Mathematical
Modeling
Formulation
of appropriate mathematical models to model the returns
process of the strategy under consideration.
Portfolio
Analysis
Development
of sample portfolios and analysis of portfolio
performance using standard risk-return measures and
linear predictive models (CAPM) within- and
out-of-sample.
Returns
Process Analysis
Distribution
tests of the return process and comparison with
S&P500 index process return distribution, including
comparative tests for randomness, Normality and higher
distribution moments.
Non-Linear
Modeling
Analysis
of the returns process using linear time series
and non-linear dynamical models to determine the
nature of short and long-term memory effects.
Volatility
Process Analysis
Analysis
of the volatility process to determine the degree of
randomness in the return series and the nature of any
departure from strict white noise, which may indicate
the presence of deterministic factors.
Multivariate
Analysis
Multivariate
analysis of portfolio composition using clustering and
other pattern recognition techniques to examine the
nature of the selection process.
Contingent
Claims Models
Modeling
of the returns process using non-linear
contingent-claims models, if appropriate.
