Effect of the Weather on Agriculture

Effect of the stick issue on Agriculture administrator SummaryAgricultural activities ar often affect by the suffer. Weather is unpredictable as it changes from date to cadence. As the countrified activities affected, the crops or the eat uppoint of the agricultural activities would be affected as well and this ca apply the income of the farmers to be affected or ca employ the investors to lose money. Therefore, atmospheric condition derivative is needed to foster the farmers and investors. So, this explore is all ab break through instanceling and price of brook derivatives where the stick out is found on the day-after-day norm temperature in Malaysia. In this seek, in that location argon two main objectives which embarrass the shamling of temperature and determine of abide derivatives. To complete this inquiry project, there are 10 stages to be at rest(p) through. The details about the stages would be discussed in the methodology of this look into.The m ock up utilise to archetype the motility of day-to-day reasonable temperature in this research would be the stochastic incomplete Brownian accomplishment. This baby-sit is elect beca practice session based on the foregone researches, this impersonate suitables the data well and successfully toughieled the dynamics of everyday fair(a) temperature. From this research, the mundane temperature is expected to be setled and described by the stated pretence well. in any case that, the set of support derivatives ordain be encountered as well. through this research, it provides a constituent of advantages. For example, it provides a better idea in the emergence of poser the temperature and the pricing method of wear derivatives. The outcome from this research gage be used as a reference for futurity researchers that do research in this field.Details of look for Project(a) Research priming1. Problem statementAgricultural activities are one of the main activities carried out by people around the world. It is one of the main sources of income for some of the countries bid Africa, India and China. Even in this modern technological era, many of the agricultural activities ease depending on the atmospheric condition condition. Weather is the daily conditions of a particular place. For example, humidity, precipitation, the daily fair temperature and visibility are all under the weather. Since weather is a topic thats beyond human control and agricultural activities are highly depending on weather, therefore, agricultural businesses are often referred to as a high stake business.In recent years, the weather restitution and weather derivatives are neat more than renowned as it reduces or hedge the risks faced by all farmers and investors that caused by weather. Jewson (2005) presented a few reasons why is the weather derivatives valuable and in Jewson (2005) and Cao and Wei (2004), a few weather hedging techniques were shown. The tradit ionalistic agricultural amends is the crop insurance. There are a lot of disadvantages of the traditional crop insurance. Some of the disadvantages complicate inefficiency due to poor nip structured, need of information and high transaction costs involved. This caused those farmers could not afford for the insurance and hence the weather derivatives are highly needed as weather derivatives normally had a lower price than the weather insurance. Thus, weather derivatives trifle a very important role in helping the farmers and investors. The premier weather related derivative deal was done by genus Aquila Energy in 1997 for Consolidated Edison Company, where a dual-commodity hedge was structured.Since the agricultural derivatives are crushting more important, more financial researchers are doing their research on the pricing of weather based derivatives. Norton (2010) stated that the weather derivative is a way to share the risk for farmers in developing countries. Malaysia is l ucky enough to be located in the equatorial region. Hence, the weather in Malaysia is calefactive and humid throughout the year. Therefore, in Malaysia, the crops are only affected by the daily average temperature and the fall of rainfall. Of course, there are catastrophes that happen in Malaysia too, like flash flooding, acid rain or drought. These catastrophes in Malaysia caused the cost to all the crops. But, the main problem that could affect the crops in Malaysia would be the amount of rainfall, the daily temperature or humidity. Hence, in Malaysia, to structure a weather derivative, it is easier as compared to other(a) four season countries because the weather factors that taken into account are lesser. Moreover, there are lack of people doing research in this field, thus, this research is quite important as to solve the agricultural problems.2. Research questions whizz of the problems faced by researchers in doing research about the pricing of weather derivatives is ofte n the pricing model or the pricing technique that is used. withal pricing technique, the model that used to describe the dynamic or the movement of the weather factors like amount of rainfall or daily average temperature in the research of weather derivatives is one of the problems faced by researchers as well. Hence, in this research, the focus would be on the border of the daily average temperature in Malaysia and the pricing of the weather derivatives. So, the questions to be answered in this research impart be how well the model is, in describing the movement of daily average temperature and how to price the weather derivatives.3. Literature reviewThere are really a lot of researchers had done their research about the weather insurance or derivatives. Some of the models used by past researchers include temperature modelling, Black-Scholes model, cartridge clip serial publication models, Brownian model, Ornstein-Uhlenbeck model, Esscher transformation and more.Taib and Benth (2012) had done a research on the pricing of the weather insurance by using three different approaches which include burn analysis approach, index modelling and temperature modelling. The weather index is outset mensurable and thence the price of the insurance remove is calculated based on the weather index. The weather index, which is based on the Cooling-Degree Day (CDD) is calculated by using the formulae of afterwards calculating the , the price of the insurance contract screwing then be now determined by using the formulaeP(t, ) = exp(r( t))E)Ft where the expected value of the claim size is found. The exp(r( t) is used to specify the present value by discounting at time as Indicates the end of the period where insurance starts paying. The formulae of P(t, ) is a standard method to price the weather related insurance or derivatives.For burning analysis approach, it is number onely introduced by Jewson and Brix (2005) as a classic method in pricing weather derivatives . The payoff of the burning analysis approach is based on the experiential dispersion of the specimen data collected. art object the convey value of observations of the sample data is used to calculate the price of the contract. The next method introduced by Jewson and Brix (2005) is the index modelling approach, and Taib and Benth(2012) modify a little bit of the model where the past claims are fitted into a distribution and the expected value of the distribution is used in pricing the contracts. Lastly, Taib and Benth (2012) proposed a new model where the changes of the daily average temperature are modelled using the autoregressive, a time series model. alike Taib and Benth (2012), Campbell and Diebold (2003) in like manner uses time series model to model and forecast the daily average temperature in certain cities of America for the purpose of weather derivatives. While Chang, Lin Shen (2009) constructed a theoretical model to price the weather derivatives and this is the extended adaptation of the model of Cao and Wei (2004). In the research paper of Chang, Lin Shen (2009), the estimation value of future Heating-Degree Day(HDD) and Cooling-Degree Day (CDD) is predicted by using Mote-Carlo simulation and they successfully utilize the time series temperature model in Campbell and Diabold (2003). Mills (2009) also uses time series model to model the current temperature inclination of Central England. In the research of Mills (2009), it is suggested that three other alternative ways could be used to model the temperature trend, which is the parametric stochastic trend model, the non-parametric local trend fit, and a low-pass filter. These 3 alternative techniques had been discussed in Mills (2003) and Pollock (2007).Other than time series models, other models were used by other researchers in pricing of weather derivatives. For example, downwind and Oren (2009) suggested a model of equilibrium pricing of the weather derivatives for various comm odities. This model is built where the risk averse utility officiate is optimized by the agents, including the weather derivatives that have been issued. There are two types of agent. The first type is the farmers where they obtain the profit with the exposure to weather risks while the warrant type of agent is those financial investors where they hope to diversify the financial portfolio. Therefore, by and by in 2010 and 2011, Lee and Oren with Hrdle and Osipenko simulate the realistic market conditions to get the equilibrium price for weather derivatives. This equilibrium pricing method of Lee and Oren is actually based on the research of Cao and Wei (1999) where Cao and Wei generalize the model of Lucas (1978) and include the daily temperature as a fundamental variable.Since Black-Scholes Model is a fashionable method to price the European options, Boto and Ciuma (2012) uses the Black-Scholes model to apply in weather derivatives. The aim of their research is to see how the B lack-Scholes model can be employ in weather type derivative and to analyze whether it is a capable model to price for weather derivatives. However, based on their findings of the research, they reason that the Black-Scholes model is not a suitable model to price for the weather derivatives as the weather market developed very quickly and it is inconsistent. Due to the inconsistencies, the model is not preferable to be used for pricing of weather derivatives contract unless it is a part of the portfolio.Benth and altyt-Benth (2005) uses a stochastic model to model the variations of temperature in their research paper. They used the Ornstein-Uhlenbeck with the driven by Levy process and having seasonal mean and volatility. They find that this model is quite a success to fit the Norwegian temperature data. Besides that, Svec and Stevenson (2006) also use a stochastic model to model and forecast the temperature.Svec and Stevenson (2006) uses Fourier transformation and stochastic Brow nian motion (SBM).They proposed a more generalized stochastic Brownian motion to model the temperature, that is, the stochastic fractional Brownian motion (FBM). The model proposed take account the low-frequency variability of weather where the SBM does not. The difference of the SBM and FBM is that the FBM include a continuous-time Gaussian process depending on the Hurst parameter. This research paper concluded that the Monte-Carlo simulation overly forecast while the autoregressive moving average (ARMA) time-series model under forecast the monthly accumulated Heating-degree Day (HDD) and Cooling-degree Day (CDD). They also concluded that the models they use in the research have better estimates than that of the Campbell and Diebold (2003) model.(b) target of ResearchThere are two main objectives in this research, that is-(i) To model the daily temperature based on the analysis of daily average temperature in Malaysia by using stochastic fractional Brownian Motion.(ii) Pricing of the weather derivative.(c) methodological analysis1. Flow Chart of Research Activities2. Gantt Chart of Research Activities3. Milestones and DatesThe flow graph, Gantt chart and milestones and date clearly show that the research activities of this research project. To complete this research project, there are 10 stages. The first stage is looking for a research supervisor so that this research is under supervision. Then, mise en scene up of research title will be the next stage. After setting up the research title, studying and reading related journals needed as to get a rough idea of what is the research needed to be done and what actually the research is all about. The fourth stage will be fixing the model to be used in the research. After reading and studying of relevant journals, the model to be used could be determined.In this research, the model to be used in modelling the daily average temperature is the FBM. The FBM that will be used is as followsThis model was chosen becau se out of a few models studied in the past research papers, it is one of the best model that fits the movement of temperature. In this FBM, it consists of several components. That is, the mean reversion process, the Ornstein-Uhlenbeck process and the fractional Brownian process which is a continuous-time Gaussian process. Besides that, the model used also included some seasonal and trend factors. With the combination of this few process and factors, it makes the stochastic FBM more efficient in describing the movement of temperature.As the fixing of the model is done, preparation of research purpose would be the next stage and it is now pending for approval by supervisor. After the proposal of research is done and it is approved, collection of data begun and then analysis works will be started. Analyses of data enable the temperature to be modelled by the model fixed in the earlier stage. In this research, the model to be used is the stochastic Brownian Motion. Hence, the eighth st age is the modelling of daily average temperature using Stochastic Brownian Motion. After the modelling, pricing of weather derivatives can be start doing and finally, after the pricing is done, the research project is finished up and completed.(d) Expected results1. New KnowledgeThroughout this research, there are actually a lot of new knowledge could be obtained. As this research is all about modelling of temperature and pricing of weather derivatives hence, by doing this research, it provides a better idea on which model is better in fitting or describing the movements of daily temperature as a lot of other models are studied. Besides that, the steps to model the movements of daily temperatures also a new knowledge. It improves the knowledge about stochastic. Since this research is using stochastic fractional Brownian Motion to model the changes of daily temperature, through this research, the suitability of the stochastic model to describe the changes of daily temperature will be reviewed. Besides that, through this research, the drill and the usage of the stochastic fractional Brownian Motion is known. Moreover, it will provide a better understanding of the method to calculate the price of the weather derivatives.2. Research publicationsThis research will be published as a thesis in semester II of 2014/2015.3. Impact on Society, Economy and NationSince in Malaysia, it is lack of researchers doing the research about the pricing weather derivatives, so, this research of modelling and pricing of weather derivatives gives some small impact on the economy. wiz of the impact is that it improves a little bit of the economic conditions of the agricultural field. As mentioned previously in this research, agricultural activities are affected a lot by the weather and agriculture activities are one of the largest activities in Malaysia. Hence, by doing this research, the forecasting of temperature can be done based on the modelling of temperature. With the foreca sting of temperature, it can help the farmers to be aware of their crops and come out with a better strategy to handle and prepare for the worst. Of course, the forecast results might not be accurate, but, with the guides provided from the modelling and forecasting, it helps to reduce the risk of losing the money, be it the farmers or the investors. This helps to prevent the farmers from stop doing agriculture activities. So, by doing this research, it indirectly affected a little bit on the economic condition of the agricultural field.ReferencesBenth, F., altyt-Benth, J. (2005). Stochastic clay sculpture of Temperature Variations with a View Towards Weather Derivatives. Applied Mathematical Finance, 53-85.Boto, H., Ciuma, C. (2012). The use of the Black-Scholes Model in the Field of Weather Derivatives.Procedia Economics and Finance,611-616.Cao, M. and Wei, J. (1999). Pricing weather derivative an equilibrium approach. Working paper.Cao, M., Li, A. and Wei, J., (2004). Precipit ation modeling and contract rating a frontier in weather derivatives. 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(1978). asset prices in an exchange economy, Econometrica 46, pp. 1429-1445.Mills, T. C. (2003). border Trends and Cycles in Economic Time Series. Palgrave Macmillan.Mills, T. C. (2009). Modelling Current Temperature Trends. Journal of Data Science 7, 89-97.Norton, M., Osgood, D., Turvey, C. (2010). Weather Index damages and the Pricing of Spatial Basis Risk. Retrieved from http//ageconsearch.umn.edu /bitstream/61734/2/Norton%20Osgood%20Turvey.Weather%20Index%20Ins urance%20and%20the%20Pricing%20of%20Spatial%20Basis%20Risk%20_ AAEA2010_.pdfPollock, D. S. G. (2007). Statistical signal parentage and filtering A partial survey. In Handbook on Computational Econometrics (Forthcoming)2. Elsevier.Svec, J., Stevenson, M. (2006). Modelling and forecasting temperature based weather derivatives.Global Finance Journal,185-204.Taib, C.M.I.C. and Benth, F.E. (2012). Pricing of temperature index insurance. inspection of Development Finance 2, pp.22-31.