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All the tests that follow were performed using oscillator entries to trade a diversified portfolio of commodities, Can oscillator entry models result in profitable trades How have they fared over time-have they become more or less profitable in recent years These questions will be addressed below. The exits are the standard ones, used throughout this book in the study of entry models. Entry rules are discussed along with the model code and under the individual tests. Trades were closed out either when an entry in the opposing direction took place or when the standard exit closed the trade, whichever came first. The test platform is also standard. Over the years, we have coded into C+ + the various oscillators described in articles from Technical Analysis of Stocks and Commodities and from other sources. When writing this chapter, we compared the output from our C+ + implementations of the classic MACD, Stochastic, and RSI oscillators with (when available) equivalent oscillators in TradeStation. In most cases, there was perfect agreement of the results. However, for one of the Stochastics, the results were extremely different, specifically for Slow %K. Examining the code revealed that TradeStation was computing Slow %K by taking an exponential moving average of Fast %K. Our code, however, computes the 3-bar simple moving averages of both the numerator and the denominator (from which Fast %K would have been computed) to obtain Slow %K. According to the equations in Meibahr s (1992) article, and in other sources we have encountered over the years, our C+ + implementation is the correct one. If the reader attempts to replicate some of our work in TradeStation and finds discrepancies, we strongly suggest checking the indicator functions of TradeStation. In addition,
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when attempting to code a correct implementation for Slow %K in TradeStation s Easy Language, we ran into problems: It appears that TradeStation can give inaccurate results, without any warning, when one user function calls another. When we modified our code so intermediate variables were computed (thus avoiding the need to have nested calls), correct results were obtained. The version of TradeStation used for those tests was 4.02, dating from July 29, 1996. The following code implements most of the oscillator-based entry models that underlie the tests. The actual computation of the oscillators is handled by calls to external functions.
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static Oid MD&l (float *parms. float l dt, float *opn, float hi, float *lo, float ~1s. float *vol, float *oi, float +dlrv, int nb, TRDSIM &tS. float *q&31 { // ,, /I /I /I I/ // // /I /I /I // // I/ Implements the oscillator-based entry models to be tested File = XllmodOl.c vector II. .MAxPRM, Of parameters wrm= vector L1. .nbl of dates in WMMDD form dt ector [I. .nbl Of opening prices opn vector II. .rlbl Of high pricea hi - vector Ll. .*I Of low prices 10 vector [I. .nbl Of closing prices ClS vector 11. .nhl Of volumes vol vector [I. .x-lb1 Of open interest numbers oi arv vector Cl. .nhl of average dollar volatilities number Of bars in data series or vectors nb trading simulator class instance C6 vector Cl. .*I of closing equity levels eqc1s
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,, declare local GCracCh variables static int rc, cb, ncontract.9, maxhold, lenl, len2, len3; static int modeltype, ordertype, osctype. signal, i, j, k; static float mmatp, ptlim. stpprice, limprice, tmp; static float exitatr [MAxBAR+ ; static float sigline mAxBAR+ , oscline wAxBAR+ i static float upperbandMAXBAR+ll , lowerbandWhXBAR+11 ;
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CHAPTER 7 Oscillator-Based Entries
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The logic of the code is very similar to the code used to test moving averages. First, a number of parameters are copied to local variables to make them easier to understand and refer to in the code that follows. A check is then made for invalid combinations of parameters; e.g., for the MACD (o&ype = 4), the length of the shorter moving average must be less than the longer moving average; otherwise the test is skipped. In the next large block of code, osctype selects the type of oscillator that will be computed (1 = fast Stochastics, 2 = slow Stochastics, 3 = classic RSI, 4 = classic MACD). The oscillator (oscline) is then computed as a data series or vector; any additional curves associated with it, such as a signal line (s&dine) or slower version of the oscillator, are generated; and upper (upperband)
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and lower (lowerband) thresholds are either set or computed. For the Stochastics, the standard thresholds of 80 and 20 are used. For the RX, 70 and 30 are specitied (also standard). Although the MACD normally has no thresholds, thresholds placed 1.5 mean deviations above and below zero. Finally, the process of stepping through the data, bar by bar, is begun. Two main blocks of code are of interest in the loop for stepping through the data. The first block generates a buy or sell signal, as well as limit and stop prices for the specified, oscillator-based entry model. The mod&p parameter selects the model to use: I = overbought/oversold model, 2 = signal line model, and 3 = divergence model. The oscillator used by the model to generate the buy and sell signals is the one computed earlier, as selected by osctype. The final block of code enters trades using the specified order type. The parameter ordertype determines the order used: 1 = entry at open, 2 = entry on limit, and 3 = entry on stop. Finally, the simulator is instructed to use the standard exit model to close out any open trades. The exact logic used for entering the market is discussed in the context of the individual tests below without requiring the reader to refer to or understand the code. TESTS RESULTS Tests were performed on three oscillator entry models: Overbought/oversold (Stochastic and RSI used), signal line (Stochastic and MACD used), and divergence (Stochastic, RX, and MACD used). All individual model-oscillator comhinations were examined with entry at the open, on a limit, and on a stop. The results for all three orders are discussed together. Tables 7-l and 7-2 contain, for each of the 21 tests, the specific commodities the model traded profitably and those that lost in-sample (Table 7-1) and out-ofsample (Table 7-2). The SYM column represents the market being studied, the first row identifies the test number. The tables show which markets were, and were not, profitable when traded by each model: One dash (-) indicates a $2,000 to $4,000 loss per trade: two dashes (- -), a $4,000 or more loss; one plus sign (+) means a $1,000 to $2,000 profit; two pluses (+ +), a $2,000 or more profit; a blank cell means a $0 to $1,999 loss or a $0 to $1,000 profit. TESTS OF OVERBOUGHT/OVERSOLD MODELS The entries were generated when the oscillator crossed below an upper threshold or above a lower one. These are countertrend models: The trader buys when the oscillator shows downward momentum in prices and sells when the oscillator depicts recent positive momentum. In Tests 1 through 6, the Stochastic and the RSI were considered since these indicators have traditional thresholds associated with them and are often used as described above.
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