Introduction
Stock market index figures occasionally suffer extremes of volatility that are sufficient to promote economic recessions. Such bubbles occurred in Japan, at the beginning of the nineties, and in the USA in the year 2000. Both events had drastic effects on the respective economies and provided examples of how difficult it can be to correct such negative situations. At an international central banks symposium in Jackson Hole in 2002, it was made plain that all the available correction measures that were being taken were insufficient to effectively limit the size of bubbles. A quoted prime reason for stock market volatility is attributed to valuation differences: on one side the value of production assets (I) from industry; and on the other side, the stock market value of equity (K) determined by the financial world. In theory, on condition that the debt assets/debt liabilities ratio is close to one, these valuations should coincide. In reality, this rarely happens. This is due to the subjective views of each side as to future values of assets and equity.The object of the following paper is to propose a new stabilization measure aimed at drawing closer these two subjective variables using two means: a new volatility indicator and, as an option, a balancing tool.
Context
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In economic studies, frequent reference is made to the Thermodynamic Theory. Its first law holds that: nothing is gained, nothing is lost, there is only transformation (Lavoisier). In accounting, for example, assets and liabilities must balance out. In macroeconomics, global revenue is related to global production. Pareto optimality means that, in a market economy, one cannot improve the welfare of one individual without reducing the welfare of another. This last concept is close to the concept of equilibrium in an isolated thermodynamic system.
However, a national economy is not a closed entity. It is subject to growth and recession movements.Thus, the Thermodynamics first law is applied to much major economic and financial data. But there is an important exception: growth forecasts. As a consequence, growth forecasts have to bear the consequences of the second law of Thermodynamics, which states that: any system left alone will suffer energy deterioration (entropy).
The consequence of this is that the stock market is no beauty contest, as Keynes has said, and it looks more like a jungle! This is based on the fact that investors have no other objective but to increase the value of their investments. Even though there is a common concern regarding the market liquidity, there is no true investment common purpose, which could regulate the market performance. As a result, there can be bouts of frenetic activity as well as of collective fear.
However, a national economy is not a closed entity. It is subject to growth and recession movements.Thus, the Thermodynamics first law is applied to much major economic and financial data. But there is an important exception: growth forecasts. As a consequence, growth forecasts have to bear the consequences of the second law of Thermodynamics, which states that: any system left alone will suffer energy deterioration (entropy).
The consequence of this is that the stock market is no beauty contest, as Keynes has said, and it looks more like a jungle! This is based on the fact that investors have no other objective but to increase the value of their investments. Even though there is a common concern regarding the market liquidity, there is no true investment common purpose, which could regulate the market performance. As a result, there can be bouts of frenetic activity as well as of collective fear.
In other words, the stock market, as a valuation term and as a whole, has no emergence property.
Growth
Growth
Thus, there is a great need to estimate growth accurately. This needs to take into account a distinction between macroeconomic and microeconomic effects.
At the macroeconomic level, several theories are used to obtain growth estimates, the most common being the GDP growth of a country. Most central banks, as well as the International Monetary Fund (IMF), refer to this method. So GDP is the main parameter used in this study. Should other parameters be considered, these could be easily incorporated into these proposals.
The relationship between the (GDP) growth and the stock market performance is the object of a hypothesis made in many theoretical models. According to this, over the long term, there is no important change in the profit and dividend performance as related to the GDP of a country. In this context, the Gordon growth model (and other models derived from it) links share prices to profits, and, in turn, profits to GDP growth, since, supposedly and over the long term, market performance follows the GDP. In the US, this hypothesis is supported by historic data which show that, since 1929, the percentage of profits after taxation, compared to GDP, generally vary from 2.17 to 8.66%, with an average of 4.83% (5% if one excludes the years 1931 and 1932) (graph 1). The noted variations cover short to medium term. For long term, the percentage is 5 % on average.
Graph 1
At the macroeconomic level, several theories are used to obtain growth estimates, the most common being the GDP growth of a country. Most central banks, as well as the International Monetary Fund (IMF), refer to this method. So GDP is the main parameter used in this study. Should other parameters be considered, these could be easily incorporated into these proposals.
The relationship between the (GDP) growth and the stock market performance is the object of a hypothesis made in many theoretical models. According to this, over the long term, there is no important change in the profit and dividend performance as related to the GDP of a country. In this context, the Gordon growth model (and other models derived from it) links share prices to profits, and, in turn, profits to GDP growth, since, supposedly and over the long term, market performance follows the GDP. In the US, this hypothesis is supported by historic data which show that, since 1929, the percentage of profits after taxation, compared to GDP, generally vary from 2.17 to 8.66%, with an average of 4.83% (5% if one excludes the years 1931 and 1932) (graph 1). The noted variations cover short to medium term. For long term, the percentage is 5 % on average.
Graph 1
Source : US Commerce Department
( For the period 1929 – 1946 = GNP)
The accompanying graph 2 shows that the reality is not at all that is claimed. The Dow Jones Industrial Index (DJI) variations, for example, are anything from 2 to 9% at variance to GDP figures.
The accompanying graph 2 shows that the reality is not at all that is claimed. The Dow Jones Industrial Index (DJI) variations, for example, are anything from 2 to 9% at variance to GDP figures.
Graph 2
Sources : Dow Jones Indexes / Federal Reserve Bank St Louis
Sources : Dow Jones Indexes / Federal Reserve Bank St Louis
In graph 2, the DJI is compared to the US GNP figures. The GNP is chosen as a proxy variable for the GDP, since GNP figures are close to GDP, and have the advantage that they are available for a longer period.
The DJI includes the 30 biggest US corporations, which represent around 24% of the nation’s total market capitalization (Dec. 2005) . The DJI has the peculiarity that it is a price-weighted index. Its sampling is statistically valid, even though it does omit the small/medium capitalizations. Other major indexes offer a bigger range of sampling, but they are market capitalization indexes, which means that they take into consideration not only the price but also the shares trading volume. These indexes are more difficult to associate with GDP, which does not include the volume aspect of the production of a country. It is important to note here that the recommendations within this study do include a much wider range of companies than the DJI does.
The following should be borne in mind:
1) The GDP and the DJI have the same ratio scale, which facilitates comparisons.
2) Over time, the GDP is less volatile than the DJI.
3) During the period 1900 – 1920, the much-overvalued US stock market had to patiently await the picking up of the economy.
The DJI includes the 30 biggest US corporations, which represent around 24% of the nation’s total market capitalization (Dec. 2005) . The DJI has the peculiarity that it is a price-weighted index. Its sampling is statistically valid, even though it does omit the small/medium capitalizations. Other major indexes offer a bigger range of sampling, but they are market capitalization indexes, which means that they take into consideration not only the price but also the shares trading volume. These indexes are more difficult to associate with GDP, which does not include the volume aspect of the production of a country. It is important to note here that the recommendations within this study do include a much wider range of companies than the DJI does.
The following should be borne in mind:
1) The GDP and the DJI have the same ratio scale, which facilitates comparisons.
2) Over time, the GDP is less volatile than the DJI.
3) During the period 1900 – 1920, the much-overvalued US stock market had to patiently await the picking up of the economy.
4) Since the Second World War, the stock market has under-performed the true picture of economic activity during the periods 1941 – 1954, 1969 – 1998 and from 2002 until now, i.e. 70% of the time.
5) The stock market peaking during the nineties was caused by the need for catching up with the improved economic situation.
According to Ellen McGrattan and Edward Prescott (Taxes, Regulations, and Asset Prices. Working Paper, 610. Federal Reserve Bank of Minneapolis), this was mainly due to a more favorable tax environment. They also argued that the stock market was not overvalued in 2000, a claim which is supported by graph 2.
Since the beginning of the 20th century, 15 crashes have been recorded. Three of them (1929, 1969, 2000) were qualified as being speculative (" irrational exuberance") because of the high price/earnings ratio observed then. According to F. Mishkin and E. White ( "What Should the Fed Do About Stock Market Crashes: A Historical Perspective"), bubbles are not always accompanied by financial instability (examples: 1903, 1940, 1946, 1962 and 2000). According to them, other crashes were either:
- highly stressing (1907, 1930/33, 1937, 1973/74);
- stressing (1987, 1929);
- moderately stressing (1917, 1920, 1969/70, 1990).
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"Divergence DJI GNP" is the ratio: (GNP-DJI)/GNP.
One can observe in Graph 3 that "not stressing" crashes (s) tend to cluster around the equilibrium point (0.00%). Out of 15 crashes, the 1903 crash is the only exception to this rule. On the other hand, worse crashes (xl and l) in terms of financial instability, tend to occur at more remote points from the equilibrium.
Graph 2 illustrates the differences between both types of evaluation: the first, which links the value of productive assets to the GDP evolution, and the second, which links the value of equity to the stock market performance. These two approaches need to be reconciled so that the graph curves correspond more and the market index follows more closely the GDP pattern.
What may be rather straightforward from a macroeconomic point of view is by no means as easy at the microeconomic scale. The stock market represents a bundle of transactions affected by corporations undergoing circumstances sometimes very different one from the other. In some instances, there may even be quoted companies that are unaffected by prevailing general economic conditions. Additionally, there are often cases where short-term volatility does not preclude medium or long-term stability.
Most financial models view investors as pollen particles ( Brownian motion) having rational expectations (Efficient Market hypothesis ). While Economic theory is based on "Newtonian" principles, Finance theory is based on Chaos theory. However, financial models did not prevent the numerous crashes which took place since they were first introduced by Bachelier in 1900, despite many improvements which have been made to them since then (derivative products). The reason is that the reference used to calculate volatility is not appropriate, making difficult the distinction between reasonable and excessive volatility. Therefore, when planet Finance moves too far away from its orbit around planet Economy, there can be financial instability.
Hence, we arrive at the question - how do we reconcile the two approaches: macroeconomic and microeconomic?
Our objective is to find an emergence property for the stock market while preserving the stochastic process of its constituents. How? By introducing a measure of volatility of the stock market vis-à-vis the nominal GDP growth as well as an optional balancing tool: a late entry/exit fee.
The volatility indicator is an envelope of four components: the GDP Target Index, a reference index and two deviation coefficients.
In contrast to existing indexes, the GDP Target Index is a GDP weighted index, which utilizes the turnover of domestic corporations as its sole weighting factor. The index would serve as a benchmark for an equilibrium state of the stock market.
Continuing with the US as an example, the percentage of profit after taxation varies as a ratio of GDP from 2 to 9%, with an average of 5% (not considering exceptional or extreme situations as in 1931/32). The GDP Target Index would have to oscillate between 2/5 and 9/5 of the GDP variation for the stock market to be in equilibrium.
(The range of variation would need to be adapted for each country, in order to match the relevant profit levels).
(click on graph for a better view).
The curve ‘Average index’ (5%) is the reference index using 100% (5/5) of the GDP variation. Example: if the GDP grows 3%, the Average index (5%) also grows 3%. The curves “Index 2/5” and “Index 9/5” respectively represent the minimum (2%) and maximum (9%) of deviation authorized around the Average index (5%).
An example: If the GDP grows 4%, the stock market would be in equilibrium when the GDP Target Index grows between 1.6% (2/5 x 4%) and 7.2% (9/5 x 4%).
Advantages of the GDP Target Index:
1) Weighted according to the single factor “revenue” of domestic companies, it can be compared directly with the GDP.
1) Weighted according to the single factor “revenue” of domestic companies, it can be compared directly with the GDP.
2) On the one hand, no reference is made to the profits made by any one company. On the other hand, the greatest number of listed domestic companies is included. Hence, any biases (such as value/growth and small/large caps), usually found in traditional indexes, are avoided.
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Optional balancing tool: late entry/exit fee
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As an option, a late entry/exit fee could be applied, allowing late comers to enter the market at a price reflecting a degree of urgency. The fee could be equal to the average dividend yield rate, for example, and charged to buyers when the market moves above the top of the envelope and to sellers when it moves below the bottom.
Addendum 13th June 2011: this idea was suggested within the context of "all other conditions being me", like the fiscal policy to name but one. In practice, this constraint makes the "optional balancing tool" a ... useless, if not a dangerous, tool ... It is believed that the mere information provided by the index could, if made public, act as a stabilization tool on its own.
Addendum 13th June 2011: this idea was suggested within the context of "all other conditions being me", like the fiscal policy to name but one. In practice, this constraint makes the "optional balancing tool" a ... useless, if not a dangerous, tool ... It is believed that the mere information provided by the index could, if made public, act as a stabilization tool on its own.
Preliminary condition ( if the late entry/exit fee is applied).
The index can help maintain the equilibrium between (I) and (K), ceteris paribus. If the late entry/exit fee is applied, authorities would need to take all appropriate measures, fiscal and others, for the equilibrium to be reached before and maintained after the implementation.
Should this condition not be met, there is a risk of a liquidity crisis.
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Opportunity for industrialized and emerging countries
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In a 2005 speech, B. Bernanke (April 14, 2005. Remarks At the Homer Jones Lecture, St. Louis, Missouri) spoke of the opportunity provided by the high growth rates in emerging countries for pension funds in industrialized countries. The higher volatility of emerging markets hinders such a development. By enhancing market stability, particularly in emerging countries, the present project could improve returns of pension funds which have to support aging populations.
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Accounting difficulty
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Our proposal assumes a timely and accurate collect of GDP data. Progress in this respect has to be made in many countries. (Delays in obtaining definite data are often quoted as a prime difficulty for the implementation of a nominal GDP targeting policy).
The generalization of technological means makes us believe that the information required could be made available in a not too distant future. Until then, and when necessary, a set of proxy data could be used for an early application.
Our proposal assumes a timely and accurate collect of GDP data. Progress in this respect has to be made in many countries. (Delays in obtaining definite data are often quoted as a prime difficulty for the implementation of a nominal GDP targeting policy).
The generalization of technological means makes us believe that the information required could be made available in a not too distant future. Until then, and when necessary, a set of proxy data could be used for an early application.
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How does this proposed solution allow solution of the equation I = K?
Under the premises:
- Interest rates are a function of growth (Taylor rule);
- Interest rates are a function of growth (Taylor rule);
- Economic growth can be measured by the GDP growth (c.f. the IMF);
- According to the neo-classic theory, which invokes the von Neumann Golden Rule, the rate of interest balancing the offer and demand of loans is the same as the rate equilibrating Investment (I) and Savings (which are the source of K) .
In consequence, strengthening the bindings between capital (K) and the GDP can but increase the relationship between (I) and (K) .
Furthermore, a closer link between (I) and (K) would create a closer association between average dividend yield and average equity risk premium.
Conclusion
Conclusion
In the macroeconomic context of a debt assets/debt liabilities ratio close to one, this study describes a method with the aim of maintaining the balance between the two values: value of production assets (I) and stock market value of equity (K). This is achieved by the use of a new volatility measure comprising a new index, a GDP Target Index, based on the evolution of the turnover of domestic companies. In cases where the debt assets/debt liability ratio is substantial, the index would require an adaptation, which is the object of a separate study.
(previous name of the index: Profitip index)
Copyright © 2011 . All rights reserved.
(previous name of the index: Profitip index)
Copyright © 2011 . All rights reserved.
First edition in April 2006.
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