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.
How to draw Bollinger Bands
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
There are, therefore, three lines of reference:
- Upper Band = 20-day moving average + (DS × 2)
- The Central Average = is the moving average at 20 days
- The Lower Band = 20-day moving average – (DS × 2)
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.
Most of the quantitative indicators used by technical analysts to study the behavior of financial markets are based on the assumption that prices have a repetitive trend.
In particular, after a period of low volatility, when prices moved laterally, within a narrow trading range, there are frequent and sudden accelerations (breakouts).
In order to try to anticipate the beginning of a directional movement, it is necessary to identify those situations in which there has recently been a marked contraction in volatility.
One of the oscillators used for this purpose is the Bollinger Bands, the most important feature of which is to expand and shrink automatically as volatility changes.
In particular, the two bands have the ability to adapt automatically to the primary trend followed by prices, while the concept of standard deviation is used to measure volatility.
The standard deviation is calculated by summing the deviations from the mean, then elevated to the square.
This value is multiplied by two to exploit the static principle of Gaussian.
What is obtained is then added and subtracted from the value of the central moving average to obtain the value of the Upper Band and the Lower Band, respectively.
The Bollinger bands consist of a central moving average and two oscillation bands, which move according to the volatility on the market.
The indicator consists of three lines:
- A central moving average, usually calculated over 20 periods, following the primary trend expressed in prices.
- Two bands, one upper and the other lower, which expand and shrink automatically, depending on the volatility expressed by the market.
When the market moves sideways, volatility decreases and the two bands squeeze around prices.
When the market is within a directional phase, however, volatility increases and the two bands move away from prices.
How to use Bollinger Bands
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.
Trading with BBs
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.
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.
Bollinger Bands and Emerging Markets
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.
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.
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