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Bryce_Bowles_My_Forecast.R

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+library(readr)
+library(ggplot2)
+library(forecast)
+library(fpp2)
+library(TTR)
+library(dplyr)
+
+#month_year - have to make sure youve got a csv with dates column in 01/01/2020 format (month_year)
+#core_deposits
+
+#read in data provided (training data)
+TSFC <- read_csv("Core_Deposits.csv")
+glimpse(TSFC)
+dates <- as.Date(TSFC$month_year, 
+             format= "%m/%d/%Y")
+
+#read in the hold out data (validation data)
+#"Core_Deposits_Validate.csv" contains just the holdout data
+TSFCV <- read_csv("Core_Deposits_Validate.csv")
+glimpse(TSFCV)
+dates <- as.Date(TSFCV$month_year, 
+                 format= "%m/%d/%Y")
+
+#convert them to time series formats
+training__data <- ts(TSFC$core_deposits, frequency=12, start=c(1988,11), end=c(1992,09))
+validation__data <- ts(TSFCV$core_deposits, frequency=12, start=c(1992,09), end=c(1993,08))
+all__data <- ts(TSFC$core_deposits, frequency=12, start=c(1992,09)) #no end because all data is in "Core_Deposits.csv" including hold out
+
+#to view the data
+plot.ts(training__data)
+plot.ts(validation__data)
+plot.ts(all__data)
+
+#taking the LN
+log_training_data <- log(training__data)
+plot.ts(log_training_data)
+
+#Naive model
+naive_mod <- naive(training__data, h = 12)
+summary(naive_mod)
+plot(naive_mod)
+
+#Simple Exponential Smoothing 
+se_model <- ses(training__data, h = 12)
+summary(se_model)
+plot(se_model)
+
+#Holts ES
+holt_model <- holt(training__data, h = 12)
+summary(holt_model)
+plot(holt_model)
+print(holt_model)
+
+#ARIMA
+arima_model <- auto.arima(training__data)
+summary(arima_model)