The And Revolutionary Black Scholes Model

11. Why is correlation data (data showing that two events occurred at the same time) not necessarily meaningful? Because one factor might not be the cause of the other.

There are several differences between correlation and causation. Correlation is if an event happens and is not related to another event and it is a coincidence. This would be if an event happened but it was not connected to another. An example of this would be catching a foul ball at a baseball game. It would be a correlation because you just happened to be in that place where the ball was hit and were able to catch it. Causation on the other hand is a cause and effect. One thing happens because another thing previously happened. An example of this would be if a person drank caffeine late at night, then they would be up all night. Another example of this would be if someone slipped on ice coming out of class.

Correlation is usually when two things tend to happen together at the same time and causation is something happens because of something else. I think it is harder to prove causation because

Researchers have studied the correlation between birth defects and tobacco. Correlation is not about cause and effect but rather how a relationship between two variables works

Correlative studies are ones where the independent variable is not manipulated. Instead, scientists research the existing variation in them. Causative studies are ones that manipulate the independent variable to see how it affects the dependent variable.

Answer: A positive correlation means that increases in the value of one variable are associated

“Insurance is expensive,” Furgeson said, “but if you have to take advantage of the insurance you purchased, it makes the insurance premium seem cheep compared to a production loss.”

True or False: Correlations are used to help identify the relationship between two variables. For

The textbook define the correlation coefficient as "a measure that is designed to indicate the strength of the relationship between two variables" (UBC Real Estate Division, 2009). The textbook also states "the correlation coefficient may be positive, negative, or zero" (UBC Real Estate Division, 2009). A strong relationship implies that there is a relationship between the two variables and "as one variable increases (decreases), the other the variable will increase (decrease)" (Estate Division, 2009). A strong relationship would have a correlation coefficient value of +1 or -1.

Mr. Brown readily admitted that he was not at ease discussing the most recent approaches to risk reduction or hedging. He had received his MBA from Harvard in the 1960s and had spent most of his career working for a company that had little international exposure. Moreover, he was not familiar with derivatives such as currency options, which until recently were not widely traded. However, Mr. Brown had recently hired an assistant, Mr. Dan Pross, who had some knowledge of hedging and derivatives. As a student at UCLA, Mr. Pross had traded various types of derivatives for his own portfolio and was familiar with how they were traded. Although Mr. Pross did not have a finance background, he was, in Mr. Brown’s opinion, extremely intelligent and highly capable. Mr. Brown suggested that Mr. Pross make a presentation to the senior management on the use of derivatives to reduce risk.

I believe it’s a correlation because of the relationship between the annual number of executions and the murder rate. I didn't think it was causation because causation is the action of causing something. Last semester, I had Statistics and I saw this study that when ice cream sales rise, so do homicides. That just proves that there’s a correlation, but it doesn’t necessarily mean there’s a causation. That applies to the Execution and the Murder

"A correlation is a statistical to determine the tendency or pattern for two (or more) variables or two sets of data to very consistently" (Creswell, (2012). any

Unger mentions the tendency for us to buy life insurance as a claim that good experiences are not the only thing that matter to us. We do not get good experiences for paying our life insurance. In fact, we will never experience anything that happens to this money. We do this so that our dependents will benefit from this money. With all this said, we are still very rational in buying this life insurance. (Unger 1990, 166) Therefore, we should value our capacity to make free decisions in the real world over just having good experiences.

Research shows that there is a correlation that shows the relationshop between the IQ and the grade point average of students. It was found that the correlation is strong at a .75 because it’s a direct relationship. For instance when someone has a higher IQ they are more likely going to have a higher GPA. However although the correlation shows a higher IQ means higher GPA does not mean that is the only reason the GPA is rising, it could be because they hired a tutor, have been studying more or are maybe just in more interesting classes. In correlation studies they show that there is a relationship between two different variables however it is not evidence or proof in any way. The reason it isn’t proof is because it has not been proven that they are directly the reason for the relationship however that they do have common results. Some of the reasons correlation cannot prove anything is because of the limitations; these would be the lack of information about the correlation, sample size or the standard deviation. In our text it states “If the word correlation is broken down co-relation it is expresses what is meant: The characteristics are related and the evidence for the relationship is that they vary together, or co-vary. As the level of one variable changes, the other changes in concert, this happens because both variables contain some of the same information. The higher the correlation the more they may have in common” (Tanner,2011).

The Black Scholes Merton (BSM) model is the best-known model for valuing options as it is the original of many option pricing models today (Haug and Taleb, 2009; Le, 2015). Developed in 1973 by Fisher Black, Myron Scholes and Robert Merton, the BSM model is still widely used today as the benchmark for many models and techniques that financial analysts use to analyse and determine the fair prices of given options (Jumarie, 2010). It is widely used due to its simplicity however there are many criticisms regarding the assumptions made by the model (Bharath and Sumway, 2008; Haug and Taleb, 2009; Le, 2015)