PS_Risk Management and Financial Institutions

Learning Goal: I’m working on a r multi-part question and need support to help me learn.

textbook: Hull. John C. Risk Management and Financial Institutions- 5’th Edition. Wiley (H)

Answer the following questions from HULL

1. Question 13.13 (Use R) a. part (a) (Use R)

b. part (b) (Use R)

c. part (c) (Use R)

d. part (d) (Use spreadsheet unless I provide you with R code)

e. Use 10000 unweighted bootstraps to estimate 95% confidence intervals for the VaR and cVaR (ES) estimates obtained in part (a).

f. Use 10000 bootstraps and weighted resampling to estimate 95% confidence intervals for the VaR and cVaR (ES) estimates obtained in part (b).

2. Question 13.17 – using the most recent 1500 (on or prior to November 15, 2021) days of NASDAQ data downloaded using quantmod. Estimate the one-day ahead VaR and cVaR values for November 16, 2021 a. part (a)

b. part (b)

c. part (c)

d. part (d) (Use spreadsheet unless I provide you with R code)

e. Use 10000 unweighted bootstraps to estimate 95% confidence intervals for the VaR and cVaR (ES) estimates obtained in part (a).

f. Use 10000 bootstraps and weighted resampling to estimate 95% confidence intervals for the VaR and cVaR (ES) estimates obtained in (b).

3. Download the DJIA, FTSE100, CAC40, Nikkei225, and the GBPUSD, USDEUR and USDJPY FX exchange rate data for the time periods 1/04/1999 through 11/15/2021. a. Construct a data set for the entire series using the procedures and assumed portfolio used in question (1) above. Keep only the days with observations for all seven variables.

b. Loop through 500 day blocks of data and use the unweighted historical process used in parts (a) above to perform an “out-of-sample” test of the 99% one-day VaR estimates using the 1999-2021 daily observations. For each day 500:(N-1) in the 1999-2021 time period, compute and store the “next day’s” estimated 99% VaR level.

  • What proportion of the times did the “next-day’s” realized value exceed its estimated one-day 99% VaR level? (over) Major Project Part 2 Assume that your insurance company plans to offer revenue insurance to a group of corn and soybean producers in the block of counties in CRD in Iowa. We will discuss this project in more detail in upcoming classes. For now you have been tasked with the following: 4. Using your 1970-2020 downloaded Iowa county yield data for CRD 90 in Iowa (a) Fill any missing data using the procedures used in the R lab. (b) Construct a corn and soybean detrended yield data series for each county. Be sure to check and adjust for possible heteroskedasticity in the residuals. (c) Generate a pdf containing plots of the original yield levels, the predicted yield trend and the detrended yield. Each page in the pdf is to contain 4 plots and each plot is to be labeled indicating which county and crop is being plotted. (d) Use the provided historical futures data to estimate the PP and HP prices for each crop. For corn, the PP and HP are constructed as the Feb. and Oct. average of the Dec. corn futures contract. For soybeans, the PP and HP are constructed as the Feb. and Oct. average of the Nov. soybean futures contract. (e) Construct a data.frame containing the joint historical HP/PP price ratios and detrended county yields for each county and crop.
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