FOR SALE: VB.NET SOLUTION TO POPULATE SQL TABLE WITH HISTORICAL STOCK DATA

FOR SALE:

VB.NET APPLICATION TO POPULATE SQL TABLES USING CUSTOM FINANCIAL FUNCTIONS FOR THE PURPOSE OF DERIVING HISTORICAL TECHNICAL INDICATOR DATA.

This custom .NET Application was created in order to build derived tables to hold historical technical indicator data. As such, it is not sold with any baseline or derived data. It is meant to be used in conjunction with your own baseline data in order to derive the historical indicator data. You will need the Ticker, Date, OHLC, and Volume. While we have our own fully populated database, we realize that there may be a desire on the part of others to use their own baseline data, build and populate their own tables, and create their own reports.In the event that you wish to make an offer OR to avail yourselves of our already populated SQL database, please contact us at [email protected]. Our Database tables contain 22 million rows and include 20 years of data for over 14,000 Stocks, ETF’s, and Indexes.

We leveraged a product from a company called FMLabs which specializes in writing advanced functions for banks, insurance companies, brokerage houses, fund managers, traders, and individual investors. In order to use this application you must have already purchased the FMLabs toolkit (approximately $200.00). You will need to install the toolkit onto a computer with Visual Studio installed. The table names described below are purely our own naming conventions. You may use any names you like.

STOCKS TABLE

This table contains the baseline data which the application uses to derive the data for the other tables. In the case of the Olaptrader database, there is data for 14,000 Stocks, Indexes, and ETFs spanning two decades – 1988-2008.

Columns & Data Type[Ticker] [nvarchar](7) NOT NULL,

[Date] [smalldatetime] NOT NULL,

[Open] [decimal](9, 2) NULL,

[High] [decimal](9, 2) NULL,

[Low] [decimal](9, 2) NULL,

[Close] [decimal](9, 2) NULL,

[Volume] [bigint] NULL,

http://fmlabs.com/

mailto:[email protected]

INDICATORS TABLE

The following is a list of the Technical Indicators which the application computes and inserts into a destination table.

Columns Function Name

Ticker Ticker

Date Date

Absolute_Breadth_Index_ABI fmABI

Accumulate_or_Running_Total fmAccumulate

Accumulation_Swing_Index fmAccumSwingIndex

Accumulation_Distribution_Line fmAccumDist

Advance_Decline_Line_Breadth fmADLineBreadth

Advance_Decline_Line fmADLine

Advance_Decline_Ratio fmADRatio

Advancing_Declining_Issues fmADIssues

Arms_Index_TRIN fmTRIN

Aroon_Oscillator fmAroonOscillator

Aroon_Down fmAroon

Aroon_Up fmAroon

Average_Directional_Movement_Index_ADX fmADX

Average_Directional_Movement_Rating_ADXR fmADXR

Average_Price fmAvgPrices

Average_True_Range_ATR fmATR

Bollinger_Band_Width fmBollingerWidth

Bollinger_Bands_Hi fmBollinger

Bollinger_Bands_Low fmBollinger

Bollinger_Bands_Mid fmBollinger

Bolton_Tremblay_Indicator fmBoltonTremblay

Breadth_Thrust fmBreadthThrust

Bretz_TRIN_5 fmBretzTRIN5

Chaikin_Money_Flow fmChaikinMoneyFlow

Chaikin_Oscillator fmChaikinOscillator

Chaikin_Volatility fmChaikinVolatility

Chande_Momentum_Oscillator_CMO fmCMO

Chicago_Floor_Trading_Pivotal_Point_First_Resistence_Level fmCFTPP

Chicago_Floor_Trading_Pivotal_Point_First_Support_Level fmCFTPP

Chicago_Floor_Trading_Pivotal_Point_Second_Resistence_Level fmCFTPP

Chicago_Floor_Trading_Pivotal_Point_Second_Support_Level fmCFTPP

Commodity_Channel_Index_CCI fmCCI

Commodity_Selection_Index_CSI fmCSIndex

Cumulative_Volume_Index_CVI fmCVI

DEMA fmDEMA

Demand_Index fmDemandIdx

Detrended_Price_Oscillator_DPO fmDPO

De_trended_Price fmDeTrend

OLAPTRADER | Candlesticks Table 2

Directional_Movement_Index_M_DI fmDI

Directional_Movement_Index_P_DI fmDI

Directional_Movement_Index_DX fmDX

Down_Average fmDownAverage

Dynamic_Momentum_Index_DMI fmDMI

Ease_Of_Movement fmArmsEMV

EMA_100 fmEMA

EMA_12 fmEMA

EMA_200 fmEMA

EMA_26 fmEMA

EMA_50 fmEMA

EMA_9 fmEMA

Envelope_Percent_Hi fmEnvelopePct

Envelope_Percent_Low fmEnvelopePct

Envelope_Hi fmEnvelope

Envelope_Low fmEnvelope

Forecast_Oscillator_FO fmForecastOscillator

Forecast_Oscillator_Signal fmForecastOscillator

Ichimoku_Kinko_Hyo_Chikou_Span fmIchimokuKinkoHyo

Ichimoku_Kinko_Hyo_Kijun_Sen fmIchimokuKinkoHyo

Ichimoku_Kinko_Hyo_Senkou_Span_A fmIchimokuKinkoHyo

Ichimoku_Kinko_Hyo_Senkou_Span_B fmIchimokuKinkoHyo

Ichimoku_Kinko_Hyo_Tenkan_Sen fmIchimokuKinkoHyo

Inertia fmInertia

Intraday_Momentum_Index_IMI fmIMI

Least_Squares_Moving_Average fmLstSqrMA

Least_Squares_Moving_Average_10_days fmLstSqrMA





Line_Oscillator fmLineOsc

Market_Facilitation_Index_MFI fmMFI

Mass_Index fmMassIndex

McClellan_Oscillator fmMcClellanOscillator

McClellan_Summation fmMcClellanSummation

Median_Price fmMedianPrices

MESA_Sinewave fmMESAsinewave

MESA_Sinewave_Lead fmMESAsinewave

Momentum fmMomentum

Money_Flow_Index fmMoneyFlowIndex

Moving_Average_Convergence_Divergence_MACD fmMACD

Moving_Average_Convergence_Divergence_MACD_Signal fmMACD

Moving_Average_Envelope_Hi fmMAEnvelope

Moving_Average_Envelope_Low fmMAEnvelope

Moving_Averages_of_the_High_and_Low_Hi fmMAHighLow

Moving_Averages_of_the_High_and_Low_Low fmMAHighLow

Moving_Correlation_Coefficient fmCorCoefMv

Moving_Covariance fmCovarianceMv


Moving_Dispersion fmDispersionMv

Moving_Regression_Line fmRegressionLineMv

Moving_Regression_Line_Slope fmRegressionLineMv

Moving_Standard_Deviation fmStdDevMv

Moving_Standard_Error fmStdErrMv

Moving_Summation fmMovingSum

Negative_Volume_Index_NVI fmNVI

Net_Momentum_Oscillator_NMO fmNMO

On_Balance_Volume_OBV fmOBV

On_Balance_Volume_Expanded_System_Balance_Volume_Array fmOBVolExp

On_Balance_Volume_Expanded_System_Breakout_Indicators fmOBVolExp

On_Balance_Volume_Expanded_System_Field_Trend_Indicators fmOBVolExp

On_Balance_Volume_Moving fmOBVolMv

Open_10_TRIN fmOpen10TRIN

Oscillator_Percent fmOscillatorPct

Oscillator fmOscillator

Overbought_Oversold fmOverBoughtSold

Parabolic_SAR fmSAR

Parabolic_SAR_Position fmSAR

Percentage_Volume_Oscillator_PVO fmPVO

Performance_Indicator fmPerformancePct

Positive_Volume_Index_PVI fmPVI

Price_and_Volume_Trend_PVT fmPVT

Price_Channels_Hi fmPriceChannels

Price_Channels_Low fmPriceChannels

Price_Oscillator_Percent fmPriceOscillatorPct

Price_Oscillator fmPriceOscillator

Price_Volume_Rank fmPVrank

Projection_Bands_Hi fmProjectionBands

Projection_Bands_Low fmProjectionBands

Projection_Bandwidth fmProjectionBandwidth

Projection_Oscillator fmProjectionOscillator

Qstick fmQstick

Random_Walk_Index_RWI_Hi fmRWI

Random_Walk_Index_RWI_Low fmRWI

Range_Indicator fmRangeIndicator

Rate_of_Change fmRateOfChange

Ratio fmRatio

Relative_Momentum_Index_RMI fmRMI

Relative_Strength_Index_RSI fmRSI

Relative_Volatility_Index_RVI_Original_Calculation fmRVIoriginal

Relative_Volatility_Index_RVI fmRVI

r_squared fmRSquared

Simple Moving Average fmSimpleMA

SMA_10 fmSimpleMA

SMA_100 fmSimpleMA

SMA_20 fmSimpleMA

SMA_200 fmSimpleMA

SMA_50 fmSimpleMA

Standard_Error_Bands_Hi fmStdErrBands

Standard_Error_Bands_Low fmStdErrBands


Standard_Error_Bands_Mid fmStdErrBands

STIX fmSTIX

Stochastic_Momentum_Index_SMI fmSMI

Stochastic_Momentum_Index_SMI_Signal fmSMI

Stochastic_Oscillator_D fmStochasticOscillator

Stochastic_Oscillator_K fmStochasticOscillator

Stochastic_RSI fmStochRSI

Swing_Index fmSwingIndex

T3 fmT3

TEMA fmTEMA

Trend_Score fmTrendScore

Triangular_Moving_Average fmTriangularMA

Triangular_Moving_Average_10_days fmTriangularMA





TRIX fmTRIX

True_Range_TR fmTR

True_Strength_Index_TSI fmTSI

Typical_Price fmTypicalPrices

Ultimate_Oscillator fmUltimateOsc

Up_Average fmUpAverage

Upside_Downside_Ratio fmUpDownRatio

Variable_Moving_Average fmVariableMA

Variable_Moving_Average_10_days fmVariableMA





Vertical_Horizontal_Filter_VHF fmVHF

VIDYA fmVIDYA

Volume_Adjusted_Moving_Average fmVolAdjustedMA

Weighted_Close fmWeightedCloses

Weighted_Moving_Average fmWeightedMA

Weighted_Moving_Average_10_days fmWeightedMA





Welles_Wilder_Moving_Average fmWellesMA

Welles_Wilder_Moving_Average_10_days fmWellesMA





Welles_Wilder_Summation fmWellesSum

Welles_Wilder_Volatility_System_ATR_Time_Constant fmWellesVolatility

Welles_Wilder_Volatility_System_Short_Long_Indicators fmWellesVolatility

Welles_Wilder_Volatility_System_Significant_Closes fmWellesVolatility

Welles_Wilder_Volatility_System_Stop_Reverse_Point fmWellesVolatility


Williams_Accumulation_Distribution fmWilliamsAD

Williams_Pct_R fmWilliamsR

Zero_Lag_Exponential_Moving_Average fmZeroLagExpMA

Zero_Lag_Exponential_Moving_Average_10_days fmZeroLagExpMA





Zig_Zag fmZigZag

CANDLESTICKS TABLE

The following is a list of the Candlestick Patterns which the application computes and inserts into a destination table.


Ticker N/A

Date N/A

Abandoned Baby Bottom fmAbandonedBabyBottom

Abandoned Baby Top fmAbandonedBabyTop

Advance Block fmAdvanceBlock

Bearish Belt Hold Line fmBeltHoldLineBear

Bearish Counter Attack fmCounterAttackBear

Bearish Engulfing Line fmEngulfingLineBear

Bearish Separating Line fmSeparatingLineBear

Black Harami Cross fmHaramiCrossBlack

Black Harami fmHaramiBlack

Body Gap Down fmBodyGapDn

Body Gap Up fmBodyGapUp

Bullish Belt Hold Line fmBeltHoldLineBull

Breakaway Bear new function

Breakaway Bull new function

Bullish Counter Attack Bull Line fmCounterAttackBull

Bullish Engulfing Line fmEngulfingLineBull

Bullish Separating Line fmSeparatingLineBull

Candlestick Color fmCandleColor

Dark Cloud Cover fmDarkCloudCover

Deliberation Bear new function

Deliberation Bull new function

DragonflyDoji Bear new function

DragonflyDoji Bull new function

Evening Doji Star fmEveningDojiStar

Evening Star fmEveningStar

Falling Three Method fmFalling3Method

Gravestone Doji fmGravestoneDoji

Hammer fmHammer

Hanging Man fmHangingman


High Wave fmHighWave

InNeck line fmInNeckLine

Inverted Hammer fmInvertedHammer

LadderBottom new function

Long Legged Doji fmLongLeggedDoji

MatHold Pattern fmMatHoldPattern

MeetingLines Bear new function

MeetingLines Bull new function

Morning Doji Star fmMorningDojiStar

Morning Star fmMorningStar

OnNeck new function

Outside Bar Formation fmOutsideBar

Piercing Line fmPiercingLine

Rising Three Method fmRising3Method

Shooting Star fmShootingStar

Side by Side White Gapping down fmSideBySideWhiteGapDn

Side by Side White Gapping up fmSideBySideWhiteGapUp

Stalled Pattern fmStalledPattern

Tasuki Downside Gap fmTasukiDownsideGap

Tasuki Upside Gap fmTasukiUpsideGap

Three Gaps Down fmThreeGapsDown

Three Gaps Up fmThreeGapsUp

Three White Soldiers fmThreeWhiteSoldiers

ThreeLineStrike Bear new function

ThreeLineStrike Bull new function

ThreeOutsideDown new function

ThreeOutsideUp new function

ThreeStarsInTheSouth new function

Thrusting Line fmThrustingLine

TriStar Bear new function

TriStar Bull new function

TweezersBottom new function

TweezersTop new function

Upside Gap Two Crows fmUpsideGap2Crows

Western Gap Down fmWesternGapDn

Western Gap Up fmWesternGapUp

White Harami fmHaramiWhite

White Harami Cross fmHaramiCrossWhite


CALCULATIONS TABLE

The following is a list of Fibonacci Retracements and Projections and the custom columns which the application computes and inserts into a destination table.


Ticker N/A

Date N/A

[Fibonacci_Project_1.270] fmFibonacciProject





[Fibonacci_Retrace_0.382] fmFibonacciRetrace





[Close_Plus_0_days] custom

[Close_+_7 days] custom








The following describes how you would use this data after using the application to populate your own destination table.

For each unique combination of Ticker and Date (Primary key), there are predicted future support and resistance prices for the stock at each corresponding projection and retracement ratio. Your DBA would write a query to compare the actual future Close prices (at intervals of 7, 14, 28, or custom days etc…) with the predicted support or resistance price for each of the ratios. This would be done for each ticker. He would save this difference as a percentage. Finally, he simply takes the average (all tickers) to see which of the Fibonacci projection and retracement ratios was cumulatively and historically, the most accurate. A trader would then use this ratio when trading with Fibonacci’s.Regardless of whether it is a bull or bear market, the numbers which you get back for the ratios are equally valid. This is because you are comparing one against the other. It is the predictive accuracy of the ratios to one another which are important

* The retracement function gives the support points for upward trends, and the projection function gives resistance points for downward trends


DARVAS BOXES TABLE

The Darvas Boxes table contains past occurrences of Darvas Boxes. The application determines the prior occurrences of a Darvas Box and, whether or not it formed due to a Bullish or Bearish price movement. It then populates the destination table. In addition, the application determines when an upward or downward breach of an existing box occurs. This is a buy or sell signal. The purpose of this calculation is to use it in conjunction with complimentary bullish or bearish indicators in an effort to find combinations which have historically yielded predictable results.

Columns Ticker

Date

Bullish

Bearish

IsNewBox

BoxTopBreached

BoxBottomBreached

Sample output from the DarvasBoxes table in the Olaptrader database.


.NET 2008 SOLUTION

Code Snippets:

INDICATORS

Public Sub PopulateIndicators()

Dim StartTime As Date Dim EndTime As Date Dim ElapsedTime As Long

Dim sql As String

Dim oDR As DataRow Dim oDT As DataTable Dim oDA As OleDbDataAdapter Dim oCB As OleDbCommandBuilder

Dim drTickers As DataRow Dim dtTickers As DataTable Dim daTickers As OleDbDataAdapter

Dim fmArrayADX As fmArray Dim fmArrayADXR As fmArray Dim fmArrayArmsEM As fmArray Dim fmArrayAroonUp As fmArray


Dim fmArrayAroonDown As fmArray Dim fmArrayAroonOscillator As fmArray

mProcessingToolStripStatusLabel.Text = "Populating the INDICATORS table ..." Application.DoEvents()

oLW.WriteMsg("PopulateIndicators - Started inserting records into the INDICATORS table.")

Thread.Sleep(5000) 'Exit Sub

StartTime = Now

'sql = " truncate table Indicators " 'Call ExecuteSQL(Con, sql)

sql = " select * from Indicators where 1=2 " oDA = New OleDbDataAdapter(sql, Con) oCB = New OleDbCommandBuilder(oDA) oDA.SelectCommand.CommandTimeout = 600 oDA.UpdateCommand = oCB.GetUpdateCommand oDA.UpdateCommand.CommandTimeout = 600 oDA.InsertCommand = oCB.GetInsertCommand oDA.InsertCommand.CommandTimeout = 600 oDA.DeleteCommand = oCB.GetDeleteCommand oDA.DeleteCommand.CommandTimeout = 600 oDT = New DataTable

CANDLESTICKS

Public Sub PopulateCandlesticks()

Dim StartTime As Date Dim EndTime As Date Dim ElapsedTime As Long

Dim sql As String

Dim oDR As DataRow Dim oDT As DataTable Dim oDA As OleDbDataAdapter Dim oCB As OleDbCommandBuilder

Dim drTickers As DataRow Dim dtTickers As DataTable Dim daTickers As OleDbDataAdapter

Dim fmArrayCrossOverFill As fmArray Dim fmArrayFormationFill As fmArray Dim fmArrayTurnFill As fmArray

mProcessingToolStripStatusLabel.Text = "Populating the CANDLESTICKS table ..." Application.DoEvents()

oLW.WriteMsg("PopulateCandlesticks - Started inserting records into the Candlesticks table.")

Thread.Sleep(5000) 'Exit Sub


StartTime = Now

sql = " select count(*) from Candlesticks "

CurDBRecordCount = 0 DBRecordCount = GetFirstValueBySQL(Con, sql)

If DBRecordCount > 0 Then sql = " select Ticker, count(*) as TickerCount from Candlesticks group by Ticker order by Ticker " oDA = New OleDbDataAdapter(sql, Con) oDT = New DataTable oDA.Fill(oDT) oDA.Dispose() CurTicker = "" For Each oDR In oDT.Rows If CurDBRecordCount + oDR("TickerCount") <= DBRecordCount Then CurTicker = oDR("Ticker") CurDBRecordCount += oDR("TickerCount") Else Exit For End If Next oDR End If


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FOR SALE: VB.NET SOLUTION TO POPULATE SQL TABLE WITH HISTORICAL STOCK DATA