flare9x

# Vix Term Stucture
# Synthetic XIV

require(xts)
require(data.table)
require(ggplot2)
require(lubridate)
require(magrittr)
require(scales)
require(reshape2)

flare9x

# VIX1|VIX2 30 Day Constant Maturity 
# Andrew Bannerman 12.10.2017 

require(xts)
require(data.table)
require(ggplot2)
require(lubridate)
require(magrittr)
require(scales)
require(reshape2)

flare9x

# Meboot time series resampling 
# Andrew Bannerman 12.29.2017

require(xts)
require(data.table)
require(ggplot2)
require(lubridate)
require(magrittr)
require(scales)
require(reshape2)

flare9x

# Block Bootstrap Time Series 
# Andrew Bannerman 12.30.2017 

require(xts)
require(data.table)
require(ggplot2)
require(lubridate)
require(magrittr)
require(scales)
require(reshape2)

flare9x

# Es Up / Down Trend Isolation 
# 2.26.2018 
# Andrew Bannerman 

###############################################################################################
# Steps 
# 1. Define a trend day when the close price was within 25% of the high / low 
# 2. Save all dates 
# 3. Subset 5 minutes bars, save each day into a list 
# 4. Output price plots 

flare9x

    using DataFrames
using Indicators
# Arrays  - see https://lectures.quantecon.org/jl/julia_arrays.html
# Initialize out_result to store time for each iteration
x_res = collect(1:1:100)
x_res = convert(Vector{Base.Dates.Millisecond}, x_res)
out_result = zeros(x_res) # Pre allocate output
#for j in 1:100
start_time = Dates.now(Dates.UTC)
# Load csv

flare9x

# Back test simple moving average strategy 
# Use 30min ES Data 

require(TTR)
require(quantmod)
require(lubridate)
require(dplyr)
require(microbenchmark)
i=1
out_results <- data.frame()

flare9x

# Vix Term Stucture
# Synthetic VXX

require(xts)
require(data.table)
require(ggplot2)
require(lubridate)
require(magrittr)
require(scales)
require(reshape2)

flare9x

# Train / Test Set VXV / VXMT Strategy 
# Andrew Bannerman 

################################################
# Procedure 
# 1. Split data into train / test sets 
# 2. Select 1 year look back for each train set (252 days)
# 3. Select 6 months test set (126)
# 4. Re-calibrate on a moving window through entire time series 
#################################################

flare9x

# Vix Term Strcuture 

require(xts)
require(data.table)
require(ggplot2)
require(lubridate)
require(magrittr)
require(scales)
require(reshape2)
require(dplyr)