Download Study on Industry Risk Assessment of Decision-making Model

Study on Industry Risk Assessment of Decision-making Model
MAO Yuzhong, YANG Guangming
Zhejiang University of Science and Technology, School of Economics and Management, Hangzhou,
P.R.China, 310023
[email protected]
Abstract: Industry faces a lot of uncertainty in decision-making factors, developing a number of risks.
How to defuse the risks is macro decision-making of important issues. In this paper, we establish a
model, and explore mechanisms for industry risk assessment, comparing the risk of differences between
industries, with a view to the application of decision-making in the industry. A new variable expected
opportunity losses is proposed, it is perfect complement scientific decision-making and of great
significance in today's changing economic environment. This paper wishes to engage in venture capital
research scholars, government management and venture capitalists help, and to some extent, the
promotion of China's venture capital industry.
Keywords: Industry Risk, Decision, Model
1. Introduction
Risk is a probability of adverse effects and severity of the measure, it is a concept. Many of these risks
find it difficult to comprehensive, and to quantify the risk makes an outsider confused, the same has
challenged the professionals. Vigorous development in the industrialization of today's world,
commercialization risks is becoming a first-class implementation of the industrialization of important
issues. Such as high-tech industry, eco-agriculture industries, such issues are particularly prominent.
According to the European implementation of the project survey of 97, which are derived from the risk
of failure, of which 80% of the market risk, 20% for the technical risks.
From 1959 to 1971, the British government's encouragement, there have been more than 90 factories
moved from London to Thetford Hill and Harvard cities of our manufacturing industry. Though the East
Anglia District has increased the number of workers in some industries, and has achieved a certain
degree of direct benefit. But because these are not the first into the enterprise itself, they are consumed
in the production of raw materials and semi-finished products, intermediate products and 90% had to
rely on long-term supply of London, the products are mostly for areas inside and outside the direct
consumption. These enterprises to create the multiplier effect of most of the leak to London, and thus
they can not drive regional economic development and has played little role. In 1960’s,the major export
countries of the Netherlands found that a large number of natural gas, the results of a series of changes
have taken place in the domestic economy, the blind development of chemical industry, the export surge
in the international balance of payments surplus, the economy appeared prosperity. However, the
booming natural gas industry in the Netherlands was a serious blow to the agricultural and other
industrial sectors, weaken the international competitiveness of export industries, to the 20th century, 70
years, the Netherlands suffered from rising inflation, decline in manufactured exports, lower revenue
growth, the unemployment rate increase in distress, the resource industry in the "boom" period of
inflated prices at the expense of other industries at the expense of the phenomenon known as "Dutch
disease." 16th century Spanish gold and silver from the Americas was hindered its industrialization
process, which is also a “Dutch disease”. The 20th century, the early 70s to 80, the global oil prices
soaring, in Saudi Arabia, Nigeria and Mexico has also exerted a similar situation.The blind development
of some of China's western region not suited to the local industry, resulting in substantial losses, the risk
of a huge industry.
Beihai, Guangxi, such as the blind development of real estate, "uncompleted flats" nationally renowned
for
"18 bio-engineering" in Yunnan Province, it is the investment of hundreds of millions, without the
formation of industrial efficiency. In 2009 China Financial Forum, the China Banking Regulatory
Commission Chairman Liu said that the banking financial institutions should play a good practice and
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innovation's role, in the low-carbon economic development and industrial structure adjustment play an
active role to strengthen credit management, and vigorously to prevent industrial the structural
adjustment process in the industry credit risk. High-tech is becoming a socio-economic development in
the 21st century, the main driving force. Faced with this trend, governments have to develop appropriate
measures with a view to the future world economy complete.China also have an important task of nation
with science and education as a government. To implement the strategy must address the risks of
high-tech industries.
Production of the above Industrial risks is with the local government decision-making related to
non-industrial risk assessment. Industry Risk The first is risk assessment, risk assessment model is
an advanced concepts and techniques and methods in the embodiment of the macro level risk
assessment on the industry, all levels of government should be the focus of the work to find suitable
conditions for the local characteristics and resources development.
2. Modeling
There is the risk of industry decision-making problems, Under normal circumstances policy-makers are
often faced with multiple possible states, called the event, denoted by b1 b2 b3. Decision-makers can
take the decision-making programs; it has more than one, denoted by d1, d2, d3. The decision-making
programs for each risk and calculate an income of each state, denoted by wij Thus: m rows n columns
matrix H = (wij), known as the risk-return decision-making matrix.
， ，
，
 w11
H =  w21
 w31
w12
w22
w32
w13 
w23 
w33 
Because the randomness of the occurrence of various states, decision-makers in decision-making prior
to the need for every state bj probability of occurrence to make a reasonable estimate, denoted by p (bj)
∑p w
j
ij
= pj. As a result, the corresponding expected return on the decision makers is j
. In this way,
the risk of decision-making problems can be attributed to the decision-making program for determining,
it must satisfy the fellow:
∑p w
j
ki
i


= max ∑ p j wi j 
 i

This is commonly used in risk decision-making guidelines for the maximum expected return.
Similarly, if easy access to the decision-making program that corresponds to dij and the like bj-state cost
of wij, From the perspective of risk considerations, in order to reduce the risk of loss, then the common
decision-making criterion is the minimum expected cost criteria to determine the decision-making
program dk, so that:
∑p w
j
i
ki


= min ∑ p j wi j 
 i

On decision-making principles, there are often ignored by many policy makers also need to have a
concept is to minimize the chance of loss. The so-called opportunity loss means: When the state bij
occurs, the result of the selection of decision-making di, may not receive maximum benefit. The
decision-making di obtained gains and likely to get maximum benefit shall be the difference it is the
loss of the opportunity, denoted as follows:
，
Li j = max wkj − wij
k
Similarly, we can also adopt the principle of minimum expected loss of the opportunity to make
decisions, select the decision-making, so that:
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∑p L
j
i
ki


= min ∑ p j Li j 
 i

In general, we have the following conclusions:
Minimum expected loss of the opportunity principle and the principle of maximum expected profit is
equivalent, at the same time there have:
∑p w +∑p
j
ij
j
j
j


Lij = ∑ p j  max wij 
 k

j


Notwithstanding the above conclusions, calculate the minimum expected loss of the opportunity there is
another meaning. Envisaged through the market survey, for which the event actually took place can get
complete information, thus the availability of corresponding maximum benefit
max wkj
k
(
j
)
. Therefore,
∑ p j max wkj
k
,
under the conditions of access to complete information, expected maximum benefit is
it is with no access to this information than the maximum expected return, exactly the difference is an
opportunity for the minimum expected loss:
∑p
j
j
(max w )− max ∑ p w  = min ∑ p L 
k
kj
j
ij
j
i
ij
i
Therefore, this value can be defined as the expected value of perfect information of the EV. For the
reality of this problem, attention should be given the opportunity loss of hope, if this value is a small
price to obtain complete information, it is considered in decision-making need to focus on the issue.
3. Model Application
The usual industry measure indicators can be simplified by GDP, because the data is easier to obtain the
results easily acceptable. Cost considerations as a decision-making, simplify the number of investment
×the volume of unit investment = GDP. If a certain area in the number of 100, the unit of volume of
investment of 10; invested 200, unit investment volume of 9; invested more than 300, the unit of volume
of investment of 8.5. If the investment opportunity losses of 0.5 failures, we seek the largest GDP, the
risk minimal loss.
For the typical industry risks, simplifying the decision-makers facing the state are three kinds of (the
primary industry, secondary and tertiary industries). Denoted by b1, b2, b3, respectively, to be industrial
investment amounted to 100,150,200 situations. Policy-makers may take the decision-making also has
three kinds, denoted in the d1, d2, d3, respectively, correspond to the number of 100,200,300 investment
in the case. After calculation, easy to get payoff matrix:
 200 175 150 
H =  100 300 600
− 150 150 450
If the decision-makers based on past experience and current information, be able to b1, b2, b3,
probability of occurrence to make a reasonable estimate, for example:
p1 = p(b1 ) = 0.5 ,
p 2 = p (b2 ) = 0.3 ,
p3 = p (b3 ) = 0.2
Then, corresponding to the decision-making d1, d2, d3 expected benefits are as follows:
G (a1 ) = ∑ p j w1 j = 182.5
j
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G (a 2 ) = ∑ p j w2 j = 210
j
G (a3 ) = ∑ p j w3 j = 60
j
In accordance with the principle of maximum expected profit, the decision should be taken for the d2,
the industry GDP is 210.
Risks of the industry, according to the principle of minimum expected loss of the opportunity available,
you should choose the decision-making d2, GDP is 210, the corresponding expected opportunity losses
as follows:
∑p w
j
2j
= 100
j
…… (2.1)
For now this problem, we look forward to the opportunity has been lost (2.1),so EV = 100 If this value
is a small price to obtain complete information, it is worthy.
The number of non-discrimination, such as investment, is uniformly distributed situation.We assume
that investment in the previous three discrete numbers of possible states. Another possible scenario is
that policymakers have learned from past experience, the number of estimated investment of 100 to 200
between, the investments may set the number of subordinate [100,200] on the uniform distribution.
Recorded the number of q for investment, s for investment, E, as the proceeds as decision-makers.
When q> s, the industry, there is no risk, but there is q<s cases, industries at risk, let c (s) as the unit
volume of investment, decision-makers the benefits are:
，
E = 12 s − c(s )s − 0.5(q − s ) = 6q + (6 − c(s ))s
10,
s = 100

c(s ) = 9,
s = 200
8.5,

s = 300
When q <s, its benefits as follows:
E = 12q + 6(s − q ) − c (s )s = 6q + (6 − c(s ))s
6q + (6 − c (s ))s,
q≤s
G=
q>s
(12.5 − c (s ))s − 0.5q,
When s = 100, the decision-makers expected return as follows:
Gs = ∫
200
100
((12.5 − 10 ) • 100 − 0.5 x ) p (x )dx = 175
p( x ) =
1
100 , (x ∈ [100 , 200 ]) , Presents the
Where p (x) is the probability density function of s,
characteristics of uniform distribution, probability function is shown in Figure 1, decision-making for
the d2, the second industry is with less risk.
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Figure 1: a uniform distribution of probability function
3. Conclusion
Industry risk assessment the amount of real difficulty lies in GDP forecasts, requires a lot of surveys and
statistics. This model is simple, but it is already quantitative analysis, a comprehensive analysis is
essential. In contrast, quantitative decision-making is of practical significance. Application of the
principle of maximum expected profit, or the principle of minimum expected cost, we need
policy-makers on the probability of random events to make the valuation. Sometimes it is very difficult.
If decision-makers can not be measured the probability of the incident, then he can not resort to the
principle of maximum expected profit decision-making. At this time, you can take to maximize the
principle of the minimum income (or a conservative principle) selection decisions.
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