start next


[ start ] [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46] [47] [48] [49] [50] [51] [52] [53] [54] [55] [56] [57] [58] [59] [60] [61] [62] [63] [64] [65] [66] [67] [68] [69] [70] [71] [72] [73] [74] [75] [76] [77] [78] [79] [80] [81] [82] [83] [84] [85] [86] [87] [88] [89] [90] [91] [92] [93] [94] [95] [96] [97] [98] [99] [100] [101] [102] [103] [104] [105] [106] [107] [108] [109] [110] [111] [112] [113] [114] [115] [116] [117] [118] [119] [120] [121] [122] [123] [124] [125] [126] [127] [128] [129] [130] [131] [132] [133] [134] [135] [136] [137] [138] [139] [140] [141] [142] [143] [144] [145] [146] [147] [148] [149] [150] [151] [152] [153] [154] [155] [156] [157] [158] [159] [160] [161] [162] [163] [164] [165] [166] [167] [168] [169] [170] [171] [172] [173] [174] [175] [176] [177] [178] [179] [180] [181] [182] [183] [184] [185] [186] [187] [188] [189] [190] [191] [192] [193] [194] [195] [196] [197] [198] [199] [200] [201] [202] [203] [204] [205]


0

closing the gap between expectations and reality

Quantitative metliods for evaluating price movement and making trading decisions have become a dominant part of market analj-sis. At one time, the only acceptable manner of trading was by understanding the factors tliat make prices move, and determining the extent or potential of future movement. The market now supports dozens of major funds and managed programs, which account for a sizable part of futures market open interest and operate primarily by decisions based on "technical analj-sis." selection, which can require sorting through thousands of individual world equities each day, has become a problem in data reduction-finding specific pattems that offer the best expectations of profit. Many commercial participants in the markets, who once restricted research to simply and demand, or institutions once only interested in earnings and debt, now include various technical methods for the pu ose of-timing-or confirming price direction.

In many waj-s, there is no conflict between fundamental and technical analj-sis. The decisions that resiUt from economic or policy changes are far-reaching: these actions may cause a long-term change in the direction of prices and may not be reflected immediately. Actions based on long-term forecasts may involve considerable risk and often can be an ineffective way to manage a position. Integrated with a technical method of known risk, which determines price frends over shorter intervals, investors at all levels have gained practical solutions to their trading problems.

Leverage in the futures markets has a strong influence on the methods of frading. With margin deposits ranging from 5 to 10°o of the contract value (the balance does not have to be borrowed as in stocks), a small movement in the underljing price can resiUt in large profits and losses based on the invested margin. Because high leverage is available, it is nearly alwaj-s used. Methods of analj-sis will therefore concentrate on short-term price fluctuations and frends, in which the profit potential is reduced, so that the rid; is often smaller than the required margin. Futures market sj-stems can be characterized as emphasizing price moves of less than 20°o of the confract value. Trading requires conservation of cspital, and the management of investment risk becomes essential.

Even with the distinction forced by high leverage, many of the basic sj-stems covered in this book were first used in the stock market. Compared with securities, the relatively small number of futures markets offer greal diversiflcation and liquidity. The relative lack of liquidity in a single stock lends itself to index analj-sis. whereas the -commodin- index, now tradeable as the CRB index, has never become very popular.

TECHNICAL VERSUS FUNDAMENTAL

Two basic approaches to tradmg futures are the same as in trading equities: fundamental and technical analj-sis. In futures, a fundamental study may be a composite of siq3ply-and-demand elements: statistical reports on production, expected use. political ramiflcations. labor influences, price support programs, industrial developmeHt-everHiing thai makes prices what they are. The result of a fundamental analj-sis is a price forecad. a prediction of where prices will be at some time in the future.

Technical analj-sis is a study of pattems and movement. Its elements are normally limited to price, volume, and open interest. It is considered to be the study of the market itself The resiUts of technical analj-sis may be a short- or long-term forecast based on recurring patterns; however, technical methods often limit their goals to the statement that todays prices are moving up or down. Some sj-stems will go as far as sajing the direction is indeterminate

Due to the rapid growth of computers, technical sj-stems now use tools previously reserved for fundamental analj-sis. Regression and cycle (seasonal) analysis are built into most spreaddieet programs and allow these more complex studies, which were once reserved for serious fundamental analj-sts, to be performed by everyone. Because they are computerized, many technicians now consider them in their own domain There will alwaj-s be purists on either side, rigid fundamentalists and technicians, but a great number of professionals combine the two techniques. This book draws on some of the more popular, automated fundamental trading spproaches.

One advantage of technical analysis is that it is completely self-contained. The accuracy of the data is certain. One of the first great advocates of price analj-sis, Charles Dow. said:

The market reflects all the jobber knows about the condition of the textile trade; all the banker knows about the money market; all that the best-informed president knows of his own business, together with his knowledge of all other businesses; it sees the general condition of transportation in a way that the president of no sin gle railroad can ever see; it is better informed on crops than the fanner or even the Department of Agriculture. In fact, the market reduces to a bloodless verdict all



knowledge bearing on finance both domestic and foreign.

Much of the price movement reflected in commodity cadi and futures markets is anticipatory; the expectations of the effects of economic developments. It is subject to change without notice. For example, a hurricane bound for the Philippines will send sugar prices higher, but if the storm tums off course, prices will drop bad; to prior levels. Majoi scheduled crop reports cause a multitude of professional guessing, which may correctly or incorrectly move prices just before the actual report is released. By the time the public is readj to act, the news is alreadj reflected in the price.

PROFESSIONAL AND AIVLTEUR

Beginning traders often find a sjstem or technique that seems extremely simple and convenient to follow, one that they think has been overlooked by the professionals. Sometimes they are right, but most often that method doesnt work. Reasons for not using a technique could be the inability to get a good execution, the rid/reward ratio, or the number of consecutive losses that occur. Speculation is a difficult business, not one to be taken casually. As Wyckoff said, "Most men make money in their own business and lose it in some other fellows."

To compete with a professional speculator, you must be more accurate in anticipating the next move or in predicting prices from current news-not the article printed in todays newspaper ("Government Buj-s Beef for School Lunch Program"), which was discounted weds ago, and not the one on the wire service ("ISo Fewer Soybeans and 10°o More Fidimeal") which went into the market two daj-s ago. You must act on news that has not yet been printed To anticipate changes, you must draw a single conclusion for the many contingencies possible from fundamental data or

1. Recognize recurring pattems in price movement and ddermine the most likely results of such patterns

2. Determine the trend of the market by isolating the basic direction of prices over a selected time interval.

The bar chart, discussed in Chapter 9 ("Charting"), is the simplest representation of the market. These pattems are the same as those recognized by Livermore on the ticker tape. Because they are interpretive, more precise methods such as point-and-figure charting are also used, which add a level of exactness to charting. Point-and-figure charts are popular because they offer specific trading rules and show formations similar to both bar charting and ticker-tape trading.

Mathematical modelmg, usmg traditional regression or discrete analj-sis, has become a popular technique tor anticipating price direction. Most modeling methods are modifications of developments in econometrics, basic probability; and iatiatical theory They are precise because they are based entirely on numerical data.

The proper assessment of the price trend is critical to most commodity trading sj-stems. Countertrend trading is just as dependent on knowing the trend as a trend-following technique. Large sections of this book are devoted to the various ways to isolate the trend, although it would be an injuatice to leave the reader with the idea that a price trend is a universally accepted concept. There have been many studies published claiming that trends, with respect to price movement, do not exist. The most authoritative papers on this topic are collected in Cootner, The Random Cbarader of stock Market Prices (MIT Press) more recent and readable discussions can often be found in The Financial Analysts Joumal, an excellent resource.

Personal financial management has gained an enormous number of tools during this period of computerized expansion The major sjreaddieet providers include linear regression and correlation analj-sis; there is inexpensive software to perform spectral analj-sis and apply advanced statistical techniques; and development software, such as TradeStation and MetaStock, have provided trading platforms and greatly reduced the effort needed to program your ideas. The professional maintains the advantage of having all of their time to concentrate on the investment problems; however, the nonprofessional is no longer at a disadvantage because of the tools.

RANDOM WALK

It has been the position of many fundamental and economic analj-sis advocates that there is no sequential correlation between the direction of price movement from one day to the next. Their position ih that prices will seek a level that will balance the supply-demand factors, but that this level will be reached in an unpredictable manner as prices move in an irregular response to the latest available information or news release.

If the random walk theory is correct, many well-defined trading methods based on mathematics and pattern recognition will fail. The problem is not a simple one, but one that should be resolved by each sj-stem developer, because it will influence the tjpe of sj-stematic approaches that will be studied. The strongest argument against the



random movement siq3porters is one of price anticipation. One can argue academically that all participants (the market) know exactly where prices should move following the release of news. However practical or unlikely this is, it is not as important as market movement based on anticipation of further movement. For example, if the prime rate was raised twice in two months, would you expect it to be increased in the third month? Do you think that others will have mixed opinions, or that they assess the likelihood of another increase at different levels (i.e., one might see a ISo chance of an increase and another see a 60°o chance). Unless the whole market view expectations the same way, then the price will move to reflect the majority opinion. As news alters that opinion the market will fluctuate. Is this random movement? No. Can this appear similar to random movement? Yes.

Excluding anticipation, the spparent random movement of prices depends on both the time interval and the frequency of data used. \ien a long time span is used, fran 1 to

20 years, and the data averaged to increase the smoothing process, the frending characteristics will change, along with seasonal and cyclic variations. Technical methods, such as moving averages, are often used to isolate these price characteristics. The averaging of data into quarterly prices smooths out the irregular daily movements and results in noticeably positive correlations between successive prices. The use of daily data over a long time interval infroduces noise and obscures uniform pattems.

In the long run, most futures prices find a level of equilibrium (with the exception of the stock index, which has had an upward bias) and, over some time period, show the characteristics of being mean reverting (returning to a local average price); however, short-term price movement can be very different from a random series of numbers. It often contains two unique properties: exceptionally long runs of price in a single direction, and asjinmetrj, the unequal size of moves in different directions. These are the qualities that allow traders to profit. Although the long-term frends thai reflect economic policy, easily seen in the quarterly data, are not of great interest to futures fraders, shortterm price movements-caused by anticipation rather than actual events, exfreme volatility, prices that are seen as far from value, counterfrend sj-stems that rely on mean reversion, and those that attempt to capture frends of less duration-have been successful.

It is alwaj-s worthwhile to understand the theoretical averts of price movement, because it does paint a picture of the way prices move. Many traders have been challeied by trying to identifj the difference between an actual daily price chart and one created by a random number generator. There are differences, but they will seem more subtle than you would expect. The ability to identify those differences is the same as finding a way to profit from actual price movements. A frading program seeks to find waj-s to operate within the theoretical framework, looking for exceptions, selecting a different time frame and capture profits-and all without ignoring the fact that the theory accounts for most of the price movements.

BACKGROUND MATERIAL

The contents of this book assume an understanding of speculative markets, particularly the futures market Ideally the reader should have read one or more of the available frading guides, and understand the workings of a buy or sell order and the specifications of contracts. Experience in actual frading would be helpful. A professional trader, a broker, or a purdiasing agent will alreadj possess all the qualifications necessarj. A fanner or rancher with some hedging experience will be well qualified to understand the rid involved. So is any investor who manages his or her own stock portfolio.

Literature on markets and frading sj-stems has greatly expanded in the years since ihe last edition of this book. During that time the most comprehensive and excellent work has been jack Schwagers two-volume set, Scbwager on Futures (Wiley, 1995), which includes one volume on fundamental analj-sis and the other on technical analj-sis. John Murphe/s Teclwical Analj-sis of the Futures Markets (New York Inatitute of Finance, 1986) and Intermarket Technical Analj-sis (Wiley, 199 1) are highly recommended. Ralph Vince published a popular work. Portfolio Management Formulas (Wiley, 1990), and there is Peter L. Bemsteins The Portable MBA in Investment (Wiley, 1995), which again provides valuable background material in readable form. There have been quite a few books on specific sj-stems and some on the development of computerized trading methods. The one comprehensive book of studies that stands out is The Encyclopedia of Technical Market Indicators by Robert W Colby and Thomas A. Meyers (Dow Jones-Irwin, 1988), which offers an intelligent description of the calculation and trading performance of most market indicators oriented toward equities traders. Comparing the resiUts of different indicators, side by side, can give you valuable insight into the practical differences in these techniques.

The basic reference book for general confract information has alwaj-s been the Commodity Trading Maimal



[ start ] [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46] [47] [48] [49] [50] [51] [52] [53] [54] [55] [56] [57] [58] [59] [60] [61] [62] [63] [64] [65] [66] [67] [68] [69] [70] [71] [72] [73] [74] [75] [76] [77] [78] [79] [80] [81] [82] [83] [84] [85] [86] [87] [88] [89] [90] [91] [92] [93] [94] [95] [96] [97] [98] [99] [100] [101] [102] [103] [104] [105] [106] [107] [108] [109] [110] [111] [112] [113] [114] [115] [116] [117] [118] [119] [120] [121] [122] [123] [124] [125] [126] [127] [128] [129] [130] [131] [132] [133] [134] [135] [136] [137] [138] [139] [140] [141] [142] [143] [144] [145] [146] [147] [148] [149] [150] [151] [152] [153] [154] [155] [156] [157] [158] [159] [160] [161] [162] [163] [164] [165] [166] [167] [168] [169] [170] [171] [172] [173] [174] [175] [176] [177] [178] [179] [180] [181] [182] [183] [184] [185] [186] [187] [188] [189] [190] [191] [192] [193] [194] [195] [196] [197] [198] [199] [200] [201] [202] [203] [204] [205]