Download Research on Derivative Pricing Theory in the Development of Contract Agriculture

Research on Derivative Pricing Theory in the Development of
Contract Agriculture
HE Sijiang, YAO Zheng
Department of FinanceZhejiang University, P.R.China, 310027
[email protected]
Abstract: The core of contract agriculture is the price. Theoretically, futures contract and options
contract meet the needs of risk allocation for contract agriculture, whose financial feature is more and
more obvious with the fast developing modern financial market. However, the question how to use
derivatives pricing theory to guide contract agriculture has hindered the sustained development of it.
Based on our research, Spring Oscillator Theory and Option Pricing of Asset with Circle Expected Rate
of Return have properly expressed the intrinsic characteristics of agricultural risk, including its financial
trait and periodically fluctuating price. We set up an equation to decide the options contract price under
certain hypotheses, analyze factors that influence the price and draw a conclusion. This theory is helpful
for promoting sustained development of agricultural products circulation mode, such as futures contract,
options contract, and futures options contract.
Key words contract agriculture, futures contract, options contract, futures options contract ; derivative
pricing theory
：
1. The Recent Problems
Since late 1980s, the contract agriculture has demonstrated unique functions. The main form of
contract agriculture is the “company +farmers” mode which emerged in the process of agricultural
industrialization. Contract agriculture has fulfilled its unique function in settling the contradiction
between small-scale production and large-scale market, mitigating the blindness of farmers when
making decisions, reducing the working costs and risks of agriculture industrialization, and boosting the
income of farmers. However, with the economic internationalization and the progress of the market
economy, contract agriculture in its practice has exposed to the market its increasingly serious problems.
The most serious problem is its high delinquency rate. Scholars have already lucubrated into the cause
of such a high delinquency rate and brought forward a handful of solutions. For example, Huang Zuhui,
Wang Zusuo(2002); Guo Hongdong(2005); Liu Fengqin(2003); Zhou Liqun, Cao Liqun(2002)
introduced Corporation Organizing Theory, Contract Theory, Game theory and Transaction Cost Theory
to discuss the mode characters of contract agriculture, as well as reasons and solutions of high default
rate. They had drawn some useful conclusions. With the development of the market, financial and global
agricultural risks are increasing gradually. Some scholars (Zhu Yuchen 2004 Gao Tiesheng 2005 Lu
Xiaoguang2005 Zhao Xiliang, Wu dong 2005 He Sijiang 2006) proved that it is more important to
direct the development of contract agriculture and set up reasonable risk scattering and profit allocation
systems by using modern financial market functions. Agriculture is a traditional high-risk industry. The
risks happen frequently and affect society widely. To remove the obstacles in the development of
contract agriculture, the measures such as “perfection of governance mechanisms and contracts;
investment on specific assets” help increase the exercise rate to some extent, but they can not solve the
problems radically. These measures can not scatter risks, which is their defect. The intrinsic risks in
contract agriculture transfer between traders in a relatively close system; the measures mentioned above
have the character of “blocking” in certain meaning. In this new situation, all methods that have the
“blocking” feature can not solve the problems radically; they will affect the normal operation of contract
agriculture and even cause it to disappear in a long period. From the trading point of view, the operation
of contract agriculture can be considered as a forward contact. The forward contract lacks the quit
mechanism before maturity, and naturally has the risk integral mechanism. With the process of
economic and financial globalization, it also cannot avoid, transfer and scatter market risks because of
；
；
312
；
；
finite trading and local information. To radically solve the problems of high default risk in contract
agriculture, we should take full advantage of the risk scattering and allocation system in modern
financial market, and combine contract agriculture and modern financial market to exclude the risks
from contract agriculture. According to this many scholars(Zhu Yuchen2004 Lu Xiaoguang 2005 He
Sijiang 2005 2006)pointed out some risk management strategy including futures contract, options
contract and futures options contract. However, it should be noted that these tools might be good ideas,
but how to implement them in practice? Many research needs to be done, especially how to decide the
contract price.
There are few articles that research on agricultural products options pricing. Almost all the pricing
methods directly apply the Black-Scholes Model (1973), which is a pricing formula for financial
products. For example, Xue Zhaosheng(2001), Zhou Yanping(2002) applied B1ack-Scho1es model to
guide the agricultural products options contract; Li Dongsheng(2001) also used B-S model and BOPM
to price the options contract. They all did not consider the features of agricultural products and simply
used the classical models; this applicability is questionable. Nie Rong(2004) applied jump-diffusion
model in stock market to discuss the pricing of agricultural products options contract. This model
considered accidental events such as natural disasters, but they still did not consider the features of
agricultural products. It is universally acknowledged that financial products and agricultural products
are totally different. Agricultural products have their special rules in the production process and demand
and supply. If we can consider these intrinsic features in the options pricing model, this may guide
contract agriculture much better. According to the reasons above, this article takes the periodically
fluctuation of APP into account, applies the Spring Oscillator Theory and Option Pricing of Asset with
Circle Expected Rate of Return, demonstrates the options pricing model of agricultural products and
relative conclusions, to better guide the development of futures contract and options contract.
；
，
；
2. Fluctuation features of Agricultural Products Price (Abbreviated as APP) and
the contract price
The pricing of derivatives such as futures or options contract is closely related to the price of
underlying assets. Compared with common financial products, the fluctuation of APP has its inherent
factors. Of course we must take these factors into consideration when researching the pricing of
derivatives.
2.1 Fluctuation features of APP
In the market economy, the relationship between supply and demand is the main factor that
determines the price. Agricultural products are necessities in our life, and the price elasticity of demand
is relatively low, therefore the demand of agricultural products is stable. On the other hand, the
production of agricultural products changes annually. The APP is driven down in the harvest season,
while it is high in winter and spring because of scarcity in supply. The price fluctuation will in turn
affects farmers’ profit and loss as well as their decision-making. In China, farmers make decisions based
on APP in the last period as described in the “cobweb model”. Farmers can only adjust output by last
year’s output and prices. For example, if the last year’s output was overabundant, they will produce less
this year; or they will produce more otherwise. This will aggregate the prices fluctuation. Further more,
the lag effect and government policy will also cause great impact to APP. Zhu Wen(2007) pointed out
that in our country the decisive factor that influences the agricultural products fluctuation is the
government policy. These policies will mobilize the enthusiasm of farmers and are the reflection of
macro decision-making. In addition, periodic activities of natural disasters, technology input and
expenditure of agriculture will also affect the output of agricultural products which fluctuates
periodically. By applying the Wave Theory, introduced by R.N. Elliott who observed the commodity
price changing process in a long time, we may consider that agricultural products are special commodity;
the price fluctuates periodically around market value, just like the motion of a spring oscillator.
2.2 Risk allocation of APP needs modern derivative market
313
The APP changes frequently in spot transactions. Farmers lack the active risk avoiding mechanism
for spot transaction; they can only adapt to the changing prices passively and bear losses, as described in
the cobweb model. Besides, because there are plenty of agricultural products species in China, and
agricultural products market are changing from a seller’s market to a buyer’s market, farmers are
puzzled by the problems that agricultural products are “hard to sell”. The farmers are directly exposed to
the risks caused by the fluctuation of APP, and the comparative advantage of agriculture is relatively low.
Lower price means less income; farmers may not increase their income when production increases. To
solve these problems we need derivatives in modern financial markets.
The law of economic development suggests that the evolution of trading follows this trail:
spot-forward-futures-options. Each trading form has its own features. The present contract agriculture in
China is similar to forward contract. This trading form solves price changing problem in spot transaction
and adapts the contradiction among production, supply and sales. However, this form lacks a
mechanism to scatter and confine the credit risks, and often weakens the traders’ delivering ability when
the contract is carrying out.
Futures
Spot
Futures Options
Forward
Options
Figure 1: The evolution of trading
Therefore, the development of contract agriculture needs the futures and options market, which will
efficiently solve the problems. First, both markets have the function of value discovering and risks
transferring. Applying the derivatives pricing method we can offer a reference to the contract price and
transfer risks to speculators. And the margin systems make default risks hardly exist in the trade, thus
this system will raise the exercise rate of the contracts. Second, both markets will enlarge the scale of
the contract agriculture and increase the farmer’s income. Trading in the form of futures or options, we
can predict the prices of the next year. This will help increase the farmers’ activeness and income by
hedging effectively in the agricultural products market. Third futures and options contracts are the
offspring of developed derivative markets. These contracts are beneficial for us to keep up to the world,
and strengthen the international competitiveness of Chinese agricultural products.
However, futures transaction has a “lock effect” on the result. The traders give up the risks that are
beneficial to them when they avoid risks that are negative to them. These behaviors do not maximize the
profit and thus are not rational, and this mode also contains the intrinsic default factors. The key to
establish a contract is to ensure the farmers more profit and less risk in their management in agricultural
industry. To further improve the profit-allocation mechanism between farmers and enterprises, and to
truly realize “benefit-sharing and risk-sharing” we may consider introducing the idea of agricultural
options.
，
，
2.3 Price is the core of options contract
Options are emerged and developed in order to solve the problems of agricultural market risks. The
research and applying of options theory make it one of the most important discoveries in the 20th century.
The Principles, methods and conclusions of options theory are widely used in macroeconomics,
microeconomics and management analysis and decision-making. If we could apply buyers’ idea in
options market and set up a profit-allocation system between farmers and companies, both sides will
share the risks and benefits. This reflects the true meaning of contract agriculture no matter how the APP
changes in the future. For the farmers, they will obtain the secured lowest income and maintain the
continuous social reproduction; the premium may be the largest loss that can be predicted. On the other
hand, for the enterprises, they can steady their source of supply; the premium will make a profit as
prices increase to compensate the loss caused by decreasing prices. Thus as illustrated in Figure 2, by
applying options to trade, farmers can not only avoid risks of lower prices, but also have the chance of
314
high-yield because of higher prices. The default risks will thus reduced (Nie Rong 2004). This is why
options is superior to futures. Besides, it will be beneficial to applying the put options mechanism to
analysis and establish profit-risk mechanisms between farmers and companies, which also has important
theoretical and practical values (Xue Zhaosheng 2001).
Therefore, the development of contract agriculture should be integrated with the modern
derivatives markets. This process will diversify the risk allocation and help farmers increase their
earnings as well as their production. If we provide derivatives trading information-such as
demand-supply and their price-to the farmers, it will guide the farmers to adjust their production
structure properly; the risks will convert to fictitious economy and get rid of fierce fluctuation. Proper
contract prices can also help avoid the disjoint of production and sale in the agricultural industry, and
ensure the production process to operate smoothly proper prices are also the basis for the
macro-control.
；
gain or loss
forward or futures
call option
strike price
X
O
market price
P(t)
premium Vc
Figure 2: The profit comparison between forward or futures and options
3. The pricing formula of agricultural options contract: the price yield fluctuates
periodically
As mentioned above, APP often fluctuates periodically. Spring Oscillator Theory, which considers
objects that wave periodically, believes that the prices of commodities move as a spring oscillator; the
prices will change regularly around a balanced value that will be eventually achieved. This offers a new
idea to research on the pricing of agricultural options contracts.
3.1 Spring Oscillator Theory and fluctuations in prices of agricultural products
Suppose the market friction coefficient, or transaction cost rate is r, the agricultural products prices
fluctuate periodically around the market value. In addition, the convergence force towards the market
value is positively related to the deviation from the market value.
Based on the hypotheses above, we set a Spring Oscillator model for the fluctuation of APP
：
2
fh(t ) − mkP(t ) − r
dP
d P
= m 2 + εt
dt
dt
(3.1.1)
f stands for values contained in the market information; h(t ) is a unit step function; k is the elastic
coefficient of the market, which represents the pricing efficiency of the market; m is the price inertial
indicator; ε t are random errors of prices.
Not considering random errors and transaction cost rate (r), Zhao Zhenyu(2005) concluded an
analytic solution to formula (3.3.1) when k > 0 :
315
p (t ) =
f
f
−
cos( kt )
mk mk
(3.1.2)
This solution of p(t ) represents the change of APP. This change is caused by new information
such as government policy, and fluctuates with the same amplitude in the period T0 =
2π
. We
k
differentiate p(t ) at time t and get µ (t ) , which represents the changing rate of APP, or
f
µ (t ) = p′(t ) =
sin( kt ) (3.1.3)
m k
3.2 Random model of APP
Influenced by certain types of factors, APP often fluctuates sharply. Suppose the fluctuation of APP
is a dynamic stochastic process which changes continuously as time t changes. The fluctuation of APP
also satisfies Markov distribution and follows Ito stochastic differential process:
dP(t )
= µ (t )dt + σ dz
P(t )
(3.2.1)
µ (t ) is the predicted changing rate of APP, calculated in continuous
t − t0 ，also is called as diffusion coefficient; σ is the volatility of expected APP
where P (t ) is the APP of time t;
compound within
changes, also called as drifting coefficient; dz = ε dt is a standard Brownian Motion.
3.3 Agricultural Options Pricing Formula
The APP will not perfectly return to the price of the last period; it has an upward or downward
trend as showed in Figure 3 with dotted lines. With the help of Spring Oscillator Theory which relates
to price fluctuates in a set period (Zhao Zhenyu2005), not considering trading costs and random errors,
we suppose APP satisfies the equation below:
，
（3.3.1）
µ (t ) = a + A sin( kt )
where a is the mean drift rate, a constant can be both positive and negative, stands for the upward
or downward trend of APP. The amplitudes (A) of expected price-changing rate are related to values
contained in policy information, price inertial indicator, and the market pricing efficiency k.
P
P
P0
P0
t
t
Figure 3: The image of anticipated APP changes with time
（ ）
From 3.1.2 we can discover that the period of APP changing is T0 = 2π k . The fluctuation rate
of APP also fluctuates around the balanced position a. Applying the above conditions and (3.2.1), we
will obtain the Ito stochastic process which the APP satisfies:
316
（ ）
dP (t ) 
3.2.5
= a + A sin( kt )  dt + σ dz
P (t ) 
Then we draw the conclusion: with the striking price X and present price P(t0 ) , the prices of call
option ( Vc ) and put option ( V p ) are
Vc = P(t0 )e
Vp = Xe
a (T −t0 )
N (d1 ) − Xe
A 
cos( kT ) − cos( kt0 ) 
k
A 
cos( kT ) − cos( kt0 ) 
k
N (d 2 )
（3.2.6）
N (− d 2 ) − P(t0 )ea (T −t0 ) N (− d1 )
respectively, in which
1 
 P(t )  A 

ln  0  −
cos( kT ) − cos( kt0 )  +  a + σ 2  (T − t0 )

2 
X 
k

, d 2 = d1 − σ T − t0
d1 = 
σ T − t0
Proof Let G = ln P (t ) then
1 

dG =  a + A sin( kt ) − σ 2  dt + σ dz
2 

Between t0 and T,
，
：
 T
1 

ln P(T ) − ln P(t0 ) ~ N  ∫  a + A sin( kt ) − σ 2  dt , σ T − t0 
2 
 t0 

Thus the agricultural price P (t ) of a future time t satisfies
T

1 


G ~ N  ln P(t0 ) +  a − σ 2  (T − t0 ) + ∫ A sin( kt )dt , σ T − t0 
t0
2 



So
is
ln P(t )
normally
distributed
，
with
its
mean
T
1 

ln P(t0 ) +  a − σ 2  (T − t0 ) + ∫ A sin( kt )dt and standard deviation σ T − t0 ; the
t0
2 

T
expectation
of
P(t)
is
T
Var[ P(t )] = [ P(t0 )]2 e
2
∫t0 a + A sin(
E[ P(t )] = P(t0 )e
kt )  dt
[eσ
2
( T − t0 )
− 1]
Therefore,
317
∫t0 a + Asin(
。
kt )  dt
,and
the
variance
is
Vc = e
=e
=e
−
T
∫t0 Asin(
T
−
∫t0 Asin(
−
∫t0 Asin(
− Xe
T
−
T
kt ) dt
kt ) dt
kt ) dt
∫t0 Asin(
E[max( P(t ) − X , 0)]
T
1 



z
−
+
(
)
ln
(
)
e
X
ϕ
P
t
A sin( kt )dt +  a − σ 2  dt ,σ T − t0  dz
0

∫ln X
∫
t0
2 



+∞
T
1 



e zϕ  ln P(t0 ) + ∫ A sin( kt )dt +  a − σ 2  dt , σ T − t0 dz
ln X
t0
2 



∫
kt ) dt
+∞
∫
+∞
ln X

T

t0


1
2



ϕ  ln P(t0 ) + ∫ A sin( kt )dt +  a − σ 2  dt , σ T − t0 dz
= P(t0 )e a (T −t0 ) N (d1 ) − Xe
A 
cos( kT ) − cos( kt0 ) 
k

N (d 2 )
We can conclude the pricing formula of put options similarly.
4. Examples
Using options pricing theory can help scatter the risks and guide the farmers’ investment. In this
section we will first consider the pricing of options with different volatility, different striking prices X,
and different time to maturity. Table 1 below presents the pricing of options under formula (3.2.6).
Suppose t0 = 0 ; P(t0 ) = 100 ; a = ±0.02 ; the fluctuation cycle of agricultural products price is 1 year,
thus T0 = 2π k =1, or k = 4π 2 .
Applying formula (3.2.6) we get Table 1 below.
：
T - t0
Volatility
10%
50%
Table 1 The pricing of call options calculated with (3.2.6)
a=0.02
a=-0.02
0.1
0.5
0.1
0.5
0.1
0.5
0.1
X
A k
A k = 0.1
A k = 0.2
A k = 0.1
90 11.91 27.31 13.56 40.67 11.50 25.31 13.17
100 2.50 19.14 4.64 33.97 2.16 17.13 3.71
9.20
0.04
110 0.00 11.08 0.04 27.26 0.00
90 13.69 30.36 15.04 41.51 13.27 28.54 14.66
100 7.42 24.68 8.32 35.83 7.18 22.98 8.18
110 3.48 19.44 4.12 30.51 3.18 17.94 3.76
0.5
= 0.2
38.67
31.97
25.26
39.64
33.87
28.50
From (3.2.6) we can discover that the options with different initial moment have different prices.
Suppose the trail of the agricultural products price is
dP(t )
= [0.02 + 0.02π sin(2π t )]dt + σ dz
P(t )
Suppose t01 = 0 and t02 = 0.5 , T1 − t01 = T2 − t02 = 0.1 then P(t01 ) = 100 , P(t02 ) = 100e0.02 = 102.02 ,
and σ = 10% .Applying formula (3.2.6) we get Table 2 below.
：
Table 2 The pricing of call options with different initial moment
A
volatility
X
10%
90
100
110
k = 0.01
；T − t
0
=0.1
P(t01 ) = 100
P(t02 ) = 102.02
t01 = 0
t02 = 0.5
10.37
1.41
1.85
12.05
2.30
0.08
318
We can draw conclusions below from Tables 1 and 2.
1 We remain volatility and striking price unchanged. If the maturity time longer, the premium
Vc is higher. This is because options are a hedging tool; a longer maturity time means higher risks,
therefore the price should be higher.
2 We remain maturity time and striking price unchanged. Volatility increases will also cause
options price Vc higher. A larger volatility means uncertainty of APP, thus the options price increases.
（）
（）
（3）The decreasing in striking price will cause options price V to raise while other factors remain
c
the same. The lower the striking price X, the higher risk farmers have to take. This will raise the options
price.
4 Suppose the original APP is P (t0 ) . The amplitude A increases while other factors remain
（）
unchanged will cause options price Vc to raise. A also represents the risks and depends on policy and
market factors. We can get the data of A through observing the amplitude of APP in recent years.
5 The options pricing is related to initial time. The reason is the price fluctuation of underlying
asset (agricultural products). For instance, when the price is at its peak, people predict the price will
probably decrease in the future, thus the options price is low. On the other hand, when the price is at its
valley, the converse situation happens.
6 The options pricing is related to the drifting rate a. We can also collect the information of a
though former data of the APP changes. The price of options whose underlying APP is in an upward
trend is a little higher than the price of options whose underlying APP is in a downward trend.
（）
（）
5. A Brief Conclusion
The model above is idealized because of some hypotheses. For example, the fluctuation rate of APP
is a sinusoidal function, and we do not consider the trade costs, ect. Options are not introduced in
Chinese agricultural market, but the changing policy and international environment are more conducive
to the introduction. The report of 17th CPC National Congress pointed out that we will “promote the
reform and innovation of rural financial system”. Economic and financial globalization is deepening
increasingly both severe fluctuation of APP and rapid development of international derivatives markets
essentially require the acceleration of the steps that modern financial markets feed back agriculture. By
applying the Spring Oscillator Theory which reflects the periodically fluctuating price, we can better
understand the changing rules of agricultural products options price and help decide the options contract
price properly.
；
References
[1] F Black, M Scholes. The pricing of options and corporate liabilities[J].Journal of Political
Economy, 1973, 81:637-654
[2] John C. Hull . Fundamentals of Futures and Options Markets[M] Tsinghua University Press
[3] Modher Bellalah, Eric Briys, Huu Minh Mai, Francois de Varenne. Options, Futures and Exotic
Derivatives Theory, Application and Practice. Machinery Industry Press 2002.6(in Chinese)
[4] An Yi. The development of derivatives market and research on macro control [M].China Market
Press 2007.1(in Chinese)
[5] Gao Tiesheng, Zhu Yuchen. The Function and Development of Chinese Agriculture Product
Futures Market [M],Chinese Financial Press, 2005(in Chinese)
[6] Guo Hongdong. Agricultural Leading Enterprises and Research on the Arrangement of Contract
Agriculture and Exercise Mechanism [M] Chinese Agriculture Press, 2005(in Chinese)
[7] He Sijiang. Research on Financial Innovation in the Development of Contract Agriculture [J]
，
，
，
，
，
319
：
Journal of Zhejiang University, 2006 6 120—127(in Chinese)
[8] He Sijiang, Tang Zhongyao. The development of contract agriculture and the innovation of
financial tools [J].Financial Research, 2005.4 (in Chinese)
[9] Huang Zuhui, Wang Zusuo. The management of agricultural industry under incomplete contracts
[J]. The Problems of Agriculture Economics, 2002 3 28—31(in Chinese)
[10] Li Dongsheng, Li Daifu. Options pricing, risk investment and contract agriculture [J]. Journal of
Agrotechnical Economics 2001.5(in Chinese)
[11] Liu Fengqin. Incomplete contract and exercise obstacles-with contract agriculture as an example
[J] Economic Research Journal, 2003 4 22—30(in Chinese)
[12] Liu Jinxia, Yang Guiqin. The risk transferring mechanism of agriculture futures and options market
[J]. Comparative Economics Forum, 2005.15(in Chinese)
[13] Lu Xiaoguang. The Agriculture Commodity Contract Mode under Modern Finance Structure [J],
Finance and Economics .2005 5 21—27(in Chinese)
[14] Nie Rong, Qian Keming, Pan Dehui. Agricultural options pricing based on jump diffusion and
contract agricultural [J]. The Journal of Quantitative and Technical Economics,2004.10(in Chinese)
[15] Nie Rong, Qian Keming, Zhang Xiaohong. Stochastic Model and Risk Measuring on the
Farm-produces Pric [J]. Mathematics in Practice and Theory,2004.11 (in Chinese)
[16] Sheng Xiudong. Inferior-market, quasi-market and agricultural industry-research on “Company
+Farmer” mechanism[J] Introduction of Agricultural Economics, 2002 .2(in Chinese)
[17] Sun Yafan. A Study on the Development of New Type of Farmers’ Specialized Cooperative
Economic Orgnization [M] Social Science Literature Press, 2006(in Chinese)
[18] Tan Dejun, Hu Zongyi. The European Option Pricing of Stock with Circle Expected Rate of Return
[J] Mathematics in Economics, 2002.3 (in Chinese)
[19] Xia Yongxiang. Agricultural efficiency and land management scale [J]. Problems of Agricultural
Economy,2002.7 (in Chinese)
[20] Xue Zhaosheng. Guidance and Application of Options Theory to Contract Agriculture [J] Chinese
Rural Economy. 2001.2 (in Chinese)
[21] Zhao Xiliang, Wu Dong. Research on the stability of commodity contract in agricultural industry
[J] Contemporary Economic Research , 2005 2 70—72(in Chinese)
[22] Zhao Zhenyu, Ouyang Lingnan, Zhu Bo. The new theorem of using Spring Oscillator Theory to
study capital market [J]. Control Theory Applications, 2005.2 (in Chinese)
[23] Zhou Liqun, Cao Liqun. Commodity contracts are superior to element contracts-take contract
selection in agriculture as an example [J]. Economics Research Journal. 2002 1 14—19(in
Chinese)
[24] Zhu Wen. Analysis on factors that influence farm-products price[J].Chinese Collective Economy,
2007.7 (in Chinese)
[25] Zhu Yuchen. The Innovation and Development of Chinese Futures Market [M]. Economics and
Science Press, 2005 (in Chinese)
，
：
，
：
：
，
，
，
：
＆
，
320