Unconditioned Response And Conditioned Response Physical Education Essay

Unconditioned Response And Conditioned Response Physical Education Essay According to Pavlov, specific terms begin to be used to describe conditioning such as unconditioned response and conditioned response. Based on Ivan Pavlovs experiment, the natural response to food for a dog is to salivate. This is called unconditioned response (UCR) to the unconditioned stimulus (UCS), which in this case is the food. Then, a neutral stimulus (NS; bell) accompanies the process. By repeating this process, there will be a conditioned response (CR) of salivating with the mere sound of the bell. This way the clicking stimulus now has become conditioned stimulus (CS), which is able to draw a conditioned response. According to Martin and Pear (2005), there are several features that increase the effectiveness of classical conditioning. One of it is that there has to be multiple pairings only between the CS and the UCS in order to increase the effectives of the CS to provoke response from the CR (highest potency). Moreover, the CS and UCS have to be stimuli that are presente d in its maximum power so that the conditioning will be stronger. Morsella (2010) explains that classical conditioning can be found around us from the time we were born. She describes that the liking we have for food that looks artificial and does not have any odour such as lollipops and certain types of candies are due to the effects of classical conditioning. Another application of classical conditioning is to treat toddlers and adults with Enuresis, and managing phobia using systemic desensitization in psychotherapy. Apart from that, classical conditioning is also applicable in the advertising sector. The application of the principles of classical conditioning in the three sectors will be further discussed in this paper. One of the most pioneer contributions of classical conditioning in the medical setting is to treat children and adults who are suffering from enuresis. According to Gross and Dornbush (1983) one form of enuresis that is common among children who are between 5 and 14 years of age is nocturnal enuresis, affecting mostly boys than girls. They explained that nocturnal enuresis is the act of constant bed-wetting at night during sleep despite being potty trained. This behaviour is considered an enuresis if it occurs at least a few times in a month without identifiable physiological cause. It has been discussed that nocturnal enuresis causes many communal and psychological dilemmas as the children will not want to spend the night away from home due to fear of embarrassment. Lemelin and Lemelin (1989) describes the results of using many forms of treatment in dealing with nocturnal enuresis and have identified that enuresis alarm is the best treatment available. According to Schmitts explanation (as cited in Lemelin Lemelin, 1989) explained how enuresis alarm works and its association with the principles of classical conditioning. An enuresis alarm is attached to the front portion of the childs underwear making it convenient to be carried along even during travelling. When a few urine droplets fall on the device, the two electrodes get connected triggering the alarm. The sound created awakens the child, which automatically prompts the child to control the bladder and stop the process of urinating. Then, the child can go to the toilet to complete the urination process. The effectiveness of this treatment will only be seen with multiple trials similar to the case of Ivan Pavlovs dogs. Initial stages (several weeks), the child would only be awake once he or she has completely urinated. Several weeks after that, the child would wake up half way through the process of urinating due to the alarm, thus enabling the child to contract the bladder muscles to stop urination, and continue in the toilet. As a result of repeating this process, in the long run the child will wake up by the mere feeling of wanting to urinate rather than the sound produced by the alarm after urination. The condition improves in one month and complete cure is achieved within three to four months. However the child will have to put on the underwear with the enuresis alarm until dry nights are achieved consecutively for three weeks. 1st Step Unconditioned Stimulus (UCS) Alarm (sound) Unconditioned Stimulus (UCR) Waking up 2nd Step UCS (multiple times) paired with Alarm (sound) Neutral Stimulus to Conditioned Stimulus (CS) Full bladder (need to urinate) Conditioned Response (CR) Waking up Many studies have found that the use of enuresis alarm has helped children suffering from any form of enuresis such as nocturnal enuresis and monosymtomatic nocturnal enuresis. Ozgur, Ozgur, Dogan and Orun (2009) has conducted a study on the effectiveness of enuresis alarm in helping 40 children ages 6 to 16 years old with monosymptomatic nocturnal enuresis to the extent of bed-wetting at least three times in a week. All the participants were told to use the alarm for 12 weeks. The parents and children were shown how the alarm reacts to urine. They only considered a persons treatment as being successful if they managed to keep their bed dry for 14 days continously. Meanwhile, a person is said to have relapsed if they wet their bed one night or more in a week. The results after the initial 12 weeks of using the alarm showed that 27 out of 40 patients kept their beds dry successfully. During the three-month follow-up of still using the alarm at bed-time, it was found that only 9 of the initial achievers stayed dry, while 18 of them relapsed. In the subsequent three- month follow-up, 7 of the 18 relapsed participants showed successful results. Finally after another three months, out of the 7 successful participants, 4 of them achieved dry nights. In total, 13 of them stayed dry and managed to get their enuresis treated. This system works in the same way as explained by Schmitts explanation (as cited in Lemelin Lemelin, 1989). The results of this study are considered to be good by Rocha, Costa and Silvares (2008). They explained that during a long-period of treatment using alarm, the familys level of motivation, socio-economic status and circumstances at home play a huge role in keeping things consistent given that the alarm has to be used daily without fail. Enuresis can be better managed without the reliance of medication as urinating is a normal bodily function that needs to be controlled everyday during sleep and as such the use of enuresis alarm is a better l ong term solution as it is carried out for long period of time. Eventually the child will learn to wake up from sleep the very moment the feeling of voiding appears, which is the normal response expected from the human physiological system. In addition to the study above, Berg, Forsythe and McGuire (1982) conducted a study on 54 children (35 boys and 9 girls) on how they responded with the pad and bell system for initially 4 weeks before extending their treatment for another five months. The pad and bell system works in the same way as the enuresis alarm where the alarm, which is the unconditioned stimulus provokes a response of waking up (unconditioned response). Over time, when full bladder (neutral stimulus) is paired with the bell sound produced by the pad and bell system, the full bladder becomes the conditioned stimulus for the conditioned response of waking up. They were also interested to study the effects of Maximum Functional Bladder Capacity (MBC) and the childs affective issues using the Rutter A (parent) Scale to determine the outcome of the treatment for enuresis. Before the pad and bell system was introduced to the children, they were wetting their beds at nights at an average of 20 times in 28 days. Howe ver, after the pad and bell approach, on average the children were found to only wet their beds approximately 11 times in four weeks. Their treatment approach in dealing with the childrens enuresis worked for 34 out of the 54 children, which could be considered as a 63% success rate. They also found that those children who had failed in responding to the treatment had higher scores on the Rutter A Scale indicating the level of the childrens emotional instability. Therefore it could be understood that the remaining 20 children who did not respond to the treatment may be affected emotionally, thus preventing them to respond like the other children who are suffering from nocturnal enuresis. Although it has been proven that enuresis alarm has been effective for many children, the fact that every child is undergoing difference circumstances must be taken into consideration, and therefore expecting a generalised response may not be accurate. Given the right approach and environment, every child will be able to respond positively towards the treatment for enuresis using the alarm system. The parenting style is also equally important, given the role of parents in waking up the child when the alarm starts in the beginning stages. In families that practise neglectful parenting, it is unlikely for the parents to take the initiative to wake up and alert the child. As such, these factors should also be considered to assess the effectiveness of the treatment of enuresis using the alarm system. The next area that widely uses the principles of classical conditioning is the advertising sector. Gorn (1982) conducted a study on 244 college students to understand the effects of external factors such as background music and setting to influence the marketability of a product. He explains that people tend to respond positively towards a product that is being advertised if the advertisement catches their attention and creates a pleasant feeling by way of eye-catching colours, lovely music and hilarity. Therefore, the features of the advertisement act as unconditioned stimulus, while, the product acts as a conditioned stimulus after observing them together multiple times to produce a good feeling (unconditioned and conditioned response). In his study he made sure that the information of the product is minimally exposed to the participants to ensure that the unconditioned features were the ones that captured the participants attention and not the information. In the experiment, there were four conditions created. The first condition involved the pairing of a piece of favoured music with a pen of light blue colour. The next condition was to match a piece of favoured music with a pen of beige colour. The third condition was to match a piece of unfavoured music with a pen of light blue colour and the forth condition was to match a piece of unfavoured music with a pen of beige colour. It was found that a majority of the participants (74%) chose the pen that was presented with their favoured music. He explained that the participants with the favoured piece of music selected the pen based on the good feeling it created. To further support the positive outcome of classical conditioning, Tsai (2012) conducted a study on 172 undergraduates to understand the effects of classical conditioning in using movie stars to promote a product. He also mentioned that using celebrities as part of an advertisement is a popular practice in the United States and Britain. Tsai used an actor named Ethan Ruan as the celebrity to leverage on his popularity to promote an orange juice brand called GARRA. No additional information was added to the advertisement. The celebrity acts as the unconditioned stimulus that naturally draws a positive response from people (unconditioned response). The celebrity is paired five times with the conditioned stimulus, which is the virtual brand to produce a positive response to the brand (conditioned response). When respondents opinion on GARRA was compared between those who were put through conditioning and without conditioning, the results showed that the conditioned group (Ethan Ruan) ha d higher or more positive attitude towards GARRA. The attraction that people have for the actor was able to be transferred to the product or brand that the actor was promoting. Hence, after repeated exposure to the same unconditioned stimulus, GARRA (conditioned stimulus) automatically drew a positive response from consumers. Tsai also found that the appearance of celebrities in advertisements leads to a higher value in promoting a particular brand regardless whether the celebrities have done other advertisements before. While, the research involving celebrity such as Ethan Ruan was successful in this Taiwan study, the same approach might not be workable in a multi racial country like Malaysia where a celebrity who is well known to the Indian community may be completely unknown to the other races in the country. Thus, celebrity endorsement may not have a generalised outcome across the Malaysian population. Another point to note is that celebrity endorsement without a good quality pr oduct will not result in repeated purchases. If people are not satisfied with the quality of a product, they will not buy it the second time even if Brad Pitt or Jonny Depp advertised it. The next big sector that uses the principles of classical conditioning is psychotherapy in the management of phobia. Wolpe (1958) developed a method of dealing with phobia using a behavioural approach. He explains that a person has to be conditioned to develop unnecessary fear on a particular stimulus such as cockroach, snake, heights or even social engagement. The classic experiment conducted by Watson and Rayner (1920) on a small boy known as Little Albert is a good example to explain the development of phobia. They found that loud noise produces fearful feelings. Thus, the loud noise acts as an unconditioned stimulus to provoke an unconditioned response of fear. They tested their finding by pairing a white rat (conditioned stimulus) with a loud noise that was created using a steel bar and a hammer behind Little Alberts head multiple times, which produced fear (conditioned response; making Albert cry and move away). After multiple times of doing the same thing to Albert, he eventua lly developed fear (phobia) at the mere sight of a white rat. Based on this principle, Wolpe derived the idea of counteracting the phobia with a contradicting stimulus such as relaxation, which is called counterconditioning. Counterconditioning can be explained using a classic study by Jones (1924) on a child named Peter. He was afraid of rabbits (conditioned stimulus). She placed a rabbit in the same room but at the distance from Peter during the time that Peter was eating some cookies (unconditioned stimulus) which made him feel good (unconditioned response). This process was conducted multiple times resulting in Peter overcoming his phobia for rabbits. At the end of the counterconditioning period, Peter was able to have a rabbit on his lap happily (conditioned response). Wolpe (1958) explained that the process of counterconditioning should be carried out in several stages and conducted at a slow pace and this process is known as systematic desensitization. He explained that a person is usually asked to make a list from the lowest to the highest fear causing stimuli. The process of desensitization starts from the lowest first before moving slowly to the higher level of fear. The stimulus that causes fear is put forward to the person together with relaxation to produce a good feeling either through imagination or in vivo. To provide research evidence on the effectiveness of systematic desensitization, McCroskey, Ralph and Barrick (1970) conducted a study on 24 university students taking the public speaking class who were found to have an elevated level of anxiety to give speeches. The participants were randomly assigned to 3 groups with five members each, an hour of systematic desensitization session, for twice in a week almost three and half weeks. In the first session, the underlying principles of systematic desensitization were explained and the participants were also taught deep muscular relaxation. In the next sessions, beginning from the lower level of anxiety present in the hierarchy, the participants watched a video recorded session of public speech presentations. At any point of time when the participants displayed anxiety, they were told to raise their right index finger as that will cue the trainer to instruct all the participants within that group to stop the imagination of giving speech a nd focus on the deep muscular relaxation before resuming the session. The deep muscular relaxation was the unconditioned stimulus, which was paired with the speech presentation (conditioned stimulus) to eventually produce a relaxed state (unconditioned to conditioned response). For successfully completely each stage of the speech anxiety hierarchy, the participants were required to complete the first presentation of 15 seconds and second presentation of 30 seconds free from any signs of anxiety before proceeding to the next one. At the end of each session, the trainers presented the previous completed level of the speech anxiety hierarchy so that the participants level of anxiety is kept at a minimum level. This is done until all the stages within the hierarchy are completed. The last session ends with the repetition of the highest speech anxiety stimuli for one minute. At the end of the complete session, the participants level of speech anxiety was measured using Personal Report of Confidence as a Speaker (PRCS; Paul, 1966). According to the results, the groups that received systematic desensitization had a decreased level of anxiety by 54% while the control group only had a decreased level of 18%. Therefore, it can be concluded that the anxiety level for speech giving or any other phobia can be significantly reduced using the systematic desensitization method. This study is reliable given that the sessions were conducted continuously every week to ensure the effectiveness of the counterconditioning. However, the fact that it was done in a group could disrupt the flow of desensitizing an individual as each participant would have different level of phobia in terms of speech anxiety throughout each session. To further support the effectiveness of systematic desensitization in treating phobia or high level of anxiety, Johnson and Sechrest (1968) conducted a study on 41 psychology students. They used the Alpert-Haber Achievement Anxiety Test to measure the level of test anxiety at pre and post systematic desensitization. Those who had high test anxiety and scored low ( This paper discussed the use of classical conditioning in three different sectors, which are treating enuresis, advertising products and managing phobia in psychotherapy sessions. In treating enuresis, the use of classical conditioning is an ideal method as it is non-invasive and the results have been found to have a high reliability and validity value. In the advertisement sector, classical conditioning has been proven to increase the marketability of the product. It is a common practice for businesses to use celebrities to advertise their products to increase the amount of sales. Meanwhile in the psychotherapy sector, systematic desensitization is one of the most prominent methods of dealing with phobia, as it helps to deal with difficult irrational fear which has affected people for a long period of time. In a nut shell, classical conditioning is effectively used in many other sectors apart from those discussed in this paper.

Ban a Pit bull, Save a Life: Why the Ontario Ban against Pit bull Terri

â€Å"Mom! Mom! The dogs got Cody. The dogs got Cody† (Vancouver Sun, 2007). Just a few days after Christmas in 2004, these are the cries that awoke Sheri Fontaine. Fontaine raced from her bed into the living room to find her three-year old son, Cody Fontaine, savaged by the dogs that were staying temporarily in her house. Tragically, young Cody did not survive the attack. A young life taken, a mother’s life ruined. Sadly, this story is not as uncommon as one of violence against people, they exhibit highly stubborn characteristics that make them difficult to control, and such bans have proven to be extremely effective. In 2005, the Ontario Liberal government passed The Dog Owner’s Liability Act: a ban against pit bull terriers in the province. After the bill passed, Attorney General Michael Bryant said, â€Å"Mark my words, Ontario will be safer† (Ontario passes ban on pit bulls, 2005). The legislation prevented people from acquiring a number of breeds of dogs that would be classified as pit bulls. In addition, Ontario residents who already owned a pit bull terrier prior to the ban were required to neuter and muzzle their animals. Such policies against this breed of animal are not unprecedented. In fact, similar laws are already in place in Britain, France and Germany. In Canada, Winnipeg has had a ban against pit bull terriers in place for 20 years (Ontario passes ban on pit bulls, 2005). Ontario and other regions have imposed these sanctions because the evidence clearly indicates that pit bull terriers pose a much higher than average risk to people. Pit bull terriers have a long track record of attacks against people and animals. A 1987 study of a particularly savage attack against a child was documented by four doctors in the hopes... ... An Analysis of the Pit bull Terrier Controversy. Anthrozoos, 2-8. Raghavan, M. (2008). Fatal dog attacks in Canada, 1990–2007. The Canadian Verterinary Journal, 577– 581. Ruryk, Z. (2008, March 2). One endangered species: But pit bull attacks are down. Retrieved April 20, 2011, from Toronto Sun: http://www.torontosun.com/News/TorontoAndGTA/2008/03/02/4887415-sun.html Smith, C. (2009, April 9). Media coverage of Surrey pit bull attack prompts protest by Vancouver pit bull owners. Retrieved April 20, 2011, from Straight.com: http://www.straight.com/article- 213929/media-coverage-surrey-pit-bull-attack-prompts-protest-vancouver-pit-bull-owners Vancouver Sun. (2007, February 6). Kids' cries woke mom of boy, 3, killed by dogs' bites. Retrieved April 20, 2011, from Canada.com: http://www.canada.com/vancouversun/news/story.html?id=a79e501c-14a2-4964-aa02- f9a5ab25d2a5 Ban a Pit bull, Save a Life: Why the Ontario Ban against Pit bull Terri â€Å"Mom! Mom! The dogs got Cody. The dogs got Cody† (Vancouver Sun, 2007). Just a few days after Christmas in 2004, these are the cries that awoke Sheri Fontaine. Fontaine raced from her bed into the living room to find her three-year old son, Cody Fontaine, savaged by the dogs that were staying temporarily in her house. Tragically, young Cody did not survive the attack. A young life taken, a mother’s life ruined. Sadly, this story is not as uncommon as one of violence against people, they exhibit highly stubborn characteristics that make them difficult to control, and such bans have proven to be extremely effective. In 2005, the Ontario Liberal government passed The Dog Owner’s Liability Act: a ban against pit bull terriers in the province. After the bill passed, Attorney General Michael Bryant said, â€Å"Mark my words, Ontario will be safer† (Ontario passes ban on pit bulls, 2005). The legislation prevented people from acquiring a number of breeds of dogs that would be classified as pit bulls. In addition, Ontario residents who already owned a pit bull terrier prior to the ban were required to neuter and muzzle their animals. Such policies against this breed of animal are not unprecedented. In fact, similar laws are already in place in Britain, France and Germany. In Canada, Winnipeg has had a ban against pit bull terriers in place for 20 years (Ontario passes ban on pit bulls, 2005). Ontario and other regions have imposed these sanctions because the evidence clearly indicates that pit bull terriers pose a much higher than average risk to people. Pit bull terriers have a long track record of attacks against people and animals. A 1987 study of a particularly savage attack against a child was documented by four doctors in the hopes... ... An Analysis of the Pit bull Terrier Controversy. Anthrozoos, 2-8. Raghavan, M. (2008). Fatal dog attacks in Canada, 1990–2007. The Canadian Verterinary Journal, 577– 581. Ruryk, Z. (2008, March 2). One endangered species: But pit bull attacks are down. Retrieved April 20, 2011, from Toronto Sun: http://www.torontosun.com/News/TorontoAndGTA/2008/03/02/4887415-sun.html Smith, C. (2009, April 9). Media coverage of Surrey pit bull attack prompts protest by Vancouver pit bull owners. Retrieved April 20, 2011, from Straight.com: http://www.straight.com/article- 213929/media-coverage-surrey-pit-bull-attack-prompts-protest-vancouver-pit-bull-owners Vancouver Sun. (2007, February 6). Kids' cries woke mom of boy, 3, killed by dogs' bites. Retrieved April 20, 2011, from Canada.com: http://www.canada.com/vancouversun/news/story.html?id=a79e501c-14a2-4964-aa02- f9a5ab25d2a5

Adult Development

The results of the interview with my three participants of varying levels of adulthood have indeed demonstrated that their changes are linked to normative age-graded influences (Bjorklund & Bee, 2006). With respect to cognitive changes, Mrs. Sarai Knowles, a 47 year-old mother of three, has within the past three or four years noticed an increase in the amount of time it takes for her to remember the names of everyday objects.She admitted that this phenomenon was preceded by increased difficulty remembering less concrete words, such as adjectives she may have used to help her articulate when having conversations. The onset of memory changes during middle adulthood was corroborated by the other two participants. Though older, Mr. Sean Blankett (72) and Mrs. Evelyn Richardson (88) do recall having such minor, yet progressive memory lapses at approximately 45 years of age.All three participants say that the change has frustrated them during conversation and two of them (Blankett and Rich ardson) say they have had to develop strategies for giving themselves time to think of words during conversations. Mrs. Knowles indicates that she is not sure whether the condition really is one that should be considered a problem. She considers herself to be doing as well as other adults her age. Here she makes reference to her functional age (2006).What activities do you know of that might help you maintain your cognitive abilities over time?To maintain memory health, two of the three participants referred to cardiovascular and neural fitness (Bjorklund & Bee, 2006, p. 126). Mrs. Richardson and Mr. Blankett have mentioned trying to eat more rich colored vegetables.They both also attempt to perform exercises, which they feel have the power to increase blood flow to their tissues (physical activity), including their brains and thereby keep them more alert (2006, p. 126). Mrs. Richardson also regularly does puzzles (Sudoku) in an attempt to keep her mind alert, and Mr. Richardson rea ds a lot.These are examples of intellectual activity (2006, p. 125). Mrs. Knowles admits she is too busy to do anything to improve her memory. She has an idea of the existence of particular vegetables that do improve memory, but she is not sure specifically which ones they are and has not had the time to find out.How did/do these roles (marriage, parenting, and grandparenting) affect their satisfaction in life?When asked about the roles they have filled and the effect that these have had on their lives, Mrs. Knowles and Mrs. Richardson found the role of parenting to be very fulfilling. They enjoyed taking care of their children and even the challenges that attended the years of child rearing. In comparison with grand-parenting, Mrs. Richardson found parenting to be easier but gained a similar amount of satisfaction from grand-parenting.She considered grand-parenting to have the added satisfaction of watching her own children fulfilling the responsibility and gaining the pleasure of being parents. Mrs. Knowles admitted she had limited knowledge of the grand-parenting stage, considering it to be as distant as retiring.On the other hand, Mr. Blankett cited the milestone of marriage as the one that really changed his life because it ushered him into the role of being the provider—first for his wife and then for the family they reared.Mrs. Richardson mentioned the idea of bereavement as being a part of marriage, as one spouse must die before the other. She admitted to feeling death anxiety before her husband died. He was chronically ill for thirteen years.Because of this, she was able to speak of the several ways in which the process death was a loss for her husband (Bjorklund & Bee, 2006, p. 325). He lost functionality gradually, and in a way she said this was like him losing his body before he died. He did lose his relationships too because he became unable to spend time with his friends in the way he used to before his illness.He was also unable to visit his children and grandchildren in the way he would have if he had been healthy. In a way, for Mrs. Richardson’s husband, his final death was only the end stage of a long process of death.All three participants speak of their impending death with some measure of apprehension, but for Mrs. Richardson it appears to be less scary as she indicates she is ready to go and be where her husband is. She apparently believes in an afterlife (2006, p. 325).She will, however, miss her children and grandchildren. Mrs. Knowles does not want to think of death as she still has children who are not yet fully grown (teenagers) and her husband needs her.[For the purposes of confidentiality, fictional names have been used.] ReferenceBjorklund, B. R. & H. L. Bee. (2006). The Journey of Adulthood. 6th Ed. Upper Saddle River: Â   Prentice Hall.

Business Essays - Online Shopping Mall - Free Essay Example

Sample details Pages: 20 Words: 5992 Downloads: 9 Date added: 2017/06/26 Category Business Essay Type Research paper Did you like this example? Online Shopping Mall This report presents the feasibility study for developing the online shopping mall for UK retail outlets and customers. The idea was generated by looking at the staggering growth of the internet user and online shopping specially in UK with a record 12.8 billion pound online sale last year. This report analysis the need for online shopping mall as it provides a big opportunity to those who have less technical skills in developing the retail online sites for themselves and these hosting sites will help them do the online business with les administration for a fee only. Don’t waste time! Our writers will create an original "Business Essays Online Shopping Mall" essay for you Create order The report is divided into nine sections starting from the explanation of what are online shopping mall and its importance in todayà ¢Ã¢â€š ¬Ã¢â€ž ¢s competitive business world along with the emphasis on how technology helps business to grow. Types of technology available for developing online shopping mall are also discussed. For backend development MySQL 5.0 database is used. On front end JSP will be used to develop the script as ità ¢Ã¢â€š ¬Ã¢â€ž ¢s easy to learn as well as more versatile. The basic cost involved is for renting the space on ISP servers, the purchase of domain name, the registration with the search engines (directories) and the most important advertisement to generate traffic for the online shopping mall. In the end a detailed project plan on the basis of time and activities is explained in context of the feasibility of online shopping mall from data study till construction of the site and maintenance. Aims and Objectives Aims The aim of this study is to present a formal report and a power point presentation on the feasibility of developing the online shopping mall for UK customers and retailers. Objectives The objective of this feasibility report is to: Provide about the background, importance and growth of the online shopping mall in UK. Preparing a feasibility report by providing the information regarding site development, technology available and cost involved Prepare the project plan and Prepare a four minute power point presentation to explain the feasibility of online shopping mall. 1. Introduction 1.1 Concept of Online Shopping Mall The idea of online shopping mall originates from e-commerce. E commerce is in practice in most of the developed countries of the world such as USA, UK, and Europe etc where shopping concept is changing from physical purchase to virtual buying. This type of business is very popular among the retail outlets that are looking for a boost in their sale by offering customers new channels or mediums to make a purchase. This way not only the customer has more options but companies also enjoy an increase in their sale due to increased online outlet. Even after the immense success of e commerce there was a big group of business who either knew how to do e-commerce or they were unable to manage the administration of such technical field which required a lot of web knowledge. This generates a need of a place where these retail outlets can start their online business but without any hassle. Online shopping mall is basically the by product of e-commerce. The idea is to provide the easiest platform to these retail outlets that can do online business without any trouble or risk. Ità ¢Ã¢â€š ¬Ã¢â€ž ¢s a site where any retail outlet can get registered and have a space and the rest of the administration will be done by the host of that online mall. Not only that but also the host will be the one who will take c are of all payment procedures. Online shopping mall provides a lot of benefits to the retail outlets on the site such as administrative, management of the site as well as invoicing of the business. Customer is benefited too. He has not only the variety but also ease to find what ever he is looking for at one place. The choices available to customer is many as products available on online shopping mall can range from within the product category (all Nike products) or an entirely different product type ( homecare, clothing, electronics etc.) from as many retailers possible . 1.2 Scope of Online Shopping Mall In UK Europe has a staggering 42 million user of internet and talking of Britain, 11 000 users are adding to the list annually. This gives an immense boost in the revenues generated by online activities on monthly basis. Among all the internet activity online shopping is not only generating the maximum revenues but also is growing at the fastest speed. It can be proved by the fact that almost 30% of all the sites are used for trading rather than attracting the advertisers for the means of business. By looking at this statistics and knowing that this will grow to another 30% within next few Yearsà ¢Ã¢â€š ¬Ã¢â€ž ¢ businesses are attracted towards internet to boost their sale with a relevant low cost, one of the best feature of online shopping. Moreover online shopping mall further reduces the cost and hassle for those retailers who have less technical skills to take the optimum advantage of the online business. According to the report of Ian Grant, as compare to Italy, Germany, F rance etc UK is the top most country in online shopping having a sale of approximately 12.8 billion pounds along with a record growth of 75% in online sale since 2005 till date 2. Building The Online Shopping Mall In general there are 4 basic steps which you have to follow to have an online shopping mall Get a company who will host your site Get yourself domain name for your online shopping mall. For a search engine you need to get directories. So Register with them Attract internet user through advertisement ( traffic generation) To maintain the sites you have to arrange the important tools required for order processing, invoicing and transaction 2.1 Background Research For Building An Online Shopping Site Before starting to build an online shopping mall we need to have clear idea of few things that will be needed once the site is complete. Domain name Website Hosting Secure Server Certificate Merchant Account Payment Transaction gateway. 2.1.1 Domain Name The domain name is that name by which will be recognized on the internet, to show our online appearance we need a domain name for our website, this name can be a of up to 67 characters in length and should be easy and meaningful to remember so that customer can remember it easily. The domain name is registered with a suffix, this suffix is a à ¢Ã¢â€š ¬Ã‹Å".à ¢Ã¢â€š ¬Ã¢â€ž ¢ Extension and represents the nature of the website. Few common extensions are .comà ¢Ã¢â€š ¬Ã¢â‚¬Å" used for commercial business website .net.à ¢Ã¢â€š ¬Ã¢â‚¬Å" used for commercial network .org à ¢Ã¢â€š ¬Ã¢â‚¬Å" used for organization. There are other extensions available as well these include, .biz, .edu, .tv etc. Choosing a domain name is a difficult task as here are around 128 Million domain names registered and that is the reason thatà ¢Ã¢â€š ¬Ã¢â€ž ¢s why choosing a name that will represent out MALL will be a difficult task as most of the name are already taken. Therefore lots of brainstorming is required to select a name with following quality. It should be short Easy to memorize Should not be confusable. Not easy to misspell Should represent the MALL Considering these factor we can choose a domain name that will represent our website. 2.1.2 Website Hosting A web hosting company provides space and bandwidth on rent, once our site is developed we can put the content of the website on the allocated space on the hosting server, this transfer can be made from development site to hosting server using File Transfer Protocol (FTP) softwareà ¢Ã¢â€š ¬Ã¢â€ž ¢s. Once website is uploaded and domain is directed to rented space. The site is up and running and whenever user enters the domain it is directed to this space. A web server is a powerful computer machine which is designed in such a way that it can bare the load of internet traffic accessing the website present on it. This server can be on any plat form either Linux or Windows but should be able to handle the load. The web hosting companies usually setup these servers in data centres; these data centres are responsible for making the backup and providing security of data. The key responsibility of data centre is to make sure that website is always present on the internet. A typical p rocess of how the web server makes a bridge between the website visitor and the administrator of the website is shown in the diagram below (courtesy of eaysiteguid.com) The visitor enter the domain name of the mall in the web browser, the domain name is resolved on the domain name server (DNS) and the user browser connects to the web server which in return send the contents of the website to the visitors browser. Similarly the developer can connect to the web server to upload new contents and for management of website. 2.1.3 SSL Protection Secure Socket layer (SSL) is the technology that provides an encrypted link between your host site and the web server. An SSL is required as we want to provide safe environment to the customer as our website will be involved in credit card transaction, and there might be a chance of theft of information and customer personal information can be jeopardized. For our Shopping Mall we require SSL certificate to make our customer feel comfortable while they are giving there information to us, they need to be sure that there information will be kept private and only will be used for the transaction they are making, we are obligated to protect our customers. In the real mall there are guards to protect customers and shops from theft same as we need SSL as our mall guard. Another reason of implementing SSL is that there can be legal consequences as if some oneà ¢Ã¢â€š ¬Ã¢â€ž ¢s information is compromised, then as we are not involved in theft but we can be the source that gives the w ay to let other people information accusable and that customer can get us in to trouble. So SSL can be our first line of defence. Therefore a SSL certificate is required for our eCommerce site as we may loose customers if we canà ¢Ã¢â€š ¬Ã¢â€ž ¢t protect there information. How SSL Protects In SSL the transfer of data from the user webpage to the web server is in encrypted form, the code is scramble in such a way that no one can use it outside, the encryption can be 128 bits or 256 bits depending on the complexity of encryption, mostly for online shopping site 128 bit encryption is used, the 256bit is usually used by banks. This certificate is issued by the SSL issuing vendor that provide certificate with a encryption key, this encryption key is put on the server that do the SSL encryption, the website host will install this certificate on the web server, once installed when a customer access the site, a padlock is shown on the bottom of the browser that tell that this site is secure, opening the padlock shows the certificate, which tell whoà ¢Ã¢â€š ¬Ã¢â€ž ¢s this certificate belongs to. The cost of SSL is declined rapidly from 400 pounds to now it is between 20 to 60 Pounds per year, SSL can be purchase by different vendors like VERISIGN. There is a facility to g et a shared SSL which is provided by the host. This SSL certificate is further cheaper but the drawback is that when a user or customer check the certificate the name of the host appears on the certificate instead of the merchant that can cause confusion on user mind as the information will not match with the site owner. So ità ¢Ã¢â€š ¬Ã¢â€ž ¢s best to have our own SSL certificate, after getting the certificate we can install the certificate on the root directory of our web server. 2.1.4 Merchant Account A merchant account is an account which is provided by banks or finical institution. This type of bank account allows any e-commerce business to accept credit cards online, it is used by customers to deposit the money electronically that is through credit cards, the process where the money is transferred through credit card is called Card Not Present (CNP) merchant account and is needed when the customer donà ¢Ã¢â€š ¬Ã¢â€ž ¢t send the money in physical form during the transaction. Merchant account can be opened by any bank which gives this facility to the merchant to accept transaction electronically. To open a merchant account negotiation is done with the bank or institution over the different charges, these charges involved Up Front Application Fees: This is the fees that the provider charges for handling the transitions, as the number of merchant account provides are increasing and competition is building up, most of the providers waive this fee off. Statement fee: This is the fix amount fee that the merchant have to pay for his account, this is normally around 10 to 15 pounds per month, and this fee is also called on going fixed fee. Discount rate: This is the sales commission charge by the merchant account provider on each transaction; it is normally between 2 to 4 percent of the sales. Fixed Transaction Fee: This is the fixed transaction fee for each sale, unlike the discount rate this fee is a fixed amount and not the percentage, this fee is usually 0.05 to 0.01 pounds per sale. Termination Fee: This fee is charged if the account is closed before the contract period is ended. Chargeback Fees: This fee is charges if a customer wants a refund and want to withdraw there money then the merchant account provider will charge a fee usually between 5 to 10 pounds on each withdrawal. A merchant account acts as a go between your gateway (Credit card processor) and your business account, the money comes to this account and passes to your b usiness account and if there are chargeback or user cancel the transaction money is takes from you business count and from merchant account gets out. 2.1.5 Payment Method The payment method on an online shopping site the process is almost same as the physical shopping site, like in shops peoples comes select items or products and pay cash on the counter, in online shopping site customer visit the website select item and put in the basket ( THE CART) and finally checkout using credit card. Once customer is checkout his credit card is needed to be verified, this is checking whether credit card is valid and that there is money in the account and also that there is no fraud case. The checking of the credit card can be done by using a payment processing method; there are two types of payment processing methods Payment Processor Payment Gateways Payment Gateway This method involves checking credit card information in real time as the transaction is taking place, The gateway service is provided by different companies like LinkPoint, Authorize Net etc. The gateway processor verifies the credit card information in real time and completes the whole process (acceptation or rejection) of payment within second and traction results are displayed to customers. The process works like this. After customer has decided the item he wants to purchase he clicks the BUY button on the webpage. Once the customer is finish with shopping, he clicks on the checkout button which takes the customer to a secure form where his personal information is entered including the credit card information. The credit card information is send to the payment gateway. The gateway processor sends the transaction data to merchantà ¢Ã¢â€š ¬Ã¢â€ž ¢s bank, which then passes the information to Credit card interchange. The credit card interchange then sends the data to credit card issuer for verification. The issuer then verifies the data and sends the result to credit card exchange whether the information is valid or not. The credit card exchange then sends the acceptance or denial information to merchantà ¢Ã¢â€š ¬Ã¢â€ž ¢s bank processor. The transaction results send by the merchants bank processor are passed to payment gateway. The payment gate way then send the denial or acceptance information to the merchant who then display the confirmation or rejection of purchase on the webpage. If transaction is successful the merchant account is debited and customers is credited (this process is done in real time). The whole process is depicted in the figure below Advantages This method provides professional solution as all the transaction is done in real time. Transaction result can be displayed on the webpage that is acceptance or denial The process is invisible to the customer. The funds are directly deposited in the merchantà ¢Ã¢â€š ¬Ã¢â€ž ¢s bank account. And merchant donà ¢Ã¢â€š ¬Ã¢â€ž ¢t have to worry about fund deposition as the whole process is automatic. This is because the fraud is detected before the product is shipped. Some service provider provide fraud protection as well, this protects the merchant and the actual card holder to become the victim of fraud. Transaction fee and service charges are less then of payment processor. Disadvantages This mode of payment processing required a merchant account Cost of setup is high then payment processor. Payment Processor This method is also called delayed response as the transaction is not completed in real time. When the user is ready to checkout he is redirected to payment processor service provider, such as PayPal, Verisign PayFlow link etc and these providers then handles the transaction for the merchants. The customer is informed about the completion of transaction once he is finish checkout but in actual the process is of verification is started at this time. The credit card is processed and transaction approval or decline results are informed to the merchant who is then responsible to inform the customer about the transaction approval or rejection thought email. The process works like this: After customer has decided the item he wants to purchase he clicks the BUY button on the webpage. Once the customer is finish with shopping, he click on the checkout button which takes the customer to a secure form on a third party website where his personal information is taken, once user finish checkout he is shown transaction is complete The user part is now done, the user thinks that transaction is complete but in actual the information is send to payment processor that then communicates with the banks to authorize the credit card. This process can take minutes or up to a days If transaction is denied the merchant are notified through an email, if transaction is successful the cash is deposited to merchants account. Other wise merchant has to inform the customer that the transaction is denied. Advantages No merchant account is required as third party processor will handle the transaction and will deposit the money to your account Cost less to setup then process gateways. Transaction fee and process charges are less then process gateways. Disadvantages Delay in transaction process to complete Credit card is checked for authorization after the user is informed that transaction is complete. Customers are redirected to third party website such as PAYPAL etc for checkout process and to finish transaction, this losses the uniqueness of branding as customers sees that he is being redirected and this causes the flow to break. Customers are informed later whether the transaction is accepted or denied, and if denied then customer can get irritated. 3. Initial Requirement 3.1 The Users The concept of this project is to design a website mall which can serve two types of customers one will be the shop owners who would like to open a shop in our virtual mall and second will the customers who will purchase item from those shops. An Administrator will be the one who will administer the mall, the shop owners and the customers. Therefore our design should coupe up there type of users, this include the ADMINISTRATOR who will be looking before the whole site, The SHOP owner who will be managing a shop in the Mall, and the CUSTOMER who will be purchasing the products. 3.1.1 Administrator Administrator will be user who will have full access to the MALL, he can be said as a super user, all the request to open a shop will be send to the administrator and then admin will decide weather to accept the request or reject it Admin will also responsible for managing the categories or subcategories of shops, he can add remove or update them as required without affecting the shop owners. Admin will also look after feedback sent and can reply to them or remove them. The Use case diagram below show what actions admin can perform in the system. 3.1.2 Shop Owner If a user want to open the shop in the mall, he will fill in the form and send it to administrator, If his request is approved by the administrator and is granted space in the mall he will become the shop owner, The responsibilities of shop owner is to manage the shop, he can add remove categories, design a catalogue and can remove, add or update item in the catalogue. He can also generate several reports regarding the sales and inventory that will keep him up to date f the business. A shop owner can remove the shop anytime he wants. The Use case diagram below shows what action shop owner can perform on the system. 3.1.3 Mall Customer Mall customers will be the users who will purchase products from the mall; they can browse the mall search shops, products within different shops and can compare prices. After they have decided what they want to buy, they can add the items to the shopping cart and can checkout at any stage during there stay on the virtual mall, when checking out customer can login and all this information will be updated in the checkout form. A customer can login any time to view his order status or he can change his personal details like shipping address and other information. The Use case diagram below shows what action mall customer can perform on the system. 3.2 Mall Interface An initial study was done on what interface will be created for the Mall, these interface includes. 3.2.1 Admin Interface ADMINISTRATOR ADMIN:This interface will only be available to administrator and let user administer the site from accepting shop request to generating reports and modifying site contents. 3.2.2 Shop Owner Interface CATALOGUE CREATOR: A catalogue creator interface will be available to shop owners where shop owners can add, remove or update items by category. These items will be added to the catalogue accessible by the customers. SHOP OWNER ADMIN: This page will be available only to shop owner from there he can perform the administration of this shop, this include link to catalogue creator, report generator and information updater. 3.2.3 Customer Interface CATALOGUE: For every shop a catalogue will be created from where customer can find item information and price. PRODUCT SEARCH: A search page will be build where customer can search for products this page will fetch the results from the data base and display them on the search page. SHOP SEARCH: This feature will allow customers to search for shops by categories SHOPPING BASKET: A shopping basket will be created which will be linked with the BUY button and when a customer hits the buy button the selected item will be added to the basked, the customer can view this basket to update or remove items. CHECKOUT FORM: A form will be created that will take customer information and send it to processor gateway for verification and save the transaction data in the database. 3.2.4 Miscellaneous LOGIN INTERFACE: A login interface will be provided where administrator, shop owner and customers (optional) can login; the user will be directed to the page his user type belongs to. REGISTRATION PAGE: This page will let user to register with the site either as a customer or shop owner. 4. Technology Available for Development Now dayà ¢Ã¢â€š ¬Ã¢â€ž ¢s different technologies are available for developing software and website. Few of them are open source and do no add cost in development. For building our website we require to choose technology for Backend and Front end development. 4.1 Backend Backend is where the Website data will be stored, this data can be of the customer, shop owner or can be site contents. For an ecommerce application databases are the foundation, all the information comes from the database and all the information will go to the data base. There are several databases technologies available like MSACCESS, MSSQL and MYSQL. MSACCESS is Microsoft database that can run on windows based servers. It is used for small scale ecommerce website, it is easy to develop database using MSACCES for developing low traffic site. It is a file based database and the problem with file based database is that if a data base crash all the data is lost. MS SQL SERVER is also Microsoft based database server which has wide support, it has powerful enhanced feature like stored procedure. It is very fast and stable. A free Express developer edition is available to create local database for development and testing. MYSQL SERVER is an open source database, it also has extremely huge support community, the version 5 has enhanced feature that can be used to create enterprise level databases. It is super fast and stable as compare to other databases. MYSQL is also multi platform so that it can be deployed on any web server running on either windows or Linux. It is important that data base should be build correctly as application will run on top of it and after launch of website if a serious flaw is found then ità ¢Ã¢â€š ¬Ã¢â€ž ¢s hard to fix the problem as data base structure has to be changes that can shake the foundation of the application. So ità ¢Ã¢â€š ¬Ã¢â€ž ¢s necessary that through time should be spend in designing of database. Few factors were conceders while choosing the database. These factors involve: Stability: The database should be stable and should not crash as this can make the site down which can cause potential loos to business. Scalability: data base should be scalable to handle large amount of data and can be extended if necessary once build. Speed: Speed is once of the important factor, the database should be able to retrieve information on fast rate so that customers or users donà ¢Ã¢â€š ¬Ã¢â€ž ¢t have to wait for the data to be fetched; the data based should be able to optimize queries. Referential integrity: This concept involves that data base should be developed in such way that inconsistent data should not be saved in tables. 4.2 Frontend Front end is what the user will see on the webpage, this user can be a customer or the Mall administrator or shop owner. The front ends code brings the information back from the backend and display to the user or take the information from the user and send it to back end for processing or storage. We require a scripting language that can be used to develop font end. There are different scripting languages available for writing server side scripts like ASP, JSP and PHP etc. ASP: Active Server pages ASP is Microsoft developed scripting language used to create dynamic WebPages, it is used by many web hosting companies and lots of material and books are available, the disadvantage of using ASP is that the code can be writing by using only VBScripts as Microsoft bounds that, and writing code in VBScripts has its own limitation. JSP: Java Server pages is another technology of creating dynamic WebPages, it is based on JAVA programming language to design server side code. The JSP cod e is incorporated in HTML files by using special tags to write dynamic contents. The JSP source code is executed from the server on JSP Servelet Engine; this Engine then generates the HTML and sends the output to client browser. The advantage of using JSP over ASP is that ASP is based on Microsoft .NET architecture and can only run on Microsoft platforms where as JSP is Cross platform and can be run on any platform like Linux and windows. Another advantage of Using JSP is that beside its Object oriented, it can be used with different technologies like, Extended java beans (EJB), SERVALETS and AJAX to make site more interactive. PHP: PHP is one of the widely used server side scripting language, by using PHP dynamic websites can be created which provide interaction of user with the website. PHP is cross platform language that is PHP scripted running from Linux web server can be executed on windows machine and vice versa. The language is open source and is available without any c ost, beside open source it has huge development community with can be contacted for help if required. The language is fast, stable and secure. 5. Selected Technology 5.1 Backend Backed will be developed using MySQL 5.0. The reason for using MySQL is that it is open source and will not add cost in development, beside that it have extremely wide support and a huge developer community from where great help can be obtain. Other reason is that it is expected that the site will have heavy traffic and fast stable and secure database server is required and MSSQL is the only open source database that can be relied upon. The 5.0 version of MySQL also includes the stored procedure call, a stored procedure call can save the query data that is frequently used so that that data does not need to be fetch from table again and again, and ità ¢Ã¢â€š ¬Ã¢â€ž ¢s a sort of caching. Beside that MySQl has built in security feature and as MySQl database is not a file thatà ¢Ã¢â€š ¬Ã¢â€ž ¢s why it canà ¢Ã¢â€š ¬Ã¢â€ž ¢t be copied from the server, MySQL is also multi platform and can be deployed on any server. 5.2 Front End JSP will be used to develop the front end scripts as we have previous background of JAVA and JSP is based on java and is easier to learn and to develop and it is more versatile and different technologies will be used like SERVALETS and AJAX to make the shopping experience more interactive and as AJAX function can be executed on user browser therefore carefully writing the function can decrease the bandwidth usage hence making the website much fast. 6. Cost Involved Building and making the ecommerce site functional require cost, this involves the cost of softwareà ¢Ã¢â€š ¬Ã¢â€ž ¢s that will be need to develop and design the website to buying the domain names and hosting service and after site is launched cost of advertisement is involve. A detailed chart of the cost involved in development and after development can be seen in table below. ITEM COST Specification Domain Name 8.99 £/year .com domain Hosting Server 70 £/month Processor 2 x Intel E5310 Quad Core Xeon 1.6GHz Memory 2 x 2GB Hard Disk 2 x 500GB RAID1 10TB Monthly Traffic Yes 100Mb Network Speed Yes SSL 14  £/year 128 bit Search Engine Submission 30 à ¢Ã¢â€š ¬Ã¢â‚¬Å" 150  £/year Maintenance 100 à ¢Ã¢â€š ¬Ã¢â‚¬Å" 500  £/year The actual cost of building a ecommerce site is around 3000 £ but most part of this cost is taken by the development company but as we are building the online shopping on by our own there fore this cost has been cut. We will be using open source software like MYSQL and JSP there the cost of development tools are also cut. The initial budget is therefore around 500 £. The actual increase of budget is when the shopping mall is up and then budget for advertisement will be made take can be around 2000 £ initially, but we donà ¢Ã¢â€š ¬Ã¢â€ž ¢t have to worry about this right now. 7. Phase of Design and Development The online shopping mall will be developed by using the Water fall model; the proceeds will be executed in phases. In first phase the feasibility was conducted which result in form of this report. Other phases that will be involved in process are. Requirement Analysis In this phase the requirement will be made that are to be implemented in design, this phase involve full study of what will be responsibilities of Admin and Shop owners. The factions they can perform on the website and the outcome they expect, on the other hand the requirement for customers will also be taken consider off, what the customers can expect from the site. After the requirement are analysed the project will be moved to next phases where the system will be analysed. System Analysis After the requirements are finalize then in next phase (based on the requirement gathered) website will be analysed by creating different UML diagram, this involves creating use cases, data flow diagram and creating the model of data base which include creating tables and then normalizing them to make them optimized. After the system analysis phase is over the Design phase will begin. System Design In this phase the architecture of the website will be designed this include designing the WebPages and to create the site map which will include how customer or admin can navigate through site, in system design phase also the design of shopping cart and catalogue will be considered. After the process of designing is complete then the Development phase will begin. System Development This phase will involve the coding the system, in this phase website code will be written, the code for shopping cart and checkout will be written. At this stage the database will be created and link to the website. The whole process of development will be done on development servers. Testing As the system is being developed the testing will be started in parallel so that flaws can be fixed as they are discovered. The process of Testing will involve the unit testing in which each page is tested one by one, also functionality of the website will be tested this include testing the process of creating of shops, catalogues and process of checkout. The process of testing will continue during the rest of the website building process. Implementation Once the system (website) is developed and tested it will be shifted to production server (the host). And production testing will begin which will test that website is configured properly and all the functions are working on production. Site Launch After the system the up and running and tested on the production server the site will be made available for the user. 8. Project Plan 9. Conclusion The study is concluded by focusing on the fact that the future is all about online business. More and more people are attracted towards internet which gives them an easy access to the business world and in return the business world enjoying the raising sale every quarter. The advancement in technology helped both, the user as well as the retailer, to gain profits. Online shopping mall is a less expensive medium not only for the hosting company to start this as a business for but also for the retail businesses to open more and more outlets online with a minimum cost of may be two to three thousand pound per annum providing customer with a lot of options with a click. With this, it may be concluded that online shopping mall is a feasible business for people with technical skills and knowledge. References Practical Advice for business [online].Available from: www.businesslink.gov.uk E-commerce information [online].Available from: globalpay.co.kr/worldpay/news/ecom_info.shtml Black Enterprise. 1998. Opening your own shopping mall [online].Available from https://findarticles.com/p/articles/mi_m1365/is_12_28/ai_54195646 How to choose domain name for your site [online]. Available from: https://www.siteground.com/choose_domain_name.htm Web Host Guide- INSTRODUCTION [online]. Available from: https://www.tizag.com/webhost/ Choosing an Internet Merchant Account [online]. Available from: https://www.findmyhosting.com/web-resources/Articles/internet-merchant.htm Secure Socket Layer [online]. Available from: https://info.ssl.com/article.aspx?id=10241 Simple guide of taking payment online [online]. Available from: https://www.easysiteguide.com/articles/web-hosting/basic-web-hosting-model.html Merchant Accounts [online]. Available from: https://www.lubashawebsolution.com/Results.tpl?rnd=421cart=1205311913808444category=46startat=1 Virtual Shopping Mall [online]. Available from: https://www.oracle.com/technology/sample_code/tutorials/vsm1.3/files/over.pdf Website Development Budget [online]. Available from: https://www.easysiteguide.com/articles/web-hosting/basic-web-hosting-model.html

The Markowitz Mean Variance Optimization Model Finance Essay - Free Essay Example

Sample details Pages: 17 Words: 5144 Downloads: 2 Date added: 2017/06/26 Category Finance Essay Type Analytical essay Did you like this example? Abstract This project examined the optimal allocation of stocks based on the Markowitz Mean Variance Optimization Model. It is mainly based on the comparison between two samples of stock returns. The first sample is referred to as the full data set, and contains the returns of the stocks GE, Baxter, Dow, Caterpillar, Apple, and Procter and Gamble calculated over the period of five years. Don’t waste time! Our writers will create an original "The Markowitz Mean Variance Optimization Model Finance Essay" essay for you Create order The second sample takes the 250 most recent daily returns as the base data set. The objective is to find the optimal allocation in a portfolio of risky assets only and the Complete Portfolio that an investor could choose in order to maximize his utility. Before analyzing the results from the optimization process, we started by analyzing the data, and verifying that the assumption of normality the model is valid in both data sets. Then we describe the results given by the different optimizations that we calculated and we compared both samples showing the optimal allocation for risky assets only and the optimal allocation that includes the risk free asset. Then, we graph the efficient frontier along with the capital allocation line, and we make some comments about the results obtained. Finally, we formulate the recommendation to the investor based on the results obtained, and we point out some of the limitations of the model that could explain some of the unrealistic results that we fo und. The methodology of the calculations, the tables and the charts used are all referenced in the appendix of this paper in order to illustrate the results obtained. Introduction This project is based on the Markowitz Mean Variance Optimization Model for defining the optimal weights of assets in a given portfolio based on various investment constraints. The model generally seeks to maximize return for a given level of risk, or minimize risk for a given level of return. Markowitz formulated the portfolio construction problem as a utility maximization problem and used this to develop a framework for selecting a range of optimal portfolios. In his model, Markowitz made several assumptions on which this project is based. These assumptions designed the portfolio selection problem to a mean-variance portfolio optimization problem and are as follows: All investors have a single holding period during which they will maximize their utility function. Investors dont incur any transaction costs or taxes while trading the securities. Investors have a quadratic utility function that they should maximize based on the expected return, variance, and risk aversion. The returns used should be normally distributed. Investors are assumed to be risk averse where they prefer to maximize the returns given a minimum level of risk All the investors share the same economic view of the world, and they analyze the securities in the same way. I/ Analyzing Stock Returns and Standard Deviations According to Table 1 and 2 in Appendix 2, the results show that the expected returns in the full data set obtained were generally lower than the expected returns in the sample of the 250 most recent returns. (Please refer to Appendix 1 for the methodology of calculations.) The major explanation is that the full data set covers the 2007/08 financial crisis in which the U.S stock market has dropped down by more than 50%, which had an implication on the mean expected returns calculated over the period from 2006 until 2011, and shows relatively lower returns. In comparison, the 250 most recent returns sample covers a period of one year starting from the 2nd of March, 2010 until the 31st of January, 2011. During this period, the stock market has recovered from the historic lows of March 2009, and is still facing a market rally that has been consistent until now, which affects the performance of individual stocks at the exception of Baxter, and Procter Gamble, which underperformed due t o some fundamental issues that are related to their business sectors. Regarding standard deviation, we can see that the stocks in the full data set present a higher standard deviation than in the second data set. This shows that during the period from 2006 to 2011, there has been a high volatility in the market, which is illustrated by the stocks demonstrating some extreme returns. This is mainly due the shape of the recovery after the financial crisis, which displayed some significant drops in the share prices and recovering back at a rapid rate of growth, after March 2009. However, the volatility has stabilized during the last year which means that stocks are becoming less risky in comparison with the last three years. II/ Analyzing the Data Sets 1) Testing for normality Before going through the process of selecting the optimal portfolios, we first examine the returns computed and see if they match the assumptions of normality that have been stated earlier for the model to be valid. In order to do so, the Jarque-Bera test for normality is chosen, and provides a formal method in which Skewness and Kurtosis are used to analyze the distribution of the returns. (Please refer to the appendix for the description of the Jarque and Bera test for normality) Analysis of the results: The data in tables 3 and 4 from Appendix 2 show different results for the two sample sizes. In the Full data set, the JB test statistics computed are all higher than the 9.21 critical value with 99% confidence level, which means that the distribution of the returns is not normal as we reject the null hypothesis. This is mainly explained by the fact that the kurtosis observed in all the stocks returns is positive and is higher than 3, which shows that the distributions exhibit fat tails. Moreover, Skewness is different from zero for all the distributions showing that they are not perfectly symmetrical, which rejects another condition for the normality of returns. If the returns display positive Skewness, this means that there is a high probability that the stocks involved will show positive returns in the future. By comparison in the second data set, we notice that the distributions of returns of the Stocks GE, Baxter, Procter Gamble, and Apple can all be assumed normal, as the JB statistic is lower than 9.21. One similarity between the stocks that dont have a normal distribution of returns in both data sets is that they display a leptokurtic distribution which means that the distribution is more focused around the center and in the tails than the normal distribution, and this is due to the excess kurtosis. 2) Testing for evidence of Volatility Clustering Volatility clustering is mainly characterized by the historical data of stock returns showing periods of high volatilities giving some extreme returns, which are then followed by periods of relatively low volatilities. Analysis of the results: According to the volatility charts in Appendix 2, we notice that all the stocks in the complete data set showed evidence of volatility clustering with a certain similarity in the clusters observed. In fact, most of the volatility clusters observed can be located between the periods of late 2007 to the mid 2009. This is explained by the high volatility of returns during the period of the financial crisis, where most stocks showed some extreme variations in the returns due to the investors trying to digest the panic that was going on in the market, and then they reacted accordingly by liquidating their positions. This pattern lasted until the mid of 2009 until some of the confidence was restored and investors came back into the market again. In comparison with the sample of the 250 most recent returns and according to the graphs, we cannot detect any significant evidence of volatility clustering for the stocks of Caterpillar and DOW, but we can clearly observe some evidence regarding Apple, PG, GE, and Baxter as the cluster can be clearly identifiable. This is mainly interpreted by the fact that since the information arrives in cluster, investors tend to take more or less time to react relative to the kinds of information that they receive with respect to the stocks. III/ The Portfolio Selection Process The Main objective of the portfolio optimization process is to find the optimal allocation of assets in the two data sets given two kinds of portfolios: one containing risky assets only, and another one that would include a risk free asset. For this, we used the Excel Solver to run three types of optimizations that result in three types of portfolios: the Minimum Variance Portfolio, the Optimal Risky Portfolio, and the Optimal Complete Portfolio. 1) Analyzing the results given by the Minimum Variance Portfolios In the Markowitz model, we have assumed that investors seek to maximize the return at a given level of risk, or minimize the risk at a given level of return. The minimum variance portfolio is the one that gives the optimal allocation of risky assets by minimizing the general risk of the portfolio. In order to do so, we used the Excel Solver and we set the portfolio variance as the target to minimize given both the constrained and unconstrained optimization criteria. The formula for the portfolio variance is given in the Appendix and is derived from the correlation matrixes that were computed for both data sets. The general parameters used in the Excel Solver are also explained for both the constrained and the unconstrained portfolios. Analysis of the results: According to table 5 and 6 in Appendix 2, the minimum variance portfolio for the full data gives two results based on the constrained optimization and the unconstrained optimization. In the Long Only Portfolio, the results suggest that the investor should invest in three stocks which are Baxter, Procter Gamble and, Apple with the respective weights of 32.87%, 62.14% and 4.99%. This gives a portfolio expected return of 6.60% with a standard deviation of 18.63%. In the Unconstrained Portfolio, the results suggest that the investor should invest in all the stocks by going long on Baxter (33.66%,) Caterpillar (3.90%,) Procter Gamble (65.22%,) and Apple (6.06%,) and shorting GE (-1.08%) and DOW (-7.75%.) The portfolio expected return in this scenario is 7.48% and the standard deviation is 18.43%. In the second data set, for the constrained portfolio, the results suggest that the investor should invest only in stocks Baxter, Procter Gamble, and Apple with the respective proportions of 11.90%, 84%, and 4.10%. The expected return obtained is 2.06%, for a standard deviation of 13.15%. In the unconstrained portfolio, the results suggest that the investor should go long GE (2.30%,) Baxter (12.51%,) Caterpillar (2.96%,) Procter Gamble (88.77%,) and Apple (9.44%,) and short Dow (-15.97%.) The expected return obtained is 2.42% for a standard deviation of 12.51%. Comparing the results obtained in the full data set and the 250 most recent return sample, we can notice that there are differences in the results we get. This difference is mainly explained by the change in the expected returns and standard deviations of the stocks in both data sets, and we can notice that this change has an impact on the performance of the portfolios expected return as well as the allocation of the assets in the portfolio. The best portfolio is chosen by using comparing the Sharpe ratios, which gives a risk adjustment measure that compares the performance of individual portfolios. From table X and Y in the appendix, we can say that best portfolio from the two samples is the Unrestricted Portfolio in the full data set since it gives a higher Sharpe ratio of 0.2432 relative to the other portfolios. 2) The Optimal Risky Portfolio The optimal risky portfolio is the one that maximizes the Sharpe Ratio and allows identifying the optimal weights of the risky assets in the portfolio. The formula for the Sharpe ratio is given in the appendix in the Methodology section. The ratio seeks to know how much additional return an investor would receive for the additional risk of holding the risky assets over a risk-free asset. The higher is this ratio the better is the performance of the portfolio with respect to risk and return. Analysis of the results: According to the table 7 and 8 in Appendix 2, for the full data set, the Long only portfolio suggests that the investor should be fully invested in Apple stock, which gives an expected return that is equivalent to the stocks expected return of 37.97% and a standard deviation also equivalent of 40.28%. By comparison, the unconstrained portfolio suggests that the investors should go long the stocks Baxter (48.77 %,) Caterpillar (91.02%,) and Apple (211.44%,) and short the stocks GE (-161.16%,) Dow (32.51,) and Procter and Gamble (-57.55%.) This gives a portfolio expected return of 102.24% and a standard deviation of 86.71%. In the second data set, the results suggest that the investor should invest in stocks Caterpillar (43.63%,) and Apple (56.37%.) this gives a portfolio expected return of 60.33% and a standard deviation of 24.65%. In the unconstrained scenario, the results suggest that the investor should go long the stocks Caterpillar (100.00%,) Procter Gamble (3.88%,) and App le (100.00%,) and short the stocks GE (-18.38%,) Dow (-41.73%,) and Baxter (-43.77%.) the expected return in this scenario is 110.34% and the standard deviation is 36.57%. By comparing the results of the two data sets, we notice that both optimizations give some unrealistic results in terms of the expected returns and variances of the portfolios, but also in terms of the proportions to be invested in the stocks. In fact, in the full data set, the Long-Only portfolio suggests that the investor should be invested in only one stock which eliminates any benefits from diversification and is a very risky strategy to pursue for long term asset allocation in general. The unconstrained portfolio is also unrealistic in terms of the weights that are attributed to the portfolios as some of them reach 100% proportion to be invested in, which is not possible because it doesnt allow for proper asset diversification. The only portfolio that seems to be realistic is given in the second data set w here the expected return is of 60.33%, which seems quite attractive given the level of risk that is suggested of 24.65%, and that is what one could consider as a realistic result since the proportions to be invested are shared between two stocks as it is the minimum diversification of risky assets that one could consider given the constraint of maximizing the Sharpe ratio. 3) The Optimal Complete Portfolio The optimal complete portfolio is the portfolio that consists of the optimal risky assets and the risk free asset. The optimal complete portfolio is determined by maximizing the investors utility function which is defined in Appendix 1. The result of the optimization gives the proportions to be invested in the risky assets and the risk free assets, which allows the investors to be properly diversified based on three main components that are, expected return, volatility, and risk aversion. Analysis of the results: According to table 9 and 10 Appendix 2, for the full data set, the Long-Only portfolio suggests that the optimal complete portfolio is the one that provides an expected return of 33.13% and a standard deviation of 34.72%. The proportion to be invested in the risky assets is 86.16%, and the proportion to be invested in the risk free asset is 13.84%. In this scenario, the maximization of the investors utility function suggests that the investor should be diversified between Apple stock and the risk free asset. In the unconstrained scenario, the optimization results in a portfolio expected return of 55.39%, and a standard deviation of 45.78%. The investors portfolio in this case consists of 52.77% in risky assets and 47.23% in the risk free asset. For the positions in the risky assets, the investor should go long the stocks Baxter (48.76 %,) Caterpillar (91.06 %,) and Apple (211.53 %,) and short the stocks GE (-161.24 %,) Dow (-32.53 %,) and Procter and Gamble (-57.58 %.) The Lo ng-Only portfolio in the second data set suggests that the investor should invest 90% of the portfolio in risky asset, and 10% in the risk free asset. The proportions of the risky assets are as follows: 98.84% in Dow, and 1.16% in Caterpillar. In the unconstrained portfolio, the results suggest that the investor should invest 90% in risky assets, and 10% in the risk free asset. The distribution of the asset weights is as follows: the investor should go long the stocks DOW (100%), Caterpillar (100 %,) GE (100 %,) and short Procter Gamble (-64.13 %,) and Baxter (-100 %,) and Apple (-35.87%.) When comparing the two samples, we notice that the unconstrained portfolios in both data sets provide some unrealistic results in terms of the portfolio weights as some of them equal or exceed 100% of the portfolios total weight. In the second data sets when we eliminate some of the constraints that allow us to have more accurate data, the result obtained show very large values that are comple tely unrealistic and prevent us from drawing any meaningful conclusions. In the full data set, the Long-Only portfolio although it suggests that the investor should be mixed between risky assets and the risk free asset does not provide proper diversification as the portfolio of risky assets is concentrated on one stock which is Apple stock, however, it seems that it is the one that provides the most realistic result. 4) The Efficient Frontier and the Capital Allocation Line Drawing the efficient frontier is the last step that allows the investors to visualize the optimal portfolios computed previously and choose the best alternatives that are offered given the results that are produced, and whether they are realistic or not. The Appendix 2 provides 4 graphs for both data sets that show the efficient frontier given the constrained and the unconstrained optimized portfolios. The capital allocation line which is determined by maximizing the Sharpe ratio is represented on each of the graphs and shows the optimal risky portfolios as well as the optimal complete portfolios. The indifference curve drawn display the curve of equally preferred portfolios that will generate the same utility to the investor. In the second data set, it was not possible to draw the Capital Allocation Line as the values obtained were inaccurate and extremely large. Moreover, the points showing the Optimal Risky Portfolio and the Optimal Complete Portfolio are those that were comput ed given the constraints that we have set in Appendix 1, for the purpose of obtaining more accurate results. This shows one of the limitations of the Mean Variance optimization model as it fails to provide meaningful results when using a small number of observations in the sample that we used. 5) Recommendation to the Investor The results obtained from each type of portfolio are summarized in tables 11 and 12. For a matter of convenience, we labeled the portfolios from Portfolio 1 to 12. In the recommendation to the investor we suggest to look first at the portfolios that give some realistic results, and then we can compare which ones provide the best results by using the Sharpe ratio as a measure of performance. Based on the results obtained, the portfolios that have been chosen are Portfolio 1, 2, 4, 7 and 10. Portfolios 1 and 7 do not provide a satisfying performance to the investor as the returns are lower than the risk free asset, and the risks observed are too high. In this case the investor is better off investing all his money into the risk free asset at 3%. Portfolio 2 is based on the Optimal Risky Portfolio in the second data set, and gives the highest Sharpe ratio of 156.62% with the following proportions: Caterpillar (43.63 %,) and Apple (56.37 %.) In comparison, portfolios 4, and 10 offer lo wer returns, hence, lower Sharpe ratios, but they also allow for more diversification among the stocks, and they give a relatively lower risk compared to portfolio 2. From a fundamental perspective, we recommend that the investors should always stay diversified between risky and the risk free asset in order to protect themselves against any unexpected downturn in the markets. For this, we suggest that the investors should choose to invest 70 percent in Portfolio 2, and 30% in the risk free asset. This will lower, the standard deviation to 17.262% for an Expected return of 42.24%. This gives a pretty high expected performance in comparison with the SP500 performance of 2010 which was of 15.65%, and it allows the investors to be less exposed to risk compared with portfolios 4 and 10. Conclusion The projects main objective was to identify the optimal allocation of assets from a portfolio containing risky assets and one that includes a risk free asset. The allocations obtained were based on the Markowitz Mean Variance Optimizations, and resulted in three kinds of portfolio along with the efficient frontiers for both samples of data that we have used. In the analysis of the results, we have found some unrealistic values that we judge are due to the assumptions that we made earlier, which reflect some of the limitations of the Model. In fact the first limitation that we can state is the assumption of normality on the returns in both data sets which seems to be unrealistic given the distributions that we have obtained. There is strong evidence that most stock returns display asymmetrical returns as well as showing excess Kurtosis which makes the model used hardly applicable and is responsible for the large values obtained. Second, the model assumes that investors will hold their investment on a fixed time horizon, and will never change the asset allocation, which is false given that some times, investors need to rebalance their portfolios shifting from the risky assets to treasury bills and other risk free assets depending on the market. Finally, the model focuses mainly on minimizing the volatility given a specific return or the opposite, and this is not compatible with todays environment in the sense that investors views and objectives are more sophisticated, and therefore require to use enhanced models such as the Black and Litterman Model. Appendix 1: Methodology Section 1. Computing Returns and Standard Deviations: The first step is to process the historical prices into returns and determine the individual stock returns as well as the standard deviations. The daily stock returns from the stocks closing prices are calculated using the oldest historical prices as the base dates. The computation of the daily stock returns is done using the following formula: Daily stock return= (Closing price of the current trading day Previous days closing Price) / Previous days closing Price We then compute the expected returns of the stocks in the portfolio using the simple arithmetic mean of returns formula, which is as follows: AR = (R1 + R2 + R3 + ÃÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ + RN) / N The returns obtained are then annualized by multiplying the expected returns by 250 trading days on average in a given year. In order to calculate the risk of individual stocks, we used the STDEV function in Excel by selecting the daily returns calculated in the two data sets, and annualizing the values obtained by multiplying by the square root of 250 trading days on average per year. 2. The Jarque and Bera Test for Normality The Jarque-Bera test statistic for normality follows a chi-square distribution with 2 degrees of freedom. Concerning the analysis of the stock returns in the two data sets, I used the 99% confidence interval for which the critical value is 9.21 at 2 degrees of freedom. If the test statistic is higher than the critical value, we reject the null hypothesis that the monthly returns are normal, otherwise we accept it, and we can assume the returns are normal. Skewness gives the measure of asymmetry of the distribution, and is defined by the following formula: Where T is the time period or the length of the data used, and . Kurtosis is the measure of the flatness of the distribution, and is defined as follows: This leads to the computation of the Jarque-Bera test statistic which is as follows: 3. Volatility Clustering Volatility clustering is another important factor that can help to understand the patterns of the variations among stock returns. To show evidence of volatility clustering in the two data sets, we plotted the stock returns in a time series graph, and analyzed the different patterns of the individual stocks using the complete data set first, and then analyzing the most recent 250 stock returns to see if the patterns display some periods of high volatilities show some extreme returns, which are followed by periods of relatively low volatilities. 4. Measurement of Portfolio Risk and Return After computing the expected returns and risks of individual stocks, we define some of the formulas for computing the portfolio risk and return that will be used in the optimization process. Modeling the Portfolio Risk The portfolio risk is generally referred to as the portfolio variance. In our case of many assets, the variance of the portfolio takes the form of a matrix and has the following general formula: Where w1 to wn is a matrix that refers to the weights of the assets 1 to N in the portfolio, and ÃÆ' Ãƒâ€ Ã¢â‚¬â„¢xy is the covariance between assets x and y. In practice it is more useful to use the correlation matrix to derive the covariance matrix as it is generally unknown, and we have already computed the standard deviations of the individual stocks. In fact, we can derive the covariance matrix using the following formula: ÃÆ' Ãƒâ€šÃ‚ (x,y) = covariance(x,y)/ÃÆ' Ãƒâ€ Ã¢â‚¬â„¢x ÃÆ' Ãƒâ€ Ã¢â‚¬â„¢y Where ÃÆ' Ãƒâ€šÃ‚ xy is the correlation between assets x and y, and  ÃƒÆ' Ãƒâ€ Ã¢â‚¬â„¢n is the standard deviation of the nth asset. Hence we obtained the following: In excel, we used the following formula given that we have already computed the correlation matrix (appendix), the standard deviations and the expected returns of the stocks: {MMULT(MMULT(TRANSPOSE(wnÃÆ' Ãƒâ€ Ã¢â‚¬â„¢n); ÃÆ' Ãƒâ€šÃ‚ (x,y)); wnÃÆ' Ãƒâ€ Ã¢â‚¬â„¢n)} Where wnÃÆ' Ãƒâ€ Ã¢â‚¬â„¢n is the matrix that results from the multiplication of the portfolio weights with the standard deviations of individual stocks, and ÃÆ' Ãƒâ€šÃ‚ (x,y) is the correlation matrix. Determining the Portfolios Expected Return The portfolio expected return is the sum of the product of the holding of the assets by the expected returns of the individual assets, and is represented as follows: Where the sum of the weights = 1, n is the number of securities held in the portfolio which is 6 stocks in our case, wi is the proportion invested in a given stock i, E(ri) is the expected return on the stock i. The Optimization Process The optimizations were run based on some investment constraints and without any investment constraints. In the constrained optimization scenario, we restricted having short positions in the market meaning that all the optimal weights should be positive or equal to 0. Also, we set the sum of the proportions invested in each stock to equate 1, and finally, we select the range of cells that should be changed in order to obtain the optimal weights for each type of portfolio that we want to have. In the unconstrained optimization scenario, we allowed for both short and long positions to occur, but we still keep the restriction on the sum of the optimal weights, setting it equal to 1. In the second data set, in the Optimal Risky Portfolio and Optimal Complete Portfolios, we add more constraints such as limit the individual weights from exceeding 100% or -100% of the portfolio, and setting the proportion invested in the risky assets not to exceed 90% in order to obtain a minimum level of diversification between the risky asset and the risk free asset in both the constrained and unconstrained portfolios. Sharpe Ratio The sharpe ratio is a risk adjusted measure to evaluate portfolio performance and is based on the following formula: Source: Investopedia.com The investors utility function The investors utility function used in this project is a quadratic function that is represented as follows: Where is the utility value, and A is the investors level of risk aversion. The number 0.005 is a scaling factor used by convention to express the expected return and standard deviation as percentages. The optimal complete portfolio would be the one that provides the highest utility by maximizing the formula using the Excel Solver. The result gives the optimal proportion to be invested in the risky asset which is represented by the following formula: The proportion invested in the risk free asset is given by: 1 Y Appendix 2: Tables and Charts Asset Data (Full Data Set) Expected Return Standard Deviation GE -3.62% 38.77% DOW 5.45% 43.86% Baxter 7.68% 24.63% Caterpillar 17.78% 38.93% Procter and Gamble 3.51% 20.51% Apple 37.97% 40.29% Table 1: Stock Return and Standard Deviations Using the Full Data Set Asset Data (250 Most recent returns) Expected Return Standard Deviation GE 22.75% 27.43% DOW 31.99% 36.29% Baxter -14.10% 24.40% Caterpillar 64.69% 29.83% Procter and Gamble 1.68% 13.49% Apple 56.95% 25.49% Table 2: Stock Return and Standard Deviations Using the 250 Most recent returns Full Data Set GE DOW BAX CAT PG AAPL Kurtosis 9.283169 7.042409 7.47999063 5.080399 7.659262 4.260446 Skewness 0.417837 -0.08243 -0.622318643 0.160727 -0.03425 -0.02987 JB Test Statistic 2121.731 871.6094 1151.235074 235.9717 1156.239 84.78961 Table 3: The Jarque-Bera Test for Normality Using the Full Data Set 250 Most Recent Returns GE DOW BAX CAT PG AAPL Kurtosis 2.414595 2.058731 21.2954 1.601479884 2.562847 2.396152 Skewness 0.170671 -0.32919 -2.61641 0.112397247 -0.20665 0.316714 JB Test Statistic 4.783472 13.74422 4.783472 20.89990707 3.769913 7.977748 Table 4: The Jarque-Bera Test for Normality Using 250 Most recent returns Full Data Set Long Constraint Unconstrained Portfolio Expected return= 6.60% 7.48% Portfolio Variance = 3.47% 3.40% Portfolio SD = 18.63% 18.43% Risk Free Asset = 3.00% 3.00% Sharpe Ratio = 0.1933 0.2432 Portfolio Weights GE 0.00% -1.08% DOW 0.00% -7.75% BAXTER 32.87% 33.66% CAT 0.00% 3.90% PG 62.14% 65.22% AAPL 4.99% 6.06% Table 5: Minimum Variance Portfolio using the Full Data Set 250 Most Recent Returns Long Constraint Unconstrained Portfolio Expected Return= 9.84% 1.45% Portfolio Variance = 2.28% 1.57% Portfolio SD = 15.11% 12.52% Risk Free Asset = 3.00% 3.00% Sharpe Ratio = 45.31% -12.37% Portfolio Weights GE 7.27% 3.05% DOW 0.00% -15.57% BAXTER 32.14% 12.52% CAT 0.00% 2.38% PG 39.40% 89.78% AAPL 21.18% 7.82% Table 6: Minimum Variance Portfolio using the 250 Most Recent Returns Full Data Set Long Constraint Unconstrained Sharpe Ratio = 86.79% 114.44% Portfolio Expected Return= 37.97% 102.24% Portfolio Variance = 16.23% 75.20% Portfolio SD = 40.29% 86.72% Risk Free Asset = 3.00% 3.00% Portfolio Weights GE 0.00% -161.16% DOW 0.00% -32.51% BAXTER 0.00% 48.77% CAT 0.00% 91.02% PG 0.00% -57.55% AAPL 100.00% 211.44% Table 7: Optimal Risky Portfolio using the Full Data Sets 250 Most Recent Returns Long Constraint Unconstrained Sharpe Ratio = 232.49% 293.41% Portfolio Expected Return= 60.33% 110.34% Portfolio Variance = 6.08% 13.38% Portfolio SD = 24.66% 36.58% Risk Free Asset = 3.00% 3.00% Portfolio Weights GE 0.00% -18.38% DOW 0.00% -41.73% BAXTER 0.00% -43.77% CAT 43.63% 100.00% PG 0.00% 3.88% AAPL 56.37% 100.00% Table 8: Optimal Risky Portfolio using the 250 Most Recent Returns   Full Data Set Long Constraint Unconstrained Investor Utility Function to Maximize 0.329779696 0.551279771 Expected Return on the Complete Portfolio 33.13% 55.39% Variance of the Complete Portfolio 0.120514451 0.209559707 Standard Deviation of the Complete Portfolio 34.72% 45.78% Coefficient of Risk Aversion (A) 2.50 2.50 Y (% investment in risky assets) 86.16% 52.77% Portfolio Expected Return= 37.97% 102.29% Portfolio Variance = 16.23% 75.26% Portfolio SD = 40.29% 86.75% Risk Free Rate = 3.00% 3.00% Sharpe Ratio = 86.79% 114.44% Portfolio Weights   GE 0.00% -161.24% DOW 0.00% -32.53% BAXTER 0.00% 48.76% CAT 0.00% 91.06% PG 0.00% -57.58% AAPL 100.00% 211.53% Table 9: Optimal Complete Portfolio Using the Full Data Set  Long Constraint Unconstrained Investor Utility Function to Maximize 0.293024078 1.006325758 Expected Return on the Complete Portfolio 29.43% 101.12% Variance of the Complete Portfolio 10.57% 39.25% Standard Deviation of the Complete Portfolio 32.52% 62.65% Coefficient of Risk Aversion (A) 2.50 2.50 Y (% investment in risky assets) 90.00% 90.00% Portfolio Expected Return= 32.37% 112.03% Portfolio Variance = 13.05% 48.46% Portfolio SD = 36.13% 69.61% Risk Free Rate = 3.00% 3.00% Sharpe Ratio = 81.29% 156.62% Portfolio Weights GE 0.00% 100.00% DOW 98.84% 100.00% BAXTER 0.00% -100.00% CAT 1.16% 100.00% PG 0.00% -64.13% AAPL 0.00% -35.87% Table 10: Optimal Complete Portfolio Using the 250 Most Recent Returns Full Data Set Long Only Portfolio (Constrained)  Protfolio Expected Return Portfolio Standard Deviation Portfolio 1: Minimum Variance Portfolio 2.06% 13.15% Portfolio 2: Optimal Risky Portfolio 60.33% 24.66% Portfolio 3: Optimal Complete Portfolio 29.43% 32.52%  Long Only Portfolio (Constrained) 250 Most Recent Returns Protfolio Expected Return Portfolio Standard Deviation Portfolio 4: Minimum Variance Portfolio 6.60% 18.63% Portfolio 5: Optimal Risky Portfolio 37.97% 40.29% Portfolio 6: Optimal Complete Portfolio 33.13% 34.72% Table 11: Summary Table of the Results Obtained From the Optimizations Full Data Set Long-Short Portfolio (Unconstrained)  Portfolio Expected Return Portfolio Standard Deviation Portfolio 7: Minimum Variance Portfolio 2.42% 12.51% Portfolio 8: Optimal Risky Portfolio 110.34% 36.58% Portfolio 9: Optimal Complete Portfolio 101.12% 62.65%  Long-Short Portfolio (Unconstrained) 250 Most Recent Returns Portfolio Expected Return Portfolio Standard Deviation Portfolio 10: Minimum Variance Portfolio 7.48% 18.43% Portfolio 11: Optimal Risky Portfolio 102.24% 86.72% Portfolio 12: Optimal Complete Portfolio 55.39% 45.78% Table 11: Summary Table of the Results Obtained From the Optimizations Efficient Frontiers: Full Data Set Efficient Frontiers: 250 Most Recent Returns Volatility of Returns: Full Data Set Volatility of Returns: 250 Most Recent Returns