The inclusion of China’s A shares into global equity indices is stoking offshore asset owners’ interest in the market. Representing of almost 4,000 China-based firms that trade their shares on the Shanghai Stock Exchange (SSE) and the Shenzhen Stock Exchange (SZSE), A shares offer foreign investors a deep universe to explore. The asset class’s lower correlation with other major developed and emerging markets may also bring diversification benefits to portfolios.
At Invesco, we are convinced that Chinese equity markets will become more efficient over time, and in the meantime present ample opportunities. This is because we expect the Chinese economy to continue its transition towards highquality growth. We also believe market structure will improve, ensuring that more efficient and appealing companies join and excel within the A share universe.
An analytical framework on A shares is crucial in how we view and think about the asset class, and the role it plays in portfolios. At Invesco, this framework, or capital market assumption, is the foundation for developing outcome-oriented, multi-asset allocations.
In this white paper we will discuss how we form our long-term capital market assumption for China A shares over a 10-year time horizon. This research mainly focuses on the China A large-cap market, with the CSI 300 index – consisting 300 large-cap stocks in the A share universe – as the proxy index.
Our China A share long-term capital market assumption is consistent with our research for other major assets: we employ a “building block” based methodology to estimate asset class returns for China A shares. Building blocks represent a “bottomup” approach in which the underlying drivers of asset class returns are used to form estimates, with estimated return being divided into income and capital appreciation components.
Our extensive research on China A shares has prompted us to:
— estimate income component with level of yield;
— look to other sources as the basis of our model on capital appreciation, and;
— incorporate macroeconomic data from multiple inputs to calculate valuation change.