Hypothesis of overflow. Different sectoral reaction to inflation - Investments

Overflow hypothesis. Different industry reaction to inflation

Inflation is a significant factor leading to industry differences. The flow-through constant is one of the known hypotheses, which shows the specifics of sectoral reactions to expected and unexpected inflation. The overflow hypothesis was proposed in the mid-1980s. T. Estepom and N. Hanson and later empirically tested in different markets.

With the increase in inflation in general, investors require a larger nominal yield, which can be provided by rising prices for the assets under consideration. If the company is able to translate all inflationary profit into future growth, then the overflow ratio will be equal to one and the share price will not depend on inflation. In general, the negative impact of high inflation on stock prices will be proportional to the stable level of overflow, the stock prices are positively related to the overflow coefficient ( f ). The overflow model is derived for the traditional Gordon dividend benefit model.

The model of constant growth of dividends per share

where div0 is the dividend per share of the reporting year; g - The constant annual growth rate of the dividend.

For inflation expectations, the formula can be rewritten as follows:

where R - the real rate of return, determined by the demand and supply of money in the market; i - the expected inflation rate; G - the real rate of profit growth; f is the overflow coefficient,

This formula is based on the representation of the nominal required return through the real growth rate and inflation expectations (Fisher formula):

and on the representation of profit growth as a product of real growth in profit and inflation:

Persistent thread The overflow hypothesis is the share of inflation that flows into revenue and profit growth and then into a proportionate growth in dividends. The negative effect of increasing inflation on the share price of the firm will be inversely proportional to the ability to "overflow". Y. Asikoglu and L. Johnson estimated the flow rates for companies in different industries of the American and Canadian markets.

In a number of works conducted on the American stock market, it is shown that the coefficients of overflow vary significantly by industry. Industries with high flow rates demonstrate higher growth in stock prices during periods of inflation (for example, the study of Ya. Asikoglu and M. Erkan in the time interval of high inflation in the USA in 1976-1982 in 55 sectors). In empirical studies, the following formula is used to calculate the overflow coefficient:

where g is the expected sectoral growth rate (in studies often the rate of the past (reporting) period of time appears); G - the real rate of return in the industry (often refers to the index of industrial production in the industry). The industrial production index for the industry reflects the sectoral growth in output and can be an approximation to the real profitability in the industry; i - price indices of manufacturing enterprises.

The maximum flow rates in the 1992 Asikoglu and Erkan studies were obtained for metallurgy (2.64), the lowest in the coal industry (0.19). At the unit level, the overflow coefficient is in light industry (0.96) and utility companies (0.74).

The industry is classified as an activity line with a high "overflow effect" if the coefficient is greater than one. Industries with a high coefficient of flow experience less influence of inflation on cash flows and investors' benefits. The authors outlined the following characteristics of industries and companies that demonstrate a high flow rate: high financial leverage, rapid asset turnover, high profitability of sales, high liquidity of shares, determined by low quotation.

For the United States market, on the segment from the beginning of 2006 to the end of 2009, the quarterly cross section showed the following flow rates across industries (Table 9.3).

Table 9.3

Coefficient of overflow for companies of various industries of the United States market

Sector of Economics

Coefficient

Overflow

Degree of influence

Number of companies in the sample

Power Engineering

0.85

Low

34

Raw materials

0.625

Low

43

Products and Services

0.39

Low

17

Finance

1.46

High

10

Healthcare

2.63

High

4

Industry

0.38

Low

72

Consumer durables

0.34

Low

32

Technologies

0.37

Low

6

Telecommunications

1.4

High

13

Power Utilities

0.55

Low

17

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