18 Effective ness of technical indicators in an automatic stock trade program 1070469 2007 3 9
. MACP VR MACD 3 MACP. 3. MACD RSI 3 MACP VR 2.. 5,000 1 1,1.,,... MACD MACP. i
. MACP, VR, MACD, 3, RSI, ii
Abstract Effective ness of technical indicators in an automatic stock trade program Nami Watanabe The purpose of this research is to develope a new investment technique. I pursued the combination which can effectively use each index characteristic of the technical indicators (the detection techniques of a stock trade timing). I had verified the practicality of my investment method on my automatic stock trade program. This proposed method uses the investment technique in which MACP (Principal axis), VR and MACD are combined. With this combination, we can ascertain stock prices in three viewpoint Conversion with, Turnover, and Directivity. Possible faults of each index can be covereel by each other. For this reason, we will be able to get profits more certainly. In order to confirm advantage of this investment technique in comparison, I also programmed The three point charge investment technique (the previous investment technique by combination of MACP Principal axis, VR and RSI). and The Base technique (the investment technique by combination of MACP and VR). I carried out imitation stock trade by using these three technique, and Nikkei225 with stock price data in 2005. As a management environment, initial property was set to 50 million yen. The trading was only once per day using market information until the previous day, and continued it for one year. When the buy signal was detected, the purchase number was determined by a formula tradingpower T henumberofpurchasebrandontheday stockprice. iii
The result of performance in imitation stock trade, this proposal detected signals moderately, and sufficient profits were obtained. But compared with the Nikkei225 or the Base, the maximum drawdown was higher. It means that this technique has a defect, too. Because of the combination of MACD and MACP, once a rise market is detected the sell signal is activated before a possession brand improves to some extent. These, it shows the fault of selling rarely at a low price than the price of purchase. Also, for better results in a practical use, it should be adjuseed more precisely the intial condition of parameters in sell signals and buy signals.there is a possibility that the formula to determine the number of stocks maybe insufficient. key words MACP, VR, MACD, The three point charge investment technique, RSI, Nikkei225 iv
1 1 1.1................................ 1 1.2 4.......................... 1 1.2.1 (MACP : Moving Average Conversion Premium).. 2 1.2.2 VR (VolumeRatio)............................ 3 1.2.3 RSI (Relative Strength Index)...................... 4 1.2.4 MACD (Moving Average Convergence Divergence)............. 5 1.3 3 ( )..................... 6 2 7 3 1 9 3.1................................... 9 3.2............................. 10 3.3................................. 11 3.4.................................. 12 3.5................................... 19 3.5.1........................... 19 3.5.2........................... 21 4 23 5 2 27 5.1................................... 27 6 29 v
7 33 7.1..................... 33 7.2........................... 34 35 37 A 39 A.1 2005 JAL (3 ).......... 39 A.2 2006 JAL (3 ).......... 39 A.3 ANA (3 ).............. 40 A.4 (3 ).............. 40 A.5 NTT (3 )........... 40 vi
1.1 MACP........................... 2 1.2 VR............................. 3 1.3 RSI............................. 4 1.4 MACD........................... 5 1.5 3............................ 6 2.1............................ 7 3.1................................... 19 4.1 3....................... 23 4.2............................... 23 4.3.............................. 23 4.4 20 1.......................... 24 6.1 3....................... 29 6.2............................... 29 6.3.............................. 29 6.4 50 1.......................... 30 6.5 9301............................. 32 6.6 5713............................. 32 A.1 2005 JAL................. 39 A.2 2006 JAL................. 39 A.3 ANA..................... 40 A.4.................... 40 vii
A.5 NTT................. 40 viii
3.1............................... 9 3.2.............................. 9 4.1 20 1............................ 24 4.2 (20 )......................... 25 6.1 50 1............................ 30 6.2 (50 )......................... 30 ix
1 1.1 36.5, 4200 4300, 42 1500,, 12.,,.,,.,,. 1.2 4 4. 1
1 1.2.1 (MACP : Moving Average Conversion Premium) MACP, N MACP,,, MACP,. MACP ( ) = (A B) B 100 A = B = N 26, -5-10, +5 +10 1.1 MACP 2
1.2 4 1.2.2 VR (VolumeRatio) VR N VR 0, 100,,, VR, V R( ) = A+ 1 2 C B+ 1 2 C 100 A = B = C = 0 14, 30 70, 80 450 1.2 VR 3
1 1.2.3 RSI (Relative Strength Index) RSI N ( - ), RSI 0, 100,, RSI RSI( ) = A A+B 100 A =, B = RSI( ) = A A +B 100 C =, D = A = A (n 1) C N, B = B (n 1) D N 14, 20 30, 70 80. 1.3 RSI 4
1.2 4 1.2.4 MACD (Moving Average Convergence Divergence) MACD 2, MACD ( ) EMA ( ) EMA, 0, 0 MACD =N = EMA- EMA A = ( 0 1) = 2 N+1. EMA = EMA + A EMA EMA 12, EMA 26 1.4 MACD 5
1 1.3 3 ( ) MACP,VR,RSI,MACD,,, 1,. 1, 3 3,MACP VR RSI 3, MACP,. : MACP, VR, RSI : MACP VR 2, MACP RSI 2 1.5 3 6
2 1 3 MACP RSI,,. 1.1 1.3. 2, 3. RSI,VR MACD 3,. 2.1 3, 2.1 7
3 1 3.1,, SDK( ) java, [1]., 3,3 RSI. 3.1 3.2 3.1 MACP VR RSI MAC-D 26 25 14 EMA 12 EMA 26-7 70 25 0( ) 5 250 75 0( ) 3.1 MACP 26 MACP -7 5 3.2 3 MACP VR RSI MACP VR MACP VR MAC-D MACP VR or MACP RSI MACP VR MACP VR or MACP MAC-D 9
3 1 3.2 MACP VR MAC-D 3 MACP VR 2 MACP MAC-D 2 3 20 1. (1 1 ),,.. 0.1,., 3.2 SDK Java,,.,,, 10
3.3. : Java, SDK Java SDK : 5,000 1 2 ( ) 1 0.1 2 SDK : 50 1 (2004 9 1 2005 8 31 ) : 3.3 225 50 = * 50 5 45 45 *( 50 5 )= 450 225 = 11
3 1 3.4. import java.util.list; // List import java.util.arraylist; // ArrayList import jp.tradesc.superkaburobo.sdk.robot.abstractrobot; // SDK AbstractRobot import jp.tradesc.superkaburobo.sdk.driver.robotdriver; // SDK RobotDriver import jp.tradesc.superkaburobo.sdk.trade.informationmanager; // InformationManager import jp.tradesc.superkaburobo.sdk.trade.enumcurrentsession; // EnumCurrentSession import jp.tradesc.superkaburobo.sdk.trade.enumanalysisspan; // ( )EnumAnalysisSpan import jp.tradesc.superkaburobo.sdk.trade.tradeagent; // Manager TradeAgent import jp.tradesc.superkaburobo.sdk.trade.timemanager; // TimeManager import jp.tradesc.superkaburobo.sdk.trade.ordermanager; // OrderManager import jp.tradesc.superkaburobo.sdk.trade.portfoliomanager; // PortfolioManager import jp.tradesc.superkaburobo.sdk.trade.analysis.technicalindex.movingaverage; // MovingAverage import jp.tradesc.superkaburobo.sdk.trade.analysis.technicalindex.volumeratio; // VolumeRatio VolumeRatio import jp.tradesc.superkaburobo.sdk.trade.analysis.technicalindex.rsi; // Relative Strength Index RSI import jp.tradesc.superkaburobo.sdk.trade.analysis.technicalindex.macd; 12
3.4 // Moving Average Convergence Divergence MACD import jp.tradesc.superkaburobo.sdk.trade.data.stock; // Stock import jp.tradesc.superkaburobo.sdk.trade.data.portfolio; // Portfolio public class Original extends AbstractRobot { // AbstractRobot Original public static void main(string[] args) { // -n Original String[] v = { "-n", "Original" }; RobotDriver.main( v ); } public void order(tradeagent tradeagent) { // order TimeManager tm = TimeManager.getInstance(); InformationManager im = InformationManager.getInstance(); if(tm.getcurrentsession() == EnumCurrentSession.EARLY_SESSION){ //, checkportfolio(); } if(tm.getcurrentsession() == EnumCurrentSession.EARLY_SESSION){ //, List<Stock> targetstocklist = gettargetstock(); // if(targetstocklist.size()!= 0){ int priceforone = (int)(tradeagent.gettradablemoney()/(targetstocklist.size())); // 1 (/ ) for(stock stock: targetstocklist) { try{ int price = im.getstocksession(stock).getclosingprice(); // 13
3 1 int qty = priceforone/price; // (1 / ) OrderManager om = OrderManager.getInstance(); // om om.orderactualnowmarket(stock, Math.max(qty, stock.getunit())); // }catch(nullpointerexception e){ // NullPointerException } } } } } public void screening(tradeagent arg0) { // order screening } private List<Stock> gettargetstock() { // gettargetstock InformationManager im = InformationManager.getInstance(); List<Stock> targetstocklist = new ArrayList(); for(stock stock:im.getstocklist()){ try{ if(getbuysignal(stock) == 1){ // (1: ) targetstocklist.add(stock); } }catch(nullpointerexception e){ // NullPointerException } } return targetstocklist; // } 14
3.4 private void checkportfolio() { // checkportfolio PortfolioManager pm = PortfolioManager.getInstance(); OrderManager om = OrderManager.getInstance(); for(portfolio portfolio:pm.getportfolio()){ try{ if(getsellsignal(portfolio.getstock()) == -1) { // (-1: ) portfolio.orderreversenowmarketall(); } }catch(nullpointerexception e){ // NullPointerException } } } double getbuysignal(stock stock){ // if(getkairisignal(stock) > 0 && getmacdsignal(stock) > 0 && getvolumeratiosignal(stock) > 0) { return 1.0; } // (MACP VR MACD ) /* if(getkairisignal(stock) > 0 && getrsisignal(stock) > 0 && getvolumeratiosignal(stock) > 0) { return 1.0; } */ // 3 (MACP VR RSI ) 15
3 1 /* if(getkairisignal(stock) > 0 && getvolumeratiosignal(stock) > 0) { return 1.0; } */ // (MACP VR ) return 0.0; // } double getsellsignal(stock stock){ // if(getmacdsignal(stock) < 0 && getkairisignal(stock) < 0) { return -1.0; } else if(getvolumeratiosignal(stock) < 0 && getkairisignal(stock) < 0) { return -1.0; } // (MACP VR MACD ) /* if(getrsisignal(stock) < 0 && getkairisignal(stock) < 0) { return -1.0; } else if(getvolumeratiosignal(stock) < 0 && getkairisignal(stock) < 0) { return -1.0; } */ // 3 (MACP VR RSI ) /* if(getvolumeratiosignal(stock) < 0 && getkairisignal(stock) < 0) { return -1.0; } 16
3.4 */ // (MACP VR ) return 0.0; // } double getkairisignal(stock stock){ // 26 MACP InformationManager im = InformationManager.getInstance(); int price = im.getstocksession(stock).getclosingprice(); // MovingAverage kairi = new MovingAverage(EnumAnalysisSpan.DAILY, 26); // 26 if((price-kairi.getindexsimple(stock))/kairi.getindexsimple(stock)*100 < -7){ // -7 return 1.0; } else if((price-kairi.getindexsimple(stock))/kairi.getindexsimple(stock)*100 > 5){ // 5 return -1.0; // } return 0.0; // } double getvolumeratiosignal(stock stock){ // 25 VolumeRatio VolumeRatio volumeratio = new VolumeRatio(EnumAnalysisSpan.DAILY,25); double volumeratioindex = volumeratio.getindex(stock); //VolumeRatio if(volumeratioindex < 70){ return 1.0; // 70 } else if(volumeratioindex > 250){ return -1.0; // 250 } return 0.0; // 17
3 1 } double getmacdsignal(stock stock) { // 12 26 MACD MACD macd = new MACD(EnumAnalysisSpan.DAILY,12,26,9); // 9 MACD if (macd.getindexmacd(stock) < 0) { return 1.0; // 0 } else if (macd.getindexmacd(stock) > 0) { return -1.0; // 0 } return 0.0; // } double getrsisignal(stock stock){ // 14 RSI RSI rsi = new RSI(EnumAnalysisSpan.DAILY,14); double rsiindex = rsi.getindexsimple(stock); //RSI if (rsiindex < 25) { return 1.0; // 25 } else if (rsiindex > 75) { return -1.0; // 75 } return 0.0; // } } 18
3.5 3.5 Eclipse 3.1. 3.1 3.5.1. 2004/09/22 08:00 ( ) 50,000,000 0 50,000,000 8766 0 17 // 8766 17 2004/09/22 09:00 ( ) ( ): 687 19
3 1 2004/09/22 11:30 ( ) // 1 1, 26,346,370 23,800,000 50,146,370 // ( ) : : : : 8766 : 2004/09/22 : 17 : 1,390,000 : 23,800,000 //. // 2004/09/22 12:30 ( ) ( ): 172 2004/09/22 16:00 ( ) // (, ) 26,346,370 23,800,000 50,146,370 // ( ) : : : : 8766 : 2004/09/22 : 17 : 1,390,000 : 23,800,000 2004/09/22 23:59 ( ) ( ): 31 20
3.5 3.5.2,. 2004/11/16 08:00 ( ) 854,904 54,335,000 55,189,904 // ( ) : : : : 5108 : 2004/10/27 : 1000 : 1,926 : 1,996,000 5108 : 2004/10/26 : 2000 : 1,874 : 3,992,000 8306 : 2004/09/28 : 7 : 892,000 : 6,811,000 8766 : 2004/09/22 : 17 : 1,390,000 : 26,350,000 8766 : 2004/09/27 : 9 : 1,380,000 : 13,950,000 8802 : 2004/10/27 : 1000 : 1,128 : 1,236,000 8306 0-7 // 8306( 7 ) 8766 0-17 8766 0-9 2004/11/16 09:00 ( ) ( ): 672 2004/11/16 11:30 ( ) // 1 1, 48,753,957 21
3 1 7,161,000 55,914,957 // ( ) : : : : 5108 : 2004/10/26 : 2000 : 1,874 : 3,946,000 5108 : 2004/10/27 : 1000 : 1,926 : 1,973,000 8802 : 2004/10/27 : 1000 : 1,128 : 1,242,000 2004/11/16 12:30 ( ) ( ): 312 2004/11/16 16:00 ( ) // (, ) 48,753,957 7,133,000 55,886,957 // ( ) : : : : 5108 : 2004/10/27 : 1000 : 1,926 : 1,964,000 5108 : 2004/10/26 : 2000 : 1,874 : 3,928,000 8802 : 2004/10/27 : 1000 : 1,128 : 1,241,000 2004/11/16 23:59 ( ) ( ): 0 22
4 3. 4.1 3 4.2 4.3 23
4 4.1 4.2 4.3 1 5,000 4493 4.4 20 1 4.1 20 1 3 1 3 10 18 11.54 8.3 16.77 19.48 7.95 4.01 12.49 9.43 225 1 5,000 4.2 1 24
4.2 (20 ) ( ) ( ) ( ) ( ) 8766 2004/9/22 17 1,390,000 2004/11/16 1,550,000 2,720,000 8766 2004/9/27 9 1,380,000 2004/11/16 1,550,000 12,708,000 8306 2004/9/28 7 892,000 2004/11/16 973,000 567,000 5108 2004/10/26 2000 1,874 2004/12/27 2,035 322,000 5108 2004/10/27 1000 1,926 2004/12/27 2,035 109,000 8802 2004/10/27 1000 1,128 2004/11/17 1,241 113,000 5401 2005/4/19 45000 253 2005/7/21 276 1,035,000 6301 2005/4/19 15000 741 2005/5/13 818 1,155,000 8604 2005/4/19 8200 1,375 2005/8/11 1,421 377,200 8802 2005/4/19 9000 1,206 2005/7/5 1,250 396,000 6301 2005/4/20 5000 764 2005/5/13 818 270,000 8604 2005/4/20 2700 1,396 2005/8/11 1,421 67,500 6301 2005/4/21 1000 747 2005/5/13 818 76,000 8604 2005/4/21 900 1,350 2005/8/11 1,421 63,900 8802 2005/4/21 1000 1,158 2005/7/5 1,250 92,000 8604 2005/4/22 200 1,383 2005/8/11 1,421 7,600 4689 2005/5/13 4 56,000 2005/6/30 58,500 10,000 9984 2005/5/13 100 1,352 2005/6/29 1,423 7,100 4.1 4.2 1 (). 25
5 2 5.1 1 20 1 30 50 1. 27
6 3. 6.1 3 6.2 6.3 29
6 6.1 6.2 6.3 1 5,000 4493 6.4 50 1 6.1 50 1 3 1 18 15 35 11.54 16.78 18.34 31.05 7.95 6.19 12.41 9.56 225 1 5,000 6.2 1 6.2 (50 ) ( ) ( ) ( ) ( ) 8766 2004/9/22 17 1,390,000 2004/11/16 1,550,000 2,720,000 6.2 () 4 19 6 20 9301 ( 1,120 1,092 ) 4 20 30
( ) ( ) ( ) ( ) 8766 2004/9/27 9 1,380,000 2004/11/16 1,550,000 1,530,000 8306 2004/9/28 5 892,000 2004/11/16 973,000 405,000 8564 2004/9/28 680 6,810 2005/1/12 7,310 340,000 4452 2004/10/1 1000 2,475 2005/8/31 2,625 150,000 9983 2004/10/22 300 6,600 2004/11/15 7,470 261,000 5108 2004/10/26 100 1,874 2004/12/27 2,035 16,100 8604 2004/10/28 100 1,352 2004/12/1 1,447 9,500 1662 2004/12/7 10500 3,860 2005/1/22 4,290 4,515,000 1662 2004/12/10 1000 3,790 2005/1/22 4,290 500,000 1332 2004/12/13 4300 310 2005/1/4 343 141,900 1662 2004/12/13 300 3,890 2005/1/22 4,290 120,000 5405 2005/4/18 82000 168 2005/6/20 193 2,050,000 5713 2005/4/18 19000 728 2005/6/15 746 342,000 8830 2005/4/18 12000 1,190 2005/6/24 1,249 708,000 3861 2005/4/19 2000 559 2005/8/31 579 40,000 5401 2005/4/19 5000 253 2005/7/21 276 115,000 5405 2005/4/19 7000 172 2005/6/20 193 147,000 5713 2005/4/19 1000 730 2005/6/15 746 16,000 6301 2005/4/19 1000 741 2005/5/13 818 77,000 8308 2005/4/19 6 198,000 2005/8/31 236,000 228,000 8403 2005/4/19 1000 651 2005/8/12 743 92,000 8604 2005/4/19 900 1,375 2005/8/11 1,421 41,400 8802 2005/4/19 1000 1,206 2005/7/5 1,250 44,000 8830 2005/4/19 1000 1,202 2005/6/24 1,249 47,000 9202 2005/4/19 3000 333 2005/8/31 362 87,000 9301 2005/4/19 1000 1,120 2005/6/20 1,092-28,000 9432 2005/4/19 2 438,000 2005/6/20 468,000 60,000 5405 2005/4/20 1000 182 2005/6/20 193 11,000 5713 2005/4/20 1000 761 2005/6/15 746-15,000 31
6 ( ) ( ) ( ) ( ) 6301 2005/4/20 1000 764 2005/5/13 818 54,000 8308 2005/4/20 1 199,000 2005/8/31 236,000 37,000 8604 2005/4/20 200 1,396 2005/8/11 1,421 5,000 9202 2005/4/20 1000 342 2005/8/31 362 20,000 8308 2005/4/21 1 194,000 2005/8/31 236,000 42,000 8604 2005/4/21 100 1,350 2005/8/11 1,421 7,100 8564 2005/4/22 10 6,600 2005/6/9 7,060 4,600 8604 2005/4/22 100 1,383 2005/8/11 1,421 3,800 1662 2005/5/17 200 4,040 2005/6/9 4,520 96,000 4689 2005/5/18 4 52,750 2005/6/30 58,500 23,000 1662 2005/5/19 100 4,060 2005/6/9 4,520 46,000 4689 2005/5/19 2 54,250 2005/6/30 58,500 8,500 1332 2005/8/16 105400 402 2005/8/31 403 105,400 6 15 5713 ( 761 746 ) 2 9301 6.5 5713 6.6 6.5 9301 6.6 5713 32
7 7.1 4.1 6.1. 3. MAC-D RSI MAC-D. ( 6.5 6.6). 2005 4 19 20 6 15 20. 4 18 19 127 42 20 22 72... 6 19 6 20. 33
7..... 7.2... 50.. 5,000 50 1 1 1. 34
.. 4. 1... 35
[1],,, 2006. 37
A A.1 2005 JAL (3 ) A.1 2005 JAL A.2 2006 JAL (3 ) A.2 2006 JAL 39
A A.3 ANA (3 ) A.3 ANA A.4 (3 ) A.4 A.5 NTT (3 ) A.5 NTT 40