|
PureBytes Links
Trading Reference Links
|
The following from "Financial Markets Tick By Tick" page 248 suggests an
answer to the confusion surrounding Gaussian Vs non-Gaussian analysis in
backtesting:
"... this means that investors with horizons of one month or longer face
Gaussian risks and that conventional risk management and asset pricing is
applicable. On the other hand, investors at shorter horizons will face
non-Gaussian fat-tailed distribution and must therefore use high-frequency
data {defined as 30 minute bars} and non-Gaussian probability tools (e.g.,
fat-tail estimators, rare event analysis) to quantify their risks. ..."
As the time periods become longer for the data {i.e., end of day, weekly,
monthly} TLF processes converge Non-Gaussian distributions to Gaussian
distributions {i.e., from fat tails to higher peaked central distributions}.
"... These conclusions agree with conventional wisdom and practice ... and
suggest that high-frequency data analysis is of little value {in system
testing} to long-term investors. ..."
They go on to describe the clear seasonality that exists within the
different trading time periods.
Therefore, the analysis and the seasonality and the trading rules are time
period specific to the individual trader. You can pick your time frame and
use the appropriate analysis without being confused by the requirements of
other time periods.
Best regards
Walter
|