Publications by Sal Pollastro
Homework 3
Following the common theme of energy data, I decided to use the historical closing Henry Hub natural gas price. This data ranges almost a decade from 4/26/2012 to 4/18/2022. The Henry Hub is the benchmark index for natural gas prices. When local markets across the United States price their natural gas, they tend to do so based off a differential ...
4267 sym R (10621 sym/62 pcs) 21 img
Discussion 7
For this week’s discussion, I decided to use the Microsoft stock data from my discussion 6. The one caveat to using stock price data is that there are no data points for Saturdays and Sundays. Since tsibble() needs a continuous time series, I used tsibble::fill_gaps() to plug in the missing dates. These dates do not have a closing price and def...
1042 sym R (1752 sym/9 pcs) 3 img
Discussion 6
I chose Microsoft and Apple stocks to compare because they are in the same sectore (tech) and have similar growth patterns. Below are the plots of their historical closing prices of the last five years. # Clear the workspace rm(list = ls()) # Clear environment gc() # Clear unused memory ## used (Mb) gc trigger (Mb) max used ...
636 sym R (9397 sym/63 pcs) 10 img
Homework 2 Ch 9
Figure 9.32 shows the ACFs for 36 random numbers, 360 random numbers and 1,000 random numbers. Explain the differences among these figures. Do they all indicate that the data are white noise? The three plots below indicate that the data are white noise. The ACF bars do not exceed the bounds (dashed lines) which represent that the data is white n...
10148 sym R (29350 sym/175 pcs) 68 img
Homework 2 CH8
Consider the the number of pigs slaughtered in Victoria, available in the aus_livestock dataset. Use the ETS() function to estimate the equivalent model for simple exponential smoothing. Find the optimal values of α and ℓ0, and generate forecasts for the next four months. # 1 ------------------------- #View(aus_livestock) pigs <- aus_lives...
8257 sym R (26282 sym/110 pcs) 40 img
Discussion 5
I chose to use the EIA data on wind power generation over the years. Energy data is very interesting to me as it relates to my job but also shows the real data of what is happening in the industry. The wind generation data is in thousands of megawatt hours. For reference, the average household uses 10.7 MWh annually, according to the EIA. # Clear...
1236 sym R (7868 sym/33 pcs) 10 img
Forecasting Midterm
# Clear the workspace rm(list = ls()) # Clear environment gc() # Clear unused memory ## used (Mb) gc trigger (Mb) max used (Mb) ## Ncells 458678 24.5 991037 53 638942 34.2 ## Vcells 823618 6.3 8388608 64 1633064 12.5 cat("\f") # Clear the console library("feasts") library("seasonal") library("tsibbl...
4229 sym R (14489 sym/68 pcs) 14 img