Brianna started technical college with the goal of becoming a veterinarian but faced significant financial challenges. She took out the maximum available in loans and aid but still had an unmet need of $4,500. To make ends meet, she worked 30 hours a week between two jobs on top of a full course load. The stress took its toll, as she fell asleep in class and earned poor grades in her first term, including D's in two courses and a cumulative GPA of just 0.750.
Effects of option characteristics and underlying stock on option beta articleDharma Bagoes Oka
Beta (β) is one of the risk management tools to capture the risk exposures of hedge-fund investments. As most of hedge funds today trade derivative securities, the research on the measurement of derivative beta is important. The aim of this paper is to examine the factors, which may have impacts on option beta in the United States market. My hypothesis is comprised into three main parts. First, I hypothesize that 5 variables (type of option, strike price, days to maturity, firm size and book to market ratio) have linear relationship with the option beta. Second, I hypothesize that the strength of linear relationship is varied by the type of the industry. Third, I hypothesize that the strength of linear relationship is also varied by these 5 types of variables itself. To begin the process, I use regression method to estimate the beta of underlying stock. Then, I estimate the option beta by multiplying the beta of underlying stock and the option elasticity. I then use regression method to test whether the 5 variables have linear relationship with option beta. I find that 3 variables (type of option, strike price and days to maturity) have the most significant linear relationship with option beta, while firm size has less significant linear relationship and book to market ratio have no significant linear relationship. Furthermore, using 2-way ANOVA, I test whether strength of linear relationship is varied by the type of the industry and the 5 types of variables. There is not enough evidence to infer that the strength of linear relationship between the 5 variables to option beta is varied by the type of the industry, instead, there is enough evidence to infer that the strength of linear relationship between the 5 variables to option beta is varied by the type of variables.
Effects of option characteristics and underlying stock on option beta articleDharma Bagoes Oka
Beta (β) is one of the risk management tools to capture the risk exposures of hedge-fund investments. As most of hedge funds today trade derivative securities, the research on the measurement of derivative beta is important. The aim of this paper is to examine the factors, which may have impacts on option beta in the United States market. My hypothesis is comprised into three main parts. First, I hypothesize that 5 variables (type of option, strike price, days to maturity, firm size and book to market ratio) have linear relationship with the option beta. Second, I hypothesize that the strength of linear relationship is varied by the type of the industry. Third, I hypothesize that the strength of linear relationship is also varied by these 5 types of variables itself. To begin the process, I use regression method to estimate the beta of underlying stock. Then, I estimate the option beta by multiplying the beta of underlying stock and the option elasticity. I then use regression method to test whether the 5 variables have linear relationship with option beta. I find that 3 variables (type of option, strike price and days to maturity) have the most significant linear relationship with option beta, while firm size has less significant linear relationship and book to market ratio have no significant linear relationship. Furthermore, using 2-way ANOVA, I test whether strength of linear relationship is varied by the type of the industry and the 5 types of variables. There is not enough evidence to infer that the strength of linear relationship between the 5 variables to option beta is varied by the type of the industry, instead, there is enough evidence to infer that the strength of linear relationship between the 5 variables to option beta is varied by the type of variables.
Effects of option characteristics and underlying stock on option beta articleDharma Bagoes Oka
Beta (β) is one of the risk management tools to capture the risk exposures of hedge-fund investments. As most of hedge funds today trade derivative securities, the research on the measurement of derivative beta is important. The aim of this paper is to examine the factors, which may have impacts on option beta in the United States market. My hypothesis is comprised into three main parts. First, I hypothesize that 5 variables (type of option, strike price, days to maturity, firm size and book to market ratio) have linear relationship with the option beta. Second, I hypothesize that the strength of linear relationship is varied by the type of the industry. Third, I hypothesize that the strength of linear relationship is also varied by these 5 types of variables itself. To begin the process, I use regression method to estimate the beta of underlying stock. Then, I estimate the option beta by multiplying the beta of underlying stock and the option elasticity. I then use regression method to test whether the 5 variables have linear relationship with option beta. I find that 3 variables (type of option, strike price and days to maturity) have the most significant linear relationship with option beta, while firm size has less significant linear relationship and book to market ratio have no significant linear relationship. Furthermore, using 2-way ANOVA, I test whether strength of linear relationship is varied by the type of the industry and the 5 types of variables. There is not enough evidence to infer that the strength of linear relationship between the 5 variables to option beta is varied by the type of the industry, instead, there is enough evidence to infer that the strength of linear relationship between the 5 variables to option beta is varied by the type of variables.
A slide review of the article competing against free (HBR). This has been done in accordance with the requirements of the Brand Management course, MBA, IIM Lucknow
Effects of Option Characteristics and Underlying Stock on Option BetaDharma Bagoes Oka
Beta (β) is one of the risk management tools to capture the risk exposures of hedge-fund investments. As most of hedge funds today trade derivative securities, the research on the measurement of derivative beta is important. The aim of this paper is to examine the factors, which may have impacts on option beta in the United States market. My hypothesis is comprised into three main parts. First, I hypothesize that 5 variables (type of option, strike price, days to maturity, firm size and book to market ratio) have linear relationship with the option beta. Second, I hypothesize that the strength of linear relationship is varied by the type of the industry. Third, I hypothesize that the strength of linear relationship is also varied by these 5 types of variables itself. To begin the process, I use regression method to estimate the beta of underlying stock. Then, I estimate the option beta by multiplying the beta of underlying stock and the option elasticity. I then use regression method to test whether the 5 variables have linear relationship with option beta. I find that 3 variables (type of option, strike price and days to maturity) have the most significant linear relationship with option beta, while firm size has less significant linear relationship and book to market ratio have no significant linear relationship. Furthermore, using 2-way ANOVA, I test whether strength of linear relationship is varied by the type of the industry and the 5 types of variables. There is not enough evidence to infer that the strength of linear relationship between the 5 variables to option beta is varied by the type of the industry, instead, there is enough evidence to infer that the strength of linear relationship between the 5 variables to option beta is varied by the type of variables.
Effects of option characteristics and underlying stock on option beta articleDharma Bagoes Oka
Beta (β) is one of the risk management tools to capture the risk exposures of hedge-fund investments. As most of hedge funds today trade derivative securities, the research on the measurement of derivative beta is important. The aim of this paper is to examine the factors, which may have impacts on option beta in the United States market. My hypothesis is comprised into three main parts. First, I hypothesize that 5 variables (type of option, strike price, days to maturity, firm size and book to market ratio) have linear relationship with the option beta. Second, I hypothesize that the strength of linear relationship is varied by the type of the industry. Third, I hypothesize that the strength of linear relationship is also varied by these 5 types of variables itself. To begin the process, I use regression method to estimate the beta of underlying stock. Then, I estimate the option beta by multiplying the beta of underlying stock and the option elasticity. I then use regression method to test whether the 5 variables have linear relationship with option beta. I find that 3 variables (type of option, strike price and days to maturity) have the most significant linear relationship with option beta, while firm size has less significant linear relationship and book to market ratio have no significant linear relationship. Furthermore, using 2-way ANOVA, I test whether strength of linear relationship is varied by the type of the industry and the 5 types of variables. There is not enough evidence to infer that the strength of linear relationship between the 5 variables to option beta is varied by the type of the industry, instead, there is enough evidence to infer that the strength of linear relationship between the 5 variables to option beta is varied by the type of variables.
A slide review of the article competing against free (HBR). This has been done in accordance with the requirements of the Brand Management course, MBA, IIM Lucknow
Effects of Option Characteristics and Underlying Stock on Option BetaDharma Bagoes Oka
Beta (β) is one of the risk management tools to capture the risk exposures of hedge-fund investments. As most of hedge funds today trade derivative securities, the research on the measurement of derivative beta is important. The aim of this paper is to examine the factors, which may have impacts on option beta in the United States market. My hypothesis is comprised into three main parts. First, I hypothesize that 5 variables (type of option, strike price, days to maturity, firm size and book to market ratio) have linear relationship with the option beta. Second, I hypothesize that the strength of linear relationship is varied by the type of the industry. Third, I hypothesize that the strength of linear relationship is also varied by these 5 types of variables itself. To begin the process, I use regression method to estimate the beta of underlying stock. Then, I estimate the option beta by multiplying the beta of underlying stock and the option elasticity. I then use regression method to test whether the 5 variables have linear relationship with option beta. I find that 3 variables (type of option, strike price and days to maturity) have the most significant linear relationship with option beta, while firm size has less significant linear relationship and book to market ratio have no significant linear relationship. Furthermore, using 2-way ANOVA, I test whether strength of linear relationship is varied by the type of the industry and the 5 types of variables. There is not enough evidence to infer that the strength of linear relationship between the 5 variables to option beta is varied by the type of the industry, instead, there is enough evidence to infer that the strength of linear relationship between the 5 variables to option beta is varied by the type of variables.
Social Media State of Play Australia 2012BuzzNumbers
An Australian state of play report that looks at hard statistics and draw some top-level conclusions about how social media is shaping the Australian corporate space.
This report provides a general view of the social landscape, but we encourage you to contact us for a bespoke report on your business or for one of our industry reports.
Data science is one of the hottest and fastest-growing fields in companies around the world. But it remains a highly male-dominated field, with women making up as few as 15% of data science professionals globally. This gender imbalance is a
significant threat to sustainable growth and to unbiased, safe AI
Responses to a BCG global survey of over 9,000 current and former students across ten countries make it clear that a
significant share of the problem lies with the companies themselves.
UCL women's group presentation final versionBelinda Brown
Belinda Brown from the Gender Equity Network explores the possibility that gender equality policies designed to correct gender imbalances at the top of academia may be obscuring far more serious inequalities occurring further down
The CERIC Survey of Career Service Professionals was conducted between October 14 and November 18, 2011. The online survey was completed by 1,013 respondents from the field. Participants were recruited via an open call across CERIC’s email lists.
Supporting organizations also forwarded the survey notification to broaden representation. The survey delved into research and education issues as well as career competency and mobility. The resultant information offers a snapshot of the composition of the career services community including some of its interests and challenges, along with professional development and information needs.
In a time when young people are being described by some commentators as the ‘lost generation’, this international survey of 20-29 year olds sheds light on the views and attitudes of young people on the important questions that world leaders face today.
The broad political landscape is defined, for many, by the economic crisis and how their governments have responded. There are strong calls for the financial sector to operate in a more ethical and responsible way which may include further regulation of the sector. Although, trust in their government’s ability to deliver is weak, particularly so in Europe. The theme of behaving in an ethical and responsible way is not only limited to the financial sector, but it is also expected of global corporations and governments.
Beyond economics, poverty and corruption run through the piece as topics that are of the utmost importance to many of the world’s young. It is these factors that are perceived to be the root of inequality in many areas of civil society such as education, health, and democracy. However, there exists a sense of ineffectuality amongst many of Europe and the West’s young people as indicated by their low levels of political and civil engagement both online and ‘offline’.
Indeed, hope and optimism amongst Europeans is a lot lower than their counterparts elsewhere in the world. India and China in particular stand out as the countries that are most positive about their futures. The level of depression between the west and the rest is startling, and the political and economic context 20-29 years olds are living in is summed up by the perception that their lives will not be better than their parents’.
Video: TBA
Concurrent Paper Session 4.3 Planet
Tourism and the Sustainable Development Goals Conference 2019, 24-25 Jan 2019, Massey University, Auckland, New Zealand https://tourism-sdg.nz
This presentation explored key recommendations in the Annie E. Casey Foundation's publication, "A Child Welfare Leader’s Desk Guide to Building a High-Performing Agency," including strategies for collecting and analyzing data about disparities.
The Clearinghouse helps educational institutions improve efficiency, reduce costs and workload, and enhance the quality-of-service they provide to their students and alumni, lending institutions, employers, and other organizations.
Hang in there! You are somebody’s hope. There is a rumor mulling around
in colleges across the land that science, technology, engineering, and
math are the “hardcore” fields that some advance, others try, and many
avoid. Women and minorities are grossly underrepresented in STEM
careers and the numbers continue to decline. In a 2010 Bayer Corp. survey
of 1,226 women and underrepresented minority chemists and chemical
engineers, 40 percent said they were discouraged from pursuing a STEM
career. Sixty percent said college was where most of the discouragement
happened. STEM careers offer a rewarding journey of innovation and
powerful contributions, solutions, and tools that secure and advance our
future. So, what do you need to do to overcome challenges and succeed
in these fields?
At the end of this workshop, college students will:
a. Explore STEM Stats and common reasons students get discouraged
b. Create a resource toolbox and networking plan to overcome challenges
c. Explore 7 key habits that can increase success
d. Examine the benefits and options of a great STEM Career Path
64. Thank You
“It is not the critic who counts; not the man who points out how the
strong man stumbles, or where the doer of deeds could have
done them better. The credit belongs to the man who is actually
in the arena…who at the best knows in the end the triumph of
high achievement, and who at the worst, if he fails, at least fails
while daring greatly, so that his place shall never be with those
cold and timid souls who neither know victory nor defeat.”
Teddy Roosevelt, April 23, 1910
Josh Jarrett, Deputy Director
Education – Postsecondary Success
josh.jarrett@gatesfoundation.org
www.gatesfoundation.org
Editor's Notes
Greetings, etc
3468 W.2.2.10
Interactive Tools, Guides and ServicesDegree Search helps new students understand our majors as well as helps current students find new majors. Students find a major by searching on the name of a major, college, area of interest, campus and/or keyword. For instance, if a student searches for “people,” Degree Search lists all degrees that involve the study of people.
How Tracking WorksSun Devil Tracking helps students understand degree requirements and provides early intervention when students get off track with their degree program.Identify: Sun Devil Tracking focuses on students who initially enroll as full-time freshmen and then it tracks their progress during their first four semesters. It identifies and clearly outlines the critical courses, GPA requirements and milestones that predict success in each major. During orientation, freshmen review their major maps with their advisors in order to make sure they register for the right courses.
Plan: The student uses major maps and progress reports to plan what courses to take each semester. The university ensures there are enough seats so students can enroll in critical and required courses they need, when they need them. The Course Enrollment Dashboard report provides key information the university uses in course planning.Students pull up their Critical Requirement Audit to find out which courses they need to take next.
The Sun Devil Tracking Status report provides advisors and administration a way to track on- and off-track students by academic group.
We continue to improve the process and get students on the right track. Through critical tracking, more than 80% of our students are off to a good start and registered for the right courses.