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Carlos Salas is Fund Manager/ Sr. Equity Analyst with sector generalist experience to generate long/short ideas using Fundamental, Event Driven and Macro investment styles in global equities. He also is deeply involved with the CFA Institute UK educational initiative as co-chair of the CFA... More
  • Asia Pacific Equity Markets: Country Allocation Using "Hot Money" Data 0 comments
    Dec 5, 2013 1:10 AM

    In order to decide a sensible country allocation for our Asia Pacific Equity portfolio looking forward 2014, we decided to create a scoring model that will enable us to determine an appropriate range of country weights based on several factors. In this way, we thought that inflows could be an interesting factor to consider due to the Emerging Markets bias inherent in the region.

    High correlation between Emerging Asian countries

    We started by considering broad indices annual returns of each country as well as annual inflows/outflows over a period of 9 years (2004-2012). We obtained several interesting insights by looking at the correlation matrix below:

    Correlation Matrix: Flows (Green) / Equity Market Returns (NASDAQ:BLUE)

    (click to enlarge)

    1. Asia flow and stock returns interplay is clearly different between Emerging and Developed Asia-Pacific countries like Singapore, Japan or Australia.
    2. As expected, Emerging Asian countries are highly correlated with each other's both in terms of inflows and indices returns. Thailand is the country that exhibits the highest dependency to its Asian emerging peers in terms of flows (0.94) but lower though still significant with regards stock returns (0.81)
    3. Japan does not seem to be much correlated to the other Emerging Asian countries either in terms of flows (0.26) or returns (0.6). Nonetheless, Japan's correlation with Developed Asian countries is much higher in terms of flows and returns: 0.93 and 0.78 respectively.

    In spite of more developed stock markets in Emerging countries, some like Indonesia, Malaysia, Philippines or Thailand represent less than 1% each of total worldwide AuM. China remains more immune to inflows due to several foreign investor restrictions on A-Shares trading but things will change very quickly within the next five years as the country capital markets embrace a higher degree of openness.

    Are Inflows a good predictor of market returns in Asia Pacific?

    We conduct further analysis on country indices returns against equity capital flows. We found out that the probability of obtaining an inflow and positive return on the same year is higher in Asia than in the rest of the world: the average probability for Asian countries is around 85.9% whereas it is only of 71.1% in Europe and 33% in USA.

    High Probability at seeing positive inflows and returns at once

    (click to enlarge)

    We also considered the probability of obtaining an inflow the year following a positive return and the probability of obtaining a positive return the year following an inflow. We reached the same conclusion: Asian indices returns are more dependent on inflows than rest of the world indices. On the other hand, we haven't witnessed a clear pattern between flows and forward returns, meaning price momentum in the region does not attract inflows when considering a one year lag.

    Flows tracking returns probability has been substantially lower

    (click to enlarge)

    Inflows loose significance when considering a 1 year time lag

    (click to enlarge)

    To go further into in our analysis, we performed the following regression:

    rt = α + β rt-1+ γFt+ δFt-1+ ε

    where rt is the index return on year t and Ft is the country inflow on year t. This model gave us very good results with high R2 proving once again that inflows drive market returns in Asia. China set aside, the model explains more than 70% of the indices returns variations.

    R^2 coefficients are quite significant explaining returns

    (click to enlarge)

    Of course, we have a small size bias in our sample (annual frequency observations from 2004 to 2012) so it would be interesting to run our model using quarterly or monthly data. Expanding the time span will deliver flawed results since the majority of the countries have changed structurally over the last five or ten years, for which reason we consider a more frequent data should avoid spurious results.

    Conclusions: A Flow Scoring Factor add value to risk management and portfolio construction

    As seen in our analysis, our first intuition that inflows drive market returns in Asia is confirmed. Hence, a scoring model where countries are ranked using probability-weighted YTD equity capital flows is to be an interesting tool for us. Therefore, YTD Net Inflow percentage over each country AuM and the a priori probability that each local stock market reacts to those capital inflows or outflows are to be key inputs in the construction of this country allocation factor.

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