Revised Blog Assignment

In the speech “The route to a sustainable future”, the speaker, Alex Steffen, gave his lecture focusing on one word－sustainability. He discusses the waste created by humanity and unfair usage of natural resources to reach through his point about why we need “world changing”. World changing is a bit of new service we adopt to change the future, for examples, tools, models and ideas.  He gives two solutions that researchers are still studying for in order to reach this goal. One is building up a bright green city by enhancing the living quality and the population density in a city such as Vancouver. Another solution is about implementation for collaboration, it is particularly talking about once people have their chances to cooperate and innovate, and distinct solutions will come out. In the end, the author believes that one day the humanity will make the world better through the ideas of world changing.

Compare the differences between Azuma (1997) and Xia et al (2008)

After perusing these two articles, I found the authors of these two articles used distinct writing skills. For myself, I found reading Azuma (1997) is easier than reading Xia et al (2008), and I also observed many other differences between these two articles. I will show three aspects that I think are different between these two articles in the following paragraphs.

Audience

These two articles focus on distinct audiences. For Azuma (1997), as the author said in the beginning paragraph, “this is a computer science graduate school survival guide,” we can affirm that the audiences are more general audience. Also, we can know that the author are focus on those people who have decided to study in the field of computer science. The author himself is already a doctor, so the audiences can get to know more about this field and can be well prepared after finishing this article. What's more, the writer answer some of the complicated problems that the audiences might face in their future road, it will make the audiences feel less stressful and less confused.

The audiences of Xia et al (2008) differ from those of Azuma (1997). The audiences of this article might be used to study in this field and might be familiar with the content that means the audiences can be the students, theorists, professors or practitioners working related to the supply chain management. While reading Xia et al (2008), the readers could compare with their own methods or means and gain additional professional knowledge.

Style

There are colloquialisms and casual expressions being used in Azuma (1997). For instance, there is a paragraph using the sentence like "Why the hell am I doing this?"(P.2, 3). Also, other examples like “I would have no regrets because I had given it my best shot and was not able to make it” (P.3) and “Don't take them for granted.”(P.4). These three sentences are using colloquial words and they are informal. Furthermore, the writer often uses “I” as a subject, which would only appear in the informal writing. There is a paragraph, I got the Ph.D. because I wanted to get a research position after leaving graduate school. I wanted to work with the state of the art and extend it. I did not want to bring yesterday's technology one step closer to tomorrow. I wanted a job that would I find interesting, challenging and stimulating. Azuma (1997, P.3). I think the statement is too lengthy. The author also uses the words “good” and “bad”, those are all belong to casual expressions. In contrast, in the composition Xia et al (2008), the writer states his points confidently and offers his argument firm support.

Rhetorical Structure

It is obvious that the structure used by Azuma is informal as compared to Xia et al. In my opinion, the structure and the word used in the article are simpler and easier. The reason is because this article is written to help prospective or novice graduate students, as it states in the beginning that this article is a guidebook. Also, I think this article is more casual because the writer provides many experiences, resolutions to the problem that the reader might face.

As compared, it is obvious that Xia et al (2008) is a business academic literature. The article starts with an abstract that states what the article is writing about and what the main result is. Also, there is an introduction to let the reader know about the topic, the reason for the author to write this article and how the author completed this research. For the following several sections, the author talks about some models and means researched by others, the advantages of using those models and how are they different from the previous literature. After the discussion of methods and means, the author gives some examples to support the assumption. In the last paragraph, as formal academic writing, there is a conclusion and some references of this literature included.

In a nutshell, after comparing three aspects between these two articles, I could easily tell whether this is an academic writing or informal writings. Furthermore, I learned that the structure can be varies by different intentions. Also by recognizing who are the main audiences for the article matter the writing too.

 1.

This is a thesis.

Reference:

Aloe, A. M. (2009). A partial effect size for the synthesis of multiple regression models (Order No. 3373964). 

Available from ProQuest Dissertations & Theses Full Text; ProQuest Education Journals. 

2.

This is an article.

Reference:

Allore, H., Tinetti, M. E., Araujo, K. L. B., Hardy, S., & Peduzzi, P. (2005). A case study found that a regression tree outperformed multiple linear regression in predicting the relationship between impairments and social and productive activities scores.Journal of Clinical Epidemiology, 58(2), 154-161.

3.  

This is a book.

Reference:

Lin, C. (2009). Evaluating the transactional theory of coping as a psychosocial adaptation model for taiwanese with spinal cord injury: A multiple regression analysis 

Revised Blog Assignment

Article 1.

-Reference:

Yingsaeree, C., Nuti, G., & Treleaven, P. (2010). Computational finance. Computer, 43(12), 36-43.

The authors notified that computational finance consists of two branches, data mining and computer modeling. The authors listed some tools, methods and financial forecasting as applications. Moreover, Yingsaeree, C., Nuti, G., & Treleaven, P. (2010) noted that in parametric optimization “if the problem considered has a linear objective function and linear constraints, stat­isticians can use numerical analysis techniques such as interior-point and simplex methods. However, when the objective function and constraints are nonlinear, statisti­cians frequently use stochastic search algorithms derived from AI, such as genetic algorithms and simulated anneal­ing, to obtain an approximation of the optimal answer” (p. 39).

Article 2.

-Reference:

Zhou, S., & Zhu, N. (2013). Multiple regression models for energy consumption of office buildings in different climates in china.Frontiers in Energy, 7(1), 103-110.

Different combinations of the 8 key influencing factors were simulated in Trnsys and the regression models were proved to be feasible and accurate to estimate the Trnsys simulation. Besides, the multiple regression models were established respectively in the four climates in China based on the simulated results. Most importantly, the error rates always remain within +/-15%. The error rates in actual case evaluations seem to be larger than those in simulation evaluations. This can be explained by the fact that the regression models were established on the basis of the typical meteorological year data while the actual energy consumption was recorded in a specific year (Zhou, S., & Zhu, N., 2013, p. 109).

Article 3.

-Reference:

Chen, V. C., Stewart, R., & Lee, C. T. (2012). Weekly lottery sales volume and suicide numbers: A time series analysis on national data from Taiwan. Social Psychiatry and Psychiatric Epidemiology, 47(7), 1055-1059.

In a time-series analysis of national data, the authors investigated associations between weekly suicide numbers and weekly lottery sales volumes, finding a positive association with sales for one lottery system (higher cost, higher winnings, lower probability of winning) but a negative association with another (lower cost, lower winnings, higher probability of winning). Both associations were strongest for male compared to female suicides. The strengths of the design include the large and representative samples and potentially high level of statistical power. The principal limitation with any study of this nature is that causality is difficult to infer and we can only say that findings are consistent with a given hypothesis (Chen, V. C., Stewart, R., & Lee, C. T., 2012, p. 1058).

Revised Blog Assignment

                                                                  FRED, Federal Reserve Bank of St. Louis, 2014 

            The graph shows the movement of the S&P 20-City Case-Shiller Home Price Index and the duration is from 2000/01/01 to 2014/08/01. This index is the leading measure of U.S. residential real estate prices, tracking changes in the value of residential real estate both nationally as well as 20 metropolitan regions; many analysts and economists use this index as a major indicator of U.S. economic indicator. As we can see in the figure, the housing price in the U.S. grew steadily from the beginning of 2000 to the beginning of 2007. It seems that during that period of time, the U.S. economy was in a good condition with steady growth. However, as the outbreak of subprime crisis in the mid-2007, the situation turned the other way around. As the result, we can see that the housing price dropped dramatically during 2007 to 2009. It can be seen in the chart that the index dropped from 205 to 140. The subprime crisis not only forced the U.S. economic into a serious recession, but also caused huge raise in unemployment rate and many bank failures during that period. As we can see in the figure, the impact brought by the subprime crisis lasted for quite a long time. The U.S. economy remained in recession and the housing price stayed  between 130 and 150 during that period. Not until 2012, the housing price started to climb again, and the climb in the housing price means that the U.S. economic is reviving. Although the housing price is growing as a relatively slow pace, still, it is good to know that the recession has finally come to an end.

                                                       FFIEC, Federal Financial Institutions Examination Council, 2014

The Uniform Bank Performance Report (UBPR) is an analytical tool created for bank supervisory, examination, and management purposes. In a concise format, it shows the impact of management decisions and economic conditions on a bank's performance and balance-sheet composition. Based on the UBPR above, Citibank and peer group are the participants being analyzed.

The graph above presents the trend of the gap for both Citibank and peer group. As we can see in the figure, the average gap for Citibank is much smaller than then peer group, and the gap for both Citibank and peer group is getting more negative from 2009 to 2013. The negative gap suggests that not only Citibank, but the peer group is liability sensitive, for example, there is a -11.2% gap for Citibank and -10.8% for Peer Group. This means that if the interest rate goes up, all these banks will suffer losses, but, for Citibank, the negative gap is much smaller than the peer group, the magnitude of the impact of the raising interest rate on Citibank might be smaller comparing to other Banks in peer group. 

The reason why Citibank has much lower gap is that, in UBPR report, Citibank has more short-term assets than peer group. The short-term earning assets to total earning asset for Citibank is 51.02%, comparing with 24% for peer group. We can conclude that, since Citibank has lower gap than peer group bank, the negative impact of raising interest rate might do little damage to Citibank than to peer group, and the positive benefit that comes along with the better economic condition might benefit more Citibank than peer group.

                                                                                       Bloomberg, 2014

The graph above is to examine the correlation in the period of recession (2007 – early 2009) between US Initial Jobless Claims (INJCJC) and 90-days U.S. Treasury Bill Rates (T-Bill Rates-a short-term and risk free interest rate). Initial Jobless Claims will be the independent variable that test the degree of impact on 90-days U.S. Treasury Bill Rates. Issued one week later than the initial claims at 8:30 EDT on Thursdays by the U.S. Department of Labor, Initial Jobless Claims is a report that follows how many people first time apply for unemployment benefits in the previous week.

The amount increasing in Initial Jobless Claims indicates the number that moves from employment part to unemployment part of the working-age population. Different from Unemployment Rate, which is continually accumulated data, Initial Jobless Claims was influenced only by the newest economic environment. Moreover, since INJCJC is being reported once a week, it reflects the latest information and changes. This run chart was drawn from Bloomberg Terminal Database and the reason that this period is worth carrying is because there is a significant trend.

In addition, the Subprime Mortgage Crisis in 2007 was well-known triggered by a large decline in home prices, resulting in mortgage delinquencies and foreclosures, also, in the devaluation of housing-related securities. One year later, the bankruptcy of Lehman Brothers set off the financial crisis of 2008. According to the run chart above, we could easily identify that there is a negative relationship between INJCJC and 90 Days T-Bill Rate (Shown as the indicating arrow). Between 18 September 2007 and 30 April 2008, the target Federal Funds Rate was lowered from 5.25% to 2%. The short-term T-bill rate or so called “risk free” rate was also being trading at lower rate simultaneously. However, when the market was recovering from the crisis, Fed Funds Rate target has still been set at 0.00 – 0.25 for a long periods. Even though there was an improvement in unemployment, the short-term rate was still set at a relatively low level.

In conclusion, it is worthwhile to note that unemployment stays or becomes relatively high, the Federal Reserve would adjust the Fed Funds Rate to a lower level in order to decrease the cost of borrowing and to increase the money supply, resulting in a lower short-term T-Bill rate. 

Article 1.

-Reference:

Yingsaeree, C., Nuti, G., & Treleaven, P. (2010). Computational finance. Computer, 43(12), 36-43.

-Summary of main points made by the article's author:

The authors notified that computational finance consists of two branches, data mining and computer modeling. The authors listed some tools, methods and financial forecasting as applications.

-Relevant quote and/or an evaluation of this article in terms of the source relevance /importance:

Yingsaeree, C., Nuti, G., & Treleaven, P. (2010) noted that in parametric optimization “if the problem considered has a linear objective function and linear constraints, stat­isticians can use numerical analysis techniques such as interior-point and simplex methods. However, when the objective function and constraints are nonlinear, statisti­cians frequently use stochastic search algorithms derived from AI, such as genetic algorithms and simulated anneal­ing, to obtain an approximation of the optimal answer” (p. 39).

Article 2.

-Reference:

Zhou, S., & Zhu, N. (2013). Multiple regression models for energy consumption of office buildings in different climates in china.Frontiers in Energy, 7(1), 103-110.

-Summary of main points made by the article's author:

Different combinations of the 8 key influencing factors were simulated in Trnsys and the regression models were proved to be feasible and accurate to estimate the Trnsys simulation. Besides, the multiple regression models were established respectively in the four climates in China based on the simulated results.

-Relevant quote and/or an evaluation of this article in terms of the source relevance /importance

The error rates always remain within +/-15%. The error rates in actual case evaluations seem to be larger than those in simulation evaluations. This can be explained by the fact that the regression models were established on the basis of the typical meteorological year data while the actual energy consumption was recorded in a specific year (Zhou, S., & Zhu, N., 2013, p. 109).

Article 3.

-Reference:

Chen, V. C., Stewart, R., & Lee, C. T. (2012). Weekly lottery sales volume and suicide numbers: A time series analysis on national data from Taiwan. Social Psychiatry and Psychiatric Epidemiology, 47(7), 1055-1059.

-Summary of main points made by the article's author:

In a time-series analysis of national data, the authors investigated associations between weekly suicide numbers and weekly lottery sales volumes, finding a positive association with sales for one lottery system (higher cost, higher winnings, lower probability of winning) but a negative association with another (lower cost, lower winnings, higher probability of winning). Both associations were strongest for male compared to female suicides.

-Relevant quote and/or an evaluation of this article in terms of the source relevance /importance

The strengths of the design include the large and representative samples and potentially high level of statistical power. The principal limitation with any study of this nature is that causality is difficult to infer and we can only say that findings are consistent with a given hypothesis (Chen, V. C., Stewart, R., & Lee, C. T., 2012, p. 1058).

The graph above is to examine the correlation in the period of recession (2007 – early 2009) between US Initial Jobless Claims (INJCJC) and 90-days U.S. Treasury Bill Rates, which is a short-term and risk free interest rate. Initial Jobless Claims will be the independent variable to be tested the degree of impact that it has on 90-days U.S. Treasury Bill Rates. Issued one week later than the initial claims at 8:30 EDT on Thursdays by the U.S. Department of Labor, Initial Jobless Claims is a report that follows how many people first time apply for unemployment benefits in the previous week. The amount increasing in Initial Jobless Claims indicates the number that moves from employment part to unemployment part of the working-age population. Different from Unemployment Rate, which is a continually accumulated data, Initial Jobless Claims shows the net number that influenced only by the newest economic environment. Moreover, since it is being reported once a week, it reflects the latest information and changes. This run chart was drawn from Bloomberg Terminal Database and the period worth carrying is because there is a significant trend at that time. The Subprime Mortgage Crisis in 2007 was well-known triggered by a large decline in home prices, resulting in mortgage delinquencies and foreclosures and the devaluation of housing-related securities. One year later, the bankruptcy of Lehman Brothers set off the financial crisis of 2008. According to the run chart above, we could easily identify that there is a negative relationship between INJCJC and 90 Days T-Bill Rate (Shown as the indicating arrow). Between 18 September 2007 and 30 April 2008, the target Federal Funds Rate was lowered from 5.25% to 2%. The short-term T-bill rate or so called “risk free” rate were also being trading at lower rate simultaneously. However, when the market is recovering from the crisis, Fed Funds Rate target has still been set at 0.00 – 0.25 for a long periods. Even though there is an improvement in unemployment, the short-term rate is still set at a relatively low level. It is worthwhile to note that unemployment stays or becomes relatively high, the Federal Reserve would adjust the Fed Funds Rate to a lower level in order to decrease in cost of borrowing and to increase in the money supply, resulting in a lower short-term T-Bill rate. The FOMC (Federal Open Market Committee) recently says, “To support continued progress toward maximum employment and price stability, the Committee reaffirmed in its September 2014 statement its view that a highly accommodate stance of monetary policy remains appropriate.”

The graph shows the movement of the S&P 20-City Case-Shiller Home Price Index and the duration is from 2000/01/01 to 2014/08/01. This index is the leading measure of U.S. residential real estate prices, tracking changes in the value of residential real estate both nationally as well as 20 metropolitan regions; many analysts and economists use this index as a major indicator of U.S. economic indicator. As we can see in the figure, the housing price in the U.S. grow steadily from the beginning of 2000 to the beginning of 2007. It seems that during that period of time, the U.S. economic is in a good condition with steady growth. As the outbreak of subprime crisis in the mid-2007, the situation turned the other way around. As the result, we can see that the housing price drops dramatically during 2007 to 2009. The subprime crisis not only forced the U.S. economic into a serious recession, but also caused huge raise in unemployment rate and many bank failures during that period. As we can see in the figure, the impact brought by the subprime crisis last for quite a long time. The U.S. economic remains in recession and the housing price remain fluctuating between 130 and 150 during that period. Not until 2012, the housing price starts to climb again, and the climb in the housing price means that the U.S. economic is reviving. Although the housing price is growing in a relatively slow pace, still, it is good to know that the recession has finally come to an end.

Based on the Uniform Bank Performance Report (UBPR), we can know that the reprising risk of Citibank was lower than that risk of peer group from 2009 to 2013. That is to say, because the ratios of mortgage loans and loans & securities over five years and over fifteen years are all smaller than those ratios of peer group, these ratios indicate that Citibank has lower mortgage loans and long-term loans and securities during these five years.The graph above presents the trend of the gap for both Citibank and peer group. As we can see in the figure, the average gap for Citibank is much smaller than then peer group, and the gap for both Citibank and peer group is getting more negative from 2009 to 2013. The negative gap suggests that not only Citibank, but the peer group is liability sensitive. This means that if the interest rate goes up, all these banks will suffer losses, but, for Citibank, the negative gap is much smaller than the peer group, the magnitude of the impact of the raising interest rate on Citibank might be smaller comparing to other Banks in peer group. The reason why Citibank have much lower gap is that, in UBPR report, Citibank has more short-term assets than peer group. The short-term earning assets to total earning asset for Citibank is 51.02%, comparing with 24% for peer group. We can conclude that, since Citibank has lower gap than peer group bank, the negative impact of raising interest rate might do much little damage to Citibank than to peer group, and the positive benefit that comes along with the better economic condition might benefit more on Citibank than peer group.

---

 

1.  “But in spite of that vicious-circle relationship for all individuals when taken together as the whole body of producers and customers, each person in our present industrial system is striving to make money.”

This is a sentence from a book, it is primary source.

Reference:

Joseph E. Shafer, (1928). An Explanation of the Business Cycle. The American Economic Review, Vol. 18, No. 4, pp.619.

Retrieved from http://www.jstor.org.proxygw.wrlc.org/stable/1810445?seq=3

2.  “Mr. Shafer's discussion of the business cycle in the December, 1928, number of this journal contains a section on the equation of exchange. He starts out wisely by defining his concept of the various terms in Professor Fisher's familiar form of the equation: MV + M'V' = PT.”

This is a citation from an article, which is a secondary source. 

Reference:

Caroline Whitney, (1929). Mr. Shafer on the Equation of Exchange and the Business Cycle, pp.76.

Retrieved from

http://www.jstor.org.proxygw.wrlc.org/stable/view/1809586

3.  A bibliography (not listed) of a book, it is a tertiary source.

Reference:

William D. Wells (1971), "Factor analysis in marketing research,” Faculty working papers, Handbook of Marketing Research, McGraw-Hill Book Company.

In the speech “The route to a sustainable future”, the speaker, Alex Steffen, gave his speech focusing on one word－sustainability. He uses the waste created by humanity and unfair usage of natural resources to reach through his point about why we need “world changing”. He gives two solutions that they are still studying for in order to reach this goal. One is building up a bright green city by enhancing the living quality and the population density in a city. Another solution is about implements for collaboration, it is particularly about there will come out distinct solutions once people have their chances to cooperate and innovate. In the end, the author believes that one day the humanity will make the world better.