Using Technical Analysis To Time Mutual Fund Buying

Mutual fund investments are assessed globally based on the fundamentals of the underlying and the suitability of the fund for an investor's risk-return profile. Some of the professional organisations around the world use five ‘P's, namely People, Process, Parent, Performance and Price, to select the right kind of mutual fund for investing. The reason these firms employ such methodology is because mutual fund investments are meant for the long term and these fundamental parameters help in assessing the fund's performance over the long run. There is also another method of analysing financial time series, which is, technical analysis. This analysis is based on the principle that history repeats itself and past prices along with few other related constituents and statistics can help you to forecast future prices of the financial instruments.

Technical analysis, though used extensively in analysing individual stock prices, is sparingly used in selecting and investing in a mutual fund. The main reason being, a mutual fund is not a single stock but a portfolio of stocks, with the added caveat of fund manager's exclusive discretion on which stocks to include or exclude in the portfolio. This means that many participants required for a proper price discovery are missing in the case of mutual fund investment. Moreover, most of the technical analyst use open, high, low and close (OHLC) data to analyse various price patterns. In the case of mutual fund, however, you only have a single data of net asset value (NAV) of the fund, that too received at the end of the day (EOD).

Nevertheless, these two shortcomings can be overcome. In the case of lesser number of participants, although these are missing in determining the mutual fund NAV, these are available while determining the price of their underlying, based on which the NAV is computed.

For the second shortcoming, although on an intraday basis, a single data is available for mutual funds, it will only deter short term traders and not the long-term investors, who always check long term data to analyse any investments. Hence, daily EOD data can be used to create either weekly, monthly or quarterly OHLC data. This can be now used to do technical analysis of the mutual fund schemes.

To understand whether we can use the NAVs of MF schemes to time the entry into a fund, we used four different funds from different houses and with different asset allocations. We applied the most common technical analysis to understand how it works in the case of MFs. The results were not so different from the common patterns that are visible while using technical analysis on any stock price. The same patterns were evident with NAVs of these funds.

For example (Check Figure-1), we plotted the fund's weekly NAV for the last three and half years. The figure is clearly depicting the classic pattern of inverse Head & Shoulders pattern breakout at Rs 500. Currently, the fund witnessed profit-booking at higher levels after hitting the inverse Head & Shoulders pattern target. Now the fund is trading at the lower Bollinger band support, which means it is trading in the support zone of Rs 585-600. In case the support is broken on the downside, Rs 500-510 will act as the next support.

Otherwise, the fund can witness a reversal from the current levels, up to the levels of Rs 630-640 in the first place.

In the case of second fund, it is currently consolidating at peak levels and can see some more downside, but the view remains bullish for now.

Nevertheless, there are some caveats regarding the use of mutual fund NAVs for doing technical analysis. There are various variants of NAVs available for a particular scheme, such as direct, regular, growth, dividend, dividend re-investment, etc. We would suggest use of growth NAVs to make a proper chart and do analysis. The reason being that the dividend options may not give out the correct picture due to frequent dividend pay-outs impacting the NAVs.

The above examples clearly show that technical analysis can also be applied to mutual fund investments. Although the data are not readily available for normal mutual funds in a given format (these are available for ETFs), you can get it from the websites of AMFI or respective mutual funds. Once you get the data, you can process and use it for technical analysis.

HDFC Equity Fund: The Fund plunged sharply from January 2018 and has formed Head & Shoulder like pattern on the weekly timeframe. Currently, the Fund is trailing at its multiple support zone, i.e., the neckline level at around 575-585 level, and if broken can give sharp downside. Oscillators and indicators have still not cued any reversal from the aforesaid support zone. 

HDFC Mid-Cap Opportunities Fund: The Fund has witnessed multiple point upward sloping trendline breakdown, which can be also termed as a kind of Head & Shoulders pattern breakdown at around 57 levels. The Fund also hit below its Lower Bollinger Band at around 54.20 levels. Further, MACD has turned down below 0 at -0.4 and has crossed below the Signal line at 0.2. With the said cues, we may see some more downside in the upcoming sessions, if it breaches the recent low. 

ICICI Prudential Balanced Advantage Fund: The Fund hit Double top at the start of January 2018 and thereby corrected up to 33.50-33.80 levels which were its Lower Bollinger Band support zone. Thereby, the fund bounced back near to its top; but is seen consolidating now near to the Middle Bollinger Band area. We may see some more consolidation in the near future; unless 33-32.80 is broken on the downside or 33.90 is broken on the upside. 

ICICI Prudential Bluechip Fund: The Fund hit a Shooting Star like pattern on the weekly timeframe during the start of January 2018 after which it tumbled badly. The stock bounced back from Lower Bollinger Band but has resisted near 50% retracement of the prior downward rally from near 44 to 38 level. The fund has inclined southwards and can give some more correction below 39-38.50.data can be used to create either weekly, monthly or quarterly OHLC data. This can be now used to do technical analysis of the mutual fund schemes. 

To understand whether we can use the NAVs of MF schemes to time the entry into a fund, we used four different funds from different houses and with different asset allocations. We applied the most common technical analysis to understand how it works in the case of MFs. The results were not so different from the common patterns that are visible while using technical analysis on any stock price. The same patterns were evident with NAVs of these funds. 

For example (Check Figure-1), we plotted the fund’s weekly NAV for the last three and half years. The figure is clearly depicting the classic pattern of inverse Head & Shoulders pattern breakout at Rs 500. Currently, the fund witnessed profit-booking at higher levels after hitting the inverse Head & Shoulders pattern target. Now the fund is trading at the lower Bollinger band support, which means it is trading in the support zone of Rs 585-600. In case the support is broken on the downside, Rs 500-510 will act as the next support. Otherwise, the fund can witness a reversal from the current levels, up to the levels of Rs 630-640 in the first place. 

In the case of second fund, it is currently consolidating at peak levels and can see some more downside, but the view remains bullish for now. 

Nevertheless, there are some caveats regarding the use of mutual fund NAVs for doing technical analysis. There are various variants of NAVs available for a particular scheme, such as direct, regular, growth, dividend, dividend re-investment, etc. We would suggest use of growth NAVs to make a proper chart and do analysis. The reason being that the dividend options may not give out the correct picture due to frequent dividend pay-outs impacting the NAVs. 

The above examples clearly show that technical analysis can also be applied to mutual fund investments. Although the data are not readily available for normal mutual funds in a given format (these are available for ETFs), you can get it from the websites of AMFI or respective mutual funds. Once you get the data, you can process and use it for technical analysis.

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