Rod M rodmorley
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| model mpg cyl disp hp drat wt qsec vs am gear carb | |
| Mazda RX4 21 6 160 110 3.9 2.62 16.46 0 1 4 4 | |
| Mazda RX4 Wag 21 6 160 110 3.9 2.875 17.02 0 1 4 4 | |
| Datsun 710 22.8 4 108 93 3.85 2.32 18.61 1 1 4 1 | |
| Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1 | |
| Hornet Sportabout 18.7 8 360 175 3.15 3.44 17.02 0 0 3 2 | |
| Valiant 18.1 6 225 105 2.76 3.46 20.22 1 0 3 1 | |
| Duster 360 14.3 8 360 245 3.21 3.57 15.84 0 0 3 4 | |
| Merc 240D 24.4 4 146.7 62 3.69 3.19 20 1 0 4 2 | |
| Merc 230 22.8 4 140.8 95 3.92 3.15 22.9 1 0 4 2 |
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| index_returns <- function(years = 10, tickers = c("SPX Index","SXXP Index", "UKX Index", "HSI Index", "TPX Index","AS51 Index")){ | |
| require(Rblpapi) | |
| con <- blpConnect() | |
| opt <- c("periodicitySelection"="MONTHLY") | |
| dataset = bdh(securities = tickers, | |
| fields = "PX_LAST", |
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| mix_it_up <- function(names, topics){ | |
| for(i in 1:length(names)){ | |
| name = sample(names , 1, replace = FALSE) | |
| topic = sample(topics, 1, replace = FALSE) | |
| print(paste0(name, " : ", topic)) | |
| names = names[names != name] |
rodmorley
/ market_regime
Created
August 17, 2022 08:18
Calcualate the market regime (calm v turbulent) as per Krtizman.
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| market_regime <- function(full_data, window=24, cut_off_perc=0.80, lookback=24){ | |
| rows = nrow(full_data) | |
| kritz = NULL | |
| for (i in window:(rows-1)){ | |
| start_row <- i-window+1 | |
| end_row <- i |
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| rolling_mahalanobis <- function(dataset, width = 24){ | |
| mahalanobis <- function(dataset){ | |
| N <- nrow(dataset) | |
| y_t <- last(dataset) | |
| mu <- colMeans(dataset[1:(N-1), ]) | |
| y_t_minus_mu <- y_t- mu | |
| Sigma_1 <- ginv(cov(dataset[1:(N-1), ])) | |
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| mahalanobis <- function(dataset){ | |
| N <- nrow(dataset) | |
| y_t <- last(dataset) | |
| mu <- colMeans(dataset[1:(N-1), ]) | |
| y_t_minus_mu <- y_t- mu | |
| Sigma_1 <- ginv(cov(dataset[1:(N-1), ])) | |
| d_t <- y_t_minus_mu %*% Sigma_1 %*% t(y_t_minus_mu) | |
rodmorley
/ rolling_market_regime
Created
April 6, 2020 15:15
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| rolling_market_regime <- function(datareturns, window=48, cutoff=0.75){ | |
| #datareturns <- coredata(datareturns) | |
| Nreturns <- dim(datareturns)[1] | |
| degsFreedom <- dim(datareturns)[2] | |
| kritz <- matrix(NA, ncol=1, nrow=Nreturns) # make this a vector ?? | |
| for(i in (1+window):Nreturns){ | |
| start_row <- i-window |
rodmorley
/ turbulenceVaRdata
Last active
November 9, 2018 14:45
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| # Calculating VaR conditional on market regime ['calm', 'turbulent' or 'full period'] | |
| # | |
| # Regime = Kritzman's measure of turbulence | |
| # | |
| # | |
| # | |
| # | |
| d.turbulence.VaR.data <- function(datareturns, wgts){ | |
| ans <- matrix(0, ncol = 1, nrow = dim(datareturns)[1]) | |
| datareturns.cov <- cov(datareturns) |
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| # | |
| # Pull 13F holdings over 1% of portfolio AuM | |
| # | |
| # link = 'copy link address' to the information table .xml file | |
| # | |
| # requires XML, RCurl, dplyr, magrittr | |
| # | |
| require(XML) | |
| require(RCurl) | |
| require(dplyr) |
rodmorley
/ FamaFrenchFactorsDownload
Last active
February 24, 2020 16:42
Fama French 6 Factors Data Download
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| # | |
| # e.g. FamaFrenchDownload("2018-08-31") | |
| # | |
| # ignore the warning message | |
| # | |
| requires xts | |
| requires lubridate | |
| FamaFrenchDownload <- function(last_date){ |
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