Hey everyone!
This week's blog post involves setting up my research schedule and discussing the data analysis techniques within my study. So, without further hesitation. Here it is:
January 16th-23rd: Compile data on all NASDAQ companies in the industries that Yelp, Facebook, LinkedIn, Twitter, and Tencent Holdings Inc. are in. Begin separating data based upon the different financial variables I will be analyzing in the study. These financial variables are based upon the multiples I have decided to use within my study.
January 23rd-30th: Finish separating and entering data on different financial variables into Excel. Write R program that parses the excel data to find comparable groups for the firms I plan on analyzing in my study. This is done with a technique implemented by a research study on biotechnology firms. To find a group of comparable firms for a particular company the study groups all firms in the companies industry into nine portfolios, sorted based on total assets and EBITDA, which is essentially earnings less any operating costs. The portfolio matching the company being analyzed is used as a comparable firm group for the company.
January 30th-February 13th: Perform all projections and error estimates for each multiple and method, recording the data in an excel spreadsheet. This is the bulk of my research and where the method section is implemented. As my entire research is essentially data analysis, the data analysis section is mostly integrated into this period of time.
My methods are detailed as follows:
I will use a linear approximation of price using a comparable multiple. This multiple will be determined in three different manners: using a harmonic mean, mean, and median of the comparable firms from the comparable firm group.
I will record the over or underestimation of the estimate price from the actual price of the IPO for each firm and each method. Ultimately, this allows me to compare the error terms more efficiently.
February 13th-20th: I will finish analyzing the error terms and make conclusions based off of the values I receive. I will compare multiples across different methods, determining which multiple was the most effective overall in valuing a firm as well as which method provided the most accurate results. This will be done by averaging errors in different cross-sections and comparing their values. The smallest errors for each section I analyze will represent the most optimal multiple in this circumstance.
After this is done, I will begin drafting my paper, including the results, conclusions, and future implications of research section. I will also begin compiling tables based off of the data analysis I will have conducted.
So that's my plan for my research! If I stick to it I'm sure that I can produce an incredibly high quality paper. (458)
Akash
This week's blog post involves setting up my research schedule and discussing the data analysis techniques within my study. So, without further hesitation. Here it is:
January 16th-23rd: Compile data on all NASDAQ companies in the industries that Yelp, Facebook, LinkedIn, Twitter, and Tencent Holdings Inc. are in. Begin separating data based upon the different financial variables I will be analyzing in the study. These financial variables are based upon the multiples I have decided to use within my study.
January 23rd-30th: Finish separating and entering data on different financial variables into Excel. Write R program that parses the excel data to find comparable groups for the firms I plan on analyzing in my study. This is done with a technique implemented by a research study on biotechnology firms. To find a group of comparable firms for a particular company the study groups all firms in the companies industry into nine portfolios, sorted based on total assets and EBITDA, which is essentially earnings less any operating costs. The portfolio matching the company being analyzed is used as a comparable firm group for the company.
January 30th-February 13th: Perform all projections and error estimates for each multiple and method, recording the data in an excel spreadsheet. This is the bulk of my research and where the method section is implemented. As my entire research is essentially data analysis, the data analysis section is mostly integrated into this period of time.
My methods are detailed as follows:
I will use a linear approximation of price using a comparable multiple. This multiple will be determined in three different manners: using a harmonic mean, mean, and median of the comparable firms from the comparable firm group.
I will record the over or underestimation of the estimate price from the actual price of the IPO for each firm and each method. Ultimately, this allows me to compare the error terms more efficiently.
February 13th-20th: I will finish analyzing the error terms and make conclusions based off of the values I receive. I will compare multiples across different methods, determining which multiple was the most effective overall in valuing a firm as well as which method provided the most accurate results. This will be done by averaging errors in different cross-sections and comparing their values. The smallest errors for each section I analyze will represent the most optimal multiple in this circumstance.
After this is done, I will begin drafting my paper, including the results, conclusions, and future implications of research section. I will also begin compiling tables based off of the data analysis I will have conducted.
So that's my plan for my research! If I stick to it I'm sure that I can produce an incredibly high quality paper. (458)
Akash
