Momentum pitfalls, possible returns, auto correlation and mutual funds

strategy”. The profitability of price momentum is comparable with other well-known strategies, such as “value investing”. As an example, taking the average monthly return of the highest earnings-to-price portfolio is a value-oriented strategy. Fama and French (1992) did this for the period between 1963 and 1990, giving a 1.72% profit. These values are comparable, which yields the relevance of both strategies and exacerbates the importance of a trend following strategy.

Chan, Jegadeesh and Lakonishok (1996) state that earnings momentum strategies, which is selecting securities with a high six-month earnings surprise performance, generate slightly lower returns than the price momentum strategy. A number of further studies were aimed at the momentum profitability causes and reasons. At the same time, they showed that the momentum strategies, based on past performance, are still profitable. For example, Grinblatt and Han (2005) also found monthly 1% average returns for momentum strategy in the 1962-1996 period, which is consistent with the findings from Jegadeesh and Titman (1993).

All the following information regarding the momentum strategies fully proves the profitability of equity momentum strategies and return autocorrelation in the US market. This profitability is documented for a long period, from the 1960s to the present. Momentum profitability is also documented in Norway for the 1978-1995 period by Rouwenhorst (1998).

Asness et al. (2013) found stock persistence (hence, momentum) for the world’s largest equity markets, in Europe, the UK, Japan and the United States. They also document momentum profitability in Norway from 1978 to the present. According to this evidence, the

trend-following strategy works on almost all of the mature markets. Moreover, the evidence indicates a profitability of momentum strategies for more than 20 years after its fundamental discovery. However, the trend-following pattern does still not have a perfect explanation, which is probably why it is still profitable.

One possible consequence of this fact is autocorrelation returns patterns. Bondt and Thaler (1985, 1987), Jegadeesh (1990) and Lehman (1990) have evidence of stock returns’

persistence and reversals. This evidence forces us to check for such patterns in the mutual funds industry.

Let us imagine a perfect portfolio with perfect information. Such a portfolio will not include securities with negative expected returns. If needed for diversification, a security can be sold and a new one with similar covariance and positive return could be acquired. Such a portfolio is probably impossible to find. However, in the modern financial market, the nearest assets to such bizarre portfolios are probably mutual funds and hedge funds. The capital market single-securities do not perform any diversification or strategy. At the same time, the investment fund shares are portfolios with a certain strategies and certain risk decreasing. The luck or skill question concerns whether mutual funds share characteristics. Following, we see three alternatives. Mutual funds characteristics can be similar to marketable single securities, as in position 1, Figure 6. Some of the mutual funds can also outperform the market by management or economy of scale, as in position 2. Alternatively, mutual funds could be very different in their characteristics compared to securities, as in position 3.

Figure 7 - Mutual funds shares characteristics

Return autocorrelations naturally deals with momentum strategies. There are two features of the momentum strategy that are important, seasonality and business cycle. This is simply because an exclusion of certain strategy conditions might destroy the sample performance, for example, as with momentum profits after 2008, as Wang and Xu (2015) mention. It was the financial crisis and a certain down economy state. This example highlighted a third important feature of momentum profits, which is market volatility. Wang and Xu (2015) posit a connection between the business cycle and market volatility, yielding high momentum profits in “down” states of the economy, and vice versa. Moreover, interpreting the mutual funds returns without these important links might lead not only to bias, but also to fundamental inference mistakes.

Seasonality of a trend-following strategy is related to higher momentum profits in certain periods. Instinctively, it is low or even negative profits in January. Abnormally high December profits and low January profits can be attributed to the January effect. Others can inhere to a momentum pattern. There is strong evidence of the January effect in the modern capital markets. Evidence of the December/January drifts for high momentum portfolios was documented by Sias (2007). However, Jegadeesh and Titman (1993) claimed analogical figures, adding April and November high profits. Sias (2007) also documents outstanding June and November profits, but not as high as Jegadeesh and Titman (1993) proved. Sias (2007) finds consistency with the hypothesis that mutual funds window-dress (impress investors) close to the last quarter’s end. Hence, the trend-following strategy is not only a subject of the January effect, but also possible patterns of window-dressing and November/April outstanding payoffs.

Momentum payoffs are positive in up-market conditions, as Cooper et al. (2004) mention.

Some other papers found trend-following payoffs in connection with business cycle, as mention by Bodie et al. (2011: 370-383). Therefore, analyzing a mutual fund’s prices or even a stock’s business cycle must be considered, especially around the year 2008. The effect of the market volatility discovered by Wang and Xu (2015) is a very strong link to the momentum strategies profitability. Hence, the market volatility pattern may also be considered, having a deeper and wider understanding. As one of the methods, periods of high market volatility can removed from the sample. Nevertheless, it can be possible to use market volatility as an explanatory variable.