From the author:
A quote from Sir Isaac Newton has come down to us in which he complains that he can now calculate the course of the stars and planets, but not the madness of the masses. He did this after losing almost all of his capital in the South Sea Bubble. A few centuries later, the Long Term Capital Management Fund (LTCM) met the same fate. Although guided by statistical models by gifted mathematicians, including Nobel Prize winners Myron Scholes and Robert Merton, the fund ended up losing all of its capital. Private and institutional investors believed in the risk-free 40% of the capital invested, in the end the central bank had to step in to save the financial system. In the summer of 2008, the mortgage crisis was far from over, and again a number of banks and funds are on the brink of the abyss.
Events like this suggest that our ideas about the nature of price action are still very much in their infancy. Indeed, the first scientific paper on the subject of the stock exchange did not appear until 1900: the "Théorie de la Speculation" by the French mathematician Louis Bachelier. He explored the question of how courses are developing - not where they are going, but what course development looks like in general. This is a matter of principle. For example, is it twice as risky to hold a stock for two weeks instead of just one week? How likely is it that the stock will move more than 10% tomorrow? What risk do I take over the course of the year if I risk EUR 1000 on the market every day? In order to be able to answer such questions, it is advantageous to have a theoretical model of the market. This model can be used to make predictions about possible future price developments and then check these results against reality for their validity. Such predictions can be, for example, an estimate of the volatility or well-founded approaches to position sizing. But I have to disappoint you at the beginning. Unfortunately, such a model does not yet exist on the market. Despite multiple attempts by the best minds, there is not even an even remotely correct theory about the market. And yet there are some theories about systems similar to the market, so these theories can be used to at least get a rough idea of what might happen tomorrow. Interestingly, many of these theories arose in the context of fortune knights and gamblers. It is only in the recent past that the subject of "methods of speculation" has also been included in the curriculum at universities.
The random walk is one of those theories that can be used to explain key market properties. The natural scientists among you know the random walk as a special case of the Brownian movement. However, the issue here is not the molecular movement, but the price development. In order to clarify this basis for describing courses, I would like to invite you to play a game. The game is a simple toss of a coin: Whenever heads appear, you win one euro; if »number« appears, you lose one euro. Make a note of your account balance after each run and you will be given a random walk chart.
This curve now has some properties that you can also observe on the market. For example, consider the emerging trends. They look something like the trends on the price chart, and yet they only came about by chance. Just as long sequences of "only red" or "only black" can occur again and again in roulette, in this game it is apparently not unlikely that heads or tails will appear several times in a row. You will also see formations like those seen on the stock exchange. Weren't there multiple double bottom formations on the chart? Do you see the head and shoulders formation? Doesn't every trend have minor corrections that could be used for acquisitions if necessary? You see the patterns, I see the patterns, and yet neither of us see anything that can be used in any way for a successful trading strategy. The curve is - and the name already tells us - a random walk. Whether the next point goes up or down depends only on whether the next coin toss shows heads or tails. Even if you as a person immediately see the supposedly suitable patterns for trading, they cannot be used for trading due to their random nature.
You can describe the random curve using the methods of charting, but you cannot benefit from this description. And yet this curve has properties that you can also use on the market. Think of your money management here. If you are not a very good trader but a disciplined trader, your trading will look something like this curve. Sometimes you win, sometimes you lose. Good phases alternate with bad ones, but "in the long run" your depot fluctuates around the zero line. Fortunately, as a retailer you don't have to dig too deeply into the mathematics of chance. The most important thing for us is to understand the implications of the theories. So many a trap can be avoided. For the random walk, this randomly created curve looks very similar to the stock market, but it is only a representation of chance. Such a curve cannot be successfully traded with the classical methods of technical analysis. Any trading approach that you would test with such a curve would result in a random walk again. Just because something looks like a stock market doesn't mean it has to be a stock market. However, since you cannot rule out that the stock market is controlled purely by chance, you have to consider whether your trading strategies are based on a property of the market that is not only controlled by chance. Unfortunately, just because you can see the patterns doesn't mean they can be used for a successful trading strategy.
The expected value
In connection with the random walk curve, I would also like to introduce another term that will be used later: the expected value. It shows the average result I'll get if I play the game long enough. In this case, the result is clear: it's zero. No matter how skillfully you play this game, in the end you will have lost everything you had won in the meantime. For this reason, this coin tossing game is also known as a zero-sum game. One game that is almost a zero sum game is roulette. If zero didn't exist, it would be a zero-sum game. The zero - if it appears, the bank wins - this game receives a slightly negative expected value. On average, the bank wins 1/37 of the bets placed at the table per round.
The stock market is also a game with a slightly negative profit expectation. In theory, it's a zero-sum game. The money is only redistributed between the winners and losers, nothing arises or disappears. In practice, however, you pay the broker fees and the bid-ask spread for every transaction. This turns the stock market into a game with a negative expected value for you. The higher the fees to be paid and the higher the bid-ask spread, the more negative the expected value. For private traders in particular, the selection of a very liquid market and a broker with minimal expenses is paramount. With the conditions of most house banks, you would have to be a clever professional to get a positive expected value for many transactions after expenses.
Efficient Markets Theory
Closely related to the random walk theory is the theory of efficient markets. It says that the current price always shows all available information. This is quick to write, but it has a huge impact on how we aim to beat the market. The next price is always formed on the market where the majority of capital willing to buy is just as convinced of its advantage as the sellers are of theirs. However, if all available information is mapped in the course, then no matter how you go about it, you cannot work out any advantage over the other market participants. This would mean the end of trading and a return to the buy-and-hold approach. Well, the markets are not quite as efficient, but they are usually much more efficient than we retailers would like. In order to understand market efficiency, we must first deal with the term information. Information can, for example, be a not yet generally known message. For example, if you are a well-informed trader and use your information network to learn something from the boardroom of an interesting company, then you may come across inside information. Let's ignore the fact that speculating with such information is not legally flawless, but let's concentrate on the effects of your actions on the market.
After learning that an AG takeover is imminent in the next few days, start buying today. By buying now and there are no new reasons to sell the stock, you drive the stock price higher. You will do this until the share price is where you expect the takeover offer to be. Whether the trade will be a profit or not is another matter. What is important here is that you have established market efficiency yourself. Even if the information about the upcoming takeover offer is still not widely known, you have already pushed the price so far that no further profit can be made from the information about the takeover. So all information, even if only one market participant has it, is included in the price of the share. However, information is not only hard economic facts such as dividends, orders and company profits, but also all information that can be derived from the past. This can be, for example, the information that you pull from an indicator or a price pattern.
The efficiency of the markets
A vivid example of this market efficiency is a trading system based on the RSI indicator. The indicator was introduced by Welles Wilder in his book New Concepts in Technical Trading Systems in 1978 and, along with the simple moving average, is one of the best-known and most widely used indicators. Unfortunately, however, it seems that this indicator has caught up with efficient markets theory. If you look at the performance of a classic RSI system, ie "buy if the cut is above the 30 line, go short if the cut is below the 70 line," then you can quickly see that the best days of this system are clearly over. Until the release of the RSI, such a trading approach seemed to have made good money, but since the release of the indicator it has apparently not been so easy to do. One reason for this can be market efficiency
How is the information transferred from an indicator to changed market behavior? At first sight this does not seem plausible, and yet the process of such a market adjustment is relatively simple. If all traders know to buy when the RSI breaks above the 30 line, then the price will rise for a short time due to the increased number of buy orders at that point. Instead of receiving the lower price that would come about without this effect, all market participants now buy at a price that is a few ticks higher. The same effect occurs when the indicator gives the counter signal and positions are closed or rotated. At this point, too, you get a worse price than would have been the case without the other RSI traders. At some point the situation will be reached where the use of the indicator in this way of interpretation is no longer useful. The information has been incorporated into the course, and the markets have once again proven their efficiency. Of course, this does not end the game. If the indicator no longer works, because the price includes the information “buy at an average above the 30 zone”, then many market participants will switch to another indicator
As a result, however, the price jump at the next RSI signal is no longer quite as large, and trading the signals may soon be worthwhile again. Then, however, the other dealers will probably again establish the efficiency. The efficient markets theory is also the sword of Damocles of trading systems. As soon as a system is traded by too many people, it will almost certainly lose its performance. This can also happen when trading a system with too large a volume. If you want to buy so many contracts on each signal that you push the market up a few points yourself, you are the trader who creates market efficiency. You can see this behavior in successful hedge funds too.
The problem of large funds
This problem often occurs with a large, systematically traded fund. The trading system had been working on a "smaller" scale for a number of years before the fund went public in 2003 and began collecting money. With the excellent performance of the underlying system, this was possible relatively quickly. But see for yourself what happened: the fund was hardly equipped with significantly more money than in previous years when the problem arose of accommodating this high volume on the market. And so this trading system began to influence the market with its large orders. Accordingly, the performance collapsed. Since 2003 you have earned significantly less than you could have expected in 2003.
If a lot of people withdraw their capital again, the performance will probably start again. The trading system can trade the market again instead of making the next price itself. The theory of efficient markets is also the basis for the random walk. If all available information is already shown in the current course, then no statement can be made about the next course. In this case, you could flip a coin to see if long or short would be the better position. But that brings you back to the Random Walk. There, too, every next point is completely independent of the previous one. No information from the past can tell me anything about the future.
So if the theory of efficient markets were always correct, then you could save yourself trading. There would be no practicable way to gain an advantage over the other market participants and to achieve a better performance than the average performance of the market. That would take us back to buy-and-hold strategies after all attempts to make money from trading.
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