October 12, 2023

**Dozens of studies and millions of backtests clearly and unequivocally show that most technical analysis indicators simply do not work (meaning they cannot beat the ****benchmark****). However, there are a few exceptions.**

The popularity of technical analysis among individual investors stems not from its effectiveness, but from its easy accessibility.

Every broker provides the ability to draw colorful lines on stock price charts, and the interpretation of individual lines is perhaps the best-described field of “finance” on the internet.

To learn the principles of technical analysis, you don’t really need any knowledge or experience. You don’t even need to know English or the basics of economics. You don’t need to read boring financial statements or know the difference between EBITDA and EPS.

Thanks to technical analysis, the entry barrier to the world of investment has been set very low. A few strokes of the cursor on the chart are enough to know what to buy and what to sell, right?

Well, not really, because the stock market is more than just geometry.

Despite the above reservations, technical analysis can be useful, provided that we use it for what it was created for, which is… to determine a good entry point to the market.

The role of fundamental analysis, therefore, is to answer the question of what is worth buying, and the role of technical analysis - when to buy it. In this respect, looking at the behavior of the stock price can indeed be helpful. **The problem, however, is that technical analysis will indicate convenient entry points even for the worst stocks in the world. **

The GIGO (garbage in, garbage out) rule applies here, meaning that if we feed any model with garbage data, we will also get garbage results at the output. That is why technical analysis alone will not help us earn any money, but when applied to the right company, it can help choose the optimal moment to buy that company.

People behave similarly in similar situations. Always. Everywhere. Region and culture do not matter. If there is an accident on the street, a crowd of onlookers will gather around the scene in a moment. If, on the other hand, a tiger jumps out onto the street, people will scatter instantly. Residents of Tokyo, Warsaw, and New York will react the same way to the same stimuli (accident, tiger). By learning to recognize specific patterns, you can learn to predict with high probability how people will behave in specific situations.

The stock market is made up of investors. **Stock prices do not change by themselves, but their movements up and down are caused by human behavior - fund managers, algorithm writers, investment bankers, and family offices, as well as a whole host of individual investors.** This is important because recognizing past behavior patterns will allow us to somewhat predict future behavior.

Entire books have been written about candlestick formations and their interpretation, so there is no need to describe them here again, but it is worth noting that the most popular formations (patterns of behavior) include double and triple bottoms or tops, all support and resistance lines, and breakouts from triangles or rectangles.

However, we should remember that interpreting what we see on the chart is more of an art than a science. There is no point in forcibly looking for something that is not visible at first glance because technical analysis will only work when all investors look at the same picture and, moreover, interpret it in the same way.

**The effectiveness of technical analysis in selecting good moments to enter the market is based solely on the mechanism of a self-fulfilling prophecy. If the majority of investors see a support line on the chart, from which the stock price has already bounced twice during the previous year, it is very likely that the third potential correction will also end at this point.** Why? Because as soon as the price reaches the same level it previously bounced from, some investors will consider it a good moment to add shares to their portfolio, and as a result, they will cause a slight rebound and an upward movement.

Seeing that the shares are indeed starting to bounce off the same level for the third time, more investors (including algorithms) will join the market, causing an even more dynamic rebound that even the biggest skeptics will not resist.

To assess what is happening with the stock price, ready-made indicators, based mainly on processing data on the strength of the upward or downward momentum, also prove helpful.

If we are currently dealing with a weakening upward momentum (prices continue to rise but at an increasingly slower pace), it means the fading determination of the demand side. This, in turn, can be interpreted as all those who wanted to buy specific shares already did so. **Therefore, since there are slowly starting to be fewer new interested parties, the first investors may come up with the idea to realize profits and start getting rid of their shares. **

What this means for stock prices is no secret to anyone. Indicators based on momentum will also allow us to determine when the prices of particular stocks have risen too strongly and too quickly, which may also prove to be a contrarian reading, suggesting an upcoming short-term reversal of the growth trend.

Similarly, the situation looks when stocks move in the opposite direction. Appropriate indicators can help us determine when stocks have fallen too much compared to how they typically fell in the past or when the downward trend is just beginning to flatten out. This gives us a signal that selling pressure is fading, and it may be a good time to take a position.

Of course, provided that the stocks meet all the purchase criteria determined by fundamental analysis.

The most popular and effective indicators are those from the oscillator family. Formulas of this type allow us to visualize the average dynamics of price changes over a longer period and then overlay current oscillations resulting from increasing or weakening price dynamics of specific stocks over a shorter period.

If the oscillator reading is at its extreme above the average, the market is overbought, meaning stock prices have risen much faster recently than they have on average so far, indicating a temporary exhaustion of demand and a reversal of the trend. Similarly, if the oscillator reading is at its extreme below the average, recent declines have been too rapid and too strong compared to the historical average, suggesting a good time to buy stocks.

**The RSI indicator shows the relative strength (or lack thereof) of the stock price, and the second indicator shows the strength of the RSI indicator itself and its relative moments of weakness (readings at extremes below the average are good for buying) or moments of great strength (readings at extremes above the average are good for selling).** Both indicators work best in pairs, as using only the RSI reading will not be suitable for what technical analysis should be used for, namely, precisely determining good entry points.

The RSI indicator sends signals too rarely (sometimes you have to wait for them for even a year), while the stochastic RSI sends a signal at least once every 40 days. Of course, the parameters of both indicators can be reduced to make signals appear more often, but keep in mind that more frequent signals will be characterized by an increased number of false indications. Therefore, the optimal levels seem to be RSI – 21 and stochastic RSI – 40.

An additional criterion worth referring to before buying or selling stocks is the position of the price relative to the weighted moving average of this price change.

Each reading falls within a specific distance from its average. This distance is called the standard deviation in statistics and is denoted by the symbol sigma (σ).

In short: 68% of all readings from a given period will be within one standard deviation of their average, and 95% of readings within two standard deviations. If we know the average stock price change and the historical deviation limits from this average for the stocks we are interested in, we can easily calculate the ranges within which the stock price should be in a specific period, with a probability of up to 95%.

The visualization of this phenomenon is facilitated by the **Bollinger Bands indicator**. The indicator consists of a weighted moving average of the stock price change from a specific time (i.e. 65 days) and two marked bands located at a distance of two standard deviations from each other (one sigma up and one sigma down from the average).

Thanks to this visualization, an investor receives information about the ranges within which the selected stock’s price can be found over the next 65 days with a 95% probability. This statistical observation can be used to determine whether, at a given moment, considering the current price, it is more likely that the price will be higher or lower in two months.

If the current stock price is at the lower limit of two standard deviations (at the lower Bollinger band), one can definitely expect that within 65 days there will be at least a regression to the mean and that the price will be higher than the current reading. On the other hand, if the price is at the upper limit of two standard deviations, a regression to the mean is more likely, but downward.

Using the indicator alone will not allow for selecting the ideal moments for entry or, even more so, exit, as stock prices can remain at one of the limits for a long time before regressing. Nevertheless, Bollinger Bands add a statistics-based element to the whole equation.

A good piece of advice before applying any indicator is to look at its historical effectiveness and ask yourself the key question:

**How would I have fared if I had followed this indicator in the past?**

Naturally, history is not an absolute guarantee for the future, but nobody has come up with anything better, and in the real world, past behaviors often (although, of course, not always) prove to be the best predictor of future behaviors.

Therefore, before drawing conclusions from a particular reading, it is always worth checking how effective these readings have been in the past with respect to the stocks being analyzed. It often happens that what has nearly 100% accuracy for some securities will be completely useless for others.

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