Proceedings of the 3rd European Conference on Intellectual Capital

3.1 The research model
Tatiana Garanina and Yana Pavlova
The model <strong>of</strong> <strong>the</strong> regression analysis which characterizes <strong>the</strong> relationship between <strong>the</strong> market-value
<strong>of</strong> assets and <strong>the</strong> fundamental value <strong>of</strong> tangible and intangible assets is analyzed in this research.
The market-value <strong>of</strong> a company’s assets can be characterized by such subordination:
P = P + P , (5)
M
A
M
E
M
D
where M M M
P , P , P – <strong>the</strong> market-value <strong>of</strong> assets, equity and debt <strong>the</strong>reafter.
A
E
D
Considering that <strong>the</strong> market-value <strong>of</strong> equity is market capitalization (Cap), and <strong>the</strong> market-value <strong>of</strong>
dept (D) is usually assumed as its book value, equation (5) can be rewritten as:
M
PA P
= Cap + D . (6)
The market-value <strong>of</strong> assets for <strong>the</strong> model calculation appointed as average weighted market
capitalization to <strong>the</strong> content <strong>of</strong> bids over a period <strong>of</strong> 2 nd quarter, which follows after <strong>the</strong> accounting
year, plus book value <strong>of</strong> debt to <strong>the</strong> end <strong>of</strong> <strong>the</strong> accounting period.
The tested model is a two-factor one which includes <strong>the</strong> influence <strong>of</strong> fundamental value <strong>of</strong> both
tangible and intangible assets upon <strong>the</strong> market-value <strong>of</strong> assets <strong>of</strong> a company:
M
A = 0 + μ1
× VT
+ μ2
× VI
μ + ε
where μ , μ 1 , μ 2
ε
1
0
1
, (M1)
- coefficients <strong>of</strong> <strong>the</strong> regression equation;
- random error.
The tested hypo<strong>the</strong>sis can be formulated as follows: <strong>the</strong> market value <strong>of</strong> assets <strong>of</strong> a company
depends on fundamental value <strong>of</strong> its tangible and intangible assets.
3.2 Statistical information
We have tested our hypo<strong>the</strong>sis for two samples <strong>of</strong> companies: Russian and UK. This helped us to
compare <strong>the</strong> results <strong>of</strong> evaluation for <strong>the</strong> emerging Russian market and <strong>the</strong> well developed UK
market.
The Russian sample includes companies that trade <strong>the</strong>ir shares within <strong>the</strong> Russian Trading System
(RTS). The final sample we have used includes 43 Russian companies. The companies have been
divided into five aggregated industries: mechanical engineering (incl. aircraft and automotive),
extractive industry (incl. oil holdings and oil-and-gas companies), power engineering,
telecommunications and metallurgy (ferrous and non-ferrous). For <strong>the</strong> research we used nonconsolidated
financial data <strong>of</strong> <strong>the</strong> sampled companies for 2001–2006.
One <strong>of</strong> <strong>the</strong> main problems <strong>of</strong> making this kind <strong>of</strong> research on <strong>the</strong> Russian market is <strong>the</strong> lack <strong>of</strong>
information. That is why only <strong>the</strong> mentioned five industries were chosen in order make <strong>the</strong> samples
comparable. For companies from o<strong>the</strong>r industries in Russia it is not possible to obtain financial
statements for <strong>the</strong> researched period as <strong>the</strong>y are not provided by companies. For both samples, first,
<strong>the</strong> model described above has been tested on <strong>the</strong> whole sample, <strong>the</strong>n separately on each industry.
For <strong>the</strong> second sample, companies which are operating in <strong>the</strong> UK and listed on <strong>the</strong> London Stock
Exchange were chosen to test <strong>the</strong> hypo<strong>the</strong>sis. The same five industries as for <strong>the</strong> Russian sample
were included in <strong>the</strong> sample: mechanical engineering, extractive industry, power engineering,
telecommunications and metallurgy. The sample size is 50 companies for <strong>the</strong> period from 2003 to
2007.
Data was obtained from <strong>the</strong> analytical reports submitted to <strong>the</strong> Lexis Nexis database.
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