Andrew Bannerman flare9x
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| # Vix Term Strcuture | |
| require(xts) | |
| require(data.table) | |
| require(ggplot2) | |
| require(lubridate) | |
| require(magrittr) | |
| require(scales) | |
| require(reshape2) | |
| require(dplyr) |
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| # Vix Term Stucture | |
| # Synthetic VXX | |
| require(xts) | |
| require(data.table) | |
| require(ggplot2) | |
| require(lubridate) | |
| require(magrittr) | |
| require(scales) | |
| require(reshape2) |
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| # Vix Term Stucture | |
| # Synthetic XIV | |
| require(xts) | |
| require(data.table) | |
| require(ggplot2) | |
| require(lubridate) | |
| require(magrittr) | |
| require(scales) | |
| require(reshape2) |
flare9x
/ gist:83753c3f162c41a06779c1b93147e06b
Last active
December 10, 2017 19:33
VIX1|VIX2 30 Day Constant Maturity
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| # 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
/ gist:933a482ae55c48d5bd91ea07a3773808
Last active
December 30, 2017 20:32
Bootstrap meboot volatility strategy
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| # 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
/ gist:8b1ae9ace2ae6e8e35eec89a1b324ddf
Created
December 31, 2017 03:19
Block Bootstrap data frame
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| # 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
/ time_series_cross_validation.R
Last active
April 11, 2018 21:17
Time Series Cross Validation
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| # 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
/ Invest each month vs Each year - Average Cost S&P500.r
Last active
July 28, 2021 12:54
Invest each month vs Each year - Average Cost S&P500
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| # Bulk Buy 1x a year Vs investing every month | |
| # Andrew Bannerman 1.3.2018 | |
| require(xts) | |
| require(data.table) | |
| require(ggplot2) | |
| require(lubridate) | |
| require(magrittr) | |
| require(scales) | |
| require(reshape2) |
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| # Optimal F Simulation In R | |
| # Make random returns | |
| # Adjust $ return output by varying fractional (f) | |
| ####################################################################### | |
| # Calculations | |
| # Calculation 1 = Optimal F calculation Start calculation = 1 + fractional amount * trade gain/loss (-/+) / abs(worst.loss) | |
| # Calculation 2 = Optimal F Calculation = prev equity * (1+fractional (f) amount * trade gain/loss (-/+) / abs(worst.loss) | |
| ##################################################################### | |
| # Required Packages |
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| # 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 |
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