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From |
Richard Herron <[email protected]> |

To |
[email protected] |

Subject |
Re: st: Implementing a Momentum Investment Strategy with Stata |

Date |
Sun, 4 Mar 2012 17:40:42 -0500 |

I don't think there's a need to use -rolling-. I think there are two main steps here. Generating the portfolios, then generating the time series of returns for eash of these portfolios. I would generate the portfolios using -xtile- from the -egemore- package (SSC). generate ret6 = s6.price / l6.price egen portfolio = xtile(ret6), nquantiles(10) by(date_ym) where -ret6- is your holding period return and -date_ym- is the year-month date (say 2001m5). Now generate the portfolio holding period returns using collapse and time series operators. collapse (mean) f6.ret6, by(date_ym portfolio) You may also want to use weightings to determine portfolio weights (although I think Jegadeesh and Titman is all equally weighted). Now you can use these portfolios to generate returns to your strategy. HTH. On Sun, Mar 4, 2012 at 09:20, Robson Glasscock <[email protected]> wrote: > Christopher Baum's "An Introduction to Stata Programming" discusses > moving-windows in Chapter 8. The -rolling- command is mentioned as > well as Cox and Baum's -mvsumm- and -mvcorr- programs (available from > SSC). Looking into these may help you think about a modified approach > to your problem. > > Instead of using matrices, I wonder if it would be better to generate > two new variables that would help you identify the top 10% of firms in > each window. First, generate a "window" variable that would take on a > value of 1 for months 1-6, 2 for months 2-7, 3 for months 3-8, etc. > Second, generate an "identifier" variable that tags the top 10% of > firms in each window. You would know exactly which firms were included > in each window and then it would be possible for you to calculate the > returns for those firms over the next six months. Or maybe clever use > of -rolling- is the better approach here. I'm not sure, but I hope > this is enough to get you started. > > best, > Robson Glasscock > > > On Sun, Mar 4, 2012 at 7:43 AM, <[email protected]> wrote: >> Dear all, >> >> I am trying to implement a Momentum Strategy following Jegadeesh/Titman(1993): Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency, JoF 48(1), pp. 65-91. >> >> I have monthly returns for ~1400 stocks for a total of 385 time periods and now have to proceed in the following way: >> >> 1) build cumulated returns over a formation period of 6months (I did that by generating new variables) >> >> 2) select the top 10% performing stocks in order to invest. This is done every month in order to generate so-called "overlapping" portfolios. >> >> 3) invest in those stocks for a holding period of 6 months >> >> 4) determine the average of the returns and adjust for risk >> >> >> For now, my approach was to generate matrices for every month t that consist of the cumulated returns over the previous 6 months. >> However I can not find an efficient way to sort these matrices while being able to identify which assets to invest in (this is crucial as I need to tell Stata somehow which assets to invest in). >> >> I am sure there is a better way to sort the cumulated returns of the previous 6 months in every month t while still being able to somehow "track" the variable name in order to invest in the corresponding stock. >> I hope I made myself clear, any help would be greatly appreciated! >> >> Best, >> Daniel >> -- >> NEU: FreePhone 3-fach-Flat mit kostenlosem Smartphone! >> Jetzt informieren: http://mobile.1und1.de/?ac=OM.PW.PW003K20328T7073a >> * >> * For searches and help try: >> * http://www.stata.com/help.cgi?search >> * http://www.stata.com/support/statalist/faq >> * http://www.ats.ucla.edu/stat/stata/ > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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