Many daytraders use the Bollinger Bands Indicator. The investors with a long-term horizon, such as pension funds, select and monitor investments based on an analysis of the outlook for the macro-economic environment, the sectors in which companies operate, and their core values. Given the high volatility in stock markets, the timing with which buying and selling transactions are carried out is essential. Market values ​ ​ do not always reflect all publicly available information, as assumed by the condition of information efficiency to a semi-strong extent, formulated by an authoritative doctrine. A significant phenomenon that characterizes financial markets is the mean reversion, that is, the fact that market prices undergo more or less large fluctuations, not always justified by news coming to the market, which is offset by trends of opposite sign, in the short or medium term. In this work, it is intended to verify the opportunity for these investors to combine

fundamental analysis and technical analysis of the stock exchange. The first would be long-term choices, while the technical analysis, in this case, the use of the Bollinger Bands Indicator, could be used for the selection of investment and exit times for some financial assets that make up their portfolio.     The purpose of our research is to test a technical analysis algorithm based on the use of the Bollinger Bands Indicator, about the performance of the MSCI Emerging Markets Index. The considerations that will follow from this analysis have no absolute validity and, therefore, no claim to generalize a phenomenon related to a specific context, both geographic and temporal.

Bollinger Bands Indicator


The mean reversion

The finding, documented by numerous empirical analyses that equity prices tend to return, after more or less large fluctuations, around their average value, may encourage purchases by long-term investors when the price is significantly lower than their average. The same applies to exit transactions, at least temporarily, carried out when market prices rise considerably, leading them to values that differ significantly from the average of previous periods. This discourse presupposes the validity, attributed by the investor, of the long-term prospects of the asset under consideration. The phenomenon in question could arise from multiple causes. The hypothesis of semi-strong information efficiency of financial markets, according to which quotations incorporate all publicly available information, could be questioned by the mean reversion. The overreaction, i.e., the finding that financial markets would tend to amplify the effects of information coming to the market unless they were subsequently corrected, has long been empirically demonstrated. The authors point out that, in many cases, securities that have shown high yields in a given period tend to reduce them in subsequent periods or to obtain negative returns. The same applies in the opposite direction. More recent studies on emerging markets have substantially confirmed this phenomenon. Explanations could also be found for behavioral finance and different perceptions of risk by many investors at various stages of the equity market cycle. The phenomenon of overconfidence implies that in a bullish market, the gains made by investors are often attributed to their ability to make weighted choices. This means, in subsequent periods, a higher risk appetite, also because these entities operate, at least in part, with capital gains realized on the market. They are therefore prepared to bear a higher level of potential losses, since, should they occur, they would be compensated by gains made in previous periods. In the downturn of the market, the downward trend in prices could, at least in part, be amplified by fears of excessive losses and, consequently, lead many investors to sell the securities held.

In some cases, panic selling may occur. In other circumstances, speculative bubbles are created as a result of exceeding expectations on the part of many investors about the possibilities of growth and increased profitability of companies operating in specific sectors. When these expectations are more realistically reduced, prices retrace from previously recorded market peaks. In a previous paper, I examined this phenomenon concerning speculated bubbles

should be formed at the end of the 1990s, about companies operating in the innovative sectors of the economy, and significantly reduced in 2001. All this evidence leads to temporary misalignments with the fundamental values of companies. More recent analyses related to this phenomenon have examined the mean reversion in the equity markets of the leading advanced economy countries, concerning a long time interval, ranging from 1900 to 2009. Research shows a high intensity of research in periods of a high level of economic uncertainty. Its power was higher as a result of financial shocks, such as the stock market collapse in 1987, with very high losses concentrated in a few trading days. At a time when uncertainty about the outlook for the economy is relatively low, this is less pronounced. The mean reversion and the possibility of using it to create profitable trading strategies have been analyzed in several studies.

bollinger Bands strategy setup

Bollinger Bands Indicator

The Bollinger Bands Indicator is a technical analysis tool designed in the early 1980s by John Bollinger and widely used by traders, along with other indicators, especially for short-term trading, also in intraday transactions. The underlying idea is attributable to the mean reversion, taking into account some corrections suggested by the same creator, developed by professional traders or proposed by finance researchers. They apply not only to equity markets but also to all those assets that are traded on regulated markets and have a high level of liquidity, such as the foreign exchange and commodities market. Among other things, it is widely used in the analysis of futures markets, characterized by high liquidity and meager trading fees compared to the value of the assets underlying the contracts. Curves are constructed that can give operational signals of technical analysis. A central curve, called the Middle Band, is represented by a moving average of prices that, according to the formulation of its creator, covers 20 periods. The duration of these periods varies depending on the trader’s time horizon. In the case of intraday trading, a few minutes are used. Around the central band, we have the construction of an upper band – Upper Band and a lower band – Lower Band. Bandwidth is affected by the level of market volatility, as measured by the Standard Deviation. In the original formulation, today predominantly applied in operational practice; the upper and lower bands have a distance from the Middle Band equal to twice the Standard Deviation.  Middle Band = MA20 Upper Band = MA20 +2σ Lower Band = MA20 – 2σ From the above, it is clear that the bandwidth increases in periods of high market volatility and decreases in the market phases characterized by a low level of volatility. There are numerous applications for trading transactions with BBs. The Author considers that price leakage from the bands does not necessarily signal a reversal of the trend. In many cases, in the presence of strongly directional market trends, the leakage of the price graph from the Lower Band or Upper Band constitutes a signal of the strength of the current trend and, therefore, a possibility of continuation of the same. There are, in this regard, trading systems called breakout systems, which open positions to the breaking of bands and, at certain market stages, manage to be profitable.     Many traders, to have signals of reversal of the trend, wait for prices to return to the bands after overtaking. Also, other technical analysis indicators not related to BBs must give concordant operational signals. For example, to open up a bullish position, prices, once they have escaped from the Lower Band, must be included. This circumstance must be confirmed by other technical analysis indicators, such as the RSI (Relative Strength Index), whose value passes from the oversold area to the neutral zone. Further confirmation should come from trading volumes, which, at this stage, should increase compared to their average values. This latter circumstance would indicate that there are “strong hands” on the market that are buying the securities, considering their market price to be convenient.     Another trading strategy could involve purchasing the asset when its price is below the Lower Band and exiting when it exceeds the Upper Band. In some situations of

the market, when price mean reversion occurs, the Bands could act as dynamic levels of support and resilience of prices.    In doctrine, analyzing the period 2004-2009, through interviews with currency traders, it was found that BBs are the most widely used instrument of technical analysis of the foreign exchange market. Other authors have empirically found, through a study conducted on major international equity markets, that the profitability of BB-based trading strategies would have been high if verified against historical data before 1983, the year of its disclosure and dissemination to investors. On the contrary, by carrying out empirical analyses after that date, the profitability of this strategy has gradually decreased. Researchers believe that this is a consequence of the application of this large-scale trading technique, which would have led to a reduction in its ability to produce excess returns compared to market returns. Another paper examines BB’s profitability in major US equity markets over the period 1995-2004. Researchers conclude that to obtain extra-efficiencies compared to benchmarks, it is necessary to combine the use of this tool with other indicators of technical analysis, as suggested by J. Bollinger himself. Other authors, based on a review of the leading US equity indices between 1990 and 2007, noted that the use of bands leads to underperformance of the market. As can be deduced from the above considerations, the evidence of empirical research is conflicting.

It depends on the other technical analysis indicators used as filters for operational signals deriving from the application of bands, as well as the type of financial instrument to which the strategy is applied.


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