.

And the mystery there is profound.

If CAPM is right, beta should be the only thing that matters.

Why should smaller firms, or so -called value stocks with high book to market ratios, systematically earn higher returns?

The prevailing thought is that they must be proxies for some missing risk, right?

The elusive variable X.

That's the hope.

Maybe small high book to market firms are more vulnerable during downturns, so these metrics are just capturing a severe form of business cycle risk.

But until we find that economic explanation, the model, while useful, is incomplete.

And beyond the stats, there are theoretical gaps in CAPM around investor preferences.

The hedging motive.

Right.

CAPM assumes investors only care about their investment portfolio returns and that they all hold the same diversified portfolio.

But that ignores what people actually consume in the real world.

Give us the classic example of the fine wine collector.

It's a great one.

A rational investor who loves fine wine might buy shares in a famous Chateau.

If wine prices rise, their cost of living goes up.

But their Chateau stock, which is highly correlated with wine prices, also goes up, hedging their consumption needs.

Which is totally rational, but it leaves them with a highly undiversified portfolio.

Exactly.

So if people have different consumption needs, they will rationally hold different undiversified portfolios, and the simple beta model breaks down.

So we need a replacement for beta, but we haven't found one yet.

Not one that has a consensus.

Merton extended CAPM to account for this, but it's incredibly hard to test because you can't see who is hedging against what.

Okay.

Problem three asks,

how important are the exceptions to the efficient market theory?

How deep are the cracks in that foundation?

Well, first we have to filter out the

some correlations like daily returns being higher around a new moon.

That's likely just a chance relationship.

We're looking for systematic, persistent errors.

And we find them in both investor underreaction and overreaction.

Right.

The persistence of momentum, the fact that past winners tend to keep winning for a while, suggest that investors initially underreact to new information.

The market is slow to learn.

And conversely, behavioral psychology tells us humans are liable to overreact.

Because we overemphasize recent events when predicting the future.

This implies investors driven by emotion might drive prices too far too fast, creating bubbles.

Which brings us to the most dramatic exceptions,

speculative bubbles.

These are price movements that just defy rational valuation.

Think about the dot com era.

The NASDAQ soared 580 % from 95 to 2000, then just plummeted almost 80%.

Or the Japanese real estate market in the late 80s, where properties in Tokyo were selling for a million dollars a square foot.

And then collapsed 70 % over the next 17 years.

A price change of that magnitude is just.

It's hard to reconcile with the idea that prices accurately reflect all available information.

And this introduces a critical agency problem inside the bubble itself.

Yes.

Why don't professional investors bail out of these overpriced stocks?

Why do they keep driving the price up when they know it's inflated?

And the answer is their incentives.

It's all about their incentives.

Their pay is usually linked to short -term performance relative to their peers.

If you get out too early and the bubble keeps growing, you look like a fool, you underperform the market, and you risk losing your job.

Which brings us to that famous or infamous remark by the CEO of Citigroup before the 2007 crisis.

A perfect encapsulation.

He said, as long as the music is playing, you've got to get up and dance.

It's the herd mentality and the short -term incentive trap in one sentence.

If you're the one manager who stops dancing, you might save your firm massive losses later, but you'll probably lose your job right now.

So how do you restructure performance metrics to reward the manager who has the foresight to stop dancing?

That remains an urgent unsolved problem.

Okay.

Shifting focus to organizational structure.

Problem four poses a very uncomfortable question for managers.

Is management an off -balance sheet liability?

This one directly challenges the law of conservation of value.

We see these clear repeated examples where the value of the whole seems to be less than some of the parts.

The classic example being closed -end funds.

Right.

These are firms whose only asset is a portfolio of common stocks.

Logically, the firm's stock price should equal the value of that portfolio, but they often sell for a substantial discount to the value of their holdings.

And it wasn't just funds.

We saw it with real estate stocks and famously with big oil companies in the late 70s and early 80s.

Right.

They were trading for substantially less than the market value of their known oil reserves.

It led to the joke that you could buy oil cheaper on Wall Street than in West Texas.

So if the value of the whole is less than the sum of the parts, there must be a negative value attached to the whole itself, the management structure.

That's the uncomfortable conclusion.

The explanation is that investors may believe the firm's management will destroy future value.

That they'll fritter away the profits.

Exactly.

They expect profits will be wasted on bureaucracy or on new projects that generally negative NPVs.

In that scenario, the present value of growth opportunities, PVGO, is actually negative.

Investors are actively discounting the stock because they believe management will waste cash rather than return it.

Right.

So we desperately need to better understand that relationship where managers provide their human capital and investors provide financial capital, especially when the clearly fail.

Problem five addresses the rapid pace of financial engineering.

How can we explain the success of new securities in new markets?

The complexity and sheer volume of financial innovation over the last few decades is just staggering.

Zero coupon bonds, options on futures, catastrophe bonds.

The list goes on.

Some of these innovations are easy to explain.

They hedge a new risk or they respond to a change in tax law.

Sure.

But many successful innovations, especially the complex new securities invented by investment bankers, they seem to outstrip our ability to value them accurately with the existing theory.

And yet they successfully find buyers.

Why?

We don't fully understand why some succeed and others just flop.

Is it just driven by investment banker fees or do they fulfill some genuine latent demand in the market?

And this was tragically highlighted during the crisis of 2007, 2009.

Absolutely.

That crisis revealed the immense complexity, the lack of transparency and the often overrated nature of securities backed by subprime mortgages.

The CDOs.

Right.

Subprime loans themselves aren't intrinsically bad, but the structured products built on them kind of catastrophic losses when house prices fell.

So the question now is forward looking.

What comes back?

Exactly.

Which of these crisis era securities will remain in the dustbin and which will be dusted off and gained their usefulness once confidence returns?

We need a theory of financial innovation to predict that.

Okay.

Problem six brings us back to a controversy we left unsettled earlier.

How can we resolve the payout controversy?

The controversy is simple and persistent.

Are dividends good?

Are tax advantage stock repurchases better?

Or is the whole payout decision irrelevant?

We still lack a solid consensus.

Perhaps the solution is to reframe the question.

Instead of asking if dividends are inherently good or bad, maybe the better question is when does it make sense for a firm to pay high or low dividends?

That shifts the focus to context and corporate characteristics.

For instance, a mature firm with few good investment opportunities, it might benefit from the financial discipline of a high dividend payout.

It forces managers to return cash to shareholders instead of wasting it.

Right.

Whereas younger high growth firms might find the tax advantage of a stock repurchase more appealing since they're generally taxed more favorably for shareholders.

And we need to understand the traumatic shift we've seen where more and more firms pay no dividends while stock repurchases have just ballooned.

That's right.

We need a better understanding of how these shifting payout policies are impacting overall firm value and manager behavior.

Problem seven relates to strategy and integrating all these tools.

What risks should a firm take?

The goal here is not just risk reduction.

It's strategic risk taking aimed at adding value.

And managers use a pretty sophisticated toolkit for this.

They build in operational options.

They reduce borrowing.

They use insurance.

They use derivatives.

All of these things reduce individual risks, but we lack general guidance on what strategic bets a firm should place.

What is the appropriate overall level of risk for the company?

We're

complicated ways.

Very.

A company that's fully hedged against commodity prices might find it can afford to take on a lot more debt.

The reduced operating risk means the benefits of the tax shield now outweigh the lower risk of financial distress.

So how does a company synthesize all of these things?

Operational flexibility, financing, hedging into one sensible value adding hole.

That's the problem.

A robust general framework for that remains elusive.

Our final section deals with the vulnerability of the financial system itself, starting with problem eight.

What is the value of liquidity?

This is the liquidity paradox every manager faces.

Cash gives you maximum liquidity, lets you react quickly,

but it pays little or no interest.

It's wrong to assume cash always has a negative NPV because you're ignoring the liquidity benefit.

But it's equally foolish to assume it has a zero NPV because the marginal value of cash drops as you hold more of it.

So we don't really understand how to value this liquidity service of cash.

How much is enough?

Is a hundred million dollars in marketable securities better or worse than a hundred million dollar unused line of credit?

Right now, managers just finesse this by aiming for an adequate reserve, which is pretty vague.

And this is also critical for private equity.

Hugely.

How much extra return the liquidity discount you need to compensate for the fact that the stock you're buying can't be easily traded.

It's often just one or two percentage points, but that small adjustment makes a massive difference to the valuation.

And the 2007 -2009 crisis showed that investors value liquidity much more highly at some times than at others.

Markets just dried up.

They did.

We lack a deep understanding of why financial markets suddenly shut down or clog up.

And we can offer surprisingly little concrete advice on how to prepare for it.

Okay.

Problem nine addresses the herd behavior causes these big market swings.

How can we explain merger waves?

We can find plausible reasons for any single merger case by case, but that doesn't explain why intense merger activity happens in specific concentrated periods like 98 to 2000 and 2006, 2007, and then suddenly goes out of fashion.

We see other financial fashions too, like hot new issue periods where there's just insatiable demand for speculative stocks.

Why do hard -headed business people sometimes behave like a flock of sheep?

Well, economists point to the concept of informational cascades.

Let's revisit the restaurant analogy.

Imagine you arrive at a street corner with two empty restaurants, the Hungry Horse and the Golden Trough.

George arrives first and indifferent, he flips a coin and picks the Hungry Horse.

Georgina arrives next.

She might slightly prefer the Golden Trough, but she sees George and the Hungry Horse and thinks, well, maybe he knows something I don't.

So she copies his choice.

Then Fred arrives.

He sees two people in the Hungry Horse, zero in the Golden Trough.

His own private information might strongly favor the other place, but the public information, two people are already there, is now overwhelming.

So he rationally goes with the flow.

And it just keeps going.

Each individual person behaves rationally, but the popularity of the restaurant was all down to George's initial coin toss.

And the analogy holds because in finance, that initial coin toss could be a trivial success by one early mover, which then triggers a cascade of other rational investors' following suit, leading to a bubble or a merger wave.

We still need to figure out how much this really explains financial fashion.

And finally, problem ten, perhaps the most critical unsolved mystery of modern finance.

Why are financial systems so prone to crisis?

The crisis that started in 2007 was a potent, very unwelcome reminder of just how fragile financial systems are.

One moment, everything seems stable.

The next, markets crash, banks fail, and a recession follows.

And the research by Carmen Reinhart and Kenneth Rogoff documented the devastating global effects.

They found that these systemic crises are typically preceded by clear warning signs, rapid credit booms, and massive asset

And when the bubbles burst, the consequences are stark.

On average, housing prices drop 35%, stock prices fall 55%, economic output falls 9 % over two years, and unemployment rises 7 % over four years.

And government debt just about doubles.

It does, as governments step in to bail out the system.

The crisis even shifted in 2010 to become a dangerous sovereign debt crisis in Europe.

Greece ultimately defaulted on its government debt in 2012.

So our understanding of what causes, prevents, and manages these massive cascading crises is still alarmingly limited.

It is.

Solving this requires integrating good governance, well -constructed compensation, and efficient risk management, especially where politics and economics collide.

This will occupy economists and regulators for generations to come.

This has been an incredibly thorough overview of the entire discipline.

We've moved from the of NPV to the existential mystery of why financial markets just periodically shut down.

We've covered the fundamental concepts, the seven ideas that form the essential toolkit for every rational manager, and we've highlighted the ten unsolved problems, which really represent the current frontiers of research and the highest stakes challenges for global finance.

And the journey through the knowns provides that reliable compass.

It allows you to consistently apply logic to daily decisions and maximize net present value.

But the real limitation here is to look closely at the unknowns, the mysteries of liquidity, the behavioral economics of bubbles, and the systemic fragility of our global system.

As the source material concludes, we sympathize with Huckleberry Finn on finishing a complex body of work, but we invite you to go on and study further what we already know about finance.

And perhaps more excitingly, to start constructing your own list of fascinating challenges and thinking about how you might contribute to solving these unknowns.

Thank you for joining us for this deep dive into the knowns and unknowns of corporate finance.

We hope this has given you a clear structure for applying what is settled and critically evaluating what is still evolving on the cutting -outch.