Manual English Strategy

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Price Action and Pattern Trading Course Sample Book

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About this book

Technical analysis for the financial trading and investment has nearly several hundred years of history. Traders use the technical analysis to collect the scientific evidence to find out the probable market direction and volatility for their trading. When many people spot the same thing in the financial market, I think we should take it very carefully, especially if they are based on the scientific evidence. Price action and pattern trading strategies were extensively used by many successful traders to identify the trading opportunity to profits in the market. Price action and pattern trading strategies concern less on the traditional technical indicators. However, they concern more on raw price patterns. With the recent development of many brilliant trading strategies within the price action and pattern trading, their usefulness are already beyond the expectation of many of us.

As a quantitative developer and trader, my job allows me to explore nearly thousands of different trading strategies to validate and verify. Several price action and pattern trading strategies have shown me that their operating characteristics are much different from the typical momentum and mean reversion strategies. Those price action and pattern trading strategies are powerful. However, the idea behind these powerful trading strategies is poorly understood by many traders. Therefore, I decided to come up with the new concept “Equilibrium Fractal-Wave process” because I was not able to encapsulate many proven trading strategies used by traders last 85 year using the existing theory.

To accomplish the concept “Equilibrium Fractal-Wave process”, I had to create more comprehensive Price Pattern Table to explain those price action and pattern trading strategies outside the trend and seasonality framework, which are the backbone of the analysis techniques for univariate price series. The main purpose is to communicate with traders for the potential market dynamics for their profitable trading by spotting the existing phenomenon in the financial market.

This book is still geared up for your practical trading. Therefore, just explaining why the strategies work is probably not sufficient for traders. This book covers many working price action and pattern trading strategies in details and with examples. At the end of this book, we have also provided some useful information towards your trading management. Especially we emphasize the importance of the risk management in this book. I tried to offer the digestible information as much as I can even for average traders. In addition, many free tools are available from the website: “http://algotrading-investment.com” for free of charge. Especially, you might need the Peak Trough Analysis tool to follow some of the chapters in this book. You can freely download the Peak Trough Analysis tool from the same website above. Finally, reader should note that this book contains some strong technical language.

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Next Generation Technical Indicator

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Next Generation Technical Indicator

Harmonic Volatility Indicator

Introduction to Volatility in Financial Trading
Volatility is the most watched variable among the institutional traders because the market volatility have a direct impact on their trading risk. It is not easy to meet up any successful traders without emphasizing the importance of the volatility for their trading. In addition, we can even find countless trading strategies or trading courses based on the market volatility around us. In spite of its high importance, unfortunately, the access to the volatility tools for average traders are not easy in general. It is partly true that the library of the price based technical analysis is ever growing whereas the development in the volatility based technical analysis is almost halt after the invention of Bollinger bands in 1980s by John Bollinger. In general, you can find fewer number of the technical analysis tools based on the volatility in the most of trading or charting platforms. Here is the list of some popular volatility indicators for traders.
• Standard Deviation indicator
• Average True Range indicator
• True Range Indicator
• Keltner Channel
• Bollinger bands indicator
Regardless of fewer tools available to analyse the market volatility for traders, the high importance of watching market volatility will never change in the future.  Market can only move as much as the fuels available in the market. Therefore, watching the market volatility will never harm your trading but will do many good things for your trading.

Overview on the Harmonic Volatility Indicator
Harmonic Volatility Indicator was originally developed to overcome the limitation of Gann’s Angle, also known as Gann’s Fan. For this reason, trader can use Harmonic Volatility Indicator like Gann’s Angle (or Gann’s Fan). At the same time, the harmonic volatility indicator bases its core concept on the Volatility and Fibonacci analysis, which is distinctive from the Gann’s Angle. Therefore, the Harmonic Volatility Indicator can offer many other benefits, which are not offered by Gann’s Angle. In this article, we will talk about the Harmonic Volatility Indicator without comparing it to the Gann’s Angle because there are many traders who are not familiar with Gann’s technique.
 

One of the very distinctive characteristic of the Harmonic Volatility Indicator is that it provide the curved support and resistance lines. In our trading, we can find out many technical analysis providing us the horizontal support and resistance lines like daily pivot analysis and Fibonacci analysis, Harmonic pattern trading. We can find out some tools providing diagonal support and resistance lines, like rising wedge and falling wedge. As if combing horizontal and diagonal support and resistance can bring the synergy to your trading, you can combine the harmonic Volatility lines with typical horizontal support and resistance levels for your trading. Two screenshots below shows some example cases.
 

 

The Harmonic Volatility indicator can be running in the several different mode. Firstly, one can apply the Harmonic Volatility indicator at the open price of day, week or month assuming you are using the intraday chart in H4 or H1 or M15 timeframe. When you apply the Harmonic Volatility indicator at the open price of day, week or month, you are visually observing the market volatility of that timeframe in the sub timeframe (H4 or H1 or M15). You will not only find out that each Harmonic Volatility line will provide you important support and resistance levels for your trading but also you will find that you can combine them with many other existing technical analysis. This mode is simple and easy. In fact, our Double Harmonic Volatility Indicator can automatically find out the open price of day, week and month from your chart and it will apply the Harmonic Volatility Indicator in place for you. Therefore, you will not have to do this manually. Since this is simper mode of running the Harmonic Volatility Indicator, we recommend this mode generally.

You can also apply the Harmonic Volatility indicator to the significant peak and trough as if you apply the Fibonacci retracement in your chart. For example, where you place your Fibonacci retracement, you can always place the Harmonic Volatility indicator. To extend the application little further, you can apply two Harmonic Volatility Indicators at the same time running it in the double Harmonic Volatility Mode. In our Double Harmonic Volatility Indicator, you can use this double harmonic Volatility mode in the automatic manner. The indicator will recommend you the significant peak and trough automatically. Which mode you want to run the harmonic Volatility indicators is entirely up to your trading experience and preferences.

Traditional Volatility indicator VS Harmonic Volatility Indicator
You will find the benefits of the Harmonic Volatility Indicator quickly if we compare the traditional volatility indicator to Harmonic volatility indicator. Many traders uses Bollinger bands to measure the current market volatility. Many years ago, I was also the big user of the Bollinger bands for the mean reversion trading too. For example, buying when the price hit the upper bands of the Bollinger bands and selling when the price hit the lower bands. As you know, such a technique does not work. I will illustrate why they do not work. For an example, you might enjoy some reversal trading as shown in the screenshot below for some period. However, there will be time, the trick will not work anymore, circled in the red in the screenshot. Even if you increase the indicator period of your Bollinger bands or increase the standard deviation parameter, the results will not change because there is something fundamentally wrong. The fundamental problem is that you do not have the full picture of current market volatility but very limited picture from Bollinger bands. To see where our mistake was, please consider the next screenshot.

I have put the Harmonic Volatility Indicator to the week open price, which is running the weekly mode. In fact, the several sell pull back was happening because the market was testing the Sideways Market line of the Harmonic Volatility indicator, where the area between the two green Harmonic Volatility lines nearly have 33% probability coverage. In fact, when your Bollinger bands trick did not work, the market was trying to breakout its state from sideways to trendy market. Now you know where the things gone wrong. It was simply because you missed to have the full picture of market volatility. This is not hard math either. Anyone can understand that we will get 33% (0.3333) if we divide the probability 1 by 3. Therefore, we can account for the three market states including bullish, bearish and sideways market.

 

Identifying mature trend in its end phase
Another excellent benefit of the Harmonic Volatility Indicator is its capability to identify the mature trend in its end phase. As we have mentioned before, the market can move as much as the fuel available in the market. Once the fuel is exhausted, the airplane have to come down to the earth. To illustrate this, please consider next screenshot. There is very thin chance for the price to move outside the last Harmonic Volatility line (red line). If they do, then it indicates that market fuel is almost exhausted. It is likely that the price will change its direction at this point, at least for short period. Pointing out this reversal moment is not difficult just watch out if the price move outside the last Harmonic Volatility line.

One practical way of applying this technique is to apply the Harmonic Volatility Indicator in the second point of your Fibonacci retracement. With strong momentum in the current trend, you will find that many trade opportunities. If you want to base your trading strategy exclusively on identifying mature trend or turning point, then switch off all other lines except the last Harmonic Volatility line (Red line) and few others.
 

Improving market timing with the Volatility tuned with Fibonacci analysis
Use of the Fibonacci analysis for financial trading can nearly go back to 85 years from today since the birth of Elliott Wave Theory by R. N. Elliott. Until now, traders use the Fibonacci analysis to identify the patterns in the price series mostly. Yet, we could not find any one attempted to use Fibonacci analysis for the Volatility. The Harmonic Volatility Indicator was the first approach of applying Fibonacci analysis to the Volatility instead of price series. The Harmonic Volatility Indicator uses the Golden ratio 0.618 and its direct derivative only, for example, 0.618^2, 0.618^3, etc, for its Fibonacci analysis. So what is the benefits? Generally, the Harmonic Volatility Indicator is supportive for mean reversion trading strategy. Therefore, often the Harmonic Volatility Indicator can work with oscillators like RSI, CCI, Stoch, etc. It can also work well with Harmonic pattern trading too. Two screenshots below shows some example cases.

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Harmonic Volatility Indicator

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About this book

Gann’s angle was one of the very first concept using the geometric study between price and time for practical trading (Gann, 1935). In spite of the powerful idea behind the Gann’s angle, the chart scaling issue makes the Gann’s angle less practical for traders. In this book, we suggested the alternative approach of establishing the geometric relationship between price and time through probability. We showed how we created the Harmonic Volatility Line indicator using this alternative approach. The Harmonic Volatility Line indicator is not suffering from the chart scaling issue like Gann’s angle does. At the same time, the Harmonic Volatility Line indicator offers many functionality similar to the Gann’s angle. This book introduced how the Harmonic Volatility Line indicator could be used for market forecasting, turning point prediction, supports and resistances for traders in details. In spite of its wonderful features, the Harmonic Volatility Line indicator is still not bullet proof trading system. It requires discipline and knowledge to use for trading like Gann’s angle does. This book was published on behalf of http://algotrading-investment.com. However, the original creation of Harmonic Volatility Line indicator was done by Young Ho Seo after spending years of time on doing empirical research and strategy building in the Forex, Stock and Futures markets.

 

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Technical Indicator Library Excel Formula

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Technical Indicator Library Excel formula

Below we list Excel formula to call technical indicator library from your Excel. All these technical indicator functions are located inside TechnicalAnlaysis.xll file. TechnicalAnalysis.xll files are free to use and free to share without any limitation. We have put some friendly Copy Right Notice on the bottom of this document to protect the developers and contributor. In general, this TechnicalAnalysis.xll file and Technical Indicator library inside the file can be used by anyone and it is free of charge. To use these functions from your Excel, you should load the TechnicalAnlaysis.xll add-in to your Excel first. For the paid users for Quant Strategy Inventor, the installation can be done automatically when you first load our Quant Strategy Inventor. For free users of this TechnicalAnlaysis.xll, please follow the simple installation steps below.

1. Install TechnicalAnalysis.xll file
To install TechnicalAnlaysis.xll file, go to Options in your Excel. Then select Add-ins.

When the Add-Ins manager pop up, click on Browse button and select the TechnicalAnalysis.xll file from your hard drive.

Once TechnicalAnalysis.xll files are loaded in your Excel. You can call any of User Defined Function below to build various trading strategies from your Excel. Above installation step can be skipped for paid users of our Quant Strategy Inventor. Below, we list the all the available Technical and Mathematical Function you can call with TechnicalAnalysis.xll file.
2. Example Usage of Functions

All the functions are array formula. Therefore, you have to enter these formula using “Ctrl +Shift+Enter” keys. You should include “=TA_” syntax before Function name.

For example, for following Bollinger Bands function below:

BBANDS – Bollinger Bands
upperband, middleband, lowerband = BBANDS(close, timeperiod=5, nbdevup=2, nbdevdn=2, matype=0)
You will enter “=TA_BBANDS(I7:I30, 12, 2, 2, 1)” to range L7:N30 assuming your price data are located at the range E6:K30.

We can take another example for CCI function as shown below.
CCI – Commodity Channel Index
real = CCI(high, low, close, timeperiod=14)
Here is how to put this CCI function in your worksheet. “=TA_CCI(G7:G30, H7:H30, I7:I30, 13)” to range L7:L30 assuming your price data are located at the range E6:K30.

3. Overlap Studies Functions

BBANDS – Bollinger Bands
upperband, middleband, lowerband = BBANDS(close, timeperiod=5, nbdevup=2, nbdevdn=2, matype=0)

DEMA – Double Exponential Moving Average
real = DEMA(close, timeperiod=30)

EMA – Exponential Moving Average
real = EMA(close, timeperiod=30)

HT_TRENDLINE – Hilbert Transform – Instantaneous Trendline
real = HT_TRENDLINE(close)

KAMA – Kaufman Adaptive Moving Average
real = KAMA(close, timeperiod=30)

MA – Moving average
real = MA(close, timeperiod=30, matype=0)

MAMA – MESA Adaptive Moving Average
mama, fama = MAMA(close, fastlimit=0, slowlimit=0)

MAVP – Moving average with variable period
real = MAVP(close, periods, minperiod=2, maxperiod=30, matype=0)

MIDPOINT – MidPoint over period
real = MIDPOINT(close, timeperiod=14)

MIDPRICE – Midpoint Price over period
real = MIDPRICE(high, low, timeperiod=14)

SAR – Parabolic SAR
real = SAR(high, low, acceleration=0, maximum=0)

SAREXT – Parabolic SAR – Extended
real = SAREXT(high, low, startvalue=0, offsetonreverse=0, accelerationinitlong=0, accelerationlong=0, accelerationmaxlong=0, accelerationinitshort=0, accelerationshort=0, accelerationmaxshort=0)

SMA – Simple Moving Average
real = SMA(close, timeperiod=30)

T3 – Triple Exponential Moving Average (T3)
real = T3(close, timeperiod=5, vfactor=0)

TEMA – Triple Exponential Moving Average
real = TEMA(close, timeperiod=30)

TRIMA – Triangular Moving Average
real = TRIMA(close, timeperiod=30)

WMA – Weighted Moving Average
real = WMA(close, timeperiod=30)

4. Oscillator Indicators

ADX – Average Directional Movement Index
real = ADX(high, low, close, timeperiod=14)

ADXR – Average Directional Movement Index Rating
real = ADXR(high, low, close, timeperiod=14)

APO – Absolute Price Oscillator
real = APO(close, fastperiod=12, slowperiod=26, matype=0)

AROON – Aroon
aroondown, aroonup = AROON(high, low, timeperiod=14)

AROONOSC – Aroon Oscillator
real = AROONOSC(high, low, timeperiod=14)

BOP – Balance Of Power
real = BOP(open, high, low, close)

CCI – Commodity Channel Index
real = CCI(high, low, close, timeperiod=14)

CMO – Chande Momentum Oscillator
real = CMO(close, timeperiod=14)

DX – Directional Movement Index
real = DX(high, low, close, timeperiod=14)

MACD – Moving Average Convergence/Divergence
macd, macdsignal, macdhist = MACD(close, fastperiod=12, slowperiod=26, signalperiod=9)

MACDEXT – MACD with controllable MA type
macd, macdsignal, macdhist = MACDEXT(close, fastperiod=12, fastmatype=0, slowperiod=26, slowmatype=0, signalperiod=9, signalmatype=0)

MACDFIX – Moving Average Convergence/Divergence Fix 12/26
macd, macdsignal, macdhist = MACDFIX(close, signalperiod=9)

MFI – Money Flow Index
real = MFI(high, low, close, volume, timeperiod=14)

MINUS_DI – Minus Directional Indicator
real = MINUS_DI(high, low, close, timeperiod=14)

MINUS_DM – Minus Directional Movement
real = MINUS_DM(high, low, timeperiod=14)

MOM – Momentum
real = MOM(close, timeperiod=10)

PLUS_DI – Plus Directional Indicator
real = PLUS_DI(high, low, close, timeperiod=14)

PLUS_DM – Plus Directional Movement
real = PLUS_DM(high, low, timeperiod=14)

PPO – Percentage Price Oscillator
real = PPO(close, fastperiod=12, slowperiod=26, matype=0)

ROC – Rate of change : ((price/prevPrice)-1)*100
real = ROC(close, timeperiod=10)

ROCP – Rate of change Percentage: (price-prevPrice)/prevPrice
real = ROCP(close, timeperiod=10)

ROCR – Rate of change ratio: (price/prevPrice)
real = ROCR(close, timeperiod=10)

ROCR100 – Rate of change ratio 100 scale: (price/prevPrice)*100
real = ROCR100(close, timeperiod=10)

RSI – Relative Strength Index
real = RSI(close, timeperiod=14)

STOCH – Stochastic
slowk, slowd = STOCH(high, low, close, fastk_period=5, slowk_period=3, slowk_matype=0, slowd_period=3, slowd_matype=0)

STOCHF – Stochastic Fast
fastk, fastd = STOCHF(high, low, close, fastk_period=5, fastd_period=3, fastd_matype=0)

STOCHRSI – Stochastic Relative Strength Index
fastk, fastd = STOCHRSI(close, timeperiod=14, fastk_period=5, fastd_period=3, fastd_matype=0)

TRIX – 1-day Rate-Of-Change (ROC) of a Triple Smooth EMA
real = TRIX(close, timeperiod=30)

ULTOSC – Ultimate Oscillator
real = ULTOSC(high, low, close, timeperiod1=7, timeperiod2=14, timeperiod3=28)

WILLR – Williams’ %R
real = WILLR(high, low, close, timeperiod=14)

5. Volume Indicators

AD – Chaikin A/D Line
real = AD(high, low, close, volume)

ADOSC – Chaikin A/D Oscillator
real = ADOSC(high, low, close, volume, fastperiod=3, slowperiod=10)

OBV – On Balance Volume
real = OBV(close, volume)

6. Volatility Indicators

ATR – Average True Range
real = ATR(high, low, close, timeperiod=14)

NATR – Normalized Average True Range
real = NATR(high, low, close, timeperiod=14)

TRANGE – True Range
real = TRANGE(high, low, close)

7. Price Transformation

AVGPRICE – Average Price
real = AVGPRICE(open, high, low, close)

MEDPRICE – Median Price
real = MEDPRICE(high, low)

TYPPRICE – Typical Price
real = TYPPRICE(high, low, close)

WCLPRICE – Weighted Close Price
real = WCLPRICE(high, low, close)

8. Cycle Indicator Functions

HT_DCPERIOD – Hilbert Transform – Dominant Cycle Period
real = HT_DCPERIOD(close)

HT_DCPHASE – Hilbert Transform – Dominant Cycle Phase
real = HT_DCPHASE(close)

HT_PHASOR – Hilbert Transform – Phasor Components
inphase, quadrature = HT_PHASOR(close)

HT_SINE – Hilbert Transform – SineWave
sine, leadsine = HT_SINE(close)

HT_TRENDMODE – Hilbert Transform – Trend vs Cycle Mode
integer = HT_TRENDMODE(close)

9. Pattern Recognition Functions

CDL2CROWS – Two Crows
integer = CDL2CROWS(open, high, low, close)

CDL3BLACKCROWS – Three Black Crows
integer = CDL3BLACKCROWS(open, high, low, close)

CDL3INSIDE – Three Inside Up/Down
integer = CDL3INSIDE(open, high, low, close)

CDL3LINESTRIKE – Three-Line Strike
integer = CDL3LINESTRIKE(open, high, low, close)

CDL3OUTSIDE – Three Outside Up/Down
integer = CDL3OUTSIDE(open, high, low, close)

CDL3STARSINSOUTH – Three Stars In The South
integer = CDL3STARSINSOUTH(open, high, low, close)

CDL3WHITESOLDIERS – Three Advancing White Soldiers
integer = CDL3WHITESOLDIERS(open, high, low, close)

CDLABANDONEDBABY – Abandoned Baby
integer = CDLABANDONEDBABY(open, high, low, close, penetration=0)

CDLADVANCEBLOCK – Advance Block
integer = CDLADVANCEBLOCK(open, high, low, close)

CDLBELTHOLD – Belt-hold
integer = CDLBELTHOLD(open, high, low, close)

CDLBREAKAWAY – Breakaway
integer = CDLBREAKAWAY(open, high, low, close)

CDLCLOSINGMARUBOZU – Closing Marubozu
integer = CDLCLOSINGMARUBOZU(open, high, low, close)

CDLCONCEALBABYSWALL – Concealing Baby Swallow
integer = CDLCONCEALBABYSWALL(open, high, low, close)

CDLCOUNTERATTACK – Counterattack
integer = CDLCOUNTERATTACK(open, high, low, close)

CDLDARKCLOUDCOVER – Dark Cloud Cover
integer = CDLDARKCLOUDCOVER(open, high, low, close, penetration=0)

CDLDOJI – Doji
integer = CDLDOJI(open, high, low, close)

CDLDOJISTAR – Doji Star
integer = CDLDOJISTAR(open, high, low, close)

CDLDRAGONFLYDOJI – Dragonfly Doji
integer = CDLDRAGONFLYDOJI(open, high, low, close)

CDLENGULFING – Engulfing Pattern
integer = CDLENGULFING(open, high, low, close)

CDLEVENINGDOJISTAR – Evening Doji Star
integer = CDLEVENINGDOJISTAR(open, high, low, close, penetration=0)

CDLEVENINGSTAR – Evening Star
integer = CDLEVENINGSTAR(open, high, low, close, penetration=0)

CDLGAPSIDESIDEWHITE – Up/Down-gap side-by-side white lines

integer = CDLGAPSIDESIDEWHITE(open, high, low, close)

CDLGRAVESTONEDOJI – Gravestone Doji
integer = CDLGRAVESTONEDOJI(open, high, low, close)

CDLHAMMER – Hammer
integer = CDLHAMMER(open, high, low, close)

CDLHANGINGMAN – Hanging Man
integer = CDLHANGINGMAN(open, high, low, close)

CDLHARAMI – Harami Pattern
integer = CDLHARAMI(open, high, low, close)

CDLHARAMICROSS – Harami Cross Pattern
integer = CDLHARAMICROSS(open, high, low, close)

CDLHIGHWAVE – High-Wave Candle
integer = CDLHIGHWAVE(open, high, low, close)

CDLHIKKAKE – Hikkake Pattern
integer = CDLHIKKAKE(open, high, low, close)

CDLHIKKAKEMOD – Modified Hikkake Pattern
integer = CDLHIKKAKEMOD(open, high, low, close)

CDLHOMINGPIGEON – Homing Pigeon
integer = CDLHOMINGPIGEON(open, high, low, close)

CDLIDENTICAL3CROWS – Identical Three Crows
integer = CDLIDENTICAL3CROWS(open, high, low, close)

CDLINNECK – In-Neck Pattern
integer = CDLINNECK(open, high, low, close)

CDLINVERTEDHAMMER – Inverted Hammer
integer = CDLINVERTEDHAMMER(open, high, low, close)

CDLKICKING – Kicking
integer = CDLKICKING(open, high, low, close)

CDLKICKINGBYLENGTH – Kicking – bull/bear determined by the longer marubozu
integer = CDLKICKINGBYLENGTH(open, high, low, close)

CDLLADDERBOTTOM – Ladder Bottom
integer = CDLLADDERBOTTOM(open, high, low, close)

CDLLONGLEGGEDDOJI – Long Legged Doji
integer = CDLLONGLEGGEDDOJI(open, high, low, close)

CDLLONGLINE – Long Line Candle
integer = CDLLONGLINE(open, high, low, close)

CDLMARUBOZU – Marubozu
integer = CDLMARUBOZU(open, high, low, close)

CDLMATCHINGLOW – Matching Low
integer = CDLMATCHINGLOW(open, high, low, close)

CDLMATHOLD – Mat Hold
integer = CDLMATHOLD(open, high, low, close, penetration=0)

CDLMORNINGDOJISTAR – Morning Doji Star
integer = CDLMORNINGDOJISTAR(open, high, low, close, penetration=0)

CDLMORNINGSTAR – Morning Star
integer = CDLMORNINGSTAR(open, high, low, close, penetration=0)

CDLONNECK – On-Neck Pattern
integer = CDLONNECK(open, high, low, close)

CDLPIERCING – Piercing Pattern
integer = CDLPIERCING(open, high, low, close)

CDLRICKSHAWMAN – Rickshaw Man
integer = CDLRICKSHAWMAN(open, high, low, close)

CDLRISEFALL3METHODS – Rising/Falling Three Methods
integer = CDLRISEFALL3METHODS(open, high, low, close)

CDLSEPARATINGLINES – Separating Lines
integer = CDLSEPARATINGLINES(open, high, low, close)

CDLSHOOTINGSTAR – Shooting Star
integer = CDLSHOOTINGSTAR(open, high, low, close)

CDLSHORTLINE – Short Line Candle
integer = CDLSHORTLINE(open, high, low, close)

CDLSPINNINGTOP – Spinning Top
integer = CDLSPINNINGTOP(open, high, low, close)

CDLSTALLEDPATTERN – Stalled Pattern
integer = CDLSTALLEDPATTERN(open, high, low, close)

CDLSTICKSANDWICH – Stick Sandwich
integer = CDLSTICKSANDWICH(open, high, low, close)

CDLTAKURI – Takuri (Dragonfly Doji with very long lower shadow)
integer = CDLTAKURI(open, high, low, close)

CDLTASUKIGAP – Tasuki Gap
integer = CDLTASUKIGAP(open, high, low, close)

CDLTHRUSTING – Thrusting Pattern
integer = CDLTHRUSTING(open, high, low, close)

CDLTRISTAR – Tristar Pattern
integer = CDLTRISTAR(open, high, low, close)

CDLUNIQUE3RIVER – Unique 3 River
integer = CDLUNIQUE3RIVER(open, high, low, close)

CDLUPSIDEGAP2CROWS – Upside Gap Two Crows
integer = CDLUPSIDEGAP2CROWS(open, high, low, close)

CDLXSIDEGAP3METHODS – Upside/Downside Gap Three Methods
integer = CDLXSIDEGAP3METHODS(open, high, low, close)

10. Statistics Functions

BETA – Beta
real = BETA(high, low, timeperiod=5)

CORREL – Pearson’s Correlation Coefficient (r)
real = CORREL(high, low, timeperiod=30)

LINEARREG – Linear Regression
real = LINEARREG(close, timeperiod=14)

LINEARREG_ANGLE – Linear Regression Angle
real = LINEARREG_ANGLE(close, timeperiod=14)

LINEARREG_INTERCEPT – Linear Regression Intercept
real = LINEARREG_INTERCEPT(close, timeperiod=14)

LINEARREG_SLOPE – Linear Regression Slope
real = LINEARREG_SLOPE(close, timeperiod=14)

STDDEV – Standard Deviation
real = STDDEV(close, timeperiod=5, nbdev=1)

TSF – Time Series Forecast
real = TSF(close, timeperiod=14)

VAR – Variance
real = VAR(close, timeperiod=5, nbdev=1)

11. Math Transform Functions

ACOS – Vector Trigonometric ACos
real = ACOS(close)

ASIN – Vector Trigonometric ASin
real = ASIN(close)

ATAN – Vector Trigonometric ATan
real = ATAN(close)

CEIL – Vector Ceil
real = CEIL(close)

COS – Vector Trigonometric Cos
real = COS(close)

COSH – Vector Trigonometric Cosh
real = COSH(close)

EXP – Vector Arithmetic Exp
real = EXP(close)

FLOOR – Vector Floor
real = FLOOR(close)

LN – Vector Log Natural
real = LN(close)

LOG10 – Vector Log10
real = LOG10(close)

SIN – Vector Trigonometric Sin
real = SIN(close)

SINH – Vector Trigonometric Sinh
real = SINH(close)

SQRT – Vector Square Root
real = SQRT(close)

TAN – Vector Trigonometric Tan
real = TAN(close)

TANH – Vector Trigonometric Tanh
real = TANH(close)

12. Math Operator Functions

ADD – Vector Arithmetic Add
real = ADD(high, low)

DIV – Vector Arithmetic Div
real = DIV(high, low)

MAX – Highest value over a specified period
real = MAX(close, timeperiod=30)

MAXINDEX – Index of highest value over a specified period
integer = MAXINDEX(close, timeperiod=30)

MIN – Lowest value over a specified period
real = MIN(close, timeperiod=30)

MININDEX – Index of lowest value over a specified period
integer = MININDEX(close, timeperiod=30)

MINMAX – Lowest and highest values over a specified period
min, max = MINMAX(close, timeperiod=30)

MINMAXINDEX – Indexes of lowest and highest values over a specified period
minidx, maxidx = MINMAXINDEX(close, timeperiod=30)

MULT – Vector Arithmetic Mult
real = MULT(high, low)

SUB – Vector Arithmetic Substraction
real = SUB(high, low)

SUM – Summation
real = SUM(close, timeperiod=30)

TechnicalAnlaysis.xll file is free to use for everyone and redistributable without any limitation. To protect the developers and contributors, the following copyright notice should be included when this file is redistributed or when the file is used.
THIS SOFTWARE IS PROVIDED “AS IS” AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE DEVELOPERS AND CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Instruction (Manual) Document

This part should be filled by author before your submission.

1. Information about Author
Your Surname ATI
Your First Name   ATI
Your Country ATI
Your Email Address ATI
Your ID on our website ATI

2. Information for the submitted materials
Title of the submitted instruction or manual Technical Indicator Library Excel Formula
Language of Instruction English
Key words (at least 3) Forex, Stock, Investment, Trading, optimization, simulation, backtesting, technical analysis, economic analysis, Quantitative Trading
Date of Completion 21 October 2016
Version of this Document 1.0

3. If it is about any trading platform or any of our products (leave empty if you don’t use)
Name of Trading Platform Quant Strategy Inventor
Trading Platform version Version 5.16R
Name of Product Quant Strategy Inventor
Product version 5.16R

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Build First VBA Strategy with Quant Strategy Inventor

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Build First VBA Strategy with Quant Strategy Inventor

Flexible Quantitative Strategy Builder for Forex, Stock and Future Market

Tutorial Overview
Quant Strategy Inventor is the powerful Excel based software to create profitable strategy for Stock, Forex and Future market. With Quant Strategy Inventor, you can create the profitable trading strategies. You can analyse and predict financial markets. You can construct your own active and passive portfolio like the fund manager. You can do all this without pain of learning any programming language like C++, C sharp, MQL4, MQL5, Easy Language, MatLab, etc. Instead, you can do everything in your Excel Spreadsheet from backtesting to optimization of your trading strategy using simple spreadsheet formula. Or if you prefer, then you can still use full VBA code to build your trading strategy In this document, we introduce how to create your own trading strategy using VBA formula. Since this is for first time user, we have put quite a lot of screenshots for better understanding. So get your Excel ready before you go through next steps. There may be quite a lot of similarity with the previous article “Build First VBA Strategy with Quant Strategy Inventor”. To follow these steps, we assumed that you have already installed our Quant Strategy Inventor in your Excel.
To build your trading strategy with VBA, there is two ways of doing the same job. Firstly, you can build your trading strategy in the fresh new workbook. Secondly, you can build your trading strategies in Quant Strategy Inventor_v5.xx.xlsm workbook. Both way will work for you. However when you build hundreds of trading strategies, it is better to use new fresh workbook for each strategy. We already shipped our Quant Strategy Inventor_v5.xx.xlsm file with several strategies. In this tutorial, we will show you how to build our VBA trading strategy using the fresh new workbook.
To do so, firstly open our Quant Strategy Inventor_v5.xx.xlsm file. I hope you have already completed installation and license activation. You can already see there are several strategies in your spreadsheets in the Quant Strategy Inventor_v5.xx.xlsm. Let us ignore them for now because they were built in using Excel Spreadsheet formula. Do not change or alter anything in this workbook since we will create new workbook to build our strategy.

We will create Macro Enabled Workbook since we will use VBA code. To create new blank workbook, just go to File menu and select New. Select Blank workbook.

Then, save it as My Test VBA Strategy.xlsm file in your hard drive. Now you have your fresh blank workbook ready for you. You will proceed to Data Steps as usual.

Even in the new workbook, you should be able to access to our Quant Strategy Inventor Menu. All of them should work.

Sometimes, you may not see our Quant Strategy Inventor menu in your new workbook. It is fine. Simply go to your Developer’s ribbon. Then click on Macros menu.

Now you will see List of macros available from your workbook. Then select “StartQSI” macro and click “Run” button. Assuming that you have your license is installed correctly and your Quant Strategy Inventor_v5.xx.xlsm file is already opened, you should be able to access to Quant Strategy Inventor menu from your new workbook. Now we will proceed to typical strategy building process. The first step is, as usual, data step.

Step 1 – Data Steps
You can use any data you want to build your strategy with our Quant Strategy Inventor including Forex, Stock, Future, etc.  From our Basic Module 1, you can download most of US and non-US stock data. If you want to build Forex trading strategy, then you can just pull historical data from your Meta Trader. In this tutorial, for simplicity we will use stock price of the Microsoft Corp to build our VBA trading strategy. If you do not have data already, then you will need to collect data to build your strategy. To do so, you need to know the ticker or symbol name for Microsoft Corp. Just type MSFT somewhere in your spreadsheet. Download data using our Basic Module 1.

In the Basic Module 1, you have data download tab and data simulation tab. In the data simulation tab, you can simulate around 11 different mathematical models to generate artificial data for you to study your trading and investment strategies. Here we will just use data download module only for simplicity. You can always play around with different feature of Quant Strategy Inventor later.

To download data, click Ticker Range and then select MSFT on your spreadsheet (i.e. only select MSFT since we only need Microsoft data for now.) Once you have downloaded with Microsoft data. We are done for our data step.

Step 2 – Signal Steps
In VBA, you can do anything you want. It is very flexible. You can create your own technical and price action indicator or any mathematical models for your trading. For simplicity and educational purpose, we will use simple Bollinger bands for our trading strategy. We can build our own Bollinger bands in VBA code but we will use easier route. We will just use the built-in Bollinger Bands technical indicators to save time.

So we will just enter the syntax “=TA_BBANDS(I11:I1467, $L$4, $M$4, $M$4)” to our range L11:N1467. Remember that this is array formula too. So you have to enter the formula using “Ctrl+Shift+Enter” key at the same time. We have placed our indicator period and standard deviation level respectively to L4 and M4 cells. We have already structured our input control this way just in case we want to do some optimization later. Once you have entered the formula correctly, you will get upper, middle and lower bands from left to right.

Our sample trading strategy here is that we will buy if the price hit upper Bollinger bands level and likewise we will sell if the price hit lower Bollinger bands. This is typical momentum trading strategy. We buy when there is momentum. We do not know yet whether this will work for Microsoft or now. In fact the whole purpose of this tutorial is to find out the profitability of this strategy.  We just chosen this example for educational purpose for now. Next bit is fun bit, since we are going to do some VBA coding. To start VBA coding, just click on Developer’s Ribbon again. Then click “Visual Basic” menu.

Ok, now you can see the famous visual basic editor used by millions of analyst and traders every day. Soon you will be one of them too.  In this tutorial, we will build what we called User Defined Function to generate our signal with Bollinger Bands.

To do so firstly insert new Module. The Module is where we can put our code. Once module is created, you will just see blank page where you can start to build your code.

Now we will create a user defined function for our signal. I named it as BBandsStrategy. You can name it to anything you want. In the code below, pRange is price range for Micro soft and iRange is indicator range for our Bollinger bands. I have put some variables we need later. For example, I declared r and c variable to loop through our price and indicator later. As you can see, you can just use all general VBA coding style as you need. “buy_sell_sig” variable is where we will hold our buy and sell signal.

Now here is important code block which we will actually generate signal from. What we try to do here is that we are collecting price data using pRange and indicator values using iRange. Then we compare close price with upper and lower bands level to generate signal. Make sure that we need to check our price and indicator values are numeric values first. If you don’t, you might get error. So let us be more protective. Since upper and lower bands values are stored in first and third columns, we collect the values using iRange.cells(r, 1) and iRange.cells(r, 3). Likewise, we collect our close price for Microsoft suing pRange.cells(r, 4).  “r” is the row number in our spreadsheet. Buy condition is easy to create. It is simply if close price is greater than upper bands, then we generate signal 1. Likewise, if close price is smaller than lower bands, then we generate signal -1 for sell. Then we will loop through all the close prices in our Microsoft data and store our signal in the “buy_sell_sig”. Then return these signals to end of our function.

Ok, our User Defined Function for Bollinger Bands signal is ready. Now let go back to our Spreadsheet and use this User Defined Function. Since this is array formula again, enter “=BBandsStrategy(F11:I1467, L11:N1467)” to the range  O11:P1467 with “Ctrl+Shift+Enter”. Well you can see that our Function works fine generate signal 1 or -1 according to our trading rules.

Now let us do our order steps. We assume that you have already read our Previous article Build First Trading Strategy with Quant Strategy Inventor. So we will enter this syntax for our buy order:
“=OrderOpenBuy_(O11:O1467, 1000, 0, 0,”na”, 1)”.
This syntax says that we will buy 1000 Microsoft shares when buy signal shows up. We will assign this strategy as ID 1. We will do the same for our buy close, sell open and sell close.

Ok I assume that you have completed all. Now let us run our backtesting to see if this strategy is really making money. So click Analytic Module 1 and open Backtesting Stock page. Fill the price range, Order range, and then run the backtesting.

The balance Growth Curve is not so impressive for our first VBA code strategy. Microsoft is not so working well with our momentum strategy.

So let us try to use mean reversion trading strategy just tweaking our previous strategy. In contrast to our previous trading set up, we will buy if the close price is hit lower bands and likewise, we will sell if the close price is hit upper bands. So we are setting up the trading rules the other way around to our previous trading rules. This is how the code looks like for our second VBA strategy. Literarily we buy when the prices hit the lower bands and sell when the prices hits the upper bands.

Make sure that you are re-entering the formula again just to refresh the values in your worksheet. Let us do the backtesting again. Ok, now our Balance Growth Curve is rather going up. So we might say that Microsoft Stock prefer mean reversion type of trading strategy.

Let us do further optimize for the indicator period and the standard deviation values. With optimization, we can find better settings. Let us select the most profitable setting from this educational strategy and do the backtesting again.

Ok after optimization, the profit have been improved quite a lot. I guess this was good exercise for you to learn how flexibly you can build trading strategy with our Quant Strategy Inventor.

The “My Test VBA Strategy.xlsm” file is shipped together. So you can find the sample VBA strategy file inside your QuantStrategyInventor.zip file. However, just in case, we will list all our code here too. This is simple strategy but you can always expand this simple strategy into more complex and serous one later as your VBA coding skills get better. Just copy and paste this code to your VB editor to start with.

Sample VBA Code for our sample Strategy

Option Explicit
Function BBandsStrategy(pRange As Range, iRange As Range)
Dim buy_sell_sig() As Variant
Dim r As Long ‘r = row counter
Dim c As Long ‘c = column counter

Dim rowSize As Long
Dim colSize As Long
rowSize = iRange.Rows.Count
colSize = iRange.Columns.Count

ReDim buy_sell_sig(1 To rowSize, 1 To 2)

Dim b_upper As Double
Dim b_lower As Double
Dim p_close As Double
Dim curSignal As Integer
curSignal = 0

For r = 1 To rowSize
If IsNumeric(iRange.Cells(r, 1).Value) = True And IsNumeric(pRange.Cells(r, 4).Value) Then
b_upper = CDbl(iRange.Cells(r, 1).Value)
b_lower = CDbl(iRange.Cells(r, 3).Value)
p_close = CDbl(pRange.Cells(r, 4).Value)

‘        ‘Buy Signal Condition
‘        If p_close > b_upper Then
‘            If curSignal = 0 Or curSignal = -1 Then
‘                buy_sell_sig(r, 1) = 1
‘                curSignal = 1
‘            End If

‘        End If

‘        ‘Sell Signal Condition
‘        If p_close < b_lower Then
‘            If curSignal = 0 Or curSignal = 1 Then
‘                buy_sell_sig(r, 2) = -1
‘                curSignal = -1
‘            End If
‘        End If

        ‘Buy Signal Condition
If p_close < b_lower Then
If curSignal = 0 Or curSignal = -1 Then
buy_sell_sig(r, 1) = 1
curSignal = 1
End If
End If

        ‘Sell Signal Condition
If p_close > b_upper Then
If curSignal = 0 Or curSignal = 1 Then
buy_sell_sig(r, 2) = -1
curSignal = -1
End If
End If

    End If
Next r

BBandsStrategy = buy_sell_sig

End Function

Instruction (Manual) Document

This part should be filled by author before your submission.

1. Information about Author
Your Surname ATI
Your First Name   ATI
Your Country ATI
Your Email Address ATI
Your ID on our website ATI

2. Information for the submitted materials
Title of the submitted instruction or manual Build VBA Trading Strategy with Quant Strategy Inventor
Language of Instruction English
Key words (at least 3) Forex, Stock, Investment, Trading, optimization, simulation, backtesting, technical analysis, economic analysis, Quantitative Trading
Date of Completion 21 October 2016
Version of this Document 1.0

3. If it is about any trading platform or any of our products (leave empty if you don’t use)
Name of Trading Platform Quant Strategy Inventor
Trading Platform version Version 5.16R
Name of Product Quant Strategy Inventor
Product version 5.16R

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Build First Trading Strategy with Quant Strategy Inventor

Below is the Text Only Excerpt automatically extracted From the Full PDF Article for Non PDF Viewer:   

Build First Trading Strategy with Quant Strategy Inventor

Flexible Quantitative Strategy Builder for Forex and Stock Market

Quant Strategy Inventor Overview
Quant Strategy Inventor is the powerful Excel based software to create profitable strategy for Stock and Forex market. With Quant Strategy Inventor, you can create the profitable trading strategies. You can analyse and predict financial markets. You can construct your own active and passive portfolio like the fund manager. You can do all this without pain of learning any programming language like C++, C sharp, MQL4, Easy Language, etc. Instead, you can do everything in your Excel Spreadsheet from backtesting to optimization of your trading strategy using simple spreadsheet formula. In this document, we introduce how to create your own trading strategy in 5 minutes in your Excel Spreadsheet. Since this is for first time user, we have put quite a lot of screenshots for better understanding. So get your Excel ready before you go through next steps.

Step 1 – Data Steps
You can use any data you want to build your strategy with our Quant Strategy Inventor including Forex, Stock, Future, etc.  In this tutorial, for simplicity we will use two instruments, S&P 500 and Microsoft Corp to build our trading strategy. If you do not have data already, then you will need to collect data to build your strategy. To do so, you need to know the ticker or symbol name for S&P 500 and Microsoft Corp. You can find these tickers in yahoo finance. Make sure that you are using correct ticker name to download data. Below we show the ticker ^GSPC and MSFT for both S&P500 and Microsoft.

Now click on ADD-INS under the Excel Menu to select our Quant Strategy Inventor Graphical User interface. Click on the Basic Module 1.

In the Basic Module 1, you have data download tab and data simulation tab. In the data simulation tab, you can simulate around 11 different mathematical models to generate artificial data for you to study your trading and investment strategies. Here we will just use data download module only for simplicity. You can always play around with different feature of Quant Strategy Inventor.

To download data, click Ticker Range and then select ^GSPC and MSFT on your spreadsheet.

Do the same for Output Range to select where you want to download the historical data on your spreadsheet. In default our starting date is 2011 January 1. If you want, you can always change the starting date to download more data. Here we will just use default. Now click “Download Historical Data” button to download the data.

Now both S&P500 and Microsoft data have been downloaded. Delete Adjusted Close since our open, high, low and close prices are already adjusted automatically.

Data downloading steps are completed. Excel is so flexible tool having interfaces with many financial tools and software. If you wish, you can always use external data to create your trading strategy. Since we are going to use S&P 500 to generate signal for Microsoft, you should swap the data between ^GSPC and MSFT. Just because it is more sensible to explain Microsoft stock in terms of S&P500 although it is just theory.

Step 2 – Signal Steps
Building strategy is like building house. Normally you need a lot of information and careful plan to go ahead with it. In this tutorial, we will create some simple strategy for an example. We have intentionally chosen two instrument to show how flexible to build the trading strategy with our Quant Strategy inventor. For now, we do not know if they are profitable strategy or not yet. We will estimate their profitability in the backtesting and optimization stage later. In this signal construction task, we will use Triple Exponential Moving Average (T3) and Simple Moving Average Cross (SMA) signal. The syntax for T3 indicator is like this: “TA_T3(close, timeperiod=6, vfactor=0.7)” and in the Excel  you will put the formula like this “=TA_T3(R10:R1466, 6, 0.7)” as an array formula. When you put array formula, you will select the range from U10 to U1466 first, then click formula bar to type  “=TA_T3(R10:R1466, 6, 0.7)”. After that, click Ctrl + Shift + Enter at the same time. I know this Ctrl + Shift + Enter might be strange thingy to the first time user. However, millions of Excel users are using Array formula every day and you will get used to it soon. It is very handy. Once you have entered the array formula for T3 correctly, T3 indicator value will be calculated in U column. If you are new to Excel Array formula, then this link is useful for you: http://www.excel-easy.com/functions/array-formulas.html.

Use the same process to enter Simple Moving average array formula to V column too. The syntax for simple moving average is: “TA_SMA(close, timeperiod=13)”. So you will put “=TA_SMA(R10:R1466, 13)” from V10 to V1466. Now you have created both T3 and Simple Moving Average together. Next we will generate T3 – SMA cross over signal.

Before we generate signal, let us exam T3 and SMA on simple line chart. We can see that T3 is much faster than SMA. Therefore, we can generate buy condition like “if T3 is cross over SMA then buy”. Likewise, you can set sell condition like “if T3 is cross down SMA, then sell”. Here when we buy or sell, we will buy Microsoft and not S&P500. We do this to show how easy to create multi-asset based trading strategy with our Quant Strategy Inventor. If you prefer single asset trading strategy, then you will just need one price data. However, normally index like S&P 500 is quite significant indicator for US Stock market. It might be quite valid idea to use S&P 500 to trade Microsoft. However, in this tutorial, we will be more stick to technical instruction to show the step-by-step guide to build trading strategy without writing coding. In fact, we are not sure whether this strategy is profitable in real world yet.

To generate buy condition, if T3 is cross over SMA, we can simply enter formula: “=IF(AND(U11>V11, U10<V10), 1, “”)”.  Note that U11 and U10 is T3 values at date 2011-01-04 and 2011-01-03 respectively. Likewise, V11 and V10 is SMA values at 2011-01-04 and 2011-01-03. This formula tells Excel to generate signal 1 if T3 value is greater than SMA value at date 2011-01-04 and if T3 value is smaller than SMA value at date 2011-01-03. So this is the mechanical way of telling Excel our cross over strategy in spreadsheet formula. Drag the formula down to cell W1466. Now your buy condition is ready.

In fact, in stock market, most of time, you will be profitable from buying the shares and not from selling the shares. In fact, you can still create sell condition if you wish. Whether you want to see the trading statistics for sell or not, it is your choice. In forex, you can make money when you are selling the instrument too. So forex traders, you should create sell signal too. To create sell condition, simply you can do the opposite for sell condition. For example, you can put the formula like this: =IF(AND(U11<V11, U10>V10), -1, “”). It is not too difficult if you think about what value each U11, U10, V11 and V10 represents. Also drag the formula to X1466. Now our sell signal is ready too. In our next step, we will generate actual order for buy and sell backtesting simulation.

Step 3 – Order Steps
To generate backtesting simulation, we will create nice heading for our order Instruction for the range Y8:AB9, which is coloured in yellow. You can use any colour or font you want. We used yellow colour for order for now. To make the virtual order which our backtesting and simulation machine will use, you will use the Order Open Buy syntax for buy like this:
OrderOpenBuy_(signal range, volume, take Profit, stop Loss, instruction, id).
Signal range are where the signal is located. For example, since we have put our buy signal at range W10:W1466, our signal range is W10:W1466. For the volume, we will put 1000. This means that we will buy 1000 shares of Microsoft, when we get the buy signal. Take Profit and Stop Loss can be empty. If stop loss and take profit is empty then in our backtesting simulation, we will assume that the order will be closed at certain condition. For example, it is common that closing buy position when the sell signal shows up. Therefore, in this tutorial, we will close buy condition when the sell signal shows up. If you wish to use take profit and stop loss, then you can use numeric values like 5 or 10. For example, when you use syntax like this: “=OrderOpenBuy_(W10:W1466, 1000, 5, 5, “”, 1)”. This means that if the price are rising by 5 dollar, the buy condition will be closed with profit and likewise, the price are dropping by 5 dollar, the buy condition will be closed with loss. Some broker may not allow you to use take profit and stop loss order, therefore, you should use this condition after you have checked with your brokers. Since we are not going to use take profit and stop loss condition, we will just use the buy syntax like this: “=OrderOpenBuy_(W10:W1466, 1000, 0, 0, “”, 1)”. Note that this is also array formula, So put this formula across the range Y10:Y1466 with Ctrl + Shift + Enter keys.

If you see the text like “Open, Buy, 1000, 0, 0, na, 1” in the same row as the buy signal row, then you have done everything correctly. This means that we will buy 1000 Microsoft shares when T3 moving average is cross over simple moving average of S&P 500. Now we will enter formula for buy close condition. We will assign ID: 1 for the signal generated. This ID is useful later when you want to combine multiple strategies in the same spreadsheet. As you imagine for second and third strategies you can give ID: 2 and ID: 3 respectively.  The syntax for Buy close is: OrderCloseBuy_(signal Range, instruction, id). Like before, signal range are where the buy close signal is located. Normally this is when the sell signal shows up. Instruction is how you want to close the buy positions. Normally you should type “all” for the instruction. This means that you will close all buy positions. When you assign ID here, then we will only close order with the same ID. Otherwise, we will close all order regardless of the ID.

This is the syntax we will enter for our buy close order “=OrderCloseBuy_(X10:X1466, “all”, 1)”. This means that when sell signal (-1) shows up, we will close buy position for Microsoft. Since for standard brokerage practice, you can make profits from buy order only for stock market, we have already completed our task of building order management. In fact, we are ready for our backtesting simulation. For Forex traders, make sure that you are completing for both buy and sell orders.

Step 4 – Backtesting Simulation
Now to do backtesting simulation, we will call our backtesting simulation for Stock Data. To do so just go to ADD-Ins again and click Analytics Module 1.

Now you will see our backtesting simulator. In our backtesting simulator, you can perform backtesting, optimization and cost simulations. There are some inputs, which you have to fill in before backtesting. Data Range is the range where your price data are located. Order Range is the range where your order instruction are located. Input Range is where your input are located for your optimization. For backtesting, you do not need input range to be filled (For some Excel version you might be prompted to fill input range too.). Therefore, to start backtesting, you need to fill data range and order range for now. You can change backtesting inputs and commission settings later. But we will just use default setting for now since this is just simple demonstration tutorial.

For Data Range, make sure that you are including Date, Open, High, Low, Close, Volume columns as shown below for Microsoft as shown in the screenshots below. Most of time do not include the headings.

For Order Range, you only need to include Buy Open (Y) and Buy Close (Z) columns since we have not create sell open and sell close instruction.

Once you have filled Data Range and Order Range. You are now ready to do backtesting for your strategy. Simple click “Backtest” button.

After we have clicked the backtest button, our backtesting simulator will perform all the calculation and print trading results in the separate worksheet. Here we have found some interesting results. Can you see that the balance growth curve is rather going up? This is not bad for this simple strategy.

You can also check the detailed trading results. Check the net profit and annual compounding growth rate (ACGR). Our net profit is around 14435 US dollar with ACGR of 4.48%. We have just beat that useless interest rate. Anyway, this is only the first step with our Quant Strategy Inventor.

Step 5 – Optimization
Optimization is a powerful technique to improve your profitability. You can say this is some sort of brutal force search meaning that you are keep running your algorithm with different inputs until you search some profitable settings for your strategies. On the other hands, optimization takes quite lengthy computation. So you should use them carefully. Luckily, the optimizer in Quant Strategy Inventor is very flexible. You can define how many trials you want to do before optimization. You can also force the optimizer to quit in the middle of optimization task. So feel free to play around with our optimizer and try to find mega profitable trading strategy.  When you want to quit during the optimization just press “X” key.
So now, we will introduce how you can start the optimization with our previous strategy. To do optimization, you need to create input control areas (range T1:V6) in your spreadsheet as we have shown below (coloured as green). In this tutorial, we will use time period of T3 moving average and time period of simple moving average as our sample input 1 and input 2. In the next step, we have to refer to our signal formula to this input cell U3 and V3. Therefore, our array formula for T3 column will become like this: “=TA_T3(R10:R1466, U3, 0.7)”. Our array formula for SMA will become like this: “=TA_SMA(R10:R1466, V3)”.  Also we need to define start, stop and steps for each inputs. Since we are using T3 cross over SMA strategy. For optimization, you must have 4 rows including inputs, start, stop and step rows. You can have 1 or 2 inputs and you can even have 10 inputs if you like.

To choose our inputs sensibly, it is not wise to have large time period for T3 because if T3 is more lagging than SMA, we won’t get any signals. So we will start time period of T3 from 5 to 13 in the step of 1. So we will test 5, 6, 7, 8, 9, 10, 11, 12 and 13 for our T3 time period. For simple moving average, we can have greater period but not too great because we might not get many trades. So we will start from 13 to 50 only in step of 1. In theory, we will test all the combination of T3 period and SMA period in this range. This will be around 350 combination of two inputs. Let us see how our Quant Strategy Inventor is handling this 350 repetitive backtesting.

When you do optimization, you must fill the input range and you should never leave it empty.

Once you are ready with optimization, then click optimization button.

In our computer, 342 backtesting took little bit more than 1 minute. I think this is not too bad comparing to what we are rewarded with the profitable trading strategy. Once the optimization is done. Quant Strategy inventor will print the optimization results in separate worksheet. Let us exam the profitability. To do so, simply use Excel’s custom sort functions.

We will sort our backtesting results in terms of net profit for now. If you wish, you can use other trading statistics you like. Some people might prefer Sharpe ratio or Calmar ratio.

You can see that at some backtesting we have more than doubled up our profits from 14,435 US dollar to 37,942 US dollar.

Also our Sharpe ratio and Calmar ratio have improved quite a lot with our optimization. If you wish to drill down particular backtesting, then you can. Just simply copy and paste the new input 1 and input 2 into our strategy worksheet. Then do backtesting with new inputs. In our case, we will use 10 and 14 as our new inputs since they have shown great profits in our optimization.

Make sure that you enter new inputs 10 and 14 in our strategy worksheet cell U3 and V3.

You can see more sharp increase in our balance curve too in the balance growth curve below.

Conclusion
This tutorial covers the strategy building, backtesting and optimization feature of Quant Strategy Inventor. Note that this is only part of the functionality you can access from our Quant Strategy Inventor. As you have seen in this tutorial, most of time, you can use native spreadsheet formula to build your trading strategy. Even though we have spent quite a lot of time to explain these basics steps, in fact, it might take less than 5 minutes to test this trading strategy to some experienced hands. Whichever strategy you are building, please make sure that you go through data steps, signal steps and order instruction steps. If you want to use VBA to test your trading strategy, then most of time, your VBA formula will be working inside signal steps.
We believe that you can create any trading strategy you can imagine. You can combine different strategies too in one single backtesting. When you want to combine multiple strategies, you need to assign different ID to different strategies. The ID should be from 1 to 100. The ID can not be smaller than 0 and greater 100 for now meaning that you can combine up to 100 trading strategies. Cost simulation is much like optimization. You might perform the cost simulation after you have found profitable trading strategies.

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Title of the submitted instruction or manual Build First Trading Strategy with Quant Strategy Inventor
Language of Instruction English
Key words (at least 3) Forex, Stock, Investment, Trading, optimization, simulation, backtesting, technical analysis, economic analysis, Quantitative Trading
Date of Completion 17 October 2016
Version of this Document 1.0

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How to catch 1000 birds in Forex Market using Vacuum Zone Trading

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How to catch 1000 birds in Forex Market using Vacuum Zone Trading

Vacuum Zone in the Market
According to Financial Econometric Professor from Lancaster University Management School in the UK, the recent financial markets and trading environments were drastically changed comparing to 1980s. In old times like 1980s, a lot of traders including reputable ones, used paper charts to analyze stock markets. The tools used by modern Professional traders and investors are much more sophisticated nowadays because of the readily available electronic analytical tools. It seems that I have to agree that back then the trajectory of financial markets was less sophisticated than now. In Today’s market, every 1 pip movement in the instrument, the price simultaneously makes a lot of noisy trajectory confusing traders to guess what the real intention of the market is. This is probably because of many people are looking at different tools including support and resistance, daily pivot analysis, psychological level, technical indicators, economic news, statistical analysis, Elliott wave, etc.  So the important question to ask here is that is it possible to spot some quiet price zone free or less influenced from all these different analysis? The answer is probably impossible because there is no one can perfectly master all different trading or analysis techniques. Even though someone might have mastered all the existing techniques on the earth, it will still take a lot of time to spot such an analysis free zone from the market. However one can still make some efforts to define such a Vacuum zone from financial market. In this article, we show some small efforts towards such an interesting attempt. We will mainly use combination of horizontal and diagonal support and resistance lines to do the task.

How to define Vacuum Zone in Financial Market
To define Vacuum Zone using support and resistance lines, it is required to use some sophisticated and automated tools can draw support and resistance. If you are trying to do this manually, it may take forever and we do not recommend. In our attempts, we will use our Price Breakout Pattern Scanner and Precision Support and Resistance Analysis. We will tell our price breakout pattern Scanner to detect all available diagonal support and resistance lines in the chart. Then we will ask the Precision Support and Resistance tool to detect all available horizontal Support and resistance lines. To do so, you need to display each pattern as support and resistance mode. Also make sure that you are setting Maximum Number of patterns to display to 20 or even more. So now price breakout pattern scanner will show 20 latest patterns in support and resistance mode.
 
Figure 1: Input setting for Price Breakout Pattern Scanner

Note that precision support and resistance tools blend both pivot lines and horizontal support and resistance lines automatically in its default setting. So you can attach it to the chart in the default setting. When you attach both price breakout pattern scanner and Precision Support and Resistance tool, you will see something like this in your charts. Depending on your trading experience, this chart may be very pleasant or may be very nasty. In my case, this is very pleasant as I can easily spot the vacuum zone which is free from both horizontal and diagonal support and resistance lines. Good things are that it is also easy to spot both entry and exit. Therefore as a trading strategy this is not too bad. For experience traders, this trading setup can be immediately ready to go with little bit of blend with their own support & resistance trading. For starters, it might be difficult to start immediately. In such a case, you can add some additional components to help your trading. For example, one might layout trend indicators to assist their trading setup. Or one might trade on fundamental news. Or you might blend both. 

 
Figure 2: Diagonal and horizontal support and resistance lines drawn from Price Breakout Pattern Scanner and Precision Support & Resistance tool.

You can use some sophisticated trend analysis beside this vacuum trading setup. For simple demonstration, we just used 20 periods Bollinger bands to have some sense on what is the major trend at the moment plus to know how extreme current trend is moving. Upper and lower Bollinger Bands touching any horizontal and diagonal support and resistance lines will simply reinforce the importance of that support and resistance. So you should treat them with care. Make sure that if price move from one vacuum zone to another one, you will be trail your stop to protect your profits.
 
Figure 3: Bollinger bands added to the trading setup.

Now here we will introduce one more element in this trading setup. That is the market volatility monitoring. This will also answer the question when to enter the market. We want to enter the market when we are expecting good market volatility. Ironically to do so, it is important to detect quiet market first because highly volatility market comes after the quiet market. For this task, we will use Market Activity Index exclusively developed by our research team. Market Activity Index is available in Panel form. So you can monitor up to 21 currency pairs’ volatility. When you find some low volatility currency pairs, all you have to do is just click the cell to open the chart.
 
Figure 4: Market Activity Index Panel.

Once we opened the USDCAD chart, we will apply the same Vacuum Zone Trading setup as before. To do this fast, you will need to save these indicators as the template.
 
Figure 5: Save Vacuum Zone trading setup as template for future use.

So we will apply Price Breakout pattern Scanner and Precision Support & Resistance tool and Bollinger bands using template. As you can see at the minutes, USDCAD is quite bearish after the big bullish movements. The price is in the middle of Vacuum Zone. If you sell USDCAD, this would be counter trend trading. If you want to wait another opportunity, it is entirely up to you. However one thing you need to make sure is that if your reward covers your risk. If you are sure about that your rewards is sufficiently covering your risk, then you might enter. Otherwise, you will wait for next opportunity. In vacuum zone trading, your rewards and risk will be identified as the height of the Vacuum zone.
 

Further Consideration
Vacuum Zone trading can be one style of trading setup for traders and investors. The advantage is that your decision is made with fully comprehensive support and resistance lines in your chart. Usual sense used for support and resistance trading are quite helpful. You can think this Vacuum Zone trading as the extended support & resistance trading. Usual disadvantage of support & resistance trading will be applicable to vacuum zone trading too. To identify diagonal support & resistance lines, we used our price breakout pattern scanner exclusively. However, it is noted that it is just one trading style you can perform with our price breakout pattern scanner and its ability is not limited there. To find out Pattern based trading style with our Price Breakout Pattern Scanner, you might read some other articles.

Instruction (Manual) Document

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Your Surname ATI team
Your First Name   ATI team
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Your Email Address http://www.algotrading-investment.com/
Your ID on our website 

2. Information for the submitted materials
Title of the submitted instruction or manual How to catch 1000 Birds in Forex Market using Vacuum Zone Trading
Language of Instruction English
Key words (at least 3) Forex, Trading, Price Breakout pattern Scanner, Precision Support & Resistance, Market Activity Index,
Date of Completion 5 May 2016
Version of this Document (date revised) 1.0

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Your First Training Course in Trading and Investment

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Your First Training Course in Trading and Investment

 

Background
I often observe starters and junior traders rushing to live trading when they are not even fully trained to go to live trading. There can be many reasons behind this. One possible reason can be due to the fact that they have lack of understanding on trading and investment itself. Another reason can be that they are psychologically too optimistic without realizing that there are so many variables and uncertainty in trading and investment. Then why do we trade and invest with all these variables and uncertainties? We do trade and invest because it is a lot easier to make quick profits comparing to setting up other business by yourself. For example, if you want to set up a restaurant, you will start with loads of paper works first. But that is just a fraction of what you have to do. You have to concern about where to open your restaurants, how many people to employ, what menu you want to provide, etc. In addition, you have to worry about paying your monthly rent to your building owner and other bills, labour cost, etc. After all these headaches, your ROI (return on investment) from your restaurants can be barely just 20% annually on average. Trading and investment does not require any physical site to operate. You will only need a good computer and good internet connection. But your ROI is often much higher than running a restaurant. So here is a clear reason why a lot of people much prefer to become a trader rather than running a restaurant or other business. However, instead of all these advantages, traders and investors should not trade on live without sufficient trading skills because you are also taking risk of losing your money. This is not to say that you can’t lose money from running a restaurant or other business. Last year one of my close friends finally closed his restaurant after 7 month struggle. He lost about 60,000 US dollar during these 7 months. The main reason for his loss was that there was too much competition around the area and he could not overcome the cost such as labour cost and monthly rents. Anyway anything you do without good preparation, there is a good chance that you will be exposed in negative outcome than positive outcome. So here let’s focus on become a good trader.
Trading and Investment requires multi disciplinary operation and this is not easy to learn for people who do not have access to some organized learning and educational resources. Of course, there is an established route for graduates through Investment Bank or Fund Management Company when they want to follow professional career path as traders and investors.  Normally full or partial training will be given to the some smart candidates from the firms for several months. However, such an opportunity may be not available to everyone. We wish this article can serve starters and junior traders as some good guide line to start their trading and investment. In this article, we will spend sometimes to explain the fundamentals of support and resistance which are, in my opinion, the most important lesson for starters and junior traders.
 
Introducing Support and Resistance
By barrowing some technical definition from StockChart.com, the support can be described like this: “Support is the price level at which demand is thought to be strong enough to prevent the price from declining further.” Likewise, the resistance can be described like this: “Resistance is the price level at which selling is thought to be strong enough to prevent the price from rising further.” This is pretty good description about support and resistance relating the supply and demand concept to price level. However this is also somewhat generalized concept about support and resistance too. In practice, traders will not expect to see the price bouncing back from supply or resistance always. Support and resistance will be penetrated at some point as the price can’t stay in between support and resistance for infinite amount time. When the price penetrates, previous supply can become new resistance and previous resistance can become new supply. Also it is important to note that penetration of support and resistance will happen as many times as bouncing back at support and resistance.
You may ask back “what is the significance of this support and resistance if we can only say the price might penetrate or bounce back at these levels?” Yes, it does matter a lot because when the price penetrate or bounce back from these levels, there are usually large trading volumes making your trading much easier. So up to this point, we might be able to reformulate our support and resistance definition from previous one barrowed from StockChart.com. The reformulated definition can be “Support and resistance are the price level where the price is either penetrating hard or bouncing back hard with unusually high volatility.” Indeed this is more operational definition of support and resistance which you should remember for your trading.
 
Figure 1: Support Example.

 
Figure 2: Resistance Example.

Different Types of Support and Resistance
Now we have learnt that the price will either penetrate hard or bounce back hard at our support and resistance level with unusually high volatility. Now the question is how we identify these support and resistance from our chart. Of course, your trading performance will really depending on how accurately you can identify important support and resistance. There are large of number of established techniques by traders over several decades. However, some are easier to use and some are more difficult to use. The accuracy also varies a lot from techniques to techniques.  

1. Daily Pivot Point
One of the simple ways to identify support and resistance is to use daily Pivot point. Pivot point can be calculated simply using previous high, low and close price. Experienced traders normally take daily pivot levels very seriously. For example, today I saw on GBPUSD price was below Resistance 1 of the pivot point. After couple of hours later, the GBPUSD penetrate beautifully Resistance 1 of the daily pivot point. Also the GBPUSD stopped at Resistance 2 of the daily pivot and it pretty looked like someone programmed. So this phenomenon exactly matches our operational definition of support and resistance either penetrating hard or bouncing back hard with unusual high volatility.

 
Figure 3: GBPUSD price action around Daily Pivot R1 and R2 lines.

2.  Support and Resistance Detection from historical price patterns
Support and Resistance can be detected by examining some important price level from historical price series. For example, we can count how many times a specific price level was visited in the past. If the price was stopped frequently at this point, we can think that this price levels are probably very important. Indeed, we use such a principle to detect support and resistance for our Precision Support Resistance. We have found that this method works very well to identify significant support and resistance level. One drawback of this technique is that, if the price moves to where it never visited before (i.e. it went up too high or it went down too low), then no support and resistance can be identified. This can occasionally happen if the market decided to make new high or new low. If such event happens, then in our precision support resistance tool, it will show daily pivot automatically together with detected support and resistance levels.

 
Figure 4: Support and Resistance lines defined from historical price patterns. This methods work pretty well for most of market yet.

3. Support and Resistance using Fibonacci Retracement
Fibonacci Retracement is a favourite tool for many traders. Indeed many traders base their entire trading strategy on Fibonacci Retracement.  You could use this technique to identify support and resistance too. To do this, you may need to identify two peaks including highest point and lowest point in your chart. Then you can draw retracement level in Fibonacci number including 23.6%, 38.2%, 50%, 61.8% and 100% etc. One drawback of this technique is that the choice for two peaks can be quite subjective and I am sure that many traders will draw quite different support and resistance levels using this method as they will pick up different peaks. The similar but much more powerful support and resistance detection is also possible using XABCD points of Harmonic Patterns. We will explain this in depth in next section.

 
Figure 5: Fibonacci retracement from two chosen peaks.

4. Support and Resistance using Potential Reversal Zone in Harmonic Pattern
Using Fibonacci Retracement is relatively simple. On the other hands, Potential Reversal Zone concept in Harmonic Pattern can be used to combine support and resistance levels of many Fibonacci retracements in your charts. This is much more reinforced version of simple Fibonacci Retracement because Potential Reversal Zone is constructed using up to 4 Fibonacci Retracement from 5 points constructing the harmonic pattern. This PRZ technique can overcome the subjective nature of simple Fibonacci Retracement techniques too.
To best understand the concept of PRZ, you can think that you are drawing Fibonacci retracement from each XABCD points of the harmonic pattern. For example, you will draw each Fibonacci retracement for XA, AB, BC and CD legs. Combining these 4 Fibonacci retracements might end up really complex multitudes of lines crossing your chart. This might be not too much readable for your trading in first place. However, experienced traders tend to identify several important PRZ lines by detecting 3 or 4 Fibonacci Retracement lines overlapping together. Identifying these crucial PRZ lines can be really useful for your trading for several reasons. For example, you will be much more justified to use these overlapping PRZ lines over simple Fibonacci Retracement drawn from two peaks only. One thing you should note is that do not expect that price will be reverse only around these PRZ lines because it is called Potential Reversal Zone. It is better to treat this PRZ lines with our operational definition of support and resistance too. So the price will either penetrate hard or bounce hard around these PRZ lines.

In terms of harmonic Pattern trading, if the PRZ lines are near the D point of harmonic pattern, this PRZ line can be your order entry for Harmonic Pattern. These PRZ lines can be known before you wait for first confirmation candle formation. Therefore, you can enter the trading much earlier than people using confirmation candle. These PRZ lines can be located below point D of bullish pattern. These PRZ line can be used as your stop loss for your harmonic pattern trading too. Likewise, you can use take profit and trail stop around these PRZ lines.

One disadvantage of using these PRZ lines is that it is really tedious task for drawing 4 Fibonacci Retracements manually. I have seen some traders doing this painful task manually but the problem is that their drawing becomes quite subjective and inaccurate as they start to feel tired with their drawing. In addition identifying 3 or 4 overlapping Fibonacci Retracements are another subjective task for human eyes. If you want to save a lot of time and efforts from drawing these PRZ lines manually, then you can use our Harmonic Pattern Plus or Harmonic Pattern Scenario Planner to draw these PRZ lines automatically for you. They will do these repeating and tiring task less than 1 second for you. You will get only reported important PRZ lines on your chart. You can even lock these PRZ lines for you to use as a reliable support and resistance lines.

 
Figure 6: Fibonacci Retracement from XA and BC upwards legs.

 
Figure 7: Fibonacci Retracement from AB and CD downward legs.

 
Figure 8: Combined Fibonacci Retracement from all XA, AB, BC and CD legs. These combined Fibonacci Retracements are really complex and not so much readable. It is important to identify overlapping PRZ among these complex lines for your practical trading.
 
Figure 9: All fuzzy PRZ lines are automatically filtered out. Only clustered and overlapping PRZ lines are shown from Harmonic Pattern Plus. As you can see, it is much easier to spot the entry with harmonic patterns.

5. Support and Resistance by technical indicators
Sometimes you can use technical indicators to identify important support and resistance levels. Moving average is probably the most common technical indicator used for this task.

 
Figure 10: Support and Resistance line drawn using simple moving average.

6. Round number or psychological number
Sometimes round number can be used as a very good support and resistance. This is in fact the one of the simplest support and resistance identification method, even more than the daily pivot method. For the case of EURUSD, round number is the price level like 1.2000 or 1.3000. For the case of stock market, round number can be the price level like 50$ or 100$. It is quite interesting to see how price react when they reach these round numbers. Again, these round numbers are quite important to watch out too for your trading.

7. Diagonal Support and Resistance
So far, we have only explained horizontal support and resistance lines. Indeed previous 6 techniques are based on horizontal support and resistance. However, human eyes can detect diagonal support and resistance lines too. For example, outline of many triangle patterns appearing in your chart can be served as your diagonal support and resistance. The exactly same principle can be applied to these horizontal support and resistance. The price can either penetrate hard or bounce hard at these diagonal support and resistance with unusually high volatility. You can draw diagonal support and resistance level by connecting some important peaks on your chart. Decreasing volatility of triangle patterns are typical pre-sign of explosive volatility in the near future. Therefore you must be quite attentive when these diagonal support and resistance lines are detected on your charts.

 
Figure 11: Typical example of diagonal support and resistance lines appearing in financial market. In this case, diagonal support and resistance line makes symmetric triangle patterns.
 
Figure 12: Typical diagonal support and resistance example appearing in financial market. In this example, these diagonal support and resistance lines make up rising wedge pattern.

Value of these diagonal support and resistance lines are quite high because these diagonal support and resistance lines can be combined with any of horizontal support and resistance lines for better prediction of price action. For example, overlapping PRZ lines can be formed quite sensible area of rising wedge patterns giving you very good clue about where the price might be breakout. In addition some horizontal support and resistance lines can be nested inside big rising wedge patterns giving your some idea about where to place your pending order. It is also common to see a small harmonic pattern nested inside big rising wedge or falling wedge. These nested harmonic patterns can offer you highly accurate trading entry by confirming both diagonal support and horizontal support lines at the same time. Once again analyzing both diagonal and horizontal support and resistance are very powerful tools for your trading but doing this manually is very tedious task. We provide fully automatic solution for your advanced trading.

 
Figure 13: Typical reinforced support between horizontal and diagonal support lines. If this reinforced support lines are breakdown, then there can be really good sell rally helping you make good pips reflecting directional prediction made by harmonic patterns and rising wedge.
 
Figure 14: Typical combination of diagonal support and resistance lines (created by Price Breakout Pattern Scanner) with horizontal Support and resistance lines (created by Precision Support Resistance Tool).

 
Figure 15: Small Nested Harmonic Patterns with PRZ entry confirmation. Naturally confirming your entry with both diagonal support and horizontal support give you highly accurate trading setup. High volatility around PRZ lines helps you to achieve the profits so easily too.

Further note about Support and Resistance
Support and resistance are relatively easy to understand but their effectiveness was proved for many decades already among traders and investors. For your trading career, you will find that you can’t ignore these support and resistance on your chart. However, it should be noted that trading with support and resistance are one of many trading techniques. Most of time, trading with support and resistance are considered as the basic or introductory classes among other topics during some structured training course. Even though, we have shown you here that combing several different support and resistance techniques can offer you highly sophisticated trading opportunity. Support and Resistance are still the most effective techniques used by many traders and we strongly encourage mastering these techniques for you. So we have spent some time here to give your first training course with support and resistance. We hope this was quite useful.

Instruction (Manual) Document

This part should be filled by author before your submission.

1. Information about Author
Your Surname ATI
Your First Name   ATI
Your Country ATI
Your Email Address ATI
Your ID on our website ATI

2. Information for the submitted materials
Title of the submitted instruction or manual Your First Training Course in Trading and Investment
Language of Instruction English
Key words (at least 3) Precision Support Resistance, Support, Resistance, Forex, Investment
Date of Completion 21 March 2015
Version of this Document 1.3

3. If it is about any trading platform or any of our products (leave empty if you don’t use)
Name of Trading Platform MetaTrader 4 or MetaTrader 5
Trading Platform version Build 950
Name of Product Precision Support Resistance (6.7), Price Breakout Pattern Scanner (5.1), Harmonic Pattern Plus (7.0)
Product version 6.7, 5.1, 7.0