Problem Statement
Businesses or companies can fall prey to default if they are not able to keep up their debt
obligations. Defaults will lead to a lower credit rating for the company which in turn reduces its
chances of getting credit in the future and may have to pay higher interests on existing debts as
well as any new obligations. From an investor's point of view, he would want to invest in a
company if it is capable of handling its financial obligations, can grow quickly, and is able to
manage the growth scale.
A balance sheet is a financial statement of a company that provides a snapshot of what a company
owns, owes, and the amount invested by the shareholders. Thus, it is an important tool that helps
evaluate the performance of a business.
Data that is available includes information from the financial statement of the companies for the
previous year XXXXXXXXXXAlso, information about the Networth of the company in the following year
(2016) is provided which can be used to drive the labeled field.
Explanation of data fields available in Data Dictionary, 'Credit Default Data Dictionary.xlsx'
Hints :
Dependent variable - We need to create a default variable that should take the value of 1 when net
worth next year is negative & 0 when net worth next year is positive.
Test Train Split - Split the data into Train and Test dataset in a ratio of 67:33 and use random
state =42. Model Building is to be done on Train Dataset and Model Validation is to be done on
Test Dataset.
Market Risk
The dataset contains 6 years of information (weekly stock information) on the stock prices of 10
different Indian Stocks. Calculate the mean and standard deviation on the stock returns and share
insights.
You are expected to do the Market Risk Analysis using Python.
Please note the following:
• Please avoid sharing code in the business report. There might be a deduction if codes are
shared in the report
• Please ensure all the graphs displayed in the report are clearly visible
• The proper interpretation should be provided wherever required
• You have to submit 2 files :
1. Business Report: It should include a detailed explanation of the approach used,
insights, inferences, all outputs of codes like graphs, tables, etc. Your report
should not be filled with codes. You will be evaluated based on the business
eport only. Hence please ensure that your business report is detailed and includes
everything apart from code.
2. Jupyter Notebook file: This is a must and will be used for reference while
evaluating.
• Any assignment found copied/ plagiarized with other submissions will not be graded and
marked as zero.
• Please ensure timely submission as a post-deadline assignment will not be accepted.
Scoring guide
(Ru
ic) - FRA Rublic
Criteria Points
1.1 Outlier Treatment 6
1.2 Missing Value Treatment 3.5
1.3 Transform Target variable into 0 and 1 2
1.4 Univariate (4 marks) & Bivariate ( 6marks) analysis with proper interpretation. (You may choose to include only those variables
which were significant in the model building) 10
1.5 Train Test Split 2
1.6 Build Logistic Regression Model (using statsmodel li
ary) on most important variables on Train Dataset and choose the
optimum cutoff. Also showcase your model building approach 10
1.7 Validate the Model on Test Dataset and state the performance matrices. Also state interpretation from the model 7
1.8 Build a Random Forest Model on Train Dataset. Also showcase your model building approach 4
1.9 Validate the Random Forest Model on test Dataset and state the performance matrices. Also state interpretation from the model 3
1.10 Build a LDA Model on Train Dataset. Also showcase your model building approach 4
1.11 Validate the LDA Model on test Dataset and state the performance matrices. Also state interpretation from the model 3
1.12 Compare the performances of Logistics, Radom Forest and LDA models (include ROC Curve) 4
1.13 State Recommendations from the above models 4
2.1 Draw Stock Price Graph(Stock Price vs Time) for any 2 given stocks with inference 4
2.2 Calculate Returns for all stocks with inference 3
2.3 Calculate Stock Means and Standard Deviation for all stocks with inference 3
2.4 Draw a plot of Stock Means vs Standard Deviation and state your inference 4.5
2.5 Conclusion and Recommendations 4
Quality of Business report(Please refer to the Evaluation Guidelines for Business report checklist. Marks in this criterion are at the
moderator's discretion) 9
Sheet2
Co_Code Co_Name Networth Next Year Equity Paid Up Networth Capital Employed Total Debt Gross Block Net Working Capital Cu
ent Assets Cu
ent Liabilities and Provisions Total Assets/Liabilities Gross Sales Net Sales Other Income Value Of Output Cost of Production Selling Cost PBIDT PBDT PBIT PBT PAT Adjusted PAT CP Revenue earnings in forex Revenue expenses in forex Capital expenses in forex Book Value (Unit Cu
) Book Value (Adj.) (Unit Cu
) Market Capitalisation CEPS (annualised) (Unit Cu
) Cash Flow From Operating Activities Cash Flow From Investing Activities Cash Flow From Financing Activities ROG-Net Worth (%) ROG-Capital Employed (%) ROG-Gross Block (%) ROG-Gross Sales (%) ROG-Net Sales (%) ROG-Cost of Production (%) ROG-Total Assets (%) ROG-PBIDT (%) ROG-PBDT (%) ROG-PBIT (%) ROG-PBT (%) ROG-PAT (%) ROG-CP (%) ROG-Revenue earnings in forex (%) ROG-Revenue expenses in forex (%) ROG-Market Capitalisation (%) Cu
ent Ratio[Latest] Fixed Assets Ratio[Latest] Inventory Ratio[Latest] Debtors Ratio[Latest] Total Asset Turnover Ratio[Latest] Interest Cover Ratio[Latest] PBIDTM (%)[Latest] PBITM (%)[Latest] PBDTM (%)[Latest] CPM (%)[Latest] APATM (%)[Latest] Debtors Velocity (Days) Creditors Velocity (Days) Inventory Velocity (Days) Value of Output/Total Assets Value of Output/Gross Block
16974 Hind.Cables -8021.6 419.36 -7,027.48 -1,007.24 5,936.03 474.3 -1,076.34 40.5 1,116.85 109.6 0 0 7.6 -0.07 137.67 0 -179.06 -926.52 -185.53 -932.99 -932.99 -937.85 -926.52 0 0 0 -167.58 -167.58 0 -22.09 -102.47 1.46 92.58 -15.31 -20.76 -9.75 0 0 1.38 -25.75 5.23 -19.29 4.43 -19.33 -19.33 -19.29 0 0 0 0.02 0 0 0 0 -0.2 0 0 0 0 0 0 0 45 0 0
21214 Tata Tele. Mah. XXXXXXXXXX 1,954.93 -2,968.08 4,458.20 7,410.18 9,070.86 -1,098.88 486.86 1,585.74 6,043.94 2,892.73 2,892.73 46.27 2,900.71 2,572.46 40.51 646.46 -4.32 35.53 -615.25 -615.25 -617.14 -4.32 6.35 143.42 141.17 -15.18 -15.18 1,544.39 -0.02 635.91 -785 176.93 -26.15 6.3 3.17 5.92 5.92 13.16 6.66 5.24 -108.77 614.89 -9.85 -9.85 -108.77 1.93 34 6.61 0.08 0.25 804.44 10.35 0.3 -0.84 -10.3 -39.74 -57.74 -57.74 -87.18 29 101 2 0.31 0.24
14852 ABG Shipyard XXXXXXXXXX 53.84 506.86 7,714.68 6,944.54 1,281.54 4,496.25 9,097.64 4,601.39 12,316.07 392.13 392.13 9.55 301.16 408.51 54.83 -281.92 -1,086.71 -381.1 -1,185.89 -897.7 -873.39 -798.52 0 86.36 2.27 94.14 94.14 1,220.81 -148.31 -873.4 -458.27 1,187.51 -61.86 15.66 -2.07 -75.87 -75.87 -69.93 -0.78 -169.69 -431.68 -221.85 -300.41 -350.43 -642.67 -100 -81.21 -6.31 1.06 0.03 0.01 0.42 0 -2.21 -5,279.14 -5,516.98 -7,780.25 -7,723.67 -7,961.51 97 558 0 -0.03 -0.26
2439 GTL XXXXXXXXXX 157.3 -623.49 2,353.88 2,326.05 1,033.69 -2,612.42 1,034.12 3,646.54 6,000.42 1,354.39 1,354.39 223.85 1,350.14 1,326.99 3.34 -213.01 -677.57 -336.73 -801.29 -801.29 -770.18 -677.57 0.89 28.88 0 -39.64 -39.64 194.27 -43.08 324.47 17.31 -412.55 -450.67 -40.84 -1.8 8.33 8.33 16.59 -10.12 -203.84 -102.72 -455.28 -80.23 -70.57 -88.52 -52.91 -33.85 -13.94 0.09 5.08 411.15 9.26 0 -0.16 -3.33 -7.21 -48.13 -47.7 -51.58 93 63 2 0.24 1.9
23505 Bharati Defence XXXXXXXXXX 50.3 -1,070.83 4,675.33 5,740.90 1,084.20 1,836.23 4,685.81 2,849.58 7,524.91 38.72 38.72 9.82 38.72 186.29 1.97 -647.86 -944.42 -710.13 -1,006.69 -864.58 -327.77 -802.31 0 15.62 0 -212.89 -212.89 113.68 -159.5 -191.54 61.34 143.65 -559.83 -11.76 0.34 -80.61 -80.61 -48.8 -5.81 -40.07 3.28 -38.72 1.87 -2.59 -1.13 -100 -91.17 -12.91 0.5 0.05 0.02 1.28 0.01 -0.73 -295.55 -400.55 -845.88 379.79 274.79 3,887 346 0 0.01 0.05
2484 Usha Ispat -2519.4 179.35 -2,519.39 -1,824.75 694.64 0.02 -1,843.74 0 1,843.74 18.99 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -140.47 -140.47 0 0 0 0 0 0 0 0 0 0 -100 0 100 100 100 100 100 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
23633 Hanung Toys XXXXXXXXXX 30.82 -1,031.57 1,536.08 2,567.65 949.98 804.82 834.86 30.04 1,566.12 136.09 135.79 0.63 -119.1 896.34 1.66 -933.14 -1,204.87 -995.5 -1,267.23 -1,267.23 -1,218.21 -1,204.87 27.26 9.87 0 -337.17 -337.17 58.26 -390.94 -10.44 4.94 10.32 -556.33 -39.08 -0.66 -72.72 -72.76 8.08 -39.07 -157.51 -103.19 -144.49 -98.69 -155.6 -167.17 -87.06 -97.31 -11.43 0.03 0.01 0.27 0.36 0 -1,230.43 -395.87 -987.73 -396.67 -672.36 -1,264.22 456 12 392 0 -0.01
3226 K S Oils XXXXXXXXXX 45.92 -1,945.45 979.13 2,664.04 920.67 263.95 705.76 441.81 1,420.94 72.47 72.46 6.17 70.08 115.92 0.45 -168.24 -174.47 -221.67 -227.9 -229.87 -59.39 -176.44 0 0 0 -42.37 -42.37 39.03 -3.84 -2.43 177.38 -179.09 -13.3 -29.21 -28.41 -92.82 -92.82 -90.29 -21.74 86.65 87.89 83.41 84.98 84.78 87.7 -100 -100 -30.89 0.41 0.03 0.32 0.19 0.03 -65.16 -447.24 -596.97 -456.4 -461.06 -610.8 828 622 799 -0.02 -0.03
1541 Quadrant Tele. XXXXXXXXXX 61.23 -1,560.94 -613.79 597.82 1,700.27 -1,121.96 117.67 1,239.63 625.85 520.79 520.79 3.62 520.79 669 37.87 -74.05 -100.89 -213.05 -239.89 -239.89 -239.74 -100.89 0 1.21 15.46 -25.49 -25.49 204.49 -1.65 144.9 -123.73 -19.92 -18.2 -62.69 5.95 28.27 28.27 15.72 -0.44 30.85 24.92 8.9 8.14 8.14 24.92 0 8.04 21.45 0.12 0.29 189.17 14.01 0 -3.73 1.9 -20.43 -3.58 -3.58 -25.91 34 145 2 0.92 0.31
2334 ITI XXXXXXXXXX 288 -1,947.85 86.35 1,220.83 1,329.82 -390.53 2,536.78 2,927.31 3,013.66 620.95 574.33 250.78 572.27 772.3 6.81 -124.56 -281.81 -139.88 -297.13 -297.13 -298.03 -281.81 0 10.41 0.09 -74.3 -74.3 588.96 -9.79 -148.56 -10.06 397.51 -4.97 127.47 0.59 -19.69 -25.01 -16.87 9.72 39.16 13.83 36.98 13.69 13.69 13.83 0 -88.37 27.41 0.65 1.14 10.26 0.87 0.59 1.92 19.23 18.18 9.76 9.76 8.71 1,112 913 62 0.54 1.16
430 Parasram. Synth -1403.7 66.28 -1,400.79 -220.49 1,158.34 399.8 -611.84 22.29 634.12 413.62 44.5 44.35 -3.88 44.4 44.54 1.22 -4.99 -5.05 -6.9 -6.96 -6.74 -2.6 -4.83 0 0.1 0 -211.35 -211.35 0 -0.73 -10.96 11.02 -0.06 -0.48 -3.15 -1.97 -2.09 -2.01 0.52 -2.72 -505.69 -520.83 -1,816.67 -1,684.62 -1,882.35 -486.4 0 25 0 0.01 0.08 82.78 1.85 0 -384 -9.09 -11.63 -9.12 -9.36 -11.9 159 427 5 0.08 0.08
4169 Electrotherm(I) XXXXXXXXXX 11.48 -1,025.02 2,057.86 3,063.30 2,141.72 565.64 868.34 302.7 2,360.56 1,950.80 1,829.21 4.05 1,703.21 2,086.31 39.78 -288.84 -295.21 -435.02 -441.39 -440.51 -440.75 -294.33 126.29 235.59 0 -892.87 -892.87 25.08 -256.39 72.13 -6.15 -49.97 -75.15 -18.97 0.43 178.63 177.21 139.06 -17.15 -15.58 -17.24 -36.24 -37.42 -37.16 -16.9 53.86 298.9 24.53 0.6 1 8.2 5.95 1.22 -9.65 4.83 -1.83 4.64 4.64 -2.03 70 32 66 0.82 0.96
5926 ICSA (India) XXXXXXXXXX 9.63 -1,117.68 39.83 1,157.04 236.5 -147.75 209.05 356.8 396.63 23.54 23.54 0.11 -3.27 135.12 0.07 -331.3 -331.45 -342.93 -343.08 -343.08 -343.08 -331.45 0 0 0 -232.18 -232.18 15.36 -68.84 -0.76 0.11 1.67 -44.29 -89.35 0 -58.9 -58.9 27.4 -48.56 45.27 45.47 44.5 44.7 44.7 45.47 0 0 -55.32 0.14 0 0 0 0 -66.38 0 0 0 0 0 4,225 181 220 0 0
3367 SpiceJet XXXXXXXXXX 599.45 -1,085.93 602.19 1,477.34 2,113.77 -1,456.25 548.14 2,004.40 2,606.59 5,243.07 5,243.07 158.44 5,243.07 5,487.15 199.46 -395.39 -560.42 -522.02 -687.05 -687.05 -746.52 -560.42 265.21 2,122.49 4.82 -26.94 -26.94 1,300.81 -9.35 -410.91 303.84 125.6 -9.2 -30.78 -2.71 -16.83 -16.83 -18.7 -11.55 44.75 34.45 39.57 31.52 31.52 34.45 -13.99 -14.52 71.74 0.26 3.26 80.65 117.77 8.64 7.51 11.23 8.03 10.16 10.16 6.96 10 64 3 2.09 2.97
2302 Hind.Organ.Chem. -981.21 67.27 -804.16 -32.81 402.03 639.79 -197.77 131.31 329.07 296.26 168.31 150.13 8.45 152.02 269.83 0.21 -155.42 -206.69 -164.22 -215.49 -215.49 -176.68 -206.69 0 0.34 0 -119.54 -119.54 94.71 -30.73 -112.55 4.61 85.33 -38.65 -151.85 -4.16 -29.04 -28.9 -19.02 -14.62 -33 -29.6 -22.34 -21.85 -21.85 -29.6 0 -69.09 18.39 0.15 0.24 3.5 27.92 0 -1.4 -78.94 -83.66 -138.86 -138.85 -143.57 34 160 81 0.52 0.24
4397 Ricoh India -949.14 39.77 168.6 885.37 701.52 144.13 766.7 1,176.47 409.77 1,295.14 1,637.82 1,637.82 16.8 1,627.37 1,373.21 42.48 160.71 71.93 139.27 50.49 33.9 33.13 55.34 65.18 387.02 4.6 42.39 42.39 2,198.09 13.71 -222.41 -14.26 265.06 20.61 74.45 31.06 56.18 56.18 49.08 50.5 106.06 55.46 125.21 67.63 96.75 65.79 -20.96 -17.33 318.87 0.69 11.18 2.95 1.98 0.94 -1.1 -12.91 -14.35 -25.92 -25.38 -26.82 109 84 54 0.75 9.66
24936 Zylog Systems -854.42 29.5 -115.42 807.85 919.71 908.28 300.83 501.39 200.56 1,008.41 313.08 313.08 -448.72 313.08 451.97 16.05 -473.73 -478.28 -634.69 -639.24 -628.41 -159.15 -467.45 14.74 0.04 0 -19.57 -19.57 24.9 -79.23 -7.86 -2.35 -1.85 -122.5 -43.64 -12.21 -71.23 -71.23 -62.94 -38.06 -191.04 -148.66 -60.99 -50.83 -43.5 -126.43 -94.71 -99.98 -60.93 0.28 0.15 961.45 3.43 0.32 -89.83 -26.71 -33.51 -27.08 -18.16 -24.96 307 14 0 0.16 0.14
24619 Jai Balaji Inds. -838.28 73.78 -180.81 2,799.73 2,980.54 2,490.95 789.42 2,181.38 1,391.96 4,191.69 1,589.55 1,477.74 34.72 1,461 1,533.98 11.42 11.04 -363.96 -115.12 -490.12 -386.37 -383.11 -260.21 2.83 116.51 1.54 -24.51 -24.51 84.63 -35.27 -61.65 32.25 42.75 -183.74 -0.27 0.25 -25.3 -24.92 -22.01 -0.75 -79.3 -28.6 -39.74 -17.05 -21.14 -42.01 -60.53 -58.64 22.72 0.78 0.68 3.75 2.45 0.67 -4.31 -3.86 -10.48 -6.29 -6.29 -12.91 178 203 127 0.4 0.66
6927 Mackinnon Macken -834.09 0.25 -833.53 -7.54 825.61 1.24 -8.45 6.1 14.56 7.02 0.15 0.15 0.07 0.15 0.36 0 -1.1 -1.11 -1.13 -1.14 -1.14 -1.07 -1.11 0.01 0 0 -3,371.57 -33,715.70 0 -4.44 -0.55 0.07 -0.01 -0.14 -17.26 0 0 0 12.5 0.57 -86.44 -88.14 -85.25 -86.89 -86.89 -88.14 0 0 0 0.41 0.14 0 0.03 0 -60 -347.06 -358.82 -352.94 -347.06 -358.82 13,043 9,449 0 0.02 0.14
27371 Everonn Educat. -814.48 24.05 132.58 917.03 781.62 320.07 570.34 621.19 50.85 967.88 28.33 28.33 0.29 28.33 58.37 1.82 -10.79 -51.62 -43.56 -84.39 -84.39 -78.05 -51.62 0.26 0.11 0 55.12 55.12 53.88 -21.46 9.79 -0.11 -20.56 -55.18 -13.98 0.01 -34.47 -34.47 -23.07 -14.08 81.88 52.63 58.8 45.61 30.15 30.83 -40.91 -72.5 -38.57 0.56 0.06 0 0.2 0.07 -0.72 -111.29 -161.98 -337.57 -2,396.03 -2,446.71 2,385 187 0 0.03 0.06
351 LML -781.73 81.98 -703.37 -465.8 103.93 528.48 -528.76 140.95 669.71 203.91 209.02 203.77 3.56 187.75 200.26 12.27 -25.33 -68.48 -37.94 -81.09 -81.09 -81.09 -68.48 144.57 11.96 1.13 -85.79 -85.79 53.78 -8.35 7.87 -0.93 -0.61 -13.96 -22.08 0.28 -23.16 -22.23 -24.12 -16.89 -27.09 -13.19 -17.61 -11.34 -11.34 -13.19 -17.28 -47.38 26.9 0.17 0.3 1.72 77.42 0 -0.65 -13.5 -19.41 -43.59 -43.59 -49.49 6 286 193 0.73 0.3
1083 Samtel Color -687.37 85.5 -645.08 -150.04 443.74 483.43 -280.3 85.94 366.24 216.2 0 0 3.17 -3.57 24.37 0.09 -12.4 -22.93 -22.84 -33.37 -33.37 -33.39 -22.93 0 0 0 -78.96 -78.96 6.41 -2.68 40.74 0.05 -40.79 -5.45 -27.09 -0.05 0 0 3.35 -5.93 48.68 62.47 33.99 53.35 53.35 62.47 0 0 -33.09 0.11 0 0 0 0 -2.93 0 0 0 0 0 0 2,370 322 0 0
27313 Parabolic Drugs -681.26 61.89 -196.07 763.88 957.49 485.98 264.63 450.89 186.26 950.14 242.93 231.78 1.24 184.88 365.77 6.92 -77.33 -176.02 -150.3 -248.99 -379.32 -379.27 -306.35 111.56 112.77 0 -35.88 -35.88 56.69 -49.5 -3.94 -15.89 16.87 -207.19 -25.66 22 -46.52 -47.07 -33.62 -24.02 -12.3 -15.86 -9.76 -13.17 -187.95 -381.3 -45.27 -39.52 105.85 0.27 0.17 2.96 1.2 0.34 -9.43 -50.59 -115.85 -62.87 -66.59 -131.86 186 144 421 0.05 0.1
31509 Pradip Overseas -666.97 48.44 -386 1,148.03 1,494.46 143.85 989.39 1,120.24 130.85 1,278.88 239.84 239.84 4.23 245.75 277.97 5.33 -308.07 -422.5 -315.11 -429.54 -413.5 -400.8 -406.46 40.32 1.11 22.59 -79.68 -79.68 9.16 -83.91 -65.34 5.75 56.19 -1,533.88 -16.8 3.06 -59.93 -59.93 -57.18 -14.69 -29,240 -220.85 -3,234.50 -206.64 -143.72 -152