How has the distribution of correlations changed over the last several years? Previously Posts about correlation boxplots explained Data Daily returns of 443 large cap US stocks from 2004 through 2012 were used. The sample correlations — almost 98,000 of them — during each year were created. If we were actually using the correlations, then … Continue reading
Portfolio Probing
US market portrait 2013 week 13
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 market portrait 2013 week 12
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
Variability of garch predictions
How variable are garch predictions? Previously There have been several posts on garch, in particular: A practical introduction to garch modeling The components garch model in the rugarch package Both of these posts speak about the two common prediction targets: prediction (of volatility) at the individual times (usually days) term structure prediction — the average … Continue reading
US market portrait 2013 week 11
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
Upcoming events
Highlighted LondonR is soon — see the “Previously Announced” section. New Events Thirsty Quants 2013 March 21, London. Some thirsty quants will be going for a drink on the 21st of March as of 18.30 at the Lamb Tavern in Leadenhall Market. http://www.lambtavernleadenhall.com/ Rethinking the Economics of Pensions 2013 March 21 & 22 in London. … Continue reading
Posted in Events, R language
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US market portrait 2013 week 10
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
Predicted correlations and portfolio optimization
What effect do predicted correlations have when optimizing trades? Background A concern about optimization that is not one of “The top 7 portfolio optimization problems” is that correlations spike during a crisis which is when you most want optimization to work. This post looks at a small piece of that question. It wonders if increasing predicted … Continue reading
US market portrait 2013 week 9
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
Portfolio tests of predicted returns
Exploring the quality of predictions using random portfolios and optimization. Previously “Simple tests of predicted returns” showed a few ways to look at expected returns at the asset level. Here we move to the portfolio level. The previous post focused on correlation. Win Vector Blog points out that gauging prediction quality using correlation can be … Continue reading
Posted in Quant finance, R language, Random portfolios
Tagged alpha generation, MACD, S&P 500
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