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The academic interest in momentum investing has gained traction since 1990s with the like Jegadeesh and Titman (1993) and Asness (1994). A study by Asness et al. (2015) suggests that momentum investing generates better return anomalies as compared to the other investment styles like size or value styles. Moreover, the momentum’s effect appears in nearly all company sizes, industrial sectors, other asset classes and global markets. Having said that, the performance of momentum investing depends on the investment time horizon. For instance, many research papers of momentum investing omit the most recent month as there is existence of a reversal or contrarian effect in stock price returns. This can be due to the liquidity or microstructure problems. In general, trading based on a single stock momentum seems to be a less effective strategy over a short historical time horizon, particularly those with less than one month. In contrast, the momentum investing is extremely profitable at intermediate time horizons of up to 24 months. The stock returns performance is more pronounced for the period range of 6 to 12 months range. Nevertheless, the strategy will reverse at longer time horizons such as over 24 months (Asness, et al., 2015). Furthermore, Jegadeesh and Titman (1993) research largely get the credit for finding the momentum effect in academia studies. Their research indicated that simple relative strength index (RSI) methods that rank stocks based on their historical 3 to 12 months’ stock price returns will be able to predict relative performance over the next 3 to 12 months.

Study has revealed that momentum investing is exceptionally useful when comingled with a value style since both are negatively correlated. Grinblatt and Moskowitz (2004) discover that a value and momentum mixture alleviates the extreme negative stock price returns experienced by the value investors. For example, during the tech bubble of the late 1990s and early 2000 or subprime crisis in 2008 many investors experienced deteriorating performance. Study also suggests that momentum

investing can be a contributing element to value style. Asness (1997) discovers that although value stocks have been losing over longer-term period, they will out-perform by a wider margin over 6 to 12 months.

On the other hand, the potential explanation to these phenomena are the investors behaviour and the trending effect. Trailing the seminal research of Kahneman and Tversky (1979), there are two potential behavioural explanations. First, investors slow to respond to new information. They state that different investors receive news from different sources and react to news over different time horizons and in different ways, creating an anchoring and adjustment effect whereby in which individuals update their views only partially when faced with new information, slowly accepting its full significance. Second, asymmetric reactions to profitable and non-profitable investments. They explain that investors tend to sell winning investments prematurely to lock in gains and hold on to losing investments too long in the hope of breaking even. The disposition effect creates an artificial headwind such that when good news is announced, the price of an asset does not immediately rise to its true value because of premature selling or lack of buying.

Another interesting finding by Scowcroft and Sefton (2005) is that, for the big capitalisation stocks, the stock price momentum is predominantly influenced by the momentum of a stock’s wider industry sector classification and not by the momentum of the individual stock itself. As any other investment strategy, momentum investing does not deliver investment gains continuously. In the case of Hancock (2010), he discovered that the momentum investing deteriorated during periods of excessive stock market volatility and that the momentum investing had lower relative performance in the first six months after the stock market corrections during bullish and bearish stock market. He had made a point that a stock price volatility is not in favour for momentum investing, mainly because stock price volatility is related to inverse for average stock returns and not following the trend pattern. Referring to the Asness et al. (2015) and Jegadeesh and Titman (1993), profitability of the strategy is relative to the short time investment horizon. Hence, the transaction expenses of

momentum investing are greater than those of value and growth styles investing. However, the costs are not extremely high to make momentum investing unattractive to the investors (Israel & Moskowitz, 2010).

There are several ways for momentum investing to work. Many leading indicators like momentum investing derived from the momentum oscillators. It indicates signal or trend relationship between dataset. For instance, momentum investing measures the rate of change of stock’s prices or earnings or any other fundamental data. As these components change, the directions of stock prices will also change in tandemly. The bigger the rate of change in stock prices, the higher the quantum of momentum over the periods. As stock prices increase swiftly between periods, the greater the increase in the stock prices momentum. When the stock prices begin to reduce gradually, the momentum of stock price returns will also be slowing down. If the stock prices start to trade sideways, the momentum of stock process begins to decay from previous high levels. However, falling momentum because of flat trading is not necessarily means bearish signal. Instead, the stock prices signalling that momentum is heading to a closer median level. Momentum indicators use many formulae to compute the price or fundamental data changes. Commonly used oscillator like RSI, measures the differences of the average price or fundamental data change of the recent periods with the average change of the previous periods (Wilder, 1978). There are noticeably many advantages of using momentum indicators. Early signals for trade entry and exit are the primary advantages (Swinkels, 2004). Momentum indicators produce more signals and therefore, permit more opportunities to trade. Furthermore, the early signals can also indicate the level of strength or weakness for the price momentum.

The empirical results on the momentum investing are compelling. For instance, Geczy and Samonov (2016) have observed dataset of stocks for 212 years and concluded that momentum investing has a significant and robust historical performance record. With that research, it has independently qualified many of the empirical findings related to a momentum investing. As momentum investing

is very well studied previously, Geczy and Samonov (2016) consider that the momentum anomaly might be an effective investment strategy since the stock price returns related with momentum investing could be driven by natural investors behavioural bias.

Asness et al. (2015) said that the concept of momentum investing is compelling not just because investors are hungry for a diversification and new strategies but also for its durability in the real world. Relatively, few other strategies have survived the transition from research paper to real world portfolio management, the way momentum investing does. In the textbooks, minting profits looks easy because the standard asset pricing theory suffers from so called return anomalies where sources of excess returns above and beyond what is implied by the academic investment models. But exploiting these anomalies in actual portfolios is hard. Trading costs, taxes and other frictions take a toll. And many profitable return patterns that look solid in the financial laboratory have an annoying habit of disappearing when the crowd comes rushing in.