US large cap market returns. Fine print The data are from Yahoo Almost all of the S&P 500 stocks are used (as implied by Wikipedia on 2013 January 5 — see the R commands to scrape the data) The initial post was “Replacing market indices” The R code is in marketportrait_funs.R

US large cap market returns. Fine print The data are from Yahoo Almost all of the S&P 500 stocks are used (as implied by Wikipedia on 2013 January 5 — see the R commands to scrape the data) The initial post was “Replacing market indices” The R code is in marketportrait_funs.R

US large cap market returns. Fine print The data are from Yahoo Almost all of the S&P 500 stocks are used (as implied by Wikipedia on 2013 January 5 — see the R commands to scrape the data) The initial post was “Replacing market indices” The R code is in marketportrait_funs.R

US large cap market returns. Fine print The data are from Yahoo Almost all of the S&P 500 stocks are used (as implied by Wikipedia on 2013 January 5 — see the R commands to scrape the data) The initial post was “Replacing market indices” The R code is in marketportrait_funs.R

Some ways to explore how good a method of predicting returns is. Data and model The universe is 443 large cap US stocks that have data back to the beginning of 2004.  The daily (adjusted) close was used. The model that is used as an example is the default signal from the MACD function of the TTR package in R.  As we’ll see, this works sometimes, and sometimes not.  The signal would need to be scaled to really be expected returns, but the scaling won’t matter for our tests....

US large cap market returns. Fine print The data are from Yahoo Almost all of the S&P 500 stocks are used (as implied by Wikipedia on 2013 January 5 — see the R commands to scrape the data) The initial post was “Replacing market indices” The R code is in marketportrait_funs.R

How to fit and use the components model. Previously Related posts are: A practical introduction to garch modeling Variability of garch estimates garch estimation on impossibly long series Variance targeting in garch estimation The model The components model (created by Engle and Lee) generally works better than the more common garch(1,1) model.  Some hints about why it is better are in “3 realms of garch modelling”. Figure 1 shows predictions of volatility for each day 20 days...

The Burns Statistics blog had it’s first real post today (about the corner function in the BurStMisc package).  The blog will talk mainly about the R language, statistics and programming — it will not have the financial focus of the Portfolio Probe blog. The posts on the Burns Statistics blog will be announced on Twitter via @burnsstat.

US large cap market returns. Fine print The data are from Yahoo Almost all of the S&P 500 stocks are used (as implied by Wikipedia on 2013 January 5 — see the R commands to scrape the data) The initial post was “Replacing market indices” The R code is in marketportrait_funs.R

What coherent risk measures are, why some people think coherence is important, and why I don’t. The rules A risk measure is considered to be coherent if it satisfies some mathematical properties.  They are formulated in various ways — here is one set: (monotonicity) If the value of portfolio X is always bigger than the value of portfolio Y, then the risk of X is less than or equal to the risk of Y. (cash invariance) The risk of the portfolio that is X without some amount of cash is...