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  1. In this age of previously unheard of technological progress many technology-related things either come unnoticed as they appear or, vice versa, are vastly extolled and turned into totems that inevitably attract a following of ardent worshippers. If such a popular technology-related phenomenon can make a difference to your business, it is, sometimes, vital to learn about this phenomenon as much as possible before you start with it so that you know what to expect from the selected technology and what to beware of while using it. For a modern trader, one of such potentially important phenomena is neural nets. So what is the neural network technology, what should and what shouldn't a trader expect from it if he selects to use it to achieve his trading goals? Dispelling the Myths Myth 1: Supernatural Intelligence One of the commonly held misconceptions about neural networks is that they represent the kind of Artificial Intelligence which is it not only capable of fully replacing the human brain, but which also possesses some nearly supernatural power, thus enhancing the capacity and functions of this brain to the point when any kind of task can be solved almost miraculously without any effort on the part of the proud owner of this Holy Grail. This vulgar and frequently occurring notion of an undoubtedly valuable trading tool is dangerous in several ways. Let us see why. First of all, neural networks are not all things to all traders. To understand what neural networks can and cannot do one should look into what they are. Neural networks are algorithms, loosely based on the nervous systems of humans and animals. Neural networks can detect and use to advantage the numerous interdependencies in data that are hidden from the human eye due to the data's complexity and non-linearity. This has been proven by the broad experience of neural networks' application in a wide array of industries, and trading is no exception. However, on no account should you consider neural networks to be something that will think or decide for you. Myth 2: Magic Software The second as, if not more, dangerous, misconception about neural networks emanates directly from the first one: somewhere out there, there is a heaven-sent trading software that basically works as a minting machine and all you need to do is find it. This misconception is not dangerous only because you will lose time and money while looking for what doesn't simply exist, but also because your delusions are well-known to those who crank out one-magic-button, slipshod software programs and fob them off on the seekers of the neural Holy Grail. Normally, those who try to exploit others' delusions make poor professionals and, thus, poor software too. Remember - neural network software can only do what neural networks themselves can do, and they can do a lot if you know how to apply them and what software to purchase. However, no neural network software can tell you the exact time and the type of action you should take at this particular time to profit. Myth 3: Neural Networks Can Predict Precise Figures The third frequent misconception is that by using a neural network you will be able to predict the future prices. Many traders believe that their networks are capable of telling them when to buy and when to sell. If you understand that those people are wasting their time and money you will probably be a success with neural networks. No neural network, no matter how sophisticated or well-built, will be able to precisely inform you about the future price or, at the push of a button, tell you, and you alone, when it's best to buy or sell (for, otherwise, there would no longer be a market). However, you can, undoubtedly, predict the likelihood of other important things happening, which will help you make better trading decisions. Therefore, even with what neural networks really can do, they remain the most powerful market analysis tool ever in situations, involving noisy data or non-linear dependencies. In other situations, using neural networks may be inexpedient. We will dwell on the predicting ability of neural networks and on what and how they can actually forecast later in this article. Myth 4: Some Nets Are Significantly Better than Others Many traders who want to employ AI for making their trading solutions mistakenly believe that the quality of the neural network capabilities of the different trading applications on the market varies significantly, and there is some special neural network somewhere that will eclipse all the rest in terms of the quality of the forecasting results. However, practice and experience show that the quality of different neural networks, no matter how much touted for, differs within the range of 10%, and even so it varies for different tasks and data sets. Of course, while selecting a trading software program one should look at the AI background of its developers (building a good neural network takes a great deal of skill and experience), but, at the same time, the application must provide the rest of the required functionality (such as, for example, the charting functionality) with excellent quality. In other words, one should look for a successful combination of neural network functionality and other vital functionality. Looking for the only magic net is much like looking for one magic technical indicator. Aside from that, this quest often feeds those who are after a quick buck. Myth 5: The Quality of the Forecasting Result Depends Solely on the Quality of the Network Used The quality of the forecasting results does depend on the quality of the network you apply, but for not more than 10-15 %. The rest depends on how well the trader has prepared the data sets the network works with. The data sets must be sufficiently representative. They must include all the important influencing factors. Besides, the application of a neural network must be combined with Money Management and classical filters. What Neural Networks Can Do for You and What You Need to Know to Make Them Work Neural networks are definitely not a solution to all problems and they shouldn't be regarded so. What they are is a most powerful, technology-based method of technical analysis that can become an inestimable addition to your trading arsenal. Just like any other method, neural networks have their advantages and limitations, but their unique ability to track even the most subtle interdependencies in the available data no other method can establish, as well as build patterns based on this analysis, definitely make neural nets stand out from the rest of the existing methods and tools. You can effectively use neural nets to: estimate the likelihood of a trend continuing; classify market phases; produce time estimates of highs and lows for various timeframes and combine results into a committee; predict the probability of a new, strong upswing after an uptrend, followed by a classic correction; track inter-market dependencies. In other words, you receive a TA tool which will be a lot more efficient than classic TA methods anywhere where there is too much noise or where the interdependencies in the data are floating and significantly non-linear. For example, if after analyzing a number of charts you have discovered that the closer an uptrend is to a pivot point, the closer the bar's Close is to the bar's High, and you are planning to create an oscillator to anticipate reversal, you should use classic math as was done by the inventor of the Stochastic oscillator George Lane. But if you are trying to find a formula for the inter-relationship between S&P, InterestRates, $/Euro, Oil prices, and so on, you will make sure that the classical correlation or ratios won't be any use, since although interdependencies do exist, they are not stationary or linear. These interdependencies oscillate, ”float” through time and are influenced by noise. In this case, neural networks can solve the task better than the classical statistics. When used in a combination with other technical analysis methods, and when sufficient attention is paid to the preparation of data sets (this procedure is, actually, central to success with neural networks), neural networks will undoubtedly provide the punch you need to success on the market. After all, this has been proven by both time and experience. Source: Trading Software, Technical Analysis, Neural Networks, Stock, Forex, Futures
  2. The Pitfalls Of Cycle Trading

    MAGIC APPEAL OF CHANGE There are technical analysis techniques that, for some reason, seem to have always been around, at least ever since the market stopped being associated with fish, daisy nosegays and the ugly pottery, manufactured by the local artisans. Why? Most probably because the trivial logic that governs these methods and their application is seemingly so hard-and-fast that most anyone trading the markets sooner or later gives them a try. A case in point is the legendary technique of cycle trading, extolled by classics (such as, for example, the rocket scientist Mr. James Hurst), revered by some, and ridiculed by others. So what is so attractive about this method that made it one of the methods of choice for a great many of our fellow-traders? At first blush, if everything is calculated correctly, the technique seems to be so simple that any more or less thinking person who gets familiar with it for the first time can hardly help asking himself how come that there’s still some money left out there. Indeed, what can be simpler – the markets move in cycles. The universe is boundless. Buy at rock-bottom, sell at the crests, and count the bucks. Simple, isn’t it? Well, don’t get too elated, here is the full story. CYCLES AND WHY THEY CAME INTO PLAY It’s pretty obvious to anyone who has as much as had a brush with the market that there is definitely something cyclical to its nature. However, the cyclical nature of the market is not governed by any clearly defined law – cycles form with constantly changing oscillating amplitude, frequency and phase displacements. Given the cyclical nature of the world around us, the human brain inadvertently looks for a “cyclical” explanation of the different aspects of life: the changes of seasons and governments, droughts and bumper crops, downturns and periods of economic growth. The recurring processes in nature have been studied and used by humans since time immemorial. Our distant ancestry were able to use their observations of these phenomena to create things that are still capable of impressing us today. Sound scientific basis for the modern spectral analysis was provided in the 17-th century by Sir Isaac Newton. The field was contributed to by a number of other luminaries, such as Daniel Bournoulli, Norbert Wiener, John Tukey. As far as trading is concerned, one cannot but mention the scientific legacy of the esteemed Jean Baptiste Joseph Fourier, the renowned French Egyptologist and Mathematician, whose paper Théorie analytique de la chaleur (1822) gave birth to the scientific notion of what is now known as the Fourier series. Another major, if the greatest, contributor to the field was Mr. John Burg, who viewed the issue from the angle of maximum entropy in his 1975 doctoral thesis. This approach laid the foundation for cyclic analysis in trading owing to the very small amount of data it required to provide spectral estimates. In theory, to profit from the cyclic nature of the market, one needs to divide the price movement into the trend, cycle and noise. Then the periods when the trend doesn’t exist need to be identified, when the cyclical component carries enough weight “to drown out” the market noise. Ideally, the trend should only be traded with when the level of the cyclical activity is low and it is only during those periods, when the cyclical activity is very strong that cycle trading can be applied. Just like any technique called to describe the nature of the market cycles are a simplified model of the market. As the basis for the creation of a market model, the sinusoid is used. Simple sinusoids are combined to model the market’s cycle nature using a range of mathematical methods, from simple cycle finders (for example, the determination of the average distance between two lows) to Fourier transforms or Maximum Entropy Spectral Analysis, reckoned to be the most efficient of the methods. As the parameters for this kind of modeling the amplitudes, frequencies and phases of the primitive cycles being combined are used. The art of cyclic analysis consists in the ability to correctly select the required combinations while taking into account the resonances and objectively determining the parameters. The cyclic analysis approach can be used for describing classical chart patterns, determining trend channels, parameter determination methods for MAs and indicators, as well as for calculating stop loss signals. TECHNICAL PITFALLS Any more or less versed trader is fully cognizant of the fact that due to the nature of the market it is nearly impossible to identify the beginning and end of a cyclical period or correctly select the cycle frequency to trade with. Basically, a market cycle is a repetition of a stock’s or currency’s average fluctuations – a low, a rally, and a new low, dividing the period of time, occupied by the cycle, into the following four stages: the initial rock-bottom/recovery stage, upward move, distribution stage, and downward move. However, even if we do wholeheartedly embrace the elegant theory of the market’s cyclical nature, how do we identify the beginning of a cycle and its end? Probably, this is both the greatest challenge and deepest pitfalls awaiting anyone who treads on the risky path of cycle-trading. Besides, normally, the market rises and falls several times before any of the three major points is reached. This can confuse the trader and mislead him into entering or exiting a position too early, which, actually, happens rather often. Actually, any cycles-based trading offers an acceptable amount of risk only if the cycles are consistently repeated at least 85-90 % of the time and the smaller moves account for not more than the remaining 10-15 %. All those who attempt to come up with a viable classification of the different cycle stages and just another smart technique of how to identify them, either mentally or automatically with a specialized software, have so far failed to either convince or impress yours sincerely. Attempting to picturesquely describe the different market stages, lulls, and upsurges with the help of tenacious psychological phenomena is one thing, identifying these phenomena as they happen is a completely different matter. In fact, in our opinion, virtually the only moderately risky and realistically profitable way of trading here is what they sometimes refer to as the “greater fool trading,” applied short-term within the second 1/3 of the upward move - the second and only feasibly detectable stage in a market cycle. The beginning of the second stage is signaled by the end of a prolonged recovery lull and appearance of a growing number of early buyers. If, having waited long enough to make sure the trend is getting stronger, you manage to both buy and sell short close to the middle of the upward move, there will always be someone to buy from you. Anyhow, on a more close inspection, it becomes clear that what you can reckon to be the beginning of an exemplary and profitable market cycle at one time is nothing but too much market noise over a longer period of time. For example, a day’s high is not more than plain noise if you are trading a year-long cycle. This makes the very notion of a market cycle vague and unconvincing¬ – after all, a cycle can take as long as a couple of decades to complete. Was that high of yesterday the promising beginning of what will turn out to be a windfall fortune in 2026? The realization of the cyclic nature of flue pandemics is unlikely to be of help while answering this question. FUNDAMENTAL PITFALLS Today, cycles remain one of the most spoken about trading-related topics. This can be chalked up to (let’s admit it) most markets having cyclical nature, as well as to the marginal simplicity of cycles’ structure. The seemingly irrefutable statements about the cyclical nature of life itself and just as convincing “discoveries” of some major cycles the world seems to be pillared upon (such as, for example, the four -year presidential term), do their bit too. In addition, in theory, cycle-trading is a real cinch: some grasp of math, a little knowledge of geography (they don’t raise coffee beans in the North Pole – who could know), and some general erudition will be all you will need to strike it rich. Alas, the whole thing gets a just a bit more complicated when it comes to practice. The relative popularity of cycles in trading can most probably be attributed to yet another reason: there is large number of seasonal commodities, being, oftentimes, strategic industrial products and the staple products of the areas from which they originate. The prices of these products are cyclic in nature as are their sales. A perfect example would be some kinds of industrial fuels, consumed for heating purposes, whose prices, which is only natural, peak in the winter and toboggan in the summer. This has allowed many of the cycle enthusiasts to develop the so called seasonal models for different seasonal commodities, which seemingly, are simply destined to make the learned minds who concocted them the movers and shakers of this world – after all, if you know when teddy bears can be flogged at double their regular price, you can do a land-office business. But as luck would have it, the world in which these would –be movers and shakers live is round and diverse, and the effect the magic cycles produce can sometimes differ drastically from what their worshippers expect it to be. The different time zones, harvest seasons, droughts and overproduction are all there to shatter the immaculately prepared forecasts and dearly cherished dreams of cycle worshippers. All the above can hardly ever be taken into account and prevented for terms sufficient for the formation of a seasonal commodity cycle: in any event, any heart-felt attempts to eliminate a Colorado bug populace hard at work on destroying your potato-trading cycle several months after its beginning will be fated to fail. However, if you feel that you are able to take into consideration all the existing multitude of fundamental (political, geographical, psychological) factors that influence the market, you can use the cycles as an auxiliary means that shows you the general direction in which the market will move, bearing it in mind that the actual price may (and, most often, will) be significantly different. In fact, the number of the market forces is so large that the average fundamental and calendar (weekly, yearly) and production cycles turn out to be a lot more robust than the multi-layer ones, artfully calculated with the help of mathematics. Another thing which should be remembered is that cycle-trading is much less suitable for stock-trading than it is for futures-trading. CONCLUSION Obviously, cycle trading can hardly be recognized a viable means of profiting on the market in the majority of cases. However, it can be applied by well-skilled professionals in some kinds of trading situations and for certain kinds of commodities as a complementary technique, for example, for long-haul agricultural futures trading. Very often those traders who trade and “think” cycles use the same trading techniques as those who consider cycles to be a bizarre figment of their colleagues’ imagination, the difference being that for these market players cycles provide a “general framework” of the market, an additional angle from which the market can be viewed. The division of the market movements into the trend and sideway periods whereby different techniques are applied during the different periods is a good example of this kind of approach. As already mentioned above, the beginning and end of a cycle are hard to predict. This is highly disadvantageous, as this very divide is the cornerstone of cyclic analysis and even the simple realization of it’s existence by a trader has a practical meaning. Often, the fluctuations of an amplitude fade just as the trend reaches the required height and the model needs to be adjusted with new parameters either manually or automatically. This takes a while and, normally, the kind of the model you receive after the adjustment can only provide a good picture of the market – alas, the trend can no longer be used. In other words, a cycle with other parameters can become dominant at any moment in time. Modeling the market’s cyclic nature, despite its individual character, is based on the gargantuan task of approximating the price time movements to analytical functions. And although the market has long stopped being a place where only medieval cooking utensils can be bought, the present-day computerized means and mathematical achievements do no allow us to use its cyclic nature to our satisfaction. Source: Tradecision trading software Trading Software, Technical Analysis, Neural Networks, Stock, Forex, Futures
  3. Candlesticks Technique

    Just like a vast number of mind-boggling and revolutionary inventions, Candlesticks originate from Japan, where they were initially used by rice traders yet in the 17-th century. This gives the technique an air of Oriental charm, invoking associations with precision, technical eminence, and some innate, hidden ancient wisdom, which, of course, can never fail. Candlesticks were first introduced as a technical analysis technique by Steven Nison in his acclaimed book Japanese Candlestick Charting Techniques. Did the guy do the right thing? We think he did, but let’s try to answer this question at a greater depth. To create a candlestick pattern, you need a data set that will contain an open, a high, a low, and a close. A candlestick is formed by a “body” and two “tails” that grow out of this body. The four milestone points, passed by every trade, are located as follows: In this pattern, the tails represent the whole range of prices, used during the trade, whilst the body represents the opening and closing prices for the selected period. If the closing price is higher than the opening one, the body will be colored blue or green; when the opposite is the case, the body will be colored red. Basically, the Candlesticks pattern provides exactly the kind of information that you can observe on about any other kind of chart. The thing is definitely a lot more pleasant to look at than most of the other types of charts, but what’s the big deal in terms of its usefulness? The most powerful advantage that this technique can give is, undoubtedly, the easily discernible respective relationship between the four points that make up the pattern. One look is enough to size up the underlying price action in terms of the two key relationships. But, the most important advantage, offered by Candlesticks, is that there are a number of sure (well, most of the time, you know) signs of a market development occurring that no other technique can offer. So what is this bag of tricks? For example, if the body of your candlestick is green and rather prolonged, this means that buyers are very active - a definitely bullish sign. Conversely, a long red candlestick body will be a sure bearish sign. Another useful sign, offered by the Candlesticks technique is Doji – the situation, when the opening and closing prices coincide. The so called Dragonfly variation of Doji, whereby the prices coincide at the top of the trading range, serves as a sign of trend reversal and a forthcoming upward advance. An equally useful sign is the so called Piercing Line, whereby the closing price point of the green bar is just slightly higher than the middle of the preceding red candlestick. This situation signals a forthcoming reversal of a downward trend. The technique offers several more eloquently referred to pattern variations, whose names sound like the names of some mortally dangerous jab or a bizarre and potentially lethal posture from an Oriental martial system. But are these tricks really as dependable as the great ancient fighting legacy of the Orient? Of course, the technique is not infallible and just like any other trading method is a bit on the dodgy side. One of the main drawbacks of the technique is that despite it clearly shows the relationship between the opening and closing prices, it does not allow seeing how volatile the price action actually was during the different stages of the trade. Actually, some significantly different scenarios can be possible. All told, a great many traders reckon candlesticks to be the primary trading method in technical analysis. Our opinion would be that although Candlesticks are, certainly, a lot more reliable than most of the other technical analysis methods, one shouldn’t still rely entirely on this single method.
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