ASSIGNMENT # 5
AMAN VIJ
ADEENA MIRZA AMIT KUMAR TRIPATHY
SECTION A
Questions 1.
(a) Explore the data. Report on the distribution of values in the attributes and how they individually relate to the outcome of interest (dependent variable).
All the attributes are combination of categorical and numeric values and cover varied ranges. Each attribute was studied along with analyzing histograms, scatterplots and log-scaled graphs. The findings are listed below with the graphs of each attribute distribution in Section B.
(i) Borrower’s age (Bo_Age):
Borrower’s age shows an overall right skewed distribution with a maximum at 36. The distribution for only defaulters shows a
…show more content…
(vi) Borrower’s total monthly debt expense (Tot_mthly_debt_exp):
Total monthly debt expense of borrower’s has a range from 0 to 17225 with an average of about 1745. The distribution of the total data as well as the defaulters is suggestively right skewed with most of the defaulters belonging to the class of borrower’s below
5500.
(vii) Borrower’s total monthly income (Tot_mthly_incm):
Borrower’s monthly income has a distribution similar to the monthly debt expense distribution and has a range from 500 to 65000 with an average of 5025. The graph also shows that most of the defaulters are from the low-income group with there being no defaulters with a monthly income of 15000 or higher.
(viii) Appraised value of home at origination (orig_apprd_val_amt):
Appraised value of homes also has a right skewed distribution with fewer records of houses with high appraised value and even fewer defaulters in that region. No defaulter was recorded for a house with an appraised value greater than 400,000.
(ix) Purchase price for house (pur_prc_amt):
Purchase price for houses shows a distribution very similar to appraised values with low frequency of borrowers for houses with high purchase price and no defaulter for a house more expensive than 400,000.
(x) Borrower debt to income ratio (DTI ratio):
Debt to income ratio is calculated by
perfect borrowers, while the borrows no longer trust lenders to give them a home ownership deal
It also reflect that there is cost of financing with debt reflecting the bankruptcy costs as well as the financial distress in the form of costs of debt. The marginal benefit is increased in decline of debt with the increase in debt leading to the increase in marginal cost. It further optimises the overall value focusing on the trade-off while selecting the amount of debt and equity to be used for financing. This theory can provide the explanation for differences in ratios for debt to equity between industries without reflecting any explanation on the differences within similar industry (Lee, et al., 2009).
STATS 415 Data Mining Project Insights into the prediction of the default payment through the history of payments, the amount of previous payment and the amount of bill payment
The risks of an individual debt may have a large standard deviation of possibilities. The lender may want to cover his maximum risk. But lenders with portfolios of debt can lower the risk premium to cover just the most probable outcome.
Giant Pools of Money Home ownership has been widely viewed as a cultural symbol in the United States. We become emotionally tied to the desire of owning a home. In order to fulfill this desire, we look towards the right financial institution willing to provide a home loan and we then start the process. However, the decision process we use to obtain a home can sometimes become clouded and covered in biases. This gives tremendous leverage to financial institutions. In the early
Describe briefly what each statistic in parts a. to c. tells you about the data.
First, an understanding of each of these attributes is needed in the interest of gaining further insight on how they
In the analysis, the expected contrast resulting from not including all residences is given by the standard mistake. There are almost 2/3 opportunities that an example and almost 19/20 opportunities. Since, the past month of these estimates are shown in the standard errors section of this publication.
The value of real estate in America is related to the need for shelter and income. As need increases and supply decreases, values go up. Personal factors, such as the desire for a particular location or type of home, also contribute to value (Donald et.al, 2013-14). Real property value is totally dependent upon and classified in to four great forces, which motivate human activity. These factors create, maintain, modify or destroy value. This study therefore examines the effect of these major factors and stated below.
Familiarise yourself with the data set provided. This will include doing research to help you understand the variables and develop a purpose for the investigation.
Find secondary data that relates to your resulting hypothesis/hypotheses. Summarize (1 page) information to support your observations.
Total debt ratio remained stable in all periods in 2011 and is below 1:1, which is a good indication of the company maintaining its leverage. Interest coverage ratio shows a downward trend in Q2 and Q3 with a slight increase in Q4. These results are derived from an increase in interest expense. These changes are not very significant to the success of the business as the company’s ratio is well above 1.5, which implies the company is not burdened by its debt expenses. Debt/Equity ratio remained stable in all periods with a slight increase in Q4 as a result of increased liabilities.
One key starting point for a House Price Index is a fixed housing stock. However, the quality of the housing stock is likely to rise as a result of newly built homes. This, in turn, causes the mean or median price to continue to rise even when individual properties are not appreciating (Bailey et al, 1963). For example, if a disproportionate number of high priced homes were sold in a given period, the mean or median price would
Each house has two types of value. The first value is the market value which the current value of the
A frequency analysis and analysis of distribution, depicted with histograms and box plots, portraying the distribution of the different age groups within the world population.