Itay Goldstein On Stock Trading Frenzies, Financial Contagion, & Whether Mutual Fund Flows Can Predict Business Cycles
Itay Goldstein is the Joel S. Ehrenkranz Family Professor of Finance at the Wharton School of the University of Pennsylvania and Chair of the Finance Department. He is also Director of the Wharton Initiative on Financial Policy and Regulation and Executive Editor of the Review of Financial Studies.
By Aiden Singh, December x, 2025
Professor Itay Goldstein.
Stock Trading Frenzies & Their Effects On Firm Behavior
Aiden Singh: Could you tell me a bit about what your research has found regarding the conditions under which stock trading frenzies are most likely to arise?
Itay Goldstein: In general, when we think about frenzies, in game theory language we call this strategic complementarities. A strategic complementarity is a situation in which people want to do the same thing as other people. That is what generates a frenzy, because a frenzy is fundamentally a situation in which everyone is rushing to buy a stock at the same time, or sell a stock at the same time.
We know frenzies well from a parallel environment that is not a financial market. If you think about banks, there is a well-known phenomenon called a bank run, where everyone wants to take their money out at the same time. This was actually the first topic I explored in my research, going back to my PhD days, and it is something I continue to explore today.
In a bank run, the situation is fairly well understood. The bank offers liquidity to everyone, but it does not have enough resources on hand to meet everyone’s liquidity needs at the same time. The bank relies on the fact that only some people will withdraw their money at any given point in time. This generates strategic complementarity, because if you believe everyone else is going to go to withdraw money from the bank at the same time, you want to do the same, since the bank will eventually run out of resources.
Financial markets are a little different because they have a price mechanism that usually generates the opposite effect. If everyone sells a stock, the price goes down, which can make it a good time to buy. If everyone buys a stock, the price goes up, which can make it a good time to sell. So the question is what could generate a frenzy, or strategic complementarity, in the context of a financial market.
In my research, I highlight one mechanism that I think is very important. It comes from the fact that whatever people do in financial markets also affects the real value of firms and their actual performance. Think about a firm that depends on its stock price to raise capital. If the price goes down, the firm has a harder time raising capital, and this hurts the firm. If the price goes up, the firm has an easier time raising capital, and this helps the firm.
This generates strategic complementarity and the potential for a trading frenzy. If you think that everyone else is going to buy the stock, you realize that this will help the firm and increase its value, which gives you an incentive to buy as well. In the other direction, if you think everyone is going to sell, the firm will be deprived of capital, which hurts the firm, and selling becomes attractive too.
Traditionally, when people thought about trading frenzies, they mostly focused on the negative side, such as short selling attacks or bear raids, where everyone is selling or short selling at the same time. The logic is exactly the same. If everyone is selling, the price goes down, the firm has difficulty raising capital, and it may even face bankruptcy.
What we saw in 2021 was an episode of frenzied trading in meme stocks, which has returned periodically since then. In this case, everyone is buying the stock. One mechanism that sustains this kind of frenzy is that firms take advantage of it. They raise capital and genuinely benefit from it. As a result, they find themselves in a stronger position afterward, which helps sustain the cycle of the frenzy.
Aiden Singh: And when these stock trading frenzies, the underlying firms can take advantage of the increased stock price to strengthen its financial position.
Itay Goldstein: Right. AMC was one of the first stocks subject to an aggressive trading frenzy. The firm benefited from it by taking advantage of a new stock price that was much higher than before and probably much higher than fundamentals, and issuing new equity at those elevated prices.
At the time, this allowed the firm to avoid bankruptcy. Analysis at the time suggested that AMC was on the verge of bankruptcy, and the fact that it could take advantage of these stock prices and raise capital at those new prices really saved the firm from going into bankruptcy. This is a clear example of how a firm can take advantage of such a situation and improve its position.
GameStop, which is probably still the most famous example of a trading frenzy, did something similar later on. It took advantage of inflated stock prices, raised capital, and was able to at least temporarily improve its situation.
That is essentially what firms can do in these circumstances. In general, CFOs who are closely attuned to the market and who follow market trends are better positioned to take advantage of these opportunities.
Aiden Singh: How do firms change their financial behavior when they anticipate that their exposure to non-fundamental price movements has increased?
Itay Goldstein: So what I was just describing concerns what firms do when a frenzy actually materializes. If you see that speculators are coordinating to buy your shares and the price goes up, then you take advantage of that situation. You issue new shares and gain access to additional capital. That improves the firm’s fundamental position.
We have also done research focusing, not on the realization of a frenzy, but rather on the anticipation that there might be a frenzy. Anticipation is different because you do not really know whether the frenzy will be on the positive side or the negative side.
What we do is classify stocks based on their fragility. Fragility means that there is greater volatility in buying and selling. These are stocks that may experience large positive order flows or large negative order flows, but the key point is that they are volatile, and the direction is uncertain.
You can quantify fragility in several ways. One approach is to look at past order flows and the extent to which they are correlated. You can also examine the ownership structure. If a firm is held by a concentrated base of investors, it will tend to be more volatile. For example, if there is one large investor and that investor experiences a shock, the firm will be affected immediately. Similarly, if a firm is held by multiple institutional investors such as mutual funds that have correlated flows, that will also affect the firm.
Using this information, you can construct a proxy for the degree of fragility a firm faces due to its shareholders. When a firm has this kind of fragility, it can work in its favor by increasing the stock price for non-fundamental reasons, but it can also work against the firm by decreasing the stock price for non-fundamental reasons.
What we find is that firms tend to be more concerned about the downside than the upside. As a result, they become more cautious and more risk averse.
This is similar to the idea of precautionary saving. If you know that you are exposed to volatility, you will take actions to mitigate the effects of the downside. If something positive happens, you can take advantage of it when it happens, and there is no need to prepare in advance. But if something negative happens, it is often too late to respond afterward.
So what we find is that firms that become more fragile due to changes in their ownership structure adjust their corporate behavior. They become more cautious, they hold more cash, invest less, and reduce activities such as research and development.
This ex-ante effect is largely one-sided. When firms know that their ownership structure is more fragile, they behave more cautiously and take precautionary measures to protect themselves against the risk of being left with insufficient cash.
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Information Sharing and Market Outcomes
Aiden Singh: You have also looked into information sharing in the stock market.
There is some nuance here because, on one hand, if you have information that is useful to you as an investor, you might want to keep it to yourself.
On the other hand, we observe a great deal of information sharing, particularly on social media.This type of information sharing contributed in part to the meme stock frenzy.
There are also different types of market participants - hedge funds and individual retail investors may behave differently when it comes to information sharing..
This is something you have conducted research into. How much does communication between investors affect financial market outcomes?
Itay Goldstein: Anecdotally, I would say that communication is very important. The paper you are referring to is a theory-based study in which we developed a model to understand the benefits of information sharing and how it evolves in an asymmetric way. In motivating that paper, we also provided a great deal of discussion based on anecdotal evidence about the extent of information sharing. Coming out of that process, I realized that there is indeed quite a lot of it.
Investors live in a social community. They attend conferences, they meet each other, and they talk to each other. That was the story in the old days. Today, although conferences still matter, much of this interaction takes place online. People go online and participate in forums and social media platforms where they exchange information.
I would say that information sharing is very pervasive. From reading accounts by people who trade in financial markets for a living, it appears that they spend a large share of their time talking to other people and exchanging information. This suggests that communication is a very important factor affecting the dynamics of the stock market and, ultimately, the prices that we observe.
It would be interesting to quantify this more precisely and determine how much of the price movement we see can be attributed to communication. I am not sure that this has been fully done, but based on what we observe, it seems to be a very important phenomenon.
In that paper, what we were trying to do was to dig deeper into the costs and benefits that investors face when they reveal information, and how this helps us understand the direction in which information moves.
In particular, we consider a setting with two speculators, one who is well informed and another who is less well informed. There is a hierarchy in which one has better information than the other. The question is whether information flows from the more informed to the less informed, or in the opposite direction.
What we show, which may be somewhat surprising, is that it is more often the less informed investors who are inclined to share information with the more informed investors, rather than the other way around.
The intuition is the following. When you share information, the obvious cost is that information that was previously exclusive to you is no longer exclusive. You give up an advantage, which works against you, since the goal in financial markets is to profit from superior information.
On the benefit side, which we uncover in the theoretical analysis, sharing information with someone who has different information can lead that person to trade against your position, because they may interpret some of your information as noise. When they trade against you, you benefit because it allows you to earn higher profits on your trades. In trading, you generally want prices to move less in the direction of your own trades. When someone places an order in the opposite direction, that provides liquidity and helps you.
What we show is that for very well-informed investors, the cost of sharing information outweighs the benefit, because giving up their information is very costly. For less-informed investors, the cost of giving up information is lower. At the same time, they can benefit significantly from having someone trade against them, which creates opportunities to profit from whatever information they possess.
The conclusion is that in a setting with different levels of information, information tends to flow from the less informed to the more informed. This suggests that much of the information shared in forums, conferences, and similar settings comes from less informed participants. I think that is an interesting implication of the model.
Aiden Singh: I’d venture that the timing of the information disclosure would also matter.
For example, suppose you’re a large hedge fund and you’ve already built a position in a stock. In that situation, there could be value in encouraging other investors to take the same trade, effectively pushing up the price of an asset that the fund has already bought.
Is there a timing component here regarding when it is optimal for a hedge fund to share the information it has?
Itay Goldstein: Yes, that is absolutely right. What you are describing is that after you have already established a position, you want other people to start trading in the same direction that you did, because that allows you to profit from the information. That introduces a more dynamic setup. You can think about information sharing at different points in time.
In that case, you would indeed like people to trade in your direction. That would be an extension of the analysis in the paper. The analysis in the paper focuses on a static environment, where you have information and you make a profit from it in a single setting.
It is essentially a one shot game. In that framework, you do not want people to trade in the same direction as you. Instead, you benefit when they trade against you.
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Can Mutual Fund Flows Predict the Business Cycle?
Aiden Singh: Let’s turn to your research on mutual fund flows and their ability to predict business cycles. You have looked in particular at flows into high yield bond mutual funds and their relationship to the business cycle. What did you find in that study, and through what transmission mechanisms do the effects you identified occur?
Itay Goldstein: In general, there is evidence that high-yield debt has predictive power for the business cycle. Over time, we observe cycles of credit booms. Credit booms tend to be associated with higher economic activity, but they are often followed by a bust.
A number of researchers have pointed out that much of this pattern can be traced not to credit booms in general, but specifically to high-yield debt. High-yield bonds represent the riskier segment of credit markets. These are bonds that are not investment grade, and are often referred to as junk bonds. When there is high issuance of these types of bonds, it signals that a credit boom is developing, and eventually this cycle tends to reverse.
There has been ongoing debate about what drives this pattern. One question is whether high-yield debt issuance simply reflects strong economic opportunities or whether it is driven by investor behavior, meaning a shift in demand toward riskier assets. In other words, is this dynamic driven by supply or by demand? Is it a pull from firms or a push from investors?
In the paper, what we did was use data on flows across mutual funds, focusing on a very specific type of data. We used information on flows within mutual fund families. The Investment Company Institute publishes data showing how money moves within fund families across different types of funds, such as equity funds, high-yield bond funds, and investment grade bond funds.
This data is useful because changes in investor demand are likely to show up first in internal reallocations within fund families. If there is a shift in investor preferences or beliefs, the first thing investors often do is reallocate money across funds within the same family.
For example, if you have an account with a large fund provider like Vanguard, it is very easy to move money from an equity fund into a bond fund, or from an investment grade bond fund into a high-yield bond fund. So if you wish to identify a shock to investor preferences, risk tolerance, or beliefs, it is likely to appear first in these internal fund flows.
There is a large literature showing that high-yield bond issuance is a leading indicator of credit booms. However, observing issuance alone does not tell you whether the underlying driver is supply or demand. What we show is that movements into and out of high-yield bond funds within mutual fund families are themselves a leading indicator of high-yield bond issuance.
These internal reallocations occur before the increase in issuance, before the broader credit boom, and before the subsequent cycle unfolds. This suggests that an important part of the story is driven by investor demand.
There are many additional questions one could ask, such as why investor demand shifts in this way, whether it reflects changes in risk tolerance, sentiment, or beliefs. We do not take a strong stance on those mechanisms. Our goal is simply to show that investors play a central role: it is not only that firms suddenly need funding and issue more high-yield debt.
A significant part of the cycle appears to start with investors deciding that they want greater exposure to high-yield bond funds, and that shift in demand helps initiate the broader credit cycle.
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Stock Prices and Corporate Takeovers
Aiden Singh: When it comes to corporate takeovers, logic would suggest that if valuations are falling, a firm should be more likely to become a takeover candidate, while if valuations are rising, it should be less likely. However, empirical studies have not always supported this line of reasoning.
Why have empirical studies come to this seemingly paradoxical result? And what has your research into this topic found?
Dr. Itay Goldstein: In general, when you think about takeovers, you are looking at two things. You observe the price of the target firm, and you observe whether a takeover occurs. A reasonable hypothesis is that firms are more likely to be taken over when prices are lower, because it is cheaper for an acquirer to take over the firm. Lower prices may also indicate that there is a problem, and in many cases acquisitions are driven by attempts to fix such problems.
However, if you simply look at the data, this relationship does not appear very clearly. This comes from work we did some time ago. If you run a naive regression with takeovers on one side and prices on the other, you do not find much of a relationship.
The reason is that prices are endogenous. Prices tend to rise in anticipation of a takeover. So there are two opposing forces at work. On the one hand, lower prices make takeovers more attractive. On the other hand, the expectation of a takeover is reflected in prices beforehand and pushes prices up. These forces move in opposite directions, which explains why a simple regression does not reveal much.
What we tried to do in that paper was identify an exogenous source of variation in prices. We used mutual fund outflows to construct such a source. There is a specific methodology for doing this, and the literature has developed substantially over time, with later work refining the proxy. The basic idea is that there can be exogenous outflows from mutual funds that generate price movements unrelated to takeover anticipation.
If you study the effect of this known non-fundamental shock to prices on the likelihood of a takeover, you can break the feedback loop. In this case, anticipation of a takeover does not drive the price change, because the price movement comes from an external shock.
The approach involves a two stage analysis. First, you instrument changes in prices using this exogenous shock. Second, you estimate the effect of the resulting price change on the probability of a takeover. This allows you to quantify how much prices affect takeover likelihood and how much of the observed price movement is driven by anticipation of a takeover.
More broadly, this paper fits into a larger theme in my research. It is closely related to the work on trading frenzies that we discussed earlier. The common theme is the feedback effect from financial markets to the real economy: changes in prices affect what happens inside firms.
In this case, an exogenous shock to a firm’s stock price affects a real outcome, namely whether the firm becomes a takeover target. This is one way to demonstrate that developments in financial markets influence firm behavior.
I think this is one of the most important questions in finance. If financial markets were merely a sideshow and had no effect on the real economy, it would be unclear why we should pay so much attention to them. If financial markets influence real firm outcomes and economic activity though, then they matter a great deal.
This paper is one of several in which we try to identify and quantify these feedback effects. We use empirical strategies to isolate exogenous price movements and examine whether they spill over into real firm outcomes, in this case the probability of being taken over.
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Financial Contagion
Aiden Singh: International financial flows and their effects on how financial crises unfold are areas you have studied extensively. You have examined how portfolio diversification can serve as an international transmission mechanism for financial crises, as well as the relationship between banking systems and currency prices.
How does portfolio diversification act as an international transmission mechanism for financial crises?
Itay Goldstein: I would start by saying that this mechanism does not have to be international. It can be international, but it can also apply to different banks within the same country. The mechanism works in a very similar way in both cases. The question of contagion has been one of the most important issues in the literature on financial crises.
I mentioned bank runs earlier. One of the most important features of bank runs is that they are rarely isolated events. When a bank experiences distress, the effects often spill over to other banks. Similarly, when a crisis occurs in one country, it frequently spreads to other countries.
I began working on issues related to financial crises when I was a PhD student, and I graduated in 2001. At that time, the Southeast Asian crisis was at the center of attention. That episode strongly shaped my interest in the topic, and it provided clear evidence of contagion. The crisis affected several countries in Southeast Asia at the same time, and there were spillovers to Russia and broader instability in other regions of the world. This made the question of contagion especially salient.
There are several mechanisms through which contagion can operate. In the paper you mentioned, we develop a mechanism based on investor behavior and how investors move money across regions, banks, and investment opportunities. The model is fairly general and can be applied to a variety of settings.
The core mechanism works as follows. Consider an investor who is invested in two different countries. If a crisis occurs in one country, the investor experiences losses. After suffering those losses, the investor begins to rebalance the portfolio. The key point is that investors’ risk aversion increases as wealth declines. When the investor loses money in one country, overall wealth falls, which makes the investor more risk averse.
This applies to individual investors as well as institutional investors. When investors become more risk averse, they reassess their exposure to risk elsewhere. If they hold assets in other countries that could also be vulnerable to a crisis, they may decide to withdraw funds from those countries as well.
As a result, losses in one market lead investors to pull money out of other markets, even if those markets are fundamentally independent. This creates a natural channel of spillover. A shock in one place increases risk aversion, which reduces investors willingness to bear risk in other places.
This mechanism has important implications. It generates higher correlations across asset prices, investment vehicles, and countries. Even if two countries are fundamentally unrelated, they may experience similar economic and financial outcomes because investors respond to losses in one country by withdrawing capital from the other.
In this way, portfolio diversification and investor rebalancing can transmit financial crises across banks, markets, and countries, creating contagion even in the absence of direct fundamental linkages.
Aiden Singh: You have also studied the relationship between banking crises and currency crises. Could you explain how these two types of crises are connected, and what this relationship implies for the ability of lenders of last resort to prevent bank runs?
Itay Goldstein: This work was also motivated by the events of that period. If you think about the crises in Southeast Asia in the late 1990s, there is a pattern that is now very well known. Banking systems collapsed at the same time that exchange rate regimes came under pressure. In these countries, financial systems experienced severe stress, and governments were forced to abandon the fixed exchange rate regimes they had in place at the time.
There is a mechanism that generates a vicious cycle between banking crises and currency crises. If investors begin to pull money out of banks, this leads to capital fleeing the country. That reduces the amount of foreign reserves available to the government and makes the country more fragile. As a result, the government becomes more exposed to what is known as a currency attack, where speculators anticipate that the government will be unable to sustain the peg and begin short selling the domestic currency.
So a flight of capital from the banking system weakens the government's ability to maintain a fixed exchange rate and makes a currency attack more likely. The mechanism also works in the opposite direction. When there is pressure on the currency and depreciation becomes more likely, banks run into trouble because many of them hold international liabilities and domestic assets.
When the domestic currency depreciates, the value of domestic assets falls relative to foreign liabilities. This creates a balance sheet mismatch that reduces the net worth of banks and makes bank runs more likely. In this way, a currency attack increases the likelihood of a banking crisis, and a banking crisis increases the likelihood of a currency attack.
This feedback loop can generate a spiral in which both types of crises reinforce each other and become much more likely. The paper studies this mechanism and examines its implications for the amplification of financial crises more broadly.
You also asked about the lender of last resort. This framework highlights limits to the ability of governments to act as lenders of last resort in an international environment. Traditionally, the lender of last resort is viewed as a key tool for preventing or mitigating financial fragility. If depositors begin to run on banks, the government or central bank can provide liquidity. Knowing that support is available, depositors may decide not to run, which stabilizes the system. This is an important line of defense against bank runs.
However, it does not fully account for the international position of the country. Once you consider the interaction between banking crises and currency crises, you see that acting as a lender of last resort can reduce the government capacity to defend the exchange rate.
When the government uses its reserves to support the banking system, it weakens its ability to maintain a fixed exchange rate, making the currency more vulnerable to attack. Because currency weakness feeds back into bank balance sheets through foreign currency liabilities, this indirect effect can make bank runs more likely.
As a result, there is a tradeoff. On one hand, lender of last resort policies directly reduce the likelihood of bank runs by reassuring depositors. On the other hand, by depleting reserves, these policies can increase currency fragility, which in turn can indirectly increase banking fragility.
This complex interaction is central to understanding the relationship between banking crises, currency crises, and the limits of policy intervention in an international setting.
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Editing by Harpreet Chohan.