Thursday, November 28, 2019

Marijuana Effects Essays - Medicinal Plants, Cannabis Smoking

Marijuana Effects Marijuana is a mood altering or psychoactive drug that has many nicknames, such as pot, weed, ganja, sensi, herb, and others. It is an ancient drug that dates back to hundreds of years to Asia. Many cultures have used it during meditation, religious worship, and for intoxication. Marijuana itself comes from the Indian Hemp plant. It is the third most widely used drug in the United States, according to a survey taken in 1988, and it is the number one illegally used drug in the United States. Marijuana is so popular that an estimated one out of every three people in the US have tried it and around 44% of US high school students have smoked it. Marijuana users are not easily detectable, nor is the drug just used in one area of society. The Indian Hemp plant is found all over the world, including the US. There are three different types of Indian Hemp. They are Cannabis Sativa, Cannabis Indica, and Cannabis Rudderalis. These three plants vary in size and mood altering effect. The hemp plant has many uses and has been farmed for centuries. Marijuana can be taken in three ways, by eating, made into a tea, or smoking (the most popular). Smoking it can be done three ways, through a pipe, a joint, blunt. A joint is a rolled piece of paper that is twisted at the ends. A blunt is normally an emptied cigar wrapper filled with marijuana. In a blunt you can fit much more marijuana. Though a blunt isn't always purely marijuana, it can be mixed with other drugs such as angel dust. The results are varied when someone smokes marijuana. Different people will get different results, and certain types of cannabis can cause different effects. The amount of THC (marijuana's main Active chemical) may also change the result. If alcohol, or other drug use is occurring while smoking marijuana, the effect could be different. A first time marijuana smoker will probably feel no effect. A chronic or heavy user will get a high (intoxication). When a person is high, normal sights, sounds, tastes, or events can seem very funny or interesting. When intoxicated, time seems to pass a lot slower. To the user, minutes will seem like hours. The intoxicated person may get very thirsty or hungry, a common effect called, " the munchies." A few minutes after the person inhales they will probably get a dry mouth, rapid heartbeat, decreased reaction time, and also a loss of coordination. The blood vessels in the user's eyes will probably enlarge, giving the person a blood shot appearance. Within 2 to 3 hours the effects will die down and the person will feel sleepy. How is marijuana harmful? There are many ways that marijuana can harm the body, both the immediate effect and long term effects. It often disables the users short-term memory and may cause trouble with challenging tasks. Even very simple tasks can become a struggle for someone who is high. A student that is under the influence of marijuana may find it hard to learn or concentrate. A persons timing and coordination are normally delayed by marijuana. As a result the person will be very confused and useless. The effect marijuana can have on the brain and central nervous system are very serious. Smoking marijuana will reduce the strength and speed of communications between the mind and body. This occurs in the brain and muscles, causing the user to not be as focused. Short-term marijuana use leads to a drowsiness and relaxing effect. This is why marijuana users have trouble remembering things. A heavy dose of marijuana can decrease the amount of blood pumped into the brain. Marijuana effects the brain's control over muscles also. Heavy usage of marijuana can have a lasting effect on the users short- term memory. The blood flow to the back of the brain is greater than the front, after smoking. This is believed to cause the high sensation the user is after. The short-term effect of marijuana will increase blood pressure and pulse rate up to 16 points above normal. It will also slow down the digestive processing of food. People who smoke marijuana often will

Monday, November 25, 2019

In what way is the Renaissance temper reflected in Brownings poetry Essays

In what way is the Renaissance temper reflected in Brownings poetry Essays In what way is the Renaissance temper reflected in Brownings poetry Paper In what way is the Renaissance temper reflected in Brownings poetry Paper Essay Topic: Poetry It was Ruskin who declared that Browning was a poet reflecting the Middle Ages. However, other critics have refuted this statement and offered conclusive evidence to support the contention that Brownings poetry reflected dominantly the ethos of the Italian Renaissance. Indeed, the major poems of Browning catch unerringly the spirit of the Italian Renaissance with its curious blend of soaring idealism and the4 depths of materialism, the demanding desires of the flesh and the elevating flights of the mind. The Renaissance was an intellectual and cultural movement which spread over Western Europe in the fifteenth and early sixteenth centuries. As its name suggests, the movement marked the rebirth or revival of interest in the classical culture and traditions of ancient Greece and Rome which had been neglected since the break up of the Roman Empire Empire in the fifth century. The revival of interest in the classical works changes mens outlook. The Middle Ages was dominated by monastic ideals and the firm conviction that the earth was a place of sin and the desires of the flesh a degrading necessity. The Renaissance freed mens from the hold of ascetic ideals, asserted the supremacy of reason, and induced men to take an artistic delight in the beauties of the world and the delights of the senses. But we must remember that with this glorifying of the body and the senses also went a passionate intellectual curiosity, a striving for widening the horizons of human knowledge. Like the painters of the Italian Renaissance, Browning too had no dislike for the body, its life, its beauty, power and charm. Fra Lippo Lippi is a picture no only of a man, but of the time and its temper, when religion and its morality had lost their ancient power over society in Florence; when the claim to give to human nature all it desired had stolen into the church itself. In this poem it is not difficult to see the passionate Renaissance love of the beauty and delights of earthly life. We also see the conflict between the medieval traditions of religions art and the new Renaissance ideals. The Prior wants Lippo to paint the souls of men in such a way as to induce religious feelings; he does not want the life-like representation of the body which would distract the mind from spiritual contemplation-this is typically the asceticism of the Middle Ages. Fra Lippo Lippi, on the hand, in true Renaissance vein, feels : This worlds no blot for us, Nor blank; it means intensely and means good. To find its meaning is my meat and drink. Thus we have the spirit of the Italian Renaissance with its free and frank enjoyment of the senses and the Renaissance ideal of art which sought to represent not merely the beauty of the mind but also the beauty of the body. At the same time, we are also struck by the curious paradoxes that fraught that great age and which Browning so well reflects in his poem-the monk and friar indulging in amorous affairs contrary to their religious vows. In another poem concerned with art, namely, Andre Del Sarto, we have created for us the spirit of the Renaissance again, though of a later vintage than in Fra Lippo Lippi. Here we have the representation of the conflict between technical perfection and imaginative or idealistic vision. Andre is a perfect craftsman, but Rafael and Michael Angelo were artists of the soul expressing in their pictures the divine discontent of their souls. Says Andrea sadly : Ah, but a mans reach should exceed his grasp, Or whats heaven for ? All is silver-grey Placid and perfect with my art : the worse ! The words imply that the great art of the period reflected the striving of the mind for higher regions, the fire of passion and glory of mans spirit through flamboyant colours-all of which, sadly, was not within reach of Andre. In a Grammarians Funeral we are given the picture of a typical Renaissance scholar whose life was dedicated to study of the classics in the endeavour whose life was dedicated to study of the classics in the endeavour to unravel minute niceties of grammar and language. Here, too, we have the poet capturing through the eulogy of one of the pall bearers the spirit of seeking for knowledge that gripped the Renaissance mind. Of course, the Renaissance spirit as reflected in this poem is more inspired by the German renaissance than the Italian Renaissance, as one critic has pointed out. In Germany the love of beauty had a distinct religious and spiritual aspect to it which was lacking in the Italy of the Renaissance. The Renaissance Germany had no love for beauty for beautys sake alone. The love of knowledge or beauty was modified into seriousness of life, carried beyond this life in thought, kept clean, and, though filled with incessant labour on the earth, aspired to reach its fruition only in the life to come. This is the spirit and the atmosphere of A Grammarians Funeral. Two famous poems which reflect to a nicety the atmosphere and ethos of the decadent Italian Renaissance are My last Duchess and The Bishop Orders his Tomb at St. Praxess Church. The Duke of Ferrara is the ultimate picture of the disagreeable aspect of the Italian Renaissance. Through the Duke of Ferraras words is conveyed the very essence of the age-its intrigue, avarice, shrewd mercenary instincts, hypocrisy, and an exquisite taste for art devoid of appreciation for life. The poem is remarkable for capturing the spirit of an age in the space of just fifty-six lines. In The Bishop Orders his Tomp at St. Praxeds Church, we once again experience the ethos of the decadent Italian Renaissance. The diverse features of the complex age are exquisitely captured. The Bishop wishes for luxurious gifts for his sons if his directions were carried out, and these gifts reflect the ages love of beauty, precious manuscripts, horses and grand houses. There is revealed all its love of colour, pomp and show as well as its greed and sensuality, as De Vane remarks. The basic Renaissance spirit-its world liness, inconsistency, pride, hypocrisy, ignorance of self, love of art, of luxury, and of good Latin find apt expression in this poem. We are places in the full decadence of the Italian Renaissance. Its total loss of religion even in the church; its immorality-the bishops deathbed is surrounded by his natural sons and the wealth he leaves has been purchased by every kind of iniquity-its pride of life, its luxury; its semi Paganism; its imitative classicism; its inconsistence; its pleasure in the adornment of death, its delight in the outsides of things and mere workmanship; its loss of originality; its love of scholarship and beauty for their own sakes; its contempt to common people; its exhaustions-are one and all revealed or suggested in this poem.

Thursday, November 21, 2019

Club it Essay Example | Topics and Well Written Essays - 750 words

Club it - Essay Example More explicitly, â€Å"Organizations can leverage their platforms to develop new Web-based applications, services and products, as well as to provide superb customer service† (Turban, ).The paper involves the club’s mission statement is primary clientele, information resources, and customer orientation as the strategy to obtain a competitive advantage. Club’s Mission Statement and its Primary Clientele The Club IT owners, Lisa Tejada and Ruben Keys, both possess a degree in Business Administration. They learned ‘Club IT’ operations and general business principles from their experiences and studies. The mission statement involves; â€Å"Written declaration of a firm's core purpose and focus which normally remain unchanged, whereas business strategies and practices may frequently be altered to adapt to the changing circumstances. Properly crafted mission statements (1) Serve as filters to separate what is important from what is no; (2) Clearly state w hich markets will be served and how; (3)Communicate a sense of intended direction to the entire organization† (Mission statement definition). The mission statement for the ‘Club IT’ illustrates as: Club IT offer live music, DJ's, dance space and refreshments that suit lifestyle for the customers. Customers are friends, and the ‘Club IT’ staff seeks to fabricate a community that meets recurrently at the ‘Club IT’ (Club IT). ‘Club IT’ community incorporates young professionals, teenagers, college students, tourists, and business travelers. The location of the ‘Club IT’ attracts many singles, couples, teenagers and business professionals to come and relax. Furthermore, the nightclub allows for the switching of entertainment and it becomes more appealing as it gets later into the evening. Likewise, the music offered by ‘Club IT’ also attracts college students. Word of mouth allows ‘Club IT’ increasing its revenues from this segment. Finally, ‘Club IT’ attracts tourists and business travelers who are visiting the city. Club’s Information Resources Information resources of ‘Club IT’ include hardware, software, applications and network components. Applications are operated throughout the network making itself as a crucial component of ‘Club IT’. Information systems of ‘Club IT’ include servers, database and workstations. However, for better performance, appropriate maintenance is required for information systems and the network components to ensure efficiency and effectiveness. There should be two logical partitions for IT resource management i.e. the information technology department and the end users. However, no standard menus are available to identify responsibilities for both ‘IT department’ and ‘end users department’. The division is usually determined by the size, nature and attitu de of the organization headed for information technology, and the quantity of IT resources. Club IT information resources consist of intranet. The intranet is an in house website. It operates in the organizations on a local area network (LAN) and serves the local staff only. Every small, medium and large organization consists of an intranet. There is a possibility of pages linked on the Internet. The intranet is not accessible to public networks. The club policies, news, schedules, training manuals, and meeting schedules are published on the intranet (Intranet definition from PC magazine encyclopedia). Customer Orientation as

Wednesday, November 20, 2019

Labor Relations Assignment Example | Topics and Well Written Essays - 2250 words

Labor Relations - Assignment Example Such warning will only be valid for 6months and after completion of 6 months; no disciplinary actions can be taken against W based on such warning. Opinion: there is no witness available for W using inappropriate languages or pushing chair towards L. No corroboration is available that confirming the fact that W had pushed the chair towards legs of L. Due to lack of evidences, no strict action can be taken against W. Answer B: According to Collective Bargaining Agreement (CBA) Article 15 (Discipline/Discharge Procedures), disciplinary actions can be taken against employees only in two conditions such as incompetence or misconduct (University of South Florida, 2013). Disciplinary actions can be taken against particular employee if his/her behavior hurts legitimate interests of employer. Behavior of W has negatively affected legitimate interests of Alternative Calendar Committee (ACC). According to Collective Bargaining Agreement (CBA) Article 15 (Discipline/Discharge Procedures), as labor union representative, employee has the right to ask for investigatory questioning for any kind disciplinary actions (University of South Florida, 2013). Upon such investigatory questioning, no witness has been found that confirming the fact that W had used inappropriate languages or pushed chair towards L. Based on above justification, W can be convicted on the ground of minor misconduct. Due to lack of evidence s, harsh disciplinary actions cannot be taken against W. Phrases like â€Å"legitimate interests†, â€Å"incompetence†, â€Å"misconduct† and â€Å"investigatory questioning† has helped me as arbitrator to understand context of the case and justify the award being mentioned in the earlier question. For example, â€Å"legitimate interests† phrase helped this arbitrator to justify the ground on which disciplinary actions can be taken against W. Therefore, it can be said that (CBA) Article 15 (Discipline/Discharge Procedures)

Monday, November 18, 2019

Popular Music in Society Essay Example | Topics and Well Written Essays - 1750 words

Popular Music in Society - Essay Example This paper focuses on how effectively music was used by Leonard Cohen to advance his political ideologies. Leonard Cohen is a Canadian musician who was born in 1934. After establishing himself as a rock, he became a reputable song writer and singer whose influences have been greatly felt not only in Canada, but in many other countries across the world including Israel and USA. Due to his expansive work, he composed and performed some of the greatest albums including Songs of Leonard Cohen (1967); Dear Heather (2004); New Skin for the Old Ceremony (1974); Recent Songs (1979); Old Ideas (2012);Various Positions (1984); The Future (1992); Ten New Songs (2001); Death of a Ladies Man (1977); Im Your Man (1988) and Popular Problems (2014). Here, he used his talent to entertain his fans as well as advance his religious and political ideologies. Since he started singing, he has demonstrated that rock music can be made to be a popular brand that discusses a wide range of topics touching on religion and politics. Given the popularity of rock, he could therefore not just sing to entertain, but had to bean active activist who used his music to condemn all sorts of societal evils and also appreciate the good work done by the administration. At one point, he said, â€Å"from the wars against disorder/ from the sirens night and day/ from the fires of the homeless/ Democracy is coming to USA† to express his satisfaction with the changes and optimism for a better future (Studwell & Lonergan, 2010). Since he joined music, Cohen has been active in advancing his political ideologies. Although himself not a politician, the musician has been using his songs to advance political philosophies that, in his opinion, are fruitful to the Canadian and global community. Having been born of Jewish parents, Cohen knows very well that the society has not been a peaceful one. Since the out break of the Israeli War, tension between his people the Israelites and the Palestinians is far from

Friday, November 15, 2019

Measuring weak-form market efficiency

Measuring weak-form market efficiency Measuring Weak-form Market Efficiency ABSTRACT This paper tests weak-form efficiency in the U.S. market. Both daily and monthly returns are employed for autocorrelation analysis, variance ratio tests and delay tests. Three conclusions are reached. Firstly, security returns are predictable to some extent. While individual stock returns are weakly negatively correlated and difficult to predict, market-wide indices with outstanding recent performance show a positive autocorrelation and offer more predictable profit opportunities. Secondly, monthly returns follow random walk better than daily returns and are thus more weak-form efficient. Finally, weak-form inefficiency is not necessarily bad. Investors should be rewarded a certain degree of predictability for bearing risks. Efficient market hypothesis (EMH), also known as information efficiency, refers to the extent to which stock prices incorporate all available information. The notion is important in helping investors to understand security behaviour so as to make wise investment decisions. According to Fama (1970), there are three versions of market efficiency: the weak, semistrong, and strong form. They differ with respect to the information that is incorporated in the stock prices. The weak form efficiency assumes that stock prices already incorporate all past trading information. Therefore, technical analysis on past stock prices will not be helpful in gaining abnormal returns. The semistrong form efficiency extends the information set to all publicly available information including not only past trading information but also fundamental data on firm prospects. Therefore, neither technical analysis nor fundamental analysis will be able to produce abnormal returns. Strong form efficiency differs fro m the above two in stating that stock prices not only reflect publicly available information but also private inside information. However, this form of market efficiency is always rejected by empirical evidence. If weak-form efficiency holds true, the information contained in past stock price will be completely and instantly reflected in the current price. Under such condition, no pattern can be observed in stock prices. In other words, stock prices tend to follow a random walk model. Therefore, the test of weak-form market efficiency is actually a test of random walk but not vice versa. The more efficient the market is, the more random are the stock prices, and efforts by fund managers to exploit past price history will not be profitable since future prices are completely unpredictable. Therefore, measuring weak-form efficiency is crucial not only in academic research but also in practice because it affects trading strategies. This paper primarily tests the weak-form efficiency for three stocks-Faro Technologies Inc. (FARO), FEI Company (FEIC) and Fidelity Southern Corporation (LION) and two decile indices-the NYSE/AMEX/NASDAQ Index capitalisation based Deciles 1 and 10 (NAN D1 and NAN D10). Both daily and monthly data are employed here to detect any violation of the random walk hypothesis. The remainder of the paper is structured in the following way. Section I provides a brief introduction of the three firms and two decile indices. Section II describes the data and discusses the methodology used. Section III presents descriptive statistics. Section IV is the result based on empirical analysis. Finally, section V concludes the paper. I. The Companies[1] A. Faro Technologies Inc (FARO) FARO Technologies is an instrument company whose principle activities include design and develop portable 3-D electronic systems for industrial applications in the manufacturing system. The companys principal products include the Faro Arm, Faro Scan Arm and Faro Gage articulated measuring devices. It mainly operates in the United States and Europe. B. FEI Company (FEI) FEI is a leading scientific instruments company which develops and manufactures diversified semiconductor equipments including electron microscopes and beam systems. It operates in four segments: NanoElectronics, NanoResearch and Industry, NanoBiology and Service and Components. With a 60-year history, it now has approximately 1800 employees and sells products to more than 50 countries around the world. C. Fidelity Southern Corp. (LION) Fidelity Southern Corp. is one of the largest community banks in metro Atlanta which provides a wide range of financial services including commercial and mortgage services to both corporate and personal customers. It also provides international trade services, trust services, credit card loans, and merchant services. The company provides financial products and services for business and retail customers primarily through branches and via internet. D. NYSE/AMEX/NASDAQ Index It is an index taken from the Center for Research in Security Prices (CRSP) which includes all common stocks listed on the NYSE, Amex, and NASDAQ National Market. The index is constructed by ranking all NYSE companies according to their market capitalization in the first place. They are then divided into 10 decile portfolios. Amex and NASDAQ stocks are then placed into the deciles based on NYSE breakpoints. The smallest and the largest firms based on market capitalization are placed into Decile 1 and Decile 10, respectively. II. Data and Methodology A. Data Data for the three stocks and two decile indices in our study are all obtained from the Center for Research in Securities Prices database (CRSP) on both daily and monthly basis from January 2000 to December 2005. Returns are then computed on both basis, generating a total of 1507 daily observations and 71 monthly observations. The NYSE/AMEX/NASDAQ Index is CRSP Capitalisation-based so that Decile 1 and 10 represent the smallest and largest firms, respectively, based on market capitalisation. In addition, The Standard and Poors 500 Index (SP 500) is used as a proxy for the market index. It is a valued-weighted index which incorporates the largest 500 stocks in US market. For comparison purposes, both continuously compounded (log) returns and simple returns are reported, although the analysis is based on the result of the first one. B. Methods B.1. Autocorrelation Tests One of the most intuitive and simple tests of random walk is to test for serial dependence, i.e. autocorrelation. The autocorrelation is a time-series phenomenon, which implies the serial correlation between certain lagged values in a time series. The first-order autocorrelation, for instance, indicates to what extent neighboring observations are correlated. The autocorrelation test is always used to test RW3, which is a less restrictive version of random walk model, allowing the existence of dependent but uncorrelated increments in return data. The formula of autocorrelation at lag k is given by: (1) where is the autocorrelation at lag ; is the log-return on stock at time; and is the log-return on stock at time. A greater than zero indicates a positive serial correlation whereas a less than zero indicates a negative serial correlation. Both positive and negative autocorrelation represent departures from the random walk model. If is significantly different from zero, the null hypothesis of a random walk is rejected. The autocorrelation coefficients up to 5 lags for daily data and 3 lags for monthly data are reported in our test. Results of the Ljung-Box test for all lags up to the above mentioned for both daily and monthly data are also reported. The Ljung-Box test is a more powerful test by summing the squared autocorrelations. It provides evidence for whether departure for zero autocorrelation is observed at all lags up to certain lags in either direction. The Q-statistic up to a certain lag m is given by: (2) B.2. Variance Ratio Tests We follow Lo and MacKinlays (1988) single variance ratio (VR) test in our study. The test is based on a very important assumption of random walk that variance of increments is a linear function of the time interval. In other words, if the random walk holds, the variance of the qth differed value should be equal to q times the variance of the first differed value. For example, the variance of a two-period return should be equal to twice the variance of the one-period return. According to its definition, the formula of variance ratio is denoted by: (3) where q is any positive integer. Under the null hypothesis of a random walk, VR(q) should be equal to one at all lags. If VR(q) is greater than one, there is positive serial correlation which indicates a persistence in prices, corresponding to the momentum effect. If VR(q) is less than one, there is negative serial correlation which indicates a reversal in prices, corresponding to the mean-reverting process. Note that the above two test are also tests of how stock prices react to publicly available information in the past. If market efficiency holds true, information from past prices should be immediately and fully reflected in the current stock price. Therefore, future stock price change conditioned on past prices should be equal to zero. B.3. Griffin-Kelly-Nardari DELAY Tests As defined by Griffin, Kelly and Nardari (2007), delay is a measure of sensitivity of current returns to past market-wide information.[2] Speaking differently, delay measures how quickly stock returns can react to market returns. The logic behind this is that a stock which is slow to incorporate market information is less efficient than a stock which responds quickly to market movements. SP 500 index is employed in delay test to examine the sensitivity of stock returns to market information. For each stock and decile index, both restricted and unrestricted models are estimated from January 2000 to December 2005. The unrestricted model is given by: (4) where is the log-return on stock i at time t; is the market log-return (return for SP 500 index) at time t; is the lagged market return; is the coefficient on the lagged market return; and is the lag which is 1, 2, 3, 4 for the daily data and 1, 2, 3 for the monthly data. The restricted model is as follows which sets all to be zero: (5) Delay is then calculated based on adjusted R-squares from above regressions as follows: (6) An alternative scaled measure of delay is given by: (7) Both measures are reported in a way that the larger the calculated delay value, the more return variation is explained by lagged market returns and thus the more delayed response to the market information. III. Descriptive Statistics A. Daily frequencies Table I shows the summary statistic of daily returns for the three stocks and two decile indices. The highest mean return is for FARO (0.0012), whereas the lowest mean return is for NAN D10 (0.0000). In terms of median return, NAN D1 (0.0015) outperforms all the other stocks. Both the highest maximum return and the lowest minimum return (0.2998 and -0.2184, respectively) are for FARO, corresponding to its highest standard deviation (0.0485) among all, indicating that FARO is the most volatile in returns. On the other hand, both the lowest maximum return and highest minimum return (0.0543 and -0.0675, respectively) are for NAN D10. However NAN D10 is only the second least volatile, while the lowest standard deviation is for NAN D1 (0.0108). Figure 1 and 2 presents the price level of the most and least volatile index (stock). All the above observations remain true if we change from log-return basis to a simple return basis. In terms of the degree of asymmetry of the return distributions, all stocks and indices are positively skewed, with the only exception of NAN D1. The positive skewness implies that more extreme values are in the right tail of the distribution, i.e. stocks are more likely to have times when performance is extremely good. On the other hand, NAN D1 is slightly negatively skewed, which means that returns are more likely to be lower that what is expected by normal distribution. In measuring the peakedness of return distributions, positive excess kurtosis is observed in all stocks and indices, also known as a leptokurtic distribution, which means that returns either cluster around the mean or disperse in the two ends of the distribution. All the above observations can be used to conclusively reject the null hypothesis that daily returns are normally distributed. What more, results from Jarque-Bera test provide supportive evidence for rejection of the normality hypothesis at all significant levels for all stocks and indices. B. Monthly frequencies Descriptive statistics of monthly returns are likewise presented in Table II. Most of the above conclusions reached for daily returns are also valid in the context of monthly returns. In other words, what is the highest (lowest) value for daily returns is also the highest (lowest) for monthly returns in most cases. The only exceptions are for the highest value in median returns and the lowest value and standard deviation in minimum returns. In this situation, NAN D10 (0.0460) and FARO (0.1944) have the least and most dispersion according to their standard deviations, compared with NAN D1 and FARO in daily case. From above observation, we can see that decile indices are more stable than individual stocks in terms of returns. Whats more, monthly returns have larger magnitude in most values than daily returns. Coming to the measurement of asymmetry and peakedness of return distributions, only NAN D10 (-0.4531) is negatively skewed. However, the degree of skewness is not far from 0. Other stocks and index are all positively skewed with both FEIC (0.0395) and LION (0.0320) having a skewness value very close to 0. Almost all stocks and index have a degree of kurtosis similar to that of normal distribution, except that NAN D1 (8.6623) is highly peaked. This is also consistent with the results of JB p-values, based on which we conclude that FEIC, LION and NAN D10 are approximately normal because we fail to reject the hypothesis that they are normally distributed at 5% or higher levels (see Figure 3 and 4 for reference). However when simple return basis is used, FEIC is no longer normally distributed even at the 1% significant level. Except this, using simple return produces similar results. IV. Results A. Autocorrelation Tests A.1. Tests for Log-Returns The results of autocorrelation tests for up to 5 lags of daily log-returns and up to 3 lags of monthly log-returns for three stocks and two decile indices from January 2000 to December 2005 are summarised in Table III. Both the autocorrelation (AC) and partial autocorrelation (PAC) are examined in our tests. As is shown in Panel A, all 5 lags of FARO, FEIC and NAN D10 for both AC and PAC are insignificant at 5% level, except for the fourth-order PAC coefficient of FARO (-0.052), which is slightly negatively significant. On the contrary, NAN D1 has significant positive AC and PAC at almost all lags except in the fourth order, its PAC (0.050) is barely within the 5% significance level. The significant AC and PAC coefficients reject the null hypothesis of no serial correlation in NAN D1, thereby rejecting the weak-form efficiency. In terms of LION, significant negative autocorrelation coefficients are only observed in the first two orders and its higher-order coefficients are not statistically significant. Besides that, we find that all the stocks and indices have negative autocorrelation coefficients at most of their lags, with the only exception of NAN D1, whose coefficients are all positive. The strictly positive AC and PAC indicates persistence in returns, i.e. a momentum effect for NAN D1, which means that good or bad performances in the past tend to continue over time. We also present the Ljung-Box (L-B) test statistic in order to see whether autocorrelation coefficients up to a specific lag are jointly significant. Since RW1 implies all autocorrelations are zero, the L-B test is more powerful because it tests the joint hypothesis. As is shown in the table, both LION and NAN D1 have significant Q values in all lags at all levels, while none of FARO, FEIC and NAN D10 has significant Q values. Based on above daily observations, we may conclude that the null hypothesis of no serial correlation is rejected at all levels for LION and NAN D1, but the null hypothesis cannot be rejected at either 5% level or 10% level for FARO, FEIC and NAN D10. This means that both LION and NAN D1 are weak-form inefficient. By looking at their past performance, we find that while NAN D1 outperformed the market in sample period, LION performed badly in the same period. Therefore, it seems that stocks or indices with best and worst recent performance have stronger autocorrelation. In particular, LION shows a positive autocorrelation in returns, suggesting that market-wide indices with outstanding recent performance have momentum in returns over short periods, which offer predictable opportunities to investors. When monthly returns are employed, no single stock or index has significant AC or PAC in any lag reported at 5% level. It is in contrast with daily returns, which means that monthly returns follow a random walk better than daily returns. More powerful L-B test confirms our conclusion by showing that Q statistics for all stocks and indices are statistically insignificant at either 5% or 10% level. Therefore, the L-B null hypothesis can be conclusively rejected for all stocks and indices up to 3 lags. When compared with daily returns, monthly returns seem to follow random walk better and are thus more weak-form efficient. A.2. Tests for Squared Log-Returns Even when returns are not correlated, their volatility may be correlated. Therefore, it is necessary for us to expand the study from returns to variances of returns. Squared log-returns and absolute value of log-returns are measures of variances and are thus useful in studying the serial dependence of return volatility. The results of autocorrelation analysis for daily squared log-returns for all three stocks and two decile indices are likewise reported in Table IV. In contrast to the results for log-returns, coefficients for FEIC, LION, NAN D1 and NAN D10 are significantly different from zero, except for the forth-order PAC coefficient (0.025) for FEIC, the fifth-order PAC coefficient for LION (-0.047) and third- and forth-order PAC coefficient for NAN D1 (-0.020 and -0.014, respectively). FARO has significant positive AC and PAC at the first lag and a significant AC at the third lag. The L-B test provides stronger evidence against the null hypothesis that sum of the squared autocorrelations up to 5 lags is zero for all stocks and indices at all significant levels, based on which we confirm our result that squared log-returns do not follow a random walk. Another contrasting result with that of log-returns is that almost all the autocorrelation coefficients are positive, indicating a stronger positive serial dependence in squared log-returns. In terms of monthly data, only FEIC and NAN D10 have significant positive third-order AC and PAC estimates. Other stocks and indices have coefficients not significantly different from zero. The result is supported by Ljung-Box test statistics showing that Q values are only statistically significant in the third lag for both FEIC and NAN D10. This is consistent with the result reached for log-returns above, which says that monthly returns appear to be more random than daily returns. A.3. Tests for the Absolute Values of Log-Returns Table V provides autocorrelation results for the absolute value of log-returns in similar manner. However, as will be discussed below, the results are even more contrasting than that in Table IV. In Panel A, all the stocks and indices have significant positive serial correlation while insignificant PAC estimates are only displayed in lag 5 for both FARO and LION. Supporting above result, Q values provide evidence against the null hypothesis of no autocorrelation. Therefore, absolute value of daily log-returns exhibit stronger serial dependence than in Table III and IV, and autocorrelations are strictly positive for all stocks and indices. Coming to the absolute value of monthly log-returns, only FEIC displays significant individual and joint serial correlation. NAN D1 also displays a significant Q value in lag 2 at 5% level, but it is insignificant at 1% level. Based on the above evidence, two consistent conclusions can be made at this point. First of all, by changing ingredients in our test from log-returns to squared log-returns and absolute value of log-returns, more positive serial correlation can be observed, especially in daily data. Therefore, return variances are more correlated. Secondly, monthly returns tend to follow a random walk model better than daily returns. A.4. Correlation Matrix of Stocks and Indices Table VI presents the correlation matrix for all stocks and indices. As is shown in Panel A for daily result, all of the correlations are positive, ranging from 0.0551 (LION-FARO) to 0.5299 (NAN D10-FEIC). Within individual stocks, correlation coefficients do not differ a lot. The highest correlation is between FEIC and FARO with only 0.1214, indicating a fairly weak relationship between individual stocks returns. However, in terms of stock-index relationships, they differ drastically from 0.0638 (NAN D10-FARO) to 0.5299 (NAN D10-FEIC). While the positive correlation implies that the three stocks follow the indices in the same direction, the extent to which they will move with the indices is quite different, indicating different levels of risk with regard to different stock. Finally, we find that the correlation between NAN D10 and NAN D1 is the second highest at 0.5052. Panel B provides the correlation matrix for monthly data. Similar to results for daily data, negative correlation is not observed. The highest correlation attributes to that between NAN D10 and FEIC (0.7109) once again, but the lowest is between LION and FEIC (0.1146) this time. Compared with results in Panel A, correlation within individual stocks is slightly higher on average. The improvement in correlation is even more obvious between stocks and indices. It implies that stock prices can change dramatically from day to day, but they tend to follow the movement of indices in a longer horizon. Finally, the correlation between two indices is once again the second highest at 0.5116, following that between NAN D10 and FEIC. It is also found that the correlation between indices improves only marginally when daily data are replaced by monthly data, indicating a relatively stable relationship between indices. B. Variance Ratio Tests The results of variance ratio tests are presented in Table VII for each of the three stocks and two decile indices. The test is designed to test for the null hypothesis of a random walk under both homoskedasticity and heteroskedasticity. Since the violation of a random walk can result either from changing variance, i.e. heteroskedasticity, or autocorrelation in returns, the test can help to discriminate reasons for deviation to some extent. The lag orders are 2, 4, 8 and 16. In Table VII, the variance ratio (VR(q)), the homoskedastic-consistent statistics (Z(q)) and the heteroskedastic-consistent statistics (Z*(q)) are presented for each lag. As is pointed out by Lo and MacKinlay (1988), the variance ratio statistic VR(2) is equal to one plus the first-order correlation coefficient. Since all the autocorrelations are zero under RW1, VR(2) should equal one. The conclusion can be generalised further to state that for all q, VR(q) should equal one. According to the first Panel in Table VII, of all stocks and indices, only LION and NAN D1 have variance ratios that are significantly different from one at all lags. Therefore, the null hypothesis of a random walk under both homoskedasticity and heteroskedasticity is rejected for LION and NAN D1, and thus they are not weak-form efficient because of autocorrelations. In terms of FARO, the null hypothesis of a homoskedastic random walk is rejected, while the hypothesis of a heteroskedastic random walk is not. This implies that the rejection of random walk under homoskedasticity could partly result from, if not entirely due to heteroskedasticity. On the other hand, both FEIC and NAN D10 follow random walk and turn out to be efficient in weak form, corresponding exactly to the autocorrelation results reached before in Table III. Panel B shows that when monthly data are used, the null hypothesis under both forms of random walk can only be rejected for FARO. As for FEIC, the random walk null hypothesis is rejected under homoskedasticity, but not under heteroskedasticity, indicating that rejection is not due to changing variances because Z*(q) is heteroskedasticity-consistent. As is shown in Panel A for daily data, all individual stocks have variance ratios less than one, implying negative autocorrelation. However, the autocorrelation for stocks is statistically insignificant except for LION. On the other hand, variance ratios for NAN D1 are greater than one and increasing in q. The above finding provides supplementary evidence to the results of autocorrelation tests. As Table III shows, NAN D1 has positive autocorrelation coefficients in all lags, suggesting a momentum effect in multiperiod returns. Both findings appear to be well supported by empirical evidence. While daily returns of individual stocks seem to be weakly negatively correlated (French and Roll (1986)), returns for best performing market indices such as NAN D1 show strong positive autocorrelation (Campbell, Lo, and MacKinlay (1997)). The fact that individual stocks have statistically insignificant autocorrelations is mainly due to the specific noise contained in company information, which m akes individual security returns unpredictable. On the contrary, while the positive serial correlation for NAN D1 violates the random walk, such deviation provides investors with confidence to forecast future prices and reliability to make profits. C. Griffin, Kelly and Nardari DELAY Tests The results of delay test for the three stocks and two decile indices over the January 2000 to December 2005 period are summarised in Table VIII. We use lag 1, 2, 3, 4 for the daily data and 1, 2, 3 for the monthly data. As is presented in Panel A for daily returns, Delay_1 value for NAN D10 is close to zero and hence not significant, while NAN D1 has the highest delay among all stocks and indices. The rank of delay within individual stocks seems to have a positive relationship between size and delay value, by showing that delay of LION, the stock with smallest market capitalization is lowest, while the delay of FEIC, the stock with largest market capitalization is highest. It seems to contradict with the Griffin, Kelly and Nardari (2006) study, which says that there is an inverse relationship between size and delay. One possible explanation for that is that delay calculated by daily data on individual firms is noisy. The scaled measure Delay_2 produces consistent conclusion but with higher magnitude in values. Delay_2 values are very different from zero for FARO, FEIC, LION and NAN D1. The largest increase in value is seen in FARO from 0.0067 for Delay_1 to 0.7901 for Delay_2. Therefore, Griffin, Kelly and Nardari delay measure is preferable, because the scaled version can result in large values without economic significance. As is displayed in Panel B, employing monthly data also leads to higher Delay_1 values, indicating that more variation of monthly returns are captured by lagged market returns and hence monthly returns are not as sensitive as daily returns to market-wide news. However, an inverse relationship is found this time between delay and market value of individual stocks. Therefore, monthly data provides consistent result to support Griffin, Kelly and Nardari (2006) result as one would normally expect larger stocks to be more efficient in responding to market. Similar to the result for daily data, scaled measure once again produces higher values than its alternative but it provides the same results. V. Conclusion The main objective of this paper is to test weak-form efficiency in the U.S. market. As is found by selected tests, NAN D10 and FEIC provide the most consistent evidence to show weak-form efficiency, while the deviation from random walk is suggested for other stocks and indices, especially for NAN D1 and LION. It indicates that security returns are predictable to some degree, especially for those having best and worst recent performance. The three autocorrelation tests provide different results in terms of daily returns. While the null hypothesis of random walk is rejected for NAN D1 and LION based on log-returns, it is rejected for all stocks and indices based on both squared and absolute value of log-returns, indicating that return variances are more correlated. On the other hand, results in the context of monthly returns are consistent. Monthly returns follow a random walk much better than daily returns in all three tests. Most evidently, the autocorrelation test fails to reject the presence of random walk for all stocks and indices when monthly log-returns are employed. The variance ratio tests provide supportive evidence for autocorrelation tests. Both tests find that in terms of daily return, NAN D1 and LION show a significant return dependence. In particular, variance ratios for NAN D1 are all above one, corresponding to its positive AC and PAC coefficients, thus implying positive autocorrelation in returns. Whats more, individual stocks have variance ratios less than one with FEIC and FARO both being insignificant. The above evidence conclusively suggest that while individual stock returns are weakly negatively related and difficult to predict, market-wide indices with outstanding recent performance such as NAN D1 tend to show a stronger positive serial correlation and thus offer predictable profit opportunities. The evidence regarding delay tests is consistent with earlier findings to a large extent. NAN D1 has highest delay in both daily and monthly cases, implying an inefficient response to market news. In the context of monthly log-returns, delay values for individual stocks rank inversely based on market capitalisation with larger cap stocks having lower delay, suggesting that small stocks do not capture past public information quickly and are thus inefficient. Finally, deviation from a random walk model and thus being weak-form inefficiency is not necessarily bad. In fact, investors should be rewarded a certain degree of predictability for bearing risks. Therefore, future research could be done by incorporating risk into the model. [1] Company information is mainly obtained from Thomson One Banker database. [2] Griffin, John M., Patrick J. Kelly, and Federico Nardari, 2006, Measuring short-term international stock market efficiency, Working Paper

Wednesday, November 13, 2019

Wind Power Essay -- Exploratory Essays Research Papers

Wind Power Energy production causes more pollution than any other industry in the country. Currently, nearly all of the electricity produced in the United States is generated by fossil fuel plants, nuclear plants, and hydroelectric plants. The build-up in the atmosphere of carbon dioxide and other greenhouse gases produced by the burning of fossil fuels now threatens far-reaching climate change. In addition to global warming, conventional methods of electricity generation release the gases responsible for acid rain, sulfur dioxide and nitrogen oxide. In order to prevent further degradation of our environment and successfully transition to a sustainable society, we must change our current patterns of production and consumption. Conservation and switching to renewable sources of energy, such as wind power, are crucial steps to achieving this goal of sustainability. Wind power alone has the potential to meet 20 percent or more of the world's electricity needs within the next four to five years, (J ohansson, 157). Wind power, however, is still a developing technology, and is therefore far from reaching its full potential. How Wind Machines Work: Wind is the product of sunlight heating the surface of the Earth unevenly. Warmer air rises and cooler air tumbles in to replace it, causing everything from gentle breezes to raging tornadoes. Whatever the amount of power in the wind, it can be harnessed by a machine called a wind turbine. The most common type of wind turbine has a horizontal axis, with two or more aerodynamic blades mounted on the horizontal shaft, (AccessScience, "Types of Wind Machines"). As the wind passes over a turbine's blade, pressure forms on the downwind side, thrusting it upward like a propeller. In these... ... state's consumers the choice of who supplies their electric power and how that power is produced. With the implementation of at least some of these changes, wind power will eventually become a clean source of energy that all people can afford to rely on. Â   Sources: keyword: "Wind Power." Carley, Sanya, Sierra Curtis-McLane, and Galen O'Toole. "Renewable Energy at Swarthmore." April 15, 2001. Jacobson, Mark Z. and Gilbert M. Masters. "Exploiting Wind Versus Coal." August 24, 2001 Johansson, Thomas B. Renewable Energy: Sources for Fuels and Electricity. Island Press, Washington D.C., 1993. Raabe, Steve and Joey Bunch. "Advocates Say Wind Power Progressing from Novelty to Mainstream Practicality." The Denver Post Knight Ridder/Tribune Business News. April 20, 2003.