## replace_date('31 December 2014');

### About time, leverage and a few grains of salt (Synthetic Prices Part II)

Just in time to be vintage 2014 I finally managed to write a long overdue blog post. Nevertheless thanks to a loyal crowd of readers this year has seen two, actually three, landmarks in the pageview stats. Once beyond the 100k milestone, the 200k mark was surpassed quite fast. A couple of weeks ago the near silent touch of a fabulous 250k followed: one quarter of a million pageviews! Wow! And right now at the cusp of 2015 the counter is steadily turning its way towards 300k. Thank you for all your interest, the rewarding exchange of ideas and your support during this remarkable year.

Regarding today's posting, it is a sequel to the Composing Synthetic Prices For Extended Historical ETF Data post back in May. Using "R", the language for statistical computing and graphics (get it here), thanks to Michael Kapler's excellent Systematic Investor Toolbox for R: SIT, it is possible to compose synthetic ETF's with extended historical data retrieved from suitable mutual funds on full auto while taking care of a seamless fit along the way.

In this post, I will demonstrate how to perform the same task in AmiBroker with two extra benefits: the application of leverage and the option for inverse data treatment. Of course, an R-savvy coder could probably achieve the same in R, but not me.

The below example shows $TLT as synthetic symbol with data going back to 1986*. The$ETF is based on the price data for TLT (green section) available from Yahoo and extended with VUSTX data (red section) from the same source.