Doc's Daily Commentary

Mind Of Mav

Understanding Market Fundamentals 

Do market prices reflect all available information? Are investors truly able to outperform the market?

As we endeavor to understand the markets, sometimes it’s best to draw from the work of some very smart people. In this case, here are 5 theories put forth by Nobel prize-winning economists to illustrate market fundamentals:

The decentralized system

Hayek (1945) began his explanation of the use of knowledge in society by asserting that the main problem of a rational economic order is the impossibility of centralizing information of the circumstances since it is dispersed within the market and possessed by different individuals. Therefore, the price system acts as a form of decentralized information system, in which “the knowledge of the relevant facts is dispersed among many people [and] prices can act to coordinate the separate actions of different [individuals]” (Hayek, 1945: 526).

The price system then becomes a mechanism to transmit information through a symbol, which, according to Hayek, includes in itself the most relevant knowledge needed for trading. Fama reformulates this theory with his market efficiency hypothesis by affirming that security prices reflect all available information. Hence, the solution to the impossibility of the centralization of information is given by the price system and by the interaction of different individuals with limited knowledge. Similarly, in financial markets, the price system communicates information about the current value of stocks, which is determined by the constant interaction of traders.

The Efficient Market Hypothesis (EMH)

Following Hayek’s work, in the 1970s financial economists such as Fama and Malkiel (1973) have hypothesized the efficiency of financial markets and the impossibility of outperforming competitors due to the full availability of information, which remains incorporated into security prices. This view may be connected to Coase’s description of economists who “think of the economic system as being coordinated by the price mechanism” (Coase, 1937:387). The market then becomes a perfect mechanism that collects information through exchange and does not allow investors to make a profit.

Since participants in the market share access to the same information, they cannot buy at a lower price or sell at a higher price and, as a consequence, their return on the investment will always be equal to 0. Malkiel, in his book “A Random Walk Down Wall Street”, points out that a blindfolded monkey throwing darts at the Wall Street Journal could select a better portfolio of investments than financial experts and describes the evolution of stock prices as a “random walk” that cannot be predicted. Hence, through the EMH, financial markets may be described as perfect information systems, in which all available information is fully reflected in prices and every opportunity of arbitrage is consequently destroyed by the interaction among participants.

Humans are irrational

On the opposite side of the fence, Shiller criticized the EMH with his study on excess volatility of speculative asset prices. According to the American economist, fluctuations in attitudes significantly influence security prices. Therefore, Shiller brings the analysis of financial markets into a psychological and behavioral perspective of the way in which information is spread among investors. He describes fashion as a key driver of traders’ decision-making process and introduces the concept of the “bandwagon effect” in financial bubbles.

A study on the 2000 Tech Bubble conducted by Griffin, Harris and Topaloglu (2011) confirms that individual investors were influenced by the behavior of institutional investors. The research shows that institutional investors bought technology stocks during the run-up and started to sell in March 2000 (beginning of collapse), while individual investors bought also during the run-up, but especially during the collapse. Findings suggest that institutional investors led the fashion with superior information (in some cases insider trading) on the value of technology stocks, while individual investors irrationally rushed to follow the trend and take advantage of the rise in prices, creating a drastic bandwagon effect that ended into a bubble.

Information is spread through social movements

Stock prices are then highly affected by social movements due to the lack of a solid theory to understand the true value of securities. This behavioral perspective may be compared to Porter’s (1998) clusters or Podolny’s (2001) networks that will be discussed later. Even though Fama and Shiller move in opposite directions on the debate on market efficiency, they both recognize the importance of information in capital markets. While Fama affirms that all available information is incorporated into security prices, Shiller rejects the market efficiency hypothesis by explaining that not all participants are rational and have access to the same degree of information. Rather, Shiller shows how information is spread through fashion and social movements.

Hence, by combining the two theories with Hayek’s work it may be assumed that financial markets act as “partial information systems” since a significant portion of information on the value of securities is constantly spread to participants through the price mechanism, while the remaining share of information remains asymmetric and accounts for the difference in profitability among investors.

The access to information is expensive and unequal

The EMH considers a market where “there are no transaction costs in trading securities [because] all available information is costlessly available to all market participants”(Fama, 1970: 387). However, even though security prices contain all available information, it is not clear how price is translated into information and vice versa. Following Coase’s (1937) idea that market participants always bear a cost for the use of the price mechanism that consists in the discovery of the relevant exchange prices, the EMH finds weak support on the non-existence of transaction costs.

If the transaction cost of trading would be equal to zero and all available information would be incorporated into security prices, then probably stockbrokers would not exist. In fact, as noted by Gale and Kariv (2007) transaction costs may force small traders to entrust their stock to an intermediary.

While Fama does not acknowledge the importance of actors within the financial market, Shiller considers them the force that keeps the wheels of the market turning. He recognizes the social interaction of investors, who constantly look for superior information that may give them an advantage in the exchange of stock. Social groups influence the trading decision process of many individuals and diffuse opinions on the value of security prices.

On what could be defined as a Coesian view, participants of an inefficient market bear transaction costs to the access and collection of exclusive information. As speculators strive to send out misleading information on stock prices as in the case of the 2000 Tech Bubble (Griffin, Harris, Shao and Topaloglu, 2011), other investors make a strong effort to carefully evaluate prices by gathering information on risk through word of mouth, newspapers, colleagues, etc. Hence, Shiller proposes a more realistic view of the definition of transaction costs related to the access of information in financial markets. Indeed, while security prices may reflect a portion of information on their value, the access to the other share of information is not for free.

Some investors are better informed than others

According to Sciubba (2005), since prices do not fully reveal the value of stocks, in financial markets we can observe the presence of informed and uninformed investors. Information is asymmetric and costly to access and informed investors always look for exclusive information in order to receive a better return on the investment and beat uninformed traders. In this case, high-status actors (informed investors) may avoid exchange relations with low-status actors(uninformed investors) and therefore keep the information only within a small circle of trusted partners (Podolny, 2001).

Information then becomes highly asymmetric and concentrated within clusters, whose characteristics are very similar to the ones described by Porter (1998). Lillo, Mantegna, Piilo and Tumminello (2007) have identified the existence of clusters of investors within networks through the analysis of their behavior and investment strategies. In order to prove a strong correlation of these findings to Porter’s research, it would be interesting to examine the location of clusters of investors. The close location of investors within one cluster could signify the possibility of accessing exclusive information or the influence of social groups in very specific places.

Since financial markets act as “information systems,” meaning that a portion of information on the value of securities is incorporated into their prices, the main objective of traders is the collection and analysis of the missing share of information to reduce uncertainty on investments. Therefore, investors engage in the creation of networks to reduce altercentric and also egocentric uncertainty (Podolny, 2011). By reducing altercentric uncertainty they build a status of trustworthy sellers, while by diminishing egocentric uncertainty they make sure to buy stock at a valuable price. These networks become extremely important since they contain relevant information to construct the whole puzzle and outperform the market. As described by Shiller this is one of the reasons why the EMH is being critiqued and evolved into the branch of behavioral finance.


Coase, R.(1937). “The Nature of the Firm”. Economica.4: 386–405

Fama, E. F. (1991) Efficient Capital Markets: II. The Journal of Finance, 46(5): 1575–1617.

Fama, E. F. (1970) Efficient Capital Markets: a Review of Theory and Empirical Work. TheJournal of Finance, 25(2): 383–417.

Gale, D. M., Kariv S. (2007) Financial Networks. The American Economic Review, 97(1):99–103.

Griffin, M. J., Harris J. H., Shu T., and Topaloglu S. (2011) Who Drove and Burst the TechBubble? The Journal of Finance,66(4): 1251–1290.

Hayek, F. A. (1945) The Use of Knowledge in Society.The American Economic Review,35(4):519–530.

Lillo, F., Mantegna R. N., Piilo J., and Tumminello M. (2007) Identification of Clusters of Investors from Their Real Trading Activity in a Financial Market. New Journal of Physics, 14(1).

Malkiel, B. J. (2003) The Efficient Market Hypothesis and its Critics. Journal of Economic Perspective, 17(1): 59–82.

Podolny, J.M. (2001) “Networks as the pipes and prisms of the market”, American Journal of Sociology, 107 (1): 33–60.

Porter, M.E. (1998) Clusters and the new economics of competition. Harvard Business Review, 76(6): 77–90.

Sciubba E. (2005) Asymmetric Information and Survival in Financial Markets. Economic Theory, 25: 353–379.

Shiller, R. J. (1981) The Use of Volatility Measure in Assessing Market Efficiency. The Journal of Finance, 36(2): 291–304.

Shiller, R. J. (1984) Stock Prices and Social Dynamics. Brookings Papers on Economic Activity, 1984(2) (1984): 457–510.

Shiller, R. J. (2003) From Efficient Market Theories to Behavioral Finance. The Journal of Economic Perspectives, 17(1): 83–10.


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CryptoCurreny – Security Tokens (STO) – Decentralized Finance (DeFi)

With this portfolio, we will identify and take advantage of the opportunities within the Three
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The Second Phase of the RSC Community Portfolio V3 was to give us a general idea of the weightings people desire in each of the three pillars and also member’s risk tolerance. The Third Phase of the RSC Community Portfolio V3 has us closing in on a finalized portfolio allocation before we consolidated onto the highest quality projects.

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This portfolio should be much more useful given the ever-changing market dynamics. In short, you rank the projects you believe deserve a spot in the top 10. It should represent a portfolio and rank that you believe will stand the test of time. Once we have a good cross-section, we can study and make an assessment as to where we see value and perhaps where some diamonds in the rough opportunities exist. In a perfect world, we will end up with a Pareto-style distribution that describes the largest value capture in the market.
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