build and implement smart beta strategies with matlab
smart beta is an investment strategy that combines passive and active management. an investor passively follows indices, while actively incorporating other factors that exploit inefficiencies in the market. smart beta are systematic investment strategies that aim to deliver higher return, lower risk, or more diversified performance in comparison to benchmark indices.
in equity investing, widely used factors in smart beta strategies are value, momentum, size, quality, and volatility. this approach can also be implemented in fixed income, commodity, and other asset classes.
developing smart beta strategies requires both mathematical modeling and statistical analysis. matlab® provides both. it supports popular techniques for efficiently developing, back-testing, and implementing these strategies:
- building, testing, and implementing an optimal portfolio
- news sentiment momentum analysis
- technical analysis using momentum indicators, oscillators, and charts
- trading cost analysis and market impact modeling
- analysis of financial time series to generate trading signals
- automated trading order workflow management
for more on tools, see financial toolbox™, optimization toolbox™, and datafeed toolbox™.
examples and how to
software reference
see also: portfolio optimization, black-litterman, momentum trading