Click here to Download Getting Started in Technical Analysis PDF Book by Jack D. Schwager having PDF Size 9.8 MB and No of Pages338.
PROFESSOR COIN: Well no, Mr. Puneyser. The Random Walkers are a group of economists who believe that market price movements are random. That is, one can no more devise a system to predict market prices than one can devise a system to predict the sequence of colors that will turn up on a roulette wheel. Both events are strictly a matter of chance.
Getting Started in Technical Analysis PDF Book by Jack D. Schwager
| Name of Book | Getting Started in Technical Analysis |
| PDF Size | 9.8 MB |
| No of Pages | 388 |
| Language | English |
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Prices have no memory, and what happened yesterday has nothing to do with what will happen tomorrow. In other words, charts can only tell you what has happened in the past; they are useless in predicting the future. MS. TREND: Professor, you overlook a very important fact: Daily prices are not drawn out of a bowl, but rather are the consequence of the collective activity of all market participants.
Human behavior may not be as predictable as the motion of planets as governed by the laws of physics, but neither is it totally random. If this is not the case, your profession—economics—is doomed to the same fate as alchemy. (Professor Coin squirms uncomfortably in his seat at this reference.) Charts reveal basic behavioral patterns.
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Insofar as similar interactions between buyers and sellers will result in similar price patterns, the past can indeed be used as a guideline for the future. PROFESSOR COIN: If past prices can be used to predict future prices, why have a myriad of academic studies concluded that tested technical rules failed to outperform a simple buyandhold policy once commissions were taken into account?
A third type of linked future series that the reader may encounter is the constant forward (also known as “perpetual”) series, which consists of quotes for prices a constant amount of time forward. A constant forward series can be constructed from futures price data through interpolation.
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For example, if we were calculating a 90day constant forward series, and the 90day forward date fell exactly onethird of the way between the expirations of the nearest two contracts, the constant forward price would be calculated as the sum of twothirds of the nearest contract price and onethird of the subsequent contract price.
As we moved forward in time, the nearest contract would be weighted less, but the weighting of the subsequent contract would increase proportionally. Eventually, the nearest contract would expire and drop out of the calculation, and the constant forward series would be based on an interpolation between the subsequent two contracts.
The constant forward series eliminates the problem of huge price gaps at rollovers and is certainly a significant improvement over a nearest futures price series. However, this type of series has two major drawbacks. First, since the series does not correspond to any real contract, one cannot actually trade a constant forward series. Getting Started in Technical Analysis PDF Book
Second, and even more serious, the constant forward series does not reflect the impact of time evaporation on actual futures contracts. This deficiency can easily result in the price pattern of a constant forward futures series deviating significantly from the patterns exhibited by actual traded contracts—a highly undesirable feature.
valid signals. For example, this revised definition would have eliminated all but two false signals in Figure 5.7; unfortunately, it would also have excluded the best signals at the market’s peak. In Figure 5.8, however, the more restrictive definition for a reversal day would have avoided all five premature reversal day signals, while leaving the single valid signal intact.
A reversal day may sound somewhat similar to a spike day, but the two patterns are not equivalent. A spike day will not necessarily be a reversal day, and a reversal day will not necessarily be a spike day. For example, a spike high day may not witness a close that is below the previous day’s low (or even below the previous day’s close—as specified by the standard definition), even if the close is at the day’s low. Getting Started in Technical Analysis PDF Book
As an example of the reverse case, a reversal high day may not significantly exceed the prior day’s high, as required by the spike high definition, or exceed to the subsequent day’s high at all, since the subsequent day’s price action is not part of the reversal day definition. Also, it is possible that a reversal day’s close may not be near the low, a standard characteristic of a spike day, even if it is below the previous day’s close.
Occasionally, a day will be both a reversal day and a spike day. Such days are far more significant than days that are only reversal days. An alternative to using the more restrictive definition for a reversal day is using the standard definition, but requiring that the day also fulfill spike day conditions.
Although a day that met both the strong reversal day condition and the spike day conditions would be most meaningful of all, such days are fairly rare. Figure 5.9 provides an example of a day that met both spike and reversal low day conditions. After plunging downward, the stock closed near its high for the day, marking the end of a significant correction within a longstanding uptrend (not pictured), and initiating a quick rebound in prices. Getting Started in Technical Analysis PDF Book
lower boundaries. The RSI and stochastics, for example, both range between 0 and 100. Overbought and oversold levels for such indicators are commonly set equidistant from the upper and lower limits—for example, 70 and 30 or 80 and 20 (although this is not required, and would even be inappropriate in strongly trending markets; see below). Figure 6.1 compares the 10day RSI and stochastic.
The additional line on the stochastic is a 3day moving average of the basic stochastic, similar to the signal line of the MACD. The RSI has overbought and oversold levels of 70 and 30, respectively, while the stochastic uses levels of 80 and 20. Although the developers of these indicators suggest a variety of applications for these oscillators, the fundamental information they convey is identical to that of the other indicators discussed in this chapter.
Overbought levels are assumed to represent selling opportunities, and oversold levels are assumed to represent buying opportunities. Besides overbought and oversold levels, the other notable countertrend oscillator signal is referred to as divergence, which describes the phenomenon of momentum moving in the opposite direction of price. Getting Started in Technical Analysis PDF Book Download
As mentioned earlier, waning momentum often signals a dying trend and a possible reversal or correction. A classic divergence refers to a higher price high accompanied by a lower oscillator high, or a lower price low accompanied by a higher oscillator low. The implication is that the market has
The spectator’s chief enemies are always boring from within. It is inseparable from human nature to hope and to fear. In speculation when the market goes against you, you hope that every day will be the last day—and you lose more than you should had you not listened to hope—to the same ally that is so potent a successbringer to empire builders and pioneers, big and little.
And when the market goes your way you become fearful that the next day will take away your profit, and you get out—too soon. Fear keeps you from making as much money as you ought to. The successful trader has to fight these two deepseated instincts. He has to reverse what you might call his natural impulses. Instead of hoping he must fear; instead of fearing he must hope. Getting Started in Technical Analysis PDF Book Download
He must fear that his loss may develop into a much bigger loss, and hope that his profit may become a big profit. —Edwin Lefèvre It is always easy to analyze a chart with the benefit of hindsight. It is quite another matter to analyze a chart in real time, with actual trading decisions dependent on the outcome.
The chart examples in this chapter represent a handful of the trade recommendations I issued in my role as director of futures research at Prudential Securities. For each trade, I noted the reasons for entry and exit, as well as any lessons provided by the trade after the smoke had cleared. To provide a rounded perspective, both winning and losing trades are included. Knowing what can go wrong in a trade is often more important that knowing what can go right.
A chart pattern does not need to be right more than 50% of the time—or, for that matter, even close to 50% of the time—to be valuable. For example, when the pattern that motivated this trade—a flag near the low end of a trading range—proves correct, it can allow the trader to capture a major downswing. Getting Started in Technical Analysis PDF Book Download
On the other hand, when it is wrong, evidence of the failure is provided quickly—a modest upside penetration of the flag pattern. In other words, trading this pattern will naturally allow for much larger average gains on winning trades than average losses on losing trades. Consequently, the pattern can be a beneficial tool even if it leads to significantly more losses than gains.
In general, it is a mistake to focus on the percentage of winning trades generated by a system or methodology. The key factor is the expected gain per trade. (The expected gain per trade is equal to the percentage of winning trades times the average profit per winning trade minus the percentage of losing trades times the average loss per losing trade.
Most lower to midlevel analytical programs are fairly intuitive and userfriendly, allowing you to perform simple charting and analysis functions without having to be a computer expert. Software programs with system testing capabilities are a different story, however. While most use simplified programming languages (usually complemented by a library of preprogrammed technical studies or systems) designed specifically for non—computer users. Getting Started in Technical Analysis PDF Book Free
The demands on the trader increase with the capabilities of the program and the complexity of the trading ideas being tested. This may make testing sophisticated systems more wishful thinking than a realistic goal unless the trader is committed to mastering basic programming as well as technical analysis skills.
A trader who only needs to test fairly straightforward ideas has no need for a demanding (and probably more expensive) program that will only add to the difficulty of performing market analysis. The object of using such tools is to simplify the analytical process, not complicate it. It is also important to be aware of certain terminology distinctions.
Analytical programs—those that allow you to perform your own analysis, based on your own opinions—should not be confused with trading programs, which are packaged mechanical trading systems that generate buy and sell recommendations for whatever price data is fed into them. The issue can become confused because some trading programs include an analysis component in addition to the trading system. Getting Started in Technical Analysis PDF Book Free
In most instances, however, what you’re paying for is the system, not the analytical features. Countertrend systems often appeal to many traders because their ultimate goal is to buy low and sell high. Unfortunately, the difficulty of achieving this goal is inversely proportional to its desirability. A critical distinction to keep in mind is that whereas a trendfollowing system is basically selfcorrecting, a countertrend system implies unlimited losses.
Therefore, it is essential to include some stoploss conditions in any countertrend system (unless it is traded simultaneously with trendfollowing systems). Otherwise, the system could end up being long for the duration of a major downtrend or short for the duration of a major uptrend.
Stoploss conditions are optional for most trendfollowing systems, since an opposite signal will usually be received before the loss on a position becomes extreme. One important advantage of using a countertrend system is that it provides the opportunity for excellent diversification with simultaneously employed trendfollowing systems, thereby reducing overall volatility (see ”Diversification” section, below. Getting Started in Technical Analysis PDF Book Free
In summary, contrary to widespread belief, there is some reasonable question as to whether optimization will yield meaningfully better results over the long run than randomly picking the parameter sets to be traded. Lest there be any confusion, let me explicitly state that this statement is not intended to imply that optimization is never of any value.
First, as indicated previously, optimization can be useful in defining poorly performing parameter ranges that should be excluded from the selection of parameter set values. Also, it is possible that for some systems, optimization may provide some edge in parameter set selection, even after suboptimal extreme ranges are excluded. However, I do mean to imply that the