SmartBeta strategy, in fact, also known as factor-based indexing, is an investment process that uses a multi-factor quantitative model to adjust the portfolio coefficient, which realizes the automation of the investment process.
From a certain point of view, Smart Beta mimics the investment strategy of an actively managed** manager, by adjusting the weights of different assets in the portfolio, emphasizing the role of factors such as size, value, momentum, volatility, etc., the Smart Beta strategy aims to "beat the market" on a consistent basis. Therefore, from this perspective, the smart beta strategy is more like an alpha strategy, which does not track a certain index exactly, but selects or adjusts the weight of a certain index.
Essentially, Smart Beta is a strategy for index investing, and according to the CAPM model, Beta measures the size of a portfolio's risk and its returns. Compared with the traditional market capitalization-weighted index strategy, Smart Beta is more active in the management of the index, through a systematic approach, combined with active management, the index component stock selection and weighting are optimized to obtain excess returns that beat the market, but compared with the traditional active management, Smart Beta has obvious advantages of indexed investment, such as regularization, transparency, low cost and high efficiency.
Therefore, smart beta can be seen as an investment between active and passive, between alpha and beta, with the goal of achieving alpha returns that are higher than traditional market capitalization-weighted indices.
The Smart Beta Index can be classified in two dimensions: sampling and weighting.
First of all, in terms of sample selection, a single factor index or a multi-factor index that can significantly and effectively distinguish market characteristics is used as the basis for stock selection, and the resulting portfolio can provide investors with tools to expose the risks of specific market factors, and obtain the excess return of the factor accordingly, such as value indicators, growth indicators, dividend indicators, mixed financial indicators, etc.
For example, the CSI 300 portfolio constructed in the A** field with equal weights performs better than the real CSI 300 Index, and a very important reason is that the scale factor effect of the A** field is particularly obvious, and in the long run, small-cap stocks have obvious excess returns compared with ** stocks.
In this way, our understanding of the portfolio can rise to the factor level, and we can choose a specific ** to make the portfolio focus on a specific risk factor, which is another way of thinking for smart beta.
The second point is in terms of weighting, under normal circumstances, market indices are weighted according to market capitalization to construct a portfolio, such as the CSI 300 Index, first select 300 constituent stocks according to certain conditions, and then determine their respective weights mainly according to the total market value of the 300 constituent stocks, and the corresponding weights of large total market capitalization are also high.
SmartBeta breaks this limitation by still based on these 300 constituent stocks, but the weighting of the constituent stocks is determined by other methods, in order to achieve a portfolio that is "smarter" than the traditional CSI 300 index. Common weight optimization methods include: fundamental weighting, equal weight weighting, risk parity weighting, minimum variance weighting, and maximum diversity weighting.