R/StressIndex.R
In AndreMikulec/econModel: Meaningful Social and Economic Data from ALFRED and elsewhere
Defines functions
FSI2
stressIndex
stLouisFEDdaily2Weekly
Documented in
FSI2
stLouisFEDdaily2Weekly
stressIndex
#' Convert an xts object Into a St Louis FED Weekly xts Object.
#'
#' @description
#' Given Dailies, return the five(5) day moving average (called a "weekly") with an Observation data on Fridays that are published on the following Thursdays.
#'
#' @param x xts object of Dailies.
#' @param Level String. Default is "Levels" Other choices are "ChangeInLevels" and "ChangeInLogLevels."
#' @return Modified xts object
#' @examples
#' \dontrun{
#' DGS2 <- quantmod::getSymbols("DGS2", src = "FRED", auto.assign = F)
#' DGS2 <- stLouisFEDdaily2Weekly(DGS2, Level = "ChangeInLevels")
#' }
#' @importFrom tryCatchLog tryCatchLog
#' @importFrom stats na.omit
#' @importFrom zoo index `index<-` coredata as.zoo rollapply
#' @importFrom xts xts as.xts lag.xts xtsAttributes `xtsAttributes<-`
#' @importFrom timeDate timeNthNdayInMonth
#' @export
stLouisFEDdaily2Weekly <- function(x, Level) {
tryCatchLog::tryCatchLog({
# if not done elsewhere
#correct for TZ
oldtz <- Sys.getenv("TZ")
if(oldtz!="UTC") {
Sys.setenv(TZ="UTC")
}
if(missing(Level)) {
Level <- "Levels"
}
if(!Level %in% c("Levels", "ChangeInLevels", "ChangeInLogLevels")) {
stop("Level must be one of \"Levels\", \"ChangeInLevels\", or \"ChangeInLogLevels\"")
}
Result <- ORIG <- x
Result <- stats::na.omit(Result)
# changes
if(Level == "ChangeInLogLevels") {
Result <- log(Result)
}
if(Level %in% c("ChangeInLevels","ChangeInLogLevels")) {
Result <- (Result - xts::lag.xts(Result))/abs(xts::lag.xts(Result))
}
# 5 days(week) rolling means of changes
Result <- zoo::rollapply(zoo::as.zoo(Result), width = 5L, mean, fill = NA , partial = F, align = "right")
# xts (with the original index class, format, and time zone)
Result <- cbind(xts::xts(, zoo::index(ORIG)[0]), xts::as.xts(Result))
# personal "xts attributes"
xts::xtsAttributes(Result) <- c(list(), xts::xtsAttributes(Result), xts::xtsAttributes(ORIG))
# FRI entries (Observation Dates)
Index <- zoo::index(Result)[weekdays(zoo::index(Result)) == "Friday"]
#
Result <- Result[Index]
# save seconds
TimeDiff <- as.POSIXct(Index) - as.POSIXct(zoo::as.Date(Index))
# next THU entries (Publication Dates) - a "better" Index
BetterIndex <- zoo::as.Date(timeDate::timeNthNdayInMonth(as.character(zoo::as.Date(Index)), nday = 4, nth = 1))
# put back TimeDiff
BetterIndex <- as.POSIXct(BetterIndex) + TimeDiff
# put back the class
BetterIndex <- eval(parse(text = paste0("as.", class(index(ORIG))[1], "(BetterIndex)")))
#
zoo::index(Result) <- BetterIndex
Sys.setenv(TZ=oldtz)
Result
}, write.error.dump.folder = getOption("econModel.tryCatchLog.write.error.dump.folder"))}
#' Stress Index
#'
#' @description
#' \preformatted{
#' Types of Risk
#'
#' "default risk":
#' interest rate spread designed to measure
#' the difference between yields on a “risky” asset
#' and a “risk-free” asset
#'
#' "liquidity risk""
#' inability to secure resources to acquire short term
#' liabilities
#'
#' Stress Index
#' Uses a precedure (Principal Components) to create
#' the "stress index".
#'
#' Creating the Stress Index
#'
#' 1. First, each of the data series is de-meaned.
#' The de-meaned series are then
#' divided by their respective sample standard deviations (SDs)
#' (Because each variable was standardized,
#' the coefficient of a variable (SEE 2.) represents the
#' "influence of a 1 SD change in that variable on the Stress Index.")
#' 2. Use the method of principal components:
#' Extracting this factor (the first principal component).
#' makes it able to create an index with a useful interpretation
#' 3. Calculate the coefficients of the variables.
#'
#' The factor loadings, also called component loadings in PCA,
#' are the correlation coefficients
#' between the variables (rows) and factors (columns).
#'
#' The elements of the eigenvectors of . . . are the
#' "coefficients" or "loadings" of the principal components.
#'
#' 4. We then scale these coefficients so that the SD of the index is 1.
#' 5. Finally, each data series is multiplied
#' by its respective adjusted coefficient.
#' 6. Stress Index for time t is
#' the sum of each series multiplied
#' by its respective adjusted coefficient.
#' (Higher values of the FSI indicate a
#' greater degree of financial stress in the economy.)
#'
#' Stress Index proc details drawbacks
#' A negative coefficient multiplied by a negative data value
#' will result in a positive contribution to financial stress.
#'
#' Stress Index percent of the total variation
#' in the many variables
#' 1 – SSE/SST
#' SST is the total sum of squares
#' SSE is the sum of squared errors
#' X(N,t) is the value of the Nth standardized variable in month t,
#' and a(N) is the set of coefficients chosen.
#' Updating the Stress Index
#'
#' When the sample changes (i.e., a new item of data is added),
#' the values of the Stress Index in the original sample can be changed.
#' This alteration can occur either through a
#' change in the coefficients of the variables in the index
#' or by a change in the actual values of the variables in the
#' original sample. The overall magnitude of the coefficients,
#' as well as their relative magnitudes, can change.
#' }
#' @param x xts object. Required. This is the input used for prediction.
#' @param ValDates List of (or vector of) pairs of vectors of begin and end date-time ranges. Required (if not all of the ValidationData is to be used).
#' @return Index that is centered about zero(0) and scaled to the standard deviation of one(1).
#' @references
#' \cite{How to compute varimax-rotated principal components in R?, 2014
#' \url{https://stats.stackexchange.com/questions/59213/how-to-compute-varimax-rotated-principal-components-in-r}
#' }
#' @references
#' \cite{Aaron Schlegel, Principal Component Analysis with R Example, Thu 19 January 2017
#' \url{https://aaronschlegel.me/principal-component-analysis-r-example.html}
#' }
#' @references
#' \cite{Introduction to Principal Components and FactorAnalysis, North Carolina State University
#' \url{ftp://statgen.ncsu.edu/pub/thorne/molevoclass/AtchleyOct19.pdf}
#' }
#' @references
#' \cite{Luke Hayden, Principal Component Analysis in R, August 9th, 2018
#' \url{https://www.datacamp.com/community/tutorials/pca-analysis-r}
#' }
#' @references
#' \cite{author(s)?, National Economic Trends, Appendix, January 2010
#' \url{https://files.stlouisfed.org/files/htdocs/publications/net/NETJan2010Appendix.pdf}
#' }
#' @references
#' \cite{Kevin L. Kliesen and Douglas C. Smith, Measuring Financial Market Stress, Economic SYNOPSES, 2010 Number 2, Posted on January 15, 2010
#' \url{https://files.stlouisfed.org/files/htdocs/publications/es/10/ES1002.pdf}
#' }
#' @examples
#' \dontrun{
#' # E.g. some (and only some of the) interest rates
#' # of the St Louis Stress Index 2 (STLFSI2)
#' for(Symbol in c("DFF","DGS2","DGS10")) {
#' quantmod::getSymbols(Symbol, src = "FRED")
#' assign(Symbol, stLouisFEDdaily2Weekly(get(Symbol), Level = "ChangeInLevels"))
#' }
#'
#' Data <- stats::na.omit(cbind(DFF,DGS2,DGS10))
#' # dygraphs::dygraph(stressIndex(Data))
#' }
#' @importFrom tryCatchLog tryCatchLog
#' @importFrom stats na.omit prcomp
#' @importFrom zoo index
#' @importFrom xts xts
#' @export
stressIndex <- function(x, ValDates,
...
) {
tryCatchLog::tryCatchLog({
x <- stats::na.omit(x)
PrCmpObj <- stats::prcomp(x, center = TRUE, scale. = TRUE)
Prediction <- predict(PrCmpObj, newdata = Data)[, "PC1"]
PredictionScaled <- scale(Prediction, center = T, scale = T)
colnames(PredictionScaled) <- "StressIndex"
StressIndex <- xts::xts(PredictionScaled, zoo::index(Data))
StressIndex
}, write.error.dump.folder = getOption("econModel.tryCatchLog.write.error.dump.folder"))}
#' Re-Createion of the St. Louis Federal Board of Governors Financial Stress Index Version 2
#'
#' @description
#' Uses a precedure (e.g. Principal Components) to create the "stress index" Financial Stress Index Version 2
#'
#' @references
#' \cite{St. Louis Fed Financial Stress Index (STLFSI2)
#' \url{https://fred.stlouisfed.org/series/STLFSI2}
#' }
#' @references
#' \cite{author(s)?, Table 1: Data Used to Construct STLFSI
#' \url{https://fredblog.stlouisfed.org/wp-content/uploads/2020/03/FSI2.pdf}
#' }
#' @references
#' \cite{Kevin Kliesen and Michael McCracken, The St. Louis Fed’s Financial Stress Index, Version 2.0, March 26, 2020
#' \url{https://fredblog.stlouisfed.org/2020/03/the-st-louis-feds-financial-stress-index-version-2-0/}
#' }
#' @references
#' \cite{List of Data Series Used to Construct the St. Louis Fed Financial Stress Index (STLFSI)
#' \url{https://www.stlouisfed.org/~/media/Files/PDFs/STLFSI-Key.pdf?la=en}
#' }
#' @references
#' \cite{list of the components that are used to construct the STLFSI
#' \url{https://www.stlouisfed.org/news-releases/st-louis-fed-financial-stress-index/stlfsi-key}
#' }
#' @references
#' \cite{St. Louis Fed Financial Stress Index (DISCONTINUED) (STLFSI)
#' \url{https://fred.stlouisfed.org/series/STLFSI}
#' }
#' @references
#' \cite{author(s)?, National Economic Trends, Appendix, January 2010
#' \url{https://files.stlouisfed.org/files/htdocs/publications/net/NETJan2010Appendix.pdf}
#' }
#' @references
#' \cite{author(s)?, The LIBOR-OIS Spread as a Summary Indicator, MonetaryTrends, November 2008
#' \url{https://files.stlouisfed.org/files/htdocs/publications/mt/20081101/cover.pdf}
#' }
#' @references
#' \cite{Kevin L. Kliesen and Douglas C. Smith, Measuring Financial Market Stress, Economic SYNOPSES, 2010 Number 2, Posted on January 15, 2010
#' \url{https://files.stlouisfed.org/files/htdocs/publications/es/10/ES1002.pdf}
#' }
#' @param TrainData xts object. Required.
#' @param TrainDates List of (or vector of) pairs of vectors of begin and end date-time ranges. Required (if not all of the ValidationData is to be used).
#' @return Index.
#' @examples
#' \dontrun{
#' }
#' @importFrom tryCatchLog tryCatchLog
#' @export
FSI2 <- function(x, TrainDates,
...
) {
tryCatchLog::tryCatchLog({
# STLFSI TrainData
# We construct the STLFSI using 18 weekly data series . . .
#
# STLFSI2
# 18 weekly data series, all of which are weekly averages of daily data series
# Date Range: 1993-12-31 to 2020-11-27 (ObservationDate) - End of Week - FRI
# Last Updated: 2020-12-03 9:00 AM CST (PublishedDate) - Following Week - THU Morn
# https://fred.stlouisfed.org/data/STLFSI2.txt
# STLFSI2
# The key difference between versions 1.0 and 2.0 is that
# 2.0 uses daily changes in interest rates and stock prices,
# rather than the levels of interest rates and stock prices in the PCA calculation.
#
# Effective Federal Funds Rate (DFF)
# Daily, 7-Day (since 1954)
# https://fred.stlouisfed.org/series/DFF
# Following are all Levels (unless noted otherwise)
# 2-Year Treasury Constant Maturity Rate (DGS2) - STLFSI2 - Change in Levels
# Daily (since 1976)
# https://fred.stlouisfed.org/series/DGS2
# 10-Year Treasury Constant Maturity Rate (DGS10) - STLFSI2 - Change in Levels
# Daily (since 1952)
# https://fred.stlouisfed.org/series/DGS10
# 30-Year Treasury Constant Maturity Rate (DGS30) - STLFSI2 - Change in Levels
# Daily (since 1977)
# https://fred.stlouisfed.org/series/DGS30
# Moodys Seasoned Baa Corporate Bond Yield (DBAA) - STLFSI2 - Change in Levels
# Daily (since 1986)
# https://fred.stlouisfed.org/series/DBAA
# Bank of America - Previously BofAML
# Bank of America Merrill Lynch is now Bank of America.
# Google query of November 2020
# Merrill Lynch High-Yield Corporate Master II Index - STLFSI2 - Change in Levels
# Merrill Lynch High Yield Master II
# https://en.wikipedia.org/wiki/Merrill_Lynch_High_Yield_Master_II
# NOT EXACTLY
# ICE BofA US High Yield Index Effective Yield (BAMLH0A0HYM2EY)
# Daily (since early 1997)
# https://fred.stlouisfed.org/series/BAMLH0A0HYM2EY
# Merrill Lynch Asset-Backed Master BBB-rated - STLFSI2 - Change in Levels
# NOT EXACTLY
# ICE BofA BBB US Corporate Index Effective Yield
# Daily (since early 1997)
# This data represents the effective yield of the ICE BofA BBB US Corporate Index,
# a subset of the ICE BofA US Corporate Master Index
# https://fred.stlouisfed.org/series/BAMLC0A4CBBBEY
# Yield Curve: 10-Year minus 3-Month Treasury - STLFSI2
# 10-Year Treasury Constant Maturity Minus 3-Month Treasury Constant Maturity (T10Y3M)
# Daily (since 1982)
# https://fred.stlouisfed.org/series/T10Y3M
# Corporate Baa-rated bond minus 10-Year Treasury - STLFSI2
# NOT EXACTLY
# Moodys Seasoned Baa Corporate Bond Yield Relative to Yield on 10-Year Treasury Constant Maturity (BAA10Y)
# Daily (since 1986)
# Series is calculated as the spread between
# Moodys Seasoned Baa Corporate Bond© (https://fred.stlouisfed.org/series/DBAA)
# and 10-Year Treasury Constant Maturity (BC_10YEAR).
# https://fred.stlouisfed.org/series/BAA10Y
# Merrill Lynch High-Yield Corporate Master II minus 10-Year Treasury - STLFSI2
# NOT EXACTLY
# ICE BofA US High Yield Index Effective Yield (BAMLH0A0HYM2EY)
# Daily (since early 1997)
# https://fred.stlouisfed.org/series/BAMLH0A0HYM2EY
# LESS
# EXACTLY
# 10-Year Treasury Constant Maturity Rate (DGS10)
# Daily (since 1952)
# https://fred.stlouisfed.org/series/DGS10
# 3-month London Interbank Offering Rate - Overnight Index Swap (LIBOR-OIS) spread
# overnight indexed swap (OIS) - STLFSI2
# (in the United States, this is the
# effective federal funds rate)
# The LIBOR-OIS Spread as a Summary Indicator
# MonetaryTrends
# November 2008
# https://files.stlouisfed.org/files/htdocs/publications/mt/20081101/cover.pdf
# NOT EXACTLY
# 3-Month London Interbank Offered Rate (LIBOR), based on U.S. Dollar (USD3MTD156N)
# Data (since 1986)
# The data series is lagged by one week due to an agreement with the source.
# https://fred.stlouisfed.org/series/USD3MTD156N
# LESS
# ???
# The OIS, meanwhile, represents a given country’s central bank rate throughout a certain period;
# in the US, that is the Fed funds rate—the key interest rate controlled
# by the Federal Reserve, commonly called "the Fed".
# https://www.investopedia.com/articles/active-trading/061114/what-ois-libor-spread-and-what-it.asp
# NOT EXACTLY OR MAYBE EXACTLY
# Effective Federal Funds Rate (DFF)
# Daily, 7-Day (since 1954)
# https://fred.stlouisfed.org/series/DFF
# 3-Month Treasury-Eurodollar (TED) spread - STLFSI2
# TED Spread (TEDRATE)
# Daily (since 1986)
# Series is calculated as the spread between 3-Month LIBOR
# based on US dollars (https://fred.stlouisfed.org/series/USD3MTD156N) and
# 3-Month Treasury Bill (https://fred.stlouisfed.org/series/DTB3).
# The series is lagged by one week because the LIBOR series is lagged by one week due to an agreement with the source.
# https://fred.stlouisfed.org/series/TEDRATE
# 3-Month Commercial Paper minus 3-Month Treasury
# 90-Day AA Financial Commercial Paper Interest Rate (RIFSPPFAAD90NB)
# Daily (since 1997)
# https://fred.stlouisfed.org/series/RIFSPPFAAD90NB
# FROM DESCRIPTION OF
# 3-Month Commercial Paper Minus Federal Funds Rate (CPFF)
# Daily (since 1997)
# https://fred.stlouisfed.org/series/CPFF
# LESS
# 3-Month Treasury Constant Maturity Rate (DGS3MO)
# Daily (since 1981)
# https://fred.stlouisfed.org/series/DGS3MO
# J.P. Morgan Emerging Markets Bond Index Plus - STLFSI2 - Change in Log Levels
# Emerging Markets Bond Index Plus
# total returns for traded external debt instruments
# (external meaning foreign currency denominated fixed income) in the emerging markets.
# The regular EMBI index covers U.S.dollar-denominated Brady bonds, loans and Eurobonds.
# An external debt version, the EMBI+ is the JPMorgan EMBI Global Index
# https://en.wikipedia.org/wiki/JPMorgan_EMBI#Emerging_Markets_Bond_Index_Plus
# NOT EXACTLY (CAN NOT FIND EMBI+)
# iShares J.P. Morgan USD Emerging Markets Bond ETF (EMB)
# NasdaqGS - NasdaqGS Real Time Price. Currency in USD
# https://finance.yahoo.com/quote/EMB/
# NOT EXACTLY AND ALTER DATA IS "NOT EASILY AVAILABLE"
# quantmod::getSymbols("EMB", from = "1960-01-01")
# 2007-12-19
# MORE INFO
# Introducing the J.P. Morgan Emerging
# Markets Bond Index Global (EMBI Global)
# capitalization-weighted indeOur current source for these classifications
# (presently, any country with a per capita income less
# than US$9,635) is the World Bank publication, Global Development Finance.
# https://faculty.darden.virginia.edu/liw/emf/embi.pdf
# MORE INFO
# The Top 5 International Bond Funds for 2020
# By MELISSA HORTON
# Updated Mar 25, 2020
# 5. GMO Emerging Country Debt Fund (GMCDX)
# objective of achieving total return in excess of its benchmark,
# which is the J.P. Morgan Emerging Markets Bond Index Global Diversified
# https://www.investopedia.com/articles/investing/010416/top-5-international-bond-funds-2016.asp
# REPLACEMENT
# quantmod::getSymbols("GMCDX", from = "1900-01-01")
# (since 1994)
# Chicago Board Options Exchange Market Volatility Index (VIX) - STLFSI2
# quantmod::getSymbols("VIX", from = "1900-01-01")
# (only since 2014)
# CBOE Volatility Index: VIX (VIXCLS)
# Daily, Close
# https://fred.stlouisfed.org/series/VIXCLS
# (since 1990)
# Merrill Lynch Bond Market Volatility Index (1-Month) - STLFSI2
# NOT EXACTLY
# Investors seeking yield should use MOVE and VIX
# The MOVE (Merrill Lynch Option Volatility Estimate) Index
# measures the implied volatility of U.S. Treasury markets and, along with the VIX,
# is a useful indicator for investors in assessing the psyche of the market
# . . .
# MOVE
# gauging options contracts on one-month Treasury issues.
# . . .
# https://financialpost.com/investing/investors-seeking-yield-should-use-move-and-vix
# ROLL MY OWN - 22 DAYS
# 1-Month Treasury Constant Maturity Rate
# Daily
# https://fred.stlouisfed.org/data/DGS1MO.txt
# (since 2001 ) too young
# 4-Week Treasury Bill: Secondary Market Rate (TB4WK)
# Daily
# https://fred.stlouisfed.org/series/TB4WK
# (since 2001) too young
# Commercial Paper
# https://www.sciencedirect.com/topics/economics-econometrics-and-finance/commercial-paper
# 30-Day AA Financial Commercial Paper Interest Rate (RIFSPPFAAD30NB)
# https://fred.stlouisfed.org/series/RIFSPPFAAD30NB
# (since 1997)
# 10-Year Nominal Treasury Yield minus 10-Year Treasury Inflation Protected Security Yield (Breakeven Inflation Rate)
# 10-Year Breakeven Inflation Rate (T10YIE) - STLFSI2
# Daily(since 2003) too young
# https://fred.stlouisfed.org/series/T10YIE
# 10-Year Treasury Inflation-Indexed Security, Constant Maturity (DFII10)
# Daily (since 2003) too young
# https://fred.stlouisfed.org/series/DFII10
# . . .
# A yield curve is a line that plots yields (interest rates) of bonds
# having equal credit quality but differing maturity dates
# https://www.investopedia.com/terms/y/yieldcurve.asp
# . . .
# Treasury Real Yield Curve Rates. These rates are commonly referred to as "Real Constant Maturity Treasury" rates,
# Real yields on Treasury Inflation Protected Securities (TIPS) at "constant maturity" are
# interpolated by the U.S. Treasury from Treasurys daily real yield curve.
# SO I WANT
# Daily Treasury Yield Curve Rates (getYieldCurve example 1)
# LESS
# Daily Treasury Real Yield Curve Rates (getYieldCurve example 4)
#
# NOTE example 5 is direct.
# . . .
# (since 1990)
# https://www.treasury.gov/resource-center/data-chart-center/interest-rates/Pages/TextView.aspx?data=yield
#
# What Is the Nominal Interest Rate? (Need Inflation Adjustment)
# Nominal interest rate refers to the interest rate before taking inflation into account.
# https://www.investopedia.com/terms/n/nominalinterestrate.asp
# S&P Financial Index - STLFSI2 - Change in Log Levels
# Vanguard Financials Index Fund ETF Shares (VFH)
# NYSEArca - NYSEArca Delayed Price. Currency in USD
# http://finance.yahoo.com/q?s=vfh&.yficrumb=CgCsdHP9jeG
# https://finance.yahoo.com/quote/vfh?ltr=1
# quantmod::getSymbols("VFH", from = "1900-01-01")
# 2004-01-30 (too young)
# ^SP500-40 S&P 500 Financials (Sector) - symbol
# https://finance.yahoo.com/lookup/index?s=sector?
# Getting data of sub-sector indexes of an S&P 500 index sector using QuantMod in R
# 2016
# https://quant.stackexchange.com/questions/29576/getting-data-of-sub-sector-indexes-of-an-sp-500-index-sector-using-quantmod-in
# quantmod::getSymbols("XLF", from = "1900-01-01")
# 1998-12-22
# STLFSI of 07/15/2010 the Vanguard Financial Exchange-Traded Fund series
# has been replaced with the S&P 500 Financials Index.
# STLFSI TrainDates
# . . . over the
# sample period December 31, 1993, to December 11, 2009
#
# STLFSI and STLFSI2 start December 31, 1993
# STLFSI ends March 13, 2020
# # The St. Louis Fed’s Financial Stress Index, Version 2.0
# https://fredblog.stlouisfed.org/2020/03/the-st-louis-feds-financial-stress-index-version-2-0/
# BUT THEY ARE DOING
# When the sample changes (i.e., a new week of data is added),
# the values of the FSI in the original sample can be changed.
#
# STLFSI proc
# Principal components analysis is used to construct the STLFSI
#
# STLFSI index
# by extracting this factor (the first principal component)
# we are able to create an index
#
# STLFSI index reports
# St. Louis Fed Financial Stress Index (DISCONTINUED) (STLFSI)
# Weekly, Ending Friday
# https://fred.stlouisfed.org/series/STLFSI
#
# St. Louis Fed Financial Stress Index (STLFSI2)
# Weekly, Ending Friday
# https://fred.stlouisfed.org/series/STLFSI2
# STLFSI index intepretation
# How to Interpret the Index:
# The average value of the index, which begins in late 1993, is designed to be zero.
# Thus, zero is viewed as representing normal financial market conditions.
# Values below zero suggest below-average financial market stress,
# while values above zero suggest above-average financial market stress.
# STLFSI proc details
# 1. First, each of the data series is de-meaned.
# The de-meaned series are then
# divided by their respective sample standard deviations (SDs)
# (Because each variable was standardized,
# the coefficient of a variable (SEE 2.) represents the
# "influence of a 1 SD change in that variable on the FSI.")
# 2. we use the method of principal components to calculate the
# coefficients of the variables
# 3. We then scale these coefficients so that the SD of the index is 1.
# 4. Finally, each data series is multiplied by its respective adjusted coefficient
# 5. FSI for time t is
# the sum of each series multiplied by its respective adjusted coefficient.
# (Higher values of the FSI indicate a
# greater degree of financial stress in the economy.)
#
# STLFSI proc details drawbacks
# A negative coefficient multiplied by a negative data value
# will result in a positive contribution to financial stress.
#
# STLFSI percent of the total variation
# in the 18 variables (DEFINITION)
# 1 – SSE/SST
#
stressIndex(x , TrainDates,
...
)
}, write.error.dump.folder = getOption("econModel.tryCatchLog.write.error.dump.folder"))}
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Defines functions FSI2 stressIndex stLouisFEDdaily2Weekly
Documented in FSI2 stLouisFEDdaily2Weekly stressIndex
#' Convert an xts object Into a St Louis FED Weekly xts Object.
#'
#' @description
#' Given Dailies, return the five(5) day moving average (called a "weekly") with an Observation data on Fridays that are published on the following Thursdays.
#'
#' @param x xts object of Dailies.
#' @param Level String. Default is "Levels" Other choices are "ChangeInLevels" and "ChangeInLogLevels."
#' @return Modified xts object
#' @examples
#' \dontrun{
#' DGS2 <- quantmod::getSymbols("DGS2", src = "FRED", auto.assign = F)
#' DGS2 <- stLouisFEDdaily2Weekly(DGS2, Level = "ChangeInLevels")
#' }
#' @importFrom tryCatchLog tryCatchLog
#' @importFrom stats na.omit
#' @importFrom zoo index `index<-` coredata as.zoo rollapply
#' @importFrom xts xts as.xts lag.xts xtsAttributes `xtsAttributes<-`
#' @importFrom timeDate timeNthNdayInMonth
#' @export
stLouisFEDdaily2Weekly <- function(x, Level) {
tryCatchLog::tryCatchLog({
# if not done elsewhere
#correct for TZ
oldtz <- Sys.getenv("TZ")
if(oldtz!="UTC") {
Sys.setenv(TZ="UTC")
}
if(missing(Level)) {
Level <- "Levels"
}
if(!Level %in% c("Levels", "ChangeInLevels", "ChangeInLogLevels")) {
stop("Level must be one of \"Levels\", \"ChangeInLevels\", or \"ChangeInLogLevels\"")
}
Result <- ORIG <- x
Result <- stats::na.omit(Result)
# changes
if(Level == "ChangeInLogLevels") {
Result <- log(Result)
}
if(Level %in% c("ChangeInLevels","ChangeInLogLevels")) {
Result <- (Result - xts::lag.xts(Result))/abs(xts::lag.xts(Result))
}
# 5 days(week) rolling means of changes
Result <- zoo::rollapply(zoo::as.zoo(Result), width = 5L, mean, fill = NA , partial = F, align = "right")
# xts (with the original index class, format, and time zone)
Result <- cbind(xts::xts(, zoo::index(ORIG)[0]), xts::as.xts(Result))
# personal "xts attributes"
xts::xtsAttributes(Result) <- c(list(), xts::xtsAttributes(Result), xts::xtsAttributes(ORIG))
# FRI entries (Observation Dates)
Index <- zoo::index(Result)[weekdays(zoo::index(Result)) == "Friday"]
#
Result <- Result[Index]
# save seconds
TimeDiff <- as.POSIXct(Index) - as.POSIXct(zoo::as.Date(Index))
# next THU entries (Publication Dates) - a "better" Index
BetterIndex <- zoo::as.Date(timeDate::timeNthNdayInMonth(as.character(zoo::as.Date(Index)), nday = 4, nth = 1))
# put back TimeDiff
BetterIndex <- as.POSIXct(BetterIndex) + TimeDiff
# put back the class
BetterIndex <- eval(parse(text = paste0("as.", class(index(ORIG))[1], "(BetterIndex)")))
#
zoo::index(Result) <- BetterIndex
Sys.setenv(TZ=oldtz)
Result
}, write.error.dump.folder = getOption("econModel.tryCatchLog.write.error.dump.folder"))}
#' Stress Index
#'
#' @description
#' \preformatted{
#' Types of Risk
#'
#' "default risk":
#' interest rate spread designed to measure
#' the difference between yields on a “risky” asset
#' and a “risk-free” asset
#'
#' "liquidity risk""
#' inability to secure resources to acquire short term
#' liabilities
#'
#' Stress Index
#' Uses a precedure (Principal Components) to create
#' the "stress index".
#'
#' Creating the Stress Index
#'
#' 1. First, each of the data series is de-meaned.
#' The de-meaned series are then
#' divided by their respective sample standard deviations (SDs)
#' (Because each variable was standardized,
#' the coefficient of a variable (SEE 2.) represents the
#' "influence of a 1 SD change in that variable on the Stress Index.")
#' 2. Use the method of principal components:
#' Extracting this factor (the first principal component).
#' makes it able to create an index with a useful interpretation
#' 3. Calculate the coefficients of the variables.
#'
#' The factor loadings, also called component loadings in PCA,
#' are the correlation coefficients
#' between the variables (rows) and factors (columns).
#'
#' The elements of the eigenvectors of . . . are the
#' "coefficients" or "loadings" of the principal components.
#'
#' 4. We then scale these coefficients so that the SD of the index is 1.
#' 5. Finally, each data series is multiplied
#' by its respective adjusted coefficient.
#' 6. Stress Index for time t is
#' the sum of each series multiplied
#' by its respective adjusted coefficient.
#' (Higher values of the FSI indicate a
#' greater degree of financial stress in the economy.)
#'
#' Stress Index proc details drawbacks
#' A negative coefficient multiplied by a negative data value
#' will result in a positive contribution to financial stress.
#'
#' Stress Index percent of the total variation
#' in the many variables
#' 1 – SSE/SST
#' SST is the total sum of squares
#' SSE is the sum of squared errors
#' X(N,t) is the value of the Nth standardized variable in month t,
#' and a(N) is the set of coefficients chosen.
#' Updating the Stress Index
#'
#' When the sample changes (i.e., a new item of data is added),
#' the values of the Stress Index in the original sample can be changed.
#' This alteration can occur either through a
#' change in the coefficients of the variables in the index
#' or by a change in the actual values of the variables in the
#' original sample. The overall magnitude of the coefficients,
#' as well as their relative magnitudes, can change.
#' }
#' @param x xts object. Required. This is the input used for prediction.
#' @param ValDates List of (or vector of) pairs of vectors of begin and end date-time ranges. Required (if not all of the ValidationData is to be used).
#' @return Index that is centered about zero(0) and scaled to the standard deviation of one(1).
#' @references
#' \cite{How to compute varimax-rotated principal components in R?, 2014
#' \url{https://stats.stackexchange.com/questions/59213/how-to-compute-varimax-rotated-principal-components-in-r}
#' }
#' @references
#' \cite{Aaron Schlegel, Principal Component Analysis with R Example, Thu 19 January 2017
#' \url{https://aaronschlegel.me/principal-component-analysis-r-example.html}
#' }
#' @references
#' \cite{Introduction to Principal Components and FactorAnalysis, North Carolina State University
#' \url{ftp://statgen.ncsu.edu/pub/thorne/molevoclass/AtchleyOct19.pdf}
#' }
#' @references
#' \cite{Luke Hayden, Principal Component Analysis in R, August 9th, 2018
#' \url{https://www.datacamp.com/community/tutorials/pca-analysis-r}
#' }
#' @references
#' \cite{author(s)?, National Economic Trends, Appendix, January 2010
#' \url{https://files.stlouisfed.org/files/htdocs/publications/net/NETJan2010Appendix.pdf}
#' }
#' @references
#' \cite{Kevin L. Kliesen and Douglas C. Smith, Measuring Financial Market Stress, Economic SYNOPSES, 2010 Number 2, Posted on January 15, 2010
#' \url{https://files.stlouisfed.org/files/htdocs/publications/es/10/ES1002.pdf}
#' }
#' @examples
#' \dontrun{
#' # E.g. some (and only some of the) interest rates
#' # of the St Louis Stress Index 2 (STLFSI2)
#' for(Symbol in c("DFF","DGS2","DGS10")) {
#' quantmod::getSymbols(Symbol, src = "FRED")
#' assign(Symbol, stLouisFEDdaily2Weekly(get(Symbol), Level = "ChangeInLevels"))
#' }
#'
#' Data <- stats::na.omit(cbind(DFF,DGS2,DGS10))
#' # dygraphs::dygraph(stressIndex(Data))
#' }
#' @importFrom tryCatchLog tryCatchLog
#' @importFrom stats na.omit prcomp
#' @importFrom zoo index
#' @importFrom xts xts
#' @export
stressIndex <- function(x, ValDates,
...
) {
tryCatchLog::tryCatchLog({
x <- stats::na.omit(x)
PrCmpObj <- stats::prcomp(x, center = TRUE, scale. = TRUE)
Prediction <- predict(PrCmpObj, newdata = Data)[, "PC1"]
PredictionScaled <- scale(Prediction, center = T, scale = T)
colnames(PredictionScaled) <- "StressIndex"
StressIndex <- xts::xts(PredictionScaled, zoo::index(Data))
StressIndex
}, write.error.dump.folder = getOption("econModel.tryCatchLog.write.error.dump.folder"))}
#' Re-Createion of the St. Louis Federal Board of Governors Financial Stress Index Version 2
#'
#' @description
#' Uses a precedure (e.g. Principal Components) to create the "stress index" Financial Stress Index Version 2
#'
#' @references
#' \cite{St. Louis Fed Financial Stress Index (STLFSI2)
#' \url{https://fred.stlouisfed.org/series/STLFSI2}
#' }
#' @references
#' \cite{author(s)?, Table 1: Data Used to Construct STLFSI
#' \url{https://fredblog.stlouisfed.org/wp-content/uploads/2020/03/FSI2.pdf}
#' }
#' @references
#' \cite{Kevin Kliesen and Michael McCracken, The St. Louis Fed’s Financial Stress Index, Version 2.0, March 26, 2020
#' \url{https://fredblog.stlouisfed.org/2020/03/the-st-louis-feds-financial-stress-index-version-2-0/}
#' }
#' @references
#' \cite{List of Data Series Used to Construct the St. Louis Fed Financial Stress Index (STLFSI)
#' \url{https://www.stlouisfed.org/~/media/Files/PDFs/STLFSI-Key.pdf?la=en}
#' }
#' @references
#' \cite{list of the components that are used to construct the STLFSI
#' \url{https://www.stlouisfed.org/news-releases/st-louis-fed-financial-stress-index/stlfsi-key}
#' }
#' @references
#' \cite{St. Louis Fed Financial Stress Index (DISCONTINUED) (STLFSI)
#' \url{https://fred.stlouisfed.org/series/STLFSI}
#' }
#' @references
#' \cite{author(s)?, National Economic Trends, Appendix, January 2010
#' \url{https://files.stlouisfed.org/files/htdocs/publications/net/NETJan2010Appendix.pdf}
#' }
#' @references
#' \cite{author(s)?, The LIBOR-OIS Spread as a Summary Indicator, MonetaryTrends, November 2008
#' \url{https://files.stlouisfed.org/files/htdocs/publications/mt/20081101/cover.pdf}
#' }
#' @references
#' \cite{Kevin L. Kliesen and Douglas C. Smith, Measuring Financial Market Stress, Economic SYNOPSES, 2010 Number 2, Posted on January 15, 2010
#' \url{https://files.stlouisfed.org/files/htdocs/publications/es/10/ES1002.pdf}
#' }
#' @param TrainData xts object. Required.
#' @param TrainDates List of (or vector of) pairs of vectors of begin and end date-time ranges. Required (if not all of the ValidationData is to be used).
#' @return Index.
#' @examples
#' \dontrun{
#' }
#' @importFrom tryCatchLog tryCatchLog
#' @export
FSI2 <- function(x, TrainDates,
...
) {
tryCatchLog::tryCatchLog({
# STLFSI TrainData
# We construct the STLFSI using 18 weekly data series . . .
#
# STLFSI2
# 18 weekly data series, all of which are weekly averages of daily data series
# Date Range: 1993-12-31 to 2020-11-27 (ObservationDate) - End of Week - FRI
# Last Updated: 2020-12-03 9:00 AM CST (PublishedDate) - Following Week - THU Morn
# https://fred.stlouisfed.org/data/STLFSI2.txt
# STLFSI2
# The key difference between versions 1.0 and 2.0 is that
# 2.0 uses daily changes in interest rates and stock prices,
# rather than the levels of interest rates and stock prices in the PCA calculation.
#
# Effective Federal Funds Rate (DFF)
# Daily, 7-Day (since 1954)
# https://fred.stlouisfed.org/series/DFF
# Following are all Levels (unless noted otherwise)
# 2-Year Treasury Constant Maturity Rate (DGS2) - STLFSI2 - Change in Levels
# Daily (since 1976)
# https://fred.stlouisfed.org/series/DGS2
# 10-Year Treasury Constant Maturity Rate (DGS10) - STLFSI2 - Change in Levels
# Daily (since 1952)
# https://fred.stlouisfed.org/series/DGS10
# 30-Year Treasury Constant Maturity Rate (DGS30) - STLFSI2 - Change in Levels
# Daily (since 1977)
# https://fred.stlouisfed.org/series/DGS30
# Moodys Seasoned Baa Corporate Bond Yield (DBAA) - STLFSI2 - Change in Levels
# Daily (since 1986)
# https://fred.stlouisfed.org/series/DBAA
# Bank of America - Previously BofAML
# Bank of America Merrill Lynch is now Bank of America.
# Google query of November 2020
# Merrill Lynch High-Yield Corporate Master II Index - STLFSI2 - Change in Levels
# Merrill Lynch High Yield Master II
# https://en.wikipedia.org/wiki/Merrill_Lynch_High_Yield_Master_II
# NOT EXACTLY
# ICE BofA US High Yield Index Effective Yield (BAMLH0A0HYM2EY)
# Daily (since early 1997)
# https://fred.stlouisfed.org/series/BAMLH0A0HYM2EY
# Merrill Lynch Asset-Backed Master BBB-rated - STLFSI2 - Change in Levels
# NOT EXACTLY
# ICE BofA BBB US Corporate Index Effective Yield
# Daily (since early 1997)
# This data represents the effective yield of the ICE BofA BBB US Corporate Index,
# a subset of the ICE BofA US Corporate Master Index
# https://fred.stlouisfed.org/series/BAMLC0A4CBBBEY
# Yield Curve: 10-Year minus 3-Month Treasury - STLFSI2
# 10-Year Treasury Constant Maturity Minus 3-Month Treasury Constant Maturity (T10Y3M)
# Daily (since 1982)
# https://fred.stlouisfed.org/series/T10Y3M
# Corporate Baa-rated bond minus 10-Year Treasury - STLFSI2
# NOT EXACTLY
# Moodys Seasoned Baa Corporate Bond Yield Relative to Yield on 10-Year Treasury Constant Maturity (BAA10Y)
# Daily (since 1986)
# Series is calculated as the spread between
# Moodys Seasoned Baa Corporate Bond© (https://fred.stlouisfed.org/series/DBAA)
# and 10-Year Treasury Constant Maturity (BC_10YEAR).
# https://fred.stlouisfed.org/series/BAA10Y
# Merrill Lynch High-Yield Corporate Master II minus 10-Year Treasury - STLFSI2
# NOT EXACTLY
# ICE BofA US High Yield Index Effective Yield (BAMLH0A0HYM2EY)
# Daily (since early 1997)
# https://fred.stlouisfed.org/series/BAMLH0A0HYM2EY
# LESS
# EXACTLY
# 10-Year Treasury Constant Maturity Rate (DGS10)
# Daily (since 1952)
# https://fred.stlouisfed.org/series/DGS10
# 3-month London Interbank Offering Rate - Overnight Index Swap (LIBOR-OIS) spread
# overnight indexed swap (OIS) - STLFSI2
# (in the United States, this is the
# effective federal funds rate)
# The LIBOR-OIS Spread as a Summary Indicator
# MonetaryTrends
# November 2008
# https://files.stlouisfed.org/files/htdocs/publications/mt/20081101/cover.pdf
# NOT EXACTLY
# 3-Month London Interbank Offered Rate (LIBOR), based on U.S. Dollar (USD3MTD156N)
# Data (since 1986)
# The data series is lagged by one week due to an agreement with the source.
# https://fred.stlouisfed.org/series/USD3MTD156N
# LESS
# ???
# The OIS, meanwhile, represents a given country’s central bank rate throughout a certain period;
# in the US, that is the Fed funds rate—the key interest rate controlled
# by the Federal Reserve, commonly called "the Fed".
# https://www.investopedia.com/articles/active-trading/061114/what-ois-libor-spread-and-what-it.asp
# NOT EXACTLY OR MAYBE EXACTLY
# Effective Federal Funds Rate (DFF)
# Daily, 7-Day (since 1954)
# https://fred.stlouisfed.org/series/DFF
# 3-Month Treasury-Eurodollar (TED) spread - STLFSI2
# TED Spread (TEDRATE)
# Daily (since 1986)
# Series is calculated as the spread between 3-Month LIBOR
# based on US dollars (https://fred.stlouisfed.org/series/USD3MTD156N) and
# 3-Month Treasury Bill (https://fred.stlouisfed.org/series/DTB3).
# The series is lagged by one week because the LIBOR series is lagged by one week due to an agreement with the source.
# https://fred.stlouisfed.org/series/TEDRATE
# 3-Month Commercial Paper minus 3-Month Treasury
# 90-Day AA Financial Commercial Paper Interest Rate (RIFSPPFAAD90NB)
# Daily (since 1997)
# https://fred.stlouisfed.org/series/RIFSPPFAAD90NB
# FROM DESCRIPTION OF
# 3-Month Commercial Paper Minus Federal Funds Rate (CPFF)
# Daily (since 1997)
# https://fred.stlouisfed.org/series/CPFF
# LESS
# 3-Month Treasury Constant Maturity Rate (DGS3MO)
# Daily (since 1981)
# https://fred.stlouisfed.org/series/DGS3MO
# J.P. Morgan Emerging Markets Bond Index Plus - STLFSI2 - Change in Log Levels
# Emerging Markets Bond Index Plus
# total returns for traded external debt instruments
# (external meaning foreign currency denominated fixed income) in the emerging markets.
# The regular EMBI index covers U.S.dollar-denominated Brady bonds, loans and Eurobonds.
# An external debt version, the EMBI+ is the JPMorgan EMBI Global Index
# https://en.wikipedia.org/wiki/JPMorgan_EMBI#Emerging_Markets_Bond_Index_Plus
# NOT EXACTLY (CAN NOT FIND EMBI+)
# iShares J.P. Morgan USD Emerging Markets Bond ETF (EMB)
# NasdaqGS - NasdaqGS Real Time Price. Currency in USD
# https://finance.yahoo.com/quote/EMB/
# NOT EXACTLY AND ALTER DATA IS "NOT EASILY AVAILABLE"
# quantmod::getSymbols("EMB", from = "1960-01-01")
# 2007-12-19
# MORE INFO
# Introducing the J.P. Morgan Emerging
# Markets Bond Index Global (EMBI Global)
# capitalization-weighted indeOur current source for these classifications
# (presently, any country with a per capita income less
# than US$9,635) is the World Bank publication, Global Development Finance.
# https://faculty.darden.virginia.edu/liw/emf/embi.pdf
# MORE INFO
# The Top 5 International Bond Funds for 2020
# By MELISSA HORTON
# Updated Mar 25, 2020
# 5. GMO Emerging Country Debt Fund (GMCDX)
# objective of achieving total return in excess of its benchmark,
# which is the J.P. Morgan Emerging Markets Bond Index Global Diversified
# https://www.investopedia.com/articles/investing/010416/top-5-international-bond-funds-2016.asp
# REPLACEMENT
# quantmod::getSymbols("GMCDX", from = "1900-01-01")
# (since 1994)
# Chicago Board Options Exchange Market Volatility Index (VIX) - STLFSI2
# quantmod::getSymbols("VIX", from = "1900-01-01")
# (only since 2014)
# CBOE Volatility Index: VIX (VIXCLS)
# Daily, Close
# https://fred.stlouisfed.org/series/VIXCLS
# (since 1990)
# Merrill Lynch Bond Market Volatility Index (1-Month) - STLFSI2
# NOT EXACTLY
# Investors seeking yield should use MOVE and VIX
# The MOVE (Merrill Lynch Option Volatility Estimate) Index
# measures the implied volatility of U.S. Treasury markets and, along with the VIX,
# is a useful indicator for investors in assessing the psyche of the market
# . . .
# MOVE
# gauging options contracts on one-month Treasury issues.
# . . .
# https://financialpost.com/investing/investors-seeking-yield-should-use-move-and-vix
# ROLL MY OWN - 22 DAYS
# 1-Month Treasury Constant Maturity Rate
# Daily
# https://fred.stlouisfed.org/data/DGS1MO.txt
# (since 2001 ) too young
# 4-Week Treasury Bill: Secondary Market Rate (TB4WK)
# Daily
# https://fred.stlouisfed.org/series/TB4WK
# (since 2001) too young
# Commercial Paper
# https://www.sciencedirect.com/topics/economics-econometrics-and-finance/commercial-paper
# 30-Day AA Financial Commercial Paper Interest Rate (RIFSPPFAAD30NB)
# https://fred.stlouisfed.org/series/RIFSPPFAAD30NB
# (since 1997)
# 10-Year Nominal Treasury Yield minus 10-Year Treasury Inflation Protected Security Yield (Breakeven Inflation Rate)
# 10-Year Breakeven Inflation Rate (T10YIE) - STLFSI2
# Daily(since 2003) too young
# https://fred.stlouisfed.org/series/T10YIE
# 10-Year Treasury Inflation-Indexed Security, Constant Maturity (DFII10)
# Daily (since 2003) too young
# https://fred.stlouisfed.org/series/DFII10
# . . .
# A yield curve is a line that plots yields (interest rates) of bonds
# having equal credit quality but differing maturity dates
# https://www.investopedia.com/terms/y/yieldcurve.asp
# . . .
# Treasury Real Yield Curve Rates. These rates are commonly referred to as "Real Constant Maturity Treasury" rates,
# Real yields on Treasury Inflation Protected Securities (TIPS) at "constant maturity" are
# interpolated by the U.S. Treasury from Treasurys daily real yield curve.
# SO I WANT
# Daily Treasury Yield Curve Rates (getYieldCurve example 1)
# LESS
# Daily Treasury Real Yield Curve Rates (getYieldCurve example 4)
#
# NOTE example 5 is direct.
# . . .
# (since 1990)
# https://www.treasury.gov/resource-center/data-chart-center/interest-rates/Pages/TextView.aspx?data=yield
#
# What Is the Nominal Interest Rate? (Need Inflation Adjustment)
# Nominal interest rate refers to the interest rate before taking inflation into account.
# https://www.investopedia.com/terms/n/nominalinterestrate.asp
# S&P Financial Index - STLFSI2 - Change in Log Levels
# Vanguard Financials Index Fund ETF Shares (VFH)
# NYSEArca - NYSEArca Delayed Price. Currency in USD
# http://finance.yahoo.com/q?s=vfh&.yficrumb=CgCsdHP9jeG
# https://finance.yahoo.com/quote/vfh?ltr=1
# quantmod::getSymbols("VFH", from = "1900-01-01")
# 2004-01-30 (too young)
# ^SP500-40 S&P 500 Financials (Sector) - symbol
# https://finance.yahoo.com/lookup/index?s=sector?
# Getting data of sub-sector indexes of an S&P 500 index sector using QuantMod in R
# 2016
# https://quant.stackexchange.com/questions/29576/getting-data-of-sub-sector-indexes-of-an-sp-500-index-sector-using-quantmod-in
# quantmod::getSymbols("XLF", from = "1900-01-01")
# 1998-12-22
# STLFSI of 07/15/2010 the Vanguard Financial Exchange-Traded Fund series
# has been replaced with the S&P 500 Financials Index.
# STLFSI TrainDates
# . . . over the
# sample period December 31, 1993, to December 11, 2009
#
# STLFSI and STLFSI2 start December 31, 1993
# STLFSI ends March 13, 2020
# # The St. Louis Fed’s Financial Stress Index, Version 2.0
# https://fredblog.stlouisfed.org/2020/03/the-st-louis-feds-financial-stress-index-version-2-0/
# BUT THEY ARE DOING
# When the sample changes (i.e., a new week of data is added),
# the values of the FSI in the original sample can be changed.
#
# STLFSI proc
# Principal components analysis is used to construct the STLFSI
#
# STLFSI index
# by extracting this factor (the first principal component)
# we are able to create an index
#
# STLFSI index reports
# St. Louis Fed Financial Stress Index (DISCONTINUED) (STLFSI)
# Weekly, Ending Friday
# https://fred.stlouisfed.org/series/STLFSI
#
# St. Louis Fed Financial Stress Index (STLFSI2)
# Weekly, Ending Friday
# https://fred.stlouisfed.org/series/STLFSI2
# STLFSI index intepretation
# How to Interpret the Index:
# The average value of the index, which begins in late 1993, is designed to be zero.
# Thus, zero is viewed as representing normal financial market conditions.
# Values below zero suggest below-average financial market stress,
# while values above zero suggest above-average financial market stress.
# STLFSI proc details
# 1. First, each of the data series is de-meaned.
# The de-meaned series are then
# divided by their respective sample standard deviations (SDs)
# (Because each variable was standardized,
# the coefficient of a variable (SEE 2.) represents the
# "influence of a 1 SD change in that variable on the FSI.")
# 2. we use the method of principal components to calculate the
# coefficients of the variables
# 3. We then scale these coefficients so that the SD of the index is 1.
# 4. Finally, each data series is multiplied by its respective adjusted coefficient
# 5. FSI for time t is
# the sum of each series multiplied by its respective adjusted coefficient.
# (Higher values of the FSI indicate a
# greater degree of financial stress in the economy.)
#
# STLFSI proc details drawbacks
# A negative coefficient multiplied by a negative data value
# will result in a positive contribution to financial stress.
#
# STLFSI percent of the total variation
# in the 18 variables (DEFINITION)
# 1 – SSE/SST
#
stressIndex(x , TrainDates,
...
)
}, write.error.dump.folder = getOption("econModel.tryCatchLog.write.error.dump.folder"))}
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