No. of Recommendations: 21
Several posters have mentioned the difficulty of getting better volatility estimates for annual screens. I thought it would be interesting to use the 1986-1998 daily data provided by Peter Kuperman in June to calculate annualized GSD. Then compare it to GSD measures from other methods.

Recall that Peter's foundation uses the following screens:

Key100 1-4, annual
Spark 1-5, annual
PEG 1-4, semiannual
RSO 1-4, monthly
PEGO 1-4, monthly (overlapped from all 10 stocks from each PEG13 and PEGRSW)

Peter announced the availability of daily data for these screens in post #72493:

Key100 Spark PEG RSO PEGO Blend
Using 36 33 36 30 47 38 53 39 63 37 49 28
Daily Data

Backtester 37 19 37 30 48 26 53 24 65 29 50 17
Jan Start

Backtester 36 27 29 n/a n/a 23
GSD Avg All

Backtester 40 37 n/a
GSD(M) for
Monthly Screens


o The Backtester Jan start GSDs are generally much lower than the GSD(D) (the daily analog of GSD(M); GSD calculated from daily data).

o The GSD(M)'s are very close to the daily GSDs for the monthly screens.

o The Backtester GSDs averaged across all start months appears to improve on a single-start-month estimate, but is not necessarily close to the daily GSD (see PEG).

o There are some small differences in CAGR between the backtester and Peter's daily data. This was addressed earlier and is due to Friday purchases/sales (and closing prices) in Peter's daily data and Monday purchases/sales in the backtester.

The backtester link for the blended screen is:

I recognize that the volatility experienced in a portfolio's return over many years (much more than 14) based on annual returns may be less than that indicated by the daily-data GSD. Emintz and others have suggested that there may be some level of autocorrelation that smooths out that daily volatility when measured annually, which may be especially true as you blend different screens and have more stocks. However, I think the daily-data GSD may give a better indication of the mid-year "nerve wrackiness" of a screen as we check our portfolios daily.

Thanks again to Peter for the initial daily data. We look forward to the future batch of daily data for a broader set of screens.


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