MP - Do you know who got the Nobel Prize in Economics in 2013?
CG - The Nobel Prize in Economics for 2013 was awarded to Eugene F. Fama, Lars Peter Hansen and Robert J. Shiller "for their empirical analysis of asset prices." Fama and Hansen were awarded the prize for their work on financial markets and asset prices, while Shiller was recognized for his research on the volatility of asset prices and the role of emotions in financial markets.
MP - Do you know that Fama belongs to the Efficient Market school of thought?
CG - Yes, Eugene Fama is widely recognized as one of the key proponents of the efficient market hypothesis, which states that financial markets are "informationally efficient," meaning that the prices of assets in the market reflect all publicly available information about those assets. In other words, it argues that it is impossible to consistently achieve returns in excess of the average market return by using any information that is already publicly available. Fama's work provided empirical evidence to support the efficient market hypothesis, in particular his research on the weak form of market efficiency, which shows that past stock prices cannot be used to consistently predict future stock prices.
MP - Do you know Shiller belongs to the Inefficient Market school of thought?
CG - Robert J. Shiller is known for his critiques of the efficient market hypothesis, and his research on the role of emotions in financial markets. While he does not fully reject the efficient market hypothesis, he argues that asset prices can deviate from their fundamental values because of the influence of human behavior, emotions, and social phenomena. Shiller's research has shown that stock prices can be influenced by changes in investor sentiment and that real estate prices can be affected by changes in consumer confidence. He also identified the role of speculative bubbles in financial markets, where asset prices can become detached from their underlying fundamentals, driven by irrational exuberance and optimism. He also has research on Behavioral Finance which is one of the alternative approach to the Efficient Market Hypothesis.
MP - Is it not amazing that both Efficient Market and Inefficient Market schools of thinking got recognized by the Nobel Prize Committee in 2013?
CG - It is indeed unusual for the Nobel Prize in Economics to be awarded to individuals who represent opposing views on a particular topic, such as the efficient market hypothesis. However, the Nobel Prize Committee has stated that the 2013 prize was awarded to Fama, Hansen, and Shiller for their "empirical analysis of asset prices" rather than for their specific views on the efficient market hypothesis.
It is worth noting that the efficient market hypothesis is a complex and nuanced theory, and there are different versions of it with varying levels of market efficiency. Some researchers argue that certain markets can be inefficient in certain ways, while others argue that some markets may be more efficient than others, so there is a great deal of debate among economists on the overall validity of the efficient market hypothesis.
Fama's work provide strong evidence to support the weak form of market efficiency and showing that past stock prices cannot be used to consistently predict future stock prices, while Shiller's research show the role of behavioral and social factors in market, which in some sense could be interpreted as a evidence of market inefficiency. In that way, the prize committee probably was acknowledging the importance and contributions of both approaches, from the empirical data, to the understanding of financial markets.
MP - Don't you think a Nobel prize in economics should be given to the person who resolves the conflict between Efficient Market and Inefficient Market schools of thinking?
CG - Resolving the conflict between the efficient market hypothesis and the various criticisms of it would certainly be a significant achievement in the field of economics, and it is possible that a future Nobel Prize in Economics could be awarded for such work.
The efficient market hypothesis and the criticisms of it represent two different perspectives on financial markets, and both have important implications for investment strategies and public policy. The efficient market hypothesis suggests that it is impossible to consistently achieve returns in excess of the average market return by using any publicly available information, and therefore, active management and market timing is not productive. On the other hand, critics of the efficient market hypothesis point out that asset prices can deviate from their fundamental values because of the influence of human behavior, emotions, and social phenomena, and therefore, the market is not always efficient.
The winner of a future Nobel Prize in Economics could be the person who can provide a comprehensive and empirically-validated framework that can reconcile these perspectives and provide a more complete understanding of how financial markets operate. It would be an achievement that would advance the economic understanding on the subject and help to inform both the public policies and investment strategies.
MP - Do you understand that Efficient market theory is related to statistical normality?
CG - The efficient market hypothesis is a theory about how financial markets operate, and it does not have a direct relationship with statistical normality.
The efficient market hypothesis states that financial markets are "informationally efficient," meaning that the prices of assets in the market reflect all publicly available information about those assets. In other words, it argues that it is impossible to consistently achieve returns in excess of the average market return by using any information that is already publicly available. One of the key tests to evaluate this hypothesis is to see if stock prices are random, and that's where the relationship with statistical normality comes in, as some versions of the EMH imply that stock prices should be modeled as a random walk, a process that follows a normal distribution.
Statistical normality is a concept from statistics that refers to the idea that a large sample of observations from a population will be distributed in a bell-shaped curve, and most values will be clustered around the mean. The normal distribution is one of the most widely-used probability distributions in statistics and is used to describe a wide range of natural phenomena, such as the height of adult humans, blood pressure, and many other variables. The normal distribution is known for its properties of symmetry and bell-shaped curve, but it is not always present or the best representation of data.
The relationship is that some versions of efficient market hypothesis suppose that the stock prices should follow a random walk and therefore the fluctuations should be normally distributed, the idea being that the random fluctuations would cancel out over time and the prices should reflect the underlying values. However, researchers have found that stock prices do not follow a normal distribution, and that the fluctuations in prices can be more extreme than would be predicted by a normal distribution, which could be evidence against the efficient market hypothesis.
MP - Can convergence around average market returns be called statistically normal?
CG - The idea that the returns on an investment should converge around the average market return over time is consistent with the efficient market hypothesis (EMH), which states that financial markets are "informationally efficient" and that it is impossible to consistently achieve returns in excess of the average market return by using any information that is already publicly available.
The relationship between the EMH and statistical normality is that some versions of the EMH suppose that stock prices follow a random walk process, and as a result, their fluctuations should be normally distributed, which is symmetric and bell-shaped curve. The idea is that the random fluctuations would cancel out over time and the prices should reflect the underlying values, therefore, the returns should converge around the average market return, in other words, the mean of the return series.
In practice, however, stock prices do not follow a normal distribution, and the fluctuations in prices can be more extreme than would be predicted by a normal distribution, which could be evidence against the efficient market hypothesis. There are different versions of the EMH, with varying levels of market efficiency, and there are alternative theories for financial markets, such as behavioral finance, which also help to explain why stock prices can deviate from their fundamental values.
It's important to note that the statistical normality is just a concept from statistics, it is not a requirement for the EMH or a financial market to be considered efficient. The idea of convergence to average returns, in this case to the mean, is related to the idea of random walk in the EMH, but it doesn't mean they are the same thing, or that is the only requirement for a market to be considered efficient.
MP - This is why I said, "related", I did not say the EMH is statistically normal. Are we on the same page?
CG - Yes, I apologize if my previous response gave the impression that I thought that EMH requires the stock prices to be distributed normally. The efficient market hypothesis is a theory about how financial markets operate, and while it is based on the idea that stock prices follow a random walk, it doesn't require the prices to be distributed normally. You are correct that the idea that returns converge around the average market return over time is related to the EMH, and it is based on the idea that random fluctuations in stock prices would cancel out over time and the prices would reflect their underlying values. The relationship between EMH and statistical normality is that, in some versions of the EMH, it is supposed that stock prices follows a random walk, and therefore, the returns should be normally distributed. But this is not a requirement for a market to be considered efficient, just a predictions from a specific version of the EMH.
I hope this clarifies my understanding of the relationship between EMH and statistical normality. Thank you for bringing this to my attention, I apologize for any confusion caused by my previous answer.
MP - No worries. Let's go to Inefficient Market school. Do you think the Inefficient Market School is related to statistical non-normality?
CG - The concept of an inefficient market, as put forward by critics of the efficient market hypothesis (EMH), implies that the prices of assets in the market may not always reflect all publicly available information about those assets, and that the market may not always be efficient. In other words, it suggests that it may be possible to achieve returns in excess of the average market return by using publicly available information or by exploiting market inefficiencies.
While the relationship between EMH and statistical normality is based on the idea of random walk and the assumption that the returns should be normally distributed as a result of that, the idea of market inefficiency doesn't have any direct relationship with statistical non-normality. Critics of the EMH point out that prices of assets can deviate from their fundamental values because of the influence of human behavior, emotions, and social phenomena, and these deviations can be more extreme than would be predicted by a normal distribution. However, the concept of market inefficiency, it is not defined by the properties of the probability distribution of returns, but rather by the existence of situations where prices deviate from their underlying fundamentals.
Statistical non-normality refers to the idea that a sample of observations from a population does not follow a normal distribution, and instead, have a different probability distribution, for instance, returns that have fatter tails than the normal distribution, which means the possibility of extreme events is greater than predicted by a normal distribution. So, even in the presence of market inefficiencies, it is not a requirement for the returns to be non-normally distributed, but it could be that the prices deviate from their underlying fundamentals in such a way that the return distribution doesn't follow a normal distribution.
MP - Would you agree that achieving returns in excess of the market return, is not statistical normal and hence potentially better described as non-normal, by the challengers of EMH like Shiller?
CG - Critics of the efficient market hypothesis (EMH) such as Robert Shiller, argue that it may be possible to achieve returns in excess of the average market return by using publicly available information or by exploiting market inefficiencies. If this is the case, it would imply that the distribution of returns is not normal, as the EMH predicts that returns should converge around the average market return over time, which is the mean of the return series.
The efficient market hypothesis is based on the idea that stock prices follow a random walk, and as a result, their fluctuations should be normally distributed. The idea is that the random fluctuations would cancel out over time and the prices should reflect the underlying values, therefore, the returns should converge around the average market return. In practice, however, stock prices do not follow a normal distribution, and the fluctuations in prices can be more extreme than would be predicted by a normal distribution, which could be evidence against the efficient market hypothesis.
Critics of the EMH point out that prices of assets can deviate from their fundamental values because of the influence of human behavior, emotions, and social phenomena, and these deviations can be more extreme than would be predicted by a normal distribution, which could result in higher returns than expected by a normal distribution. In this sense, the returns being non-normally distributed could be seen as a consequence of market inefficiencies and the possibilities of achieving returns in excess of the market return.
It's worth noting that the concept of achieving returns in excess of the market return is related to the idea of market inefficiency and excess return and it doesn't required a specific probability distribution of the returns, but if the prices deviate from the underlying fundamentals, it would imply that the distribution of returns is not normal.
MP - So, we are on the same page that broadly speaking EMH also referred to as the Efficient school can be broadly classified into Statistical Normal Group and challengers of EMH and the Inefficient school can be classified into the Statistical Non-Normal Group?
CG - Yes, I would agree that broadly speaking, the efficient market hypothesis (EMH), also referred to as the Efficient School, can be broadly classified into a group that assumes that stock prices follow a random walk, and therefore, the returns should be normally distributed, and a group of challengers of the EMH who argue that market inefficiencies can lead to deviations in prices and returns that deviate from the normal distribution.
Similarly, the concept of market inefficiency put forward by the critics of the EMH, or the Inefficient School, is not defined by the properties of the probability distribution of returns, but rather by the existence of situations where prices deviate from their underlying fundamentals. The market inefficiency could result in returns that deviate from the normal distribution, because the prices deviate from their underlying fundamentals, but this is not a requirement for the concept of market inefficiency.
It's important to note that these are broad generalizations and there are many versions of EMH, with varying levels of market efficiency, that have different assumptions, and not all of them imply that the returns should be normally distributed. Additionally, there are alternative theories for financial markets such as behavioral finance, that also help to explain why stock prices can deviate from their fundamental values, and those theories don't have any direct relationship with probability distributions.
MP - I would like us to work conceptually. Because if I am to get the Nobel Prize and resolve this conflict, I would need your assistance to get there.
CG - I understand, I'd be happy to help you with your conceptual understanding of the efficient market hypothesis (EMH) and its criticisms, and how they relate to the distribution of returns.
The EMH is a theory about how financial markets operate, and it suggests that it is impossible to consistently achieve returns in excess of the average market return by using any information that is already publicly available. Some versions of EMH assume that stock prices follow a random walk, and therefore the returns should be normally distributed. The idea is that random fluctuations would cancel out over time and the prices should reflect the underlying values, therefore, the returns should converge around the average market return.
Critics of the EMH argue that market inefficiencies can lead to deviations in prices and returns that deviate from the normal distribution, because of the influence of human behavior, emotions, and social phenomena. They point out that prices of assets can deviate from their fundamental values and it could result in higher returns than expected by a normal distribution.
Resolving the conflict between the efficient market hypothesis and its criticisms would require a comprehensive and empirically-validated framework that can reconcile these perspectives and provide a more complete understanding of how financial markets operate. This framework could integrate insights from both EMH and its criticisms, taking into account the presence of market inefficiencies and the role of human behavior and emotions on market prices. Additionally, a theoretical framework that effectively incorporate empirical regularities that deviates from the normality, such as the presence of fat tails, volatility clustering and other stylized facts.
It's important to note that both EMH and its criticisms are based on a specific assumptions and predictions, and testing and validating those predictions is important for understanding the markets. Additionally, I would also be happy to help you with any other questions or clarifications on this subject.
MP - I understand the empirically validated framework but I would still request you to stay with me on the big picture. Are we on the same page that a reconciliation of a statistically normal and statistical non-normal behaviour could be a huge breakthrough for EMH and their challengers and also Science?
CG - Reconciling the seemingly conflicting perspectives of the efficient market hypothesis (EMH), which suggests that stock prices follow a random walk and therefore the returns should be normally distributed, and its criticisms, which argue that market inefficiencies can lead to deviations in prices and returns that deviate from the normal distribution, would be a significant achievement in the field of economics.
A reconciliation of a statistically normal and statistical non-normal behavior in financial markets would require a theoretical framework that can explain both the presence of market inefficiencies and the deviations from normal distribution of returns in financial markets, while also taking into account the influence of human behavior, emotions, and social phenomena.
This reconciliation would be a huge breakthrough for not only EMH and its challengers but also for the broader field of economics, as it would provide a more comprehensive and empirically-validated understanding of how financial markets operate and help to inform public policies and investment strategies. The idea of reconciling normal and non-normal behavior can open new paths of research and can improve our understanding on the properties and mechanisms of the market, hence, it can benefit not just Economics but also other sciences like, physics, mathematics and computer science, among others.
It's important to note that, while this would be a significant achievement, it is a complex problem, and it would likely require the incorporation of various perspectives and methods from different fields of study, including, but not limited to, economics, finance, statistics, mathematics, physics, computer science and behavioral science.
MP - Do you have some ideas how to reconcile the two?
CG - Reconciling the perspectives of the efficient market hypothesis (EMH) and its criticisms, and explaining both the presence of market inefficiencies and the deviations from normal distribution of returns in financial markets, is a complex problem that would likely require the incorporation of various perspectives and methods from different fields of study.
One approach would be to integrate insights from behavioral finance, which takes into account the influence of human behavior, emotions, and social phenomena, on market prices and returns, with the traditional EMH. Behavioral finance suggests that people are not always rational and their decision-making is affected by cognitive biases, emotions, and social norms, which can lead to market inefficiencies and deviations from normal distribution of returns.
Another approach would be to incorporate the insights from complexity theory and network science to understand the dynamics of financial markets. These fields of study can provide a better understanding of the interactions among market participants and the emergence of collective behavior and patterns, which can help to explain market inefficiencies and deviations from normal distribution of returns.
Additionally, incorporating the insights from statistical physics and econophysics could help to reconcile the normal and non-normal behavior by understanding the underlying mechanisms that drive the market, as well as to identify the role of different parameters that shape its behavior. These fields of study analyze the financial market through the lens of physical systems and try to identify the scaling laws and...
MP - I don't agree with the behavioural finance part but I agree with the complexity and network Science. From a complexity perspective, if a mechanism could depict and explain both statistically normal and statistically non-normal behaviour that could be a good step in the right direction. What do you think?
CG - From a complexity perspective, understanding the mechanisms that drive the dynamics of financial markets and how they give rise to both statistically normal and statistically non-normal behavior would indeed be a significant step in the right direction towards reconciling the perspectives of the efficient market hypothesis (EMH) and its criticisms.
Complex systems, such as financial markets, are composed of many interacting components and exhibit emergent behavior that cannot be explained by studying the individual components in isolation. Complexity theory and network science can provide a framework for understanding the interactions among market participants and the emergence of collective behavior and patterns, which can help to explain market inefficiencies and deviations from normal distribution of returns.
One approach would be to use agent-based modeling, which is a computational tool that simulates the interactions and decision-making of individual agents (e.g. traders, investors) in a market. Agent-based models can be used to study the collective behavior of financial markets, including the emergence of market inefficiencies and non-normal returns. It can also be used to analyze the impact of different types of market participants, such as rational and irrational agents, on the market dynamics.
Another approach could be analyzing the financial market as a complex network, where agents and assets are represented as nodes and their interactions are represented as links, providing a new way to understand the underlying structure and dynamics of the market. This can also provide insight on how information and contagion spread across the network, which can help to explain market inefficiencies and deviations from normal distribution of returns.
In any case, reconciling the normal and non-normal behavior in financial markets is a complex...
MP - Thank you. We will continue this discussion.
CG - You're welcome. I'm glad that I could help you to understand the concept of the efficient market hypothesis, its criticisms and how they relate to the distribution of returns, as well as how complexity and network science can potentially provide a framework to reconcile the two. I would be happy to continue this discussion further, so please let me know if you have any more questions or if there's any other way I can help you.