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Debugging techniques – Part 1 – Exploration

From time to time people send us their formulas asking what happens in their own code. Or they do not know why given trade is taken or not. These questions are usually caused by the fact that people lack the insight what is happening inside and what values values their variables hold.

The first general-purpose debugging technique is using Exploration.

You need to add several AddColumn statements and run your code as Exploration, so you can actually see the values of all variables. This will reveal whenever you really have values that you expect and would make it easier for you to understand what is happening inside your code.

In simplest form add this code to your system formula:

Filter 1// show all bars
AddColumnBuy"Buy" );

and it will show you if you are getting expected values in Buy array. You can use the same technique to track the content of any variable. Add as many columns as you want. You would be surprised how much insight into your own code you will get.

You can use Exploration to learn how particular function works, for example, if you don’t understand how ValueWhen works, you can display its results this way:

Filter 1// show all bars
//
MAC10 );
cond CrossC);
bi BarIndex();
//
AddColumnC"Close" );
AddColumnm"Mov Avg" );
AddColumncond"Condition");
AddColumnbi"BarIndex" );
AddColumnValueWhencondbi ), "ValueWhen( cond, BarIndex() )" );
AddColumnValueWhencondClose), "ValueWhen( cond, Close )" );

If you run above code you will clearly see how ValueWhen picks the value when condition is true and “holds” it for all other bars (when condition is false).

Debug using Exploration

Once you get this level of insight into your code you will be better equipped to fix any errors.
Exploration is number one choice in getting detailed view on what is happening inside your code.

For more information about Exploration see http://www.amibroker.com/guide/h_exploration.html

Closing trades in delisted symbols

When we perform historical tests on databases that contain delisted symbols – we may encounter a situation, where there are open positions in those tickers remaining till the very end of the backtest, distorting the results (as these open positions will reduce remaining maximum open positions limit for the other symbols).

Here is an easy technique which allows to force closing positions in those symbols on the very last bar traded for given symbol. The code below just adds an additional Sell signal on the last available bar in the database for this symbol:

bi BarIndex();
exitLastBar bi == LastValuebi );
Sell /*your regular sell rules*/ OR exitLastBar;

If we are using 1-bar trade delays in our backtesting settings, then the exit signal would need to be triggered one bar in advance (so the delayed signal could still be traded on the last bar) and the code would look like this:

SetTradeDelays(1,1,1,1);
bi BarIndex();
exitLastBar bi == LastValuebi );
Sell /*your regular sell rules*/ OR exitLastBar;

There is also a dedicated field in Symbol->Information window which allows to store the delisting date directly in the database. AmiBroker allows to read that field from AFL code using GetFnData() function. If we have this field populated for delisted symbols for our symbols, then the code forcing exits on delisting date would be:

exitLastBar datetime() >= GetFnData("DelistingDate");
Sell /*your regular sell rules*/ OR exitLastBar

What is important, this approach would work also, when Pad and Align to reference symbol feature is used in Analysis window settings.

In order to populate Delisting Date field in the database, we can enter the dates manually through Symbol->Information window or use ASCII importer to import the information from the input text files. More details about ASCII importing can be found at:
http://www.amibroker.com/guide/d_ascii.html

How to identify signal that triggered entry/exit if multiple signals are used

When designing a trading system we often need to quickly identify which of the rules used in the code triggered the particular Buy or Sell signal. Here are some techniques that may be useful in such identification.

For the purpose of this demonstration let us use a sample formula, where the Buy signal may be triggered by one of three independent rules:

Buy1 CrossMACD(), Signal() );
Buy2 CrossCloseMA(Close50) );
Buy3 CrossRSI(), 30 );
//
Buy buy1 OR Buy2 OR Buy3

To determine which of those three rules generates the entry signal, we can either visualize signals in the chart or use Exploration feature of the Analysis window.

In case a custom chart is used, we can do the following:

  1. display the signal in custom chart title
  2. use PlotShapes function to indicate certain buy rule
  3. use PlotText to add pre-defined text labels.

The formula below shows sample implementations of these three techniques. This is actually one of many ways that can be used for coding such custom output:

Buy1 CrossMACD(), Signal() );
Buy2 CrossCloseMA(Close,50) );
Buy3 CrossRSI(), 30 );
//
Buy buy1 OR Buy2 OR Buy3;
//
// Standard price plot
PlotClose"Close"colorBlackstyleCandle);
//
// Custom title definition
BuyReason EncodeColor(colorGreen ) + WriteIf(Buy,"Buy signals: ",""
           + 
WriteIf(buy1"Buy1 """) +WriteIf(buy2"Buy2"""
           + 
WriteIf(buy3"Buy3""");
Title StrFormat"{{NAME}} - {{INTERVAL}} {{DATE}} Close %g ",Close ) +BuyReason;
//
// Plotshapes function calls
PlotShapes(Buy*shapeUpArrowcolorGreen0Low);
PlotShapes(Buy1*shapedigit1colorGreen0Low,-30);
PlotShapes(Buy2*shapedigit2colorGreen0Low,-45);
PlotShapes(Buy3*shapedigit3colorGreen0Low,-60);
//
//
// Custom text labels displayed with PlotText
if( SelectedValue(Buy) )
{    
   
SelectedValueBarIndex() );
   
maxy Status("axismaxy");
   
miny Status("axisminy");
   
0.15 * (maxy miny) + miny;
   
text WriteIf(buy1], "\nBuy1 """
          +  
WriteIf(buy2], "\nBuy2 """
          +  
WriteIf(buy3], "\nBuy3 """);
   
PlotTexttexti,  ycolorWhitecolorGreen );

The chart below shows how to use signal visualization technique implemented in the formula.

Chart Example 1

The other method is to use the Exploration feature of Analysis window that allows to generate tabular output, where we can display the values of selected variables. The detailed tutorial explaining this feature is available at:
http://www.amibroker.com/guide/h_exploration.html

For the discussed purpose of tracking the signals that triggered entry or exit, we can add the following code to our trading system to show the values of each Buy1, Buy2, Buy3 variables:

Filter Buy;
AddColumnBuy1"Buy1"1colorDefaultIIfBuy1colorGreencolorDefault ) );
AddColumnBuy2"Buy2"1colorDefaultIIfBuy2colorGreencolorDefault ) );
AddColumnBuy3"Buy3"1colorDefaultIIfBuy3colorGreencolorDefault ) ); 

Exploration Signal tracking

With regard to exit signals they can be visualized in a similar way as shown above, but there is also an additional functionality in the backtester, which allows to indicate the exit condition directly in the trade list. This can be done by assigning values higher than 1 (but not more than 127) to Sell variable.

Sell1 CrossSignal(), MACD() );
sell2 CrossMA(Close50), Close );
Sell Sell1 10 Sell2 20

The above expression will result in assigning value of 10 to Sell variable for the bars where Sell1 is true, 20 for the bars where Sell2 is true and 30 for the bars where both conditions are true.

These values will be indicated in the trade list:

Backtest exit signal tracking

It is worth to mention that values 1 to 9 are reserved for built-in stops and used internally by the backtester, and have special meaning:

  1. normal exit
  2. maximum loss stop
  3. profit target stop
  4. trailing stop
  5. n-bar stop
  6. ruin stop (losing 99.96% of entry value)
  7. reserved
  8. reserved
  9. reserved

Note also that you must not assign value greater than 127 to Sell or Cover variable. If you assign bigger value it will be truncated.

This is further discussed here: http://www.amibroker.com/guide/afl/equity.html

Broad market timing in system formulas

Some trading systems may benefit from attempt to time the broad market. A market-wide valuation, such as moving average, sentiment or some other mechanism may be used to tell if we should be in the market or not.

Flexibility of AFL language allows to create rules or indicators, which are based on more than just one symbol. This enables us to introduce additional filters based on wide-market index performance.

For the purpose of reading quotes of another symbol one can use Foreign or SetForeign functions.

The following formula shows how to generate entry signals in individual stocks when S&P500 index is above its 200-period moving average and exit signals when S&P500 is equal or below 200-period average (^GSPC is a ticker for Yahoo Finance data for S&P500)

//
// read S&P 500 values from ^GSPC ticker
//
sp500 Foreign"^GSPC""C" );
//
// market-wide filter should be in "state" form 
// (so it is True all the time when market is up)
//
marketup sp500 MAsp500200 );
marketdown NOT marketup;
//
// sample trading rules (MACD crossovers)
//
BuySignal CrossMACD(), Signal() );
SellSignal CrossSignal(), MACD() );
//
// combine per-symbo signals with broad-market timing
//
Buy BuySignal AND marketup// enter trade only when buy signal AND market is in up trend
Sell SellSignal OR marketdown// exit position if sell signal OR market turns down

A more complex broad-market timing that requires not only closing price of market index can be implemented using SetForeign function. SetForeign replaces all OHLCV data series with that of the “other” security and allows to calculate all kind of indicators that would normally use current security. Broad market timing does not need to be just “all-in” or “all-out” switch. For example one can switch the trading method depending on whenever broad market is trending or sideways.

//
// Switch to S&P symbol to calculate broad-market timing
//
SetForeign"^GSPC" );
//
// now we can calculate any indicator based on SP500 
//
MarketIsTrending ADX40 ) > 20// ADX (40 days) from SP500
//
// now go back to original data (current symbol)
// 
RestorePriceArrays();
//
// you can have different rules that are switched
// depending on what broad market is doing
//
TrendingBuy CrossCMAC30 ) );
TrendingSell CrossMAC30 ), );
//
SidewaysBuy CrossMACD(), Signal() );
SidewaysSell CrossSignal(), MACD() );
//
// switch methods using broad-market timing
//
Buy IIfMarketIsTrendingTrendingBuySidewaysBuy ); 
Sell IIfMarketIsTrendingTrendingSellSidewaysSell ); 

In this simple example we assume that market timing signals change very infrequently so they change much less often than Trending/Sideways Buy/Sell signals are generated. If that is not the case the switching logic would need to be more complex to decide what to do when we are in the “trending” trade and market switches to sideways mode. In such situation, the code above uses SidewaysSell signal to sell the position, which may or may not be what you are after.

Another example is changing position sizing depending on broad market conditions. We can choose to be fully invested when broead market is up and only 30% invested in down market.

//
// Switch to S&P symbol to calculate broad-market timing
//
SetForeign"^GSPC" );
//
// now we can calculate any indicator based on 
// SP500
//
MarketIsUp MAC200 ); // here C represents closing price of SP500
//
// now go back to origiginal data (current symbol)
// 
RestorePriceArrays();
//
// normal rules (in this example they do not chang)
//
Buy CrossMACD(), Signal() );
Sell CrossSignal(), MACD() );
//
// no more than 10 positions open at a time
//
SetOption("MaxOpenPositions"10 );
//
// change position sizing depending on broad market conditions
// in this example we will allocate:
// 10% per position
// if broad market is up (so we can be allocated upto 100% of funds)
// 3% per position 
// if broad market is down (so we can be allocated upto 30% of funds)
// 
SetPositionSizeIIfMarketIsUp10), spsPercentOfEquity );

Too small / unreadable Profit Table in the backtest report

Some of users may observe that their Profit table is too small, so the numbers get truncated or the text is too small.

First let me tell you that profit table in the backtest report is not really a table, but a bitmap image with fixed dimensions. Profit table, like any other user-definable report chart, is created by running an AFL formula present in the “Report charts” subfolder. The chart is rendered into bitmap image that gets later embedded in the backtest report.

The size of backtest report images depends on Analysis window settings. In order to increase the size of generated images, it is necessary to go to Analysis -> Settings, Report tab and increase the picture dimensions:

reportchartdim

Once you change it, newly generated reports will use enlarged image dimensions. Adjusted settings will affect new backtests only, but not the old reports that have already been generated.

Tip: You can create your own report charts by placing your own AFL formula in the “Report charts” subfolder.

Why do backtest results change?

From time to time we receive questions about why you can get different results back-testing the same code.

There are five reasons for differences in backtest results:

  1. Different data (for example if past history is updated/changed due to splits for example or backfill)
  2. Different settings / parameters (if your formula uses Param() functions that output values that may be changed from the Parameter window)
  3. Different formula (sometimes even slight change to the formula causes big change in the results, for example if your formula uses #include and included code has changed)
  4. The formula that self-references its previously generated results. Such code produces some data that is later used to produce next run output (for example your code produces composites that are later used – if those composites change – the input data change so the results change, or if your formula uses previous backtest equity)
  5. The formula directly or indirectly calls any function that produces random numbers such as Random or mtRandom, or functions that read external data that have changed

Using Zig-Zag in trading systems

Zig-zag indicator, as well as other functions using it (Peak/Trough, PeakBars, Troughbars), inherently look into the future. As such they should not be used in trading system formulas without taking precautions. The only way to fix the ‘problem’ is to delay the signal as long as it takes for zig/zag to stabilise last ‘leg’. The delay is variable and depends how much time it takes for defined percentage change to occur in the price series since last peak/trough.

Ready-to-use solution is presented in the Traders’ Tips section of the AmiBroker members area:
http://www.amibroker.com/members/traders/11-2003.html

(NOTE: access to members’ area is limited to licensed users only, if you forgot your password use reminder at http://www.amibroker.com/login.html)

Points-only backtest

Some users coming from Metastock ask for “points-only” test.

One needs to know that AmiBroker features way more sophisticated futures mode than MS ever had: http://www.amibroker.com/guide/h_futbacktest.html
It provides full support for futures trading, handling margin deposit, point value, etc.

“Points-only” test is kind of the simplest possible case, but if you want to do just that, it can be implemented using these two lines:

SetOption("FuturesMode"True );
SetPostionSize1spsShares ); // trade just 1 contract

That is all what you need to add to your formula to get point-only test.

Historical portfolio backtest metrics

Recently on the AmiBroker mailing list some users expressed wish to have access to some of portfolio backtest metrics available in “historical” form (i.e. as date series, as opposed to scalars), so they can be plotted as an indicator.

Implementing such functionality is actually easy with existing tools and does not require any OLE scripts. Everything you need is small custom-backtester procedure that just reads built-in stats every bar and puts them into composite ticker.
In the accompanying indicator code all you need to do is simply use Foreign() function to access the historical metrics data generated during backtest.

The code below shows the BACKTEST formula with custom backtester part:

// Replace lines below with YOUR TRADING SYSTEM
EnableRotationalTrading(); 
PositionScore 1/RSI(14); 
PositionSize = -25;
SetOption("WorstRankHeld");
SetOption("MaxOpenPositions"); 


////////////////////////////////////////
// BELOW IS ACTUAL CUSTOM BACKTESTER PART
// that can read any built-in metric (in this example UlcerIndex)
// and store it into composite ticker for further
// retrieval as data series

SetOption("UseCustomBacktestProc"True ); 

if( 
Status("action") == actionPortfolio )
{
  
bo GetBacktesterObject();
 
  
bo.PreProcess(); // Initialize backtester
 
  // initialize with null 
  // you can have as many historical metrics as you want 
  // (just duplicate line below for many metrics you want)
  
MyHistStat1 Null
  
MyHistStat2 Null// add your own 


  
for(bar=0bar BarCountbar++)
  {
   
bo.ProcessTradeSignalsbar );
  
   
// recalculate built-in stats on EACH BAR
   
stats bo.GetPerformanceStats); 
 
   
// the line below reads the metric and stores it as array element
   // you can add many lines for each metric of your choice
   
MyHistStat1bar ] = stats.GetValue("UlcerIndex"); // get ulcer index value calculated this bar
   
MyHistStat2bar ] = stats.GetValue("WinnersPercent"); // add your own

  
}

  
bo.PostProcess(); // Finalize backtester

  // now STORE the historical data series representing the metric of your choice
  // duplicate the line below for as many metrics as you want
  
AddToCompositeMyHistStat1"~~~UI_HISTORICAL""X"atcFlagEnableInPortfolio atcFlagDefaults );

  
// you can add your own as shown below
  
AddToCompositeMyHistStat2"~~~WP_HISTORICAL""X"atcFlagEnableInPortfolio atcFlagDefaults ); 
}

In the code above, for illustration purposes, we are exporting UlcerIndex and Winners Percent metrics as data series. They are stored in composite tickers for easy retrieval from indicator level.
You can easily extend code to include ANY number of metrics you want.

Now in order to Plot metrics as indicators, use this simple formula:

PlotForeign("~~~UI_HISTORICAL""UlcerIndex Historical"colorRedstyleLine );
PlotForeign("~~~WP_HISTORICAL""Winners Percent"colorBluestyleLine styleOwnScale );

As you can see with one Foreign function call you can read the historical value of any metric generated by the backtester.

NOTE: when running backtest please setup a filter in AA that EXCLUDES composites (group 253) from backtest set.

Low-level gfx example: Yearly/monthly profit chart

The code below is an little bit more complex example of Low Level Graphics functions (see http://www.amibroker.com/guide/a_lowlevelgfx.html)

It allows to display three kinds of charts:

  1. yearly/monthly profit table
  2. yearly profit bar chart
  3. average monthly profit bar chart

The type of chart is switchable from Parameters dialog.

It should be applied to ~~~EQUITY – portfolio equity symbol (so it only produces output if you run backtest before using it).



SetBarsRequired(1000000,1000000);
eq Foreign("~~~EQUITY""C" );

yr Year();
mo Month();

YearChange yr != Refyr, -);
MonChange mo != Refmo, -);

FirstYr 0;
LastYr 0;

startbar 0;

////////////////////////////
// SKIP non-trading bars
////////////////////////////
for( 0BarCounti++ )
{
  if( 
eq] )
  {
    
startbar i;
    break;
  } 
}

////////////////////////////
// collect yearly / monthly changes in equity
// into dynamic variables
////////////////////////////

LastYrValue eqstartbar  ];
LastMoValue eqstartbar  ];

MaxYrProfit MinYrProfit 0;
MaxMoProfit MinMoProfit 0;

for( 
startbar 1BarCounti++ )
{
  if( 
YearChange] || == BarCount )
  {
    
Chg 100 * ( -eq] / LastYrValue );
    
VarSet("ChgYear"yr], Chg );

    
MaxYrProfit MaxMaxYrProfitChg );
    
MinYrProfit MinMinYrProfitChg );

    if( 
FirstYr == FirstYr yr];
    
LastYr yr];

    
LastYrValue eq];
  }

  if( 
MonChange ] || == BarCount )
  {
    
mon mo];

    
Chg 100 * ( -eq] / LastMoValue );

    
VarSet("ChgMon" yr] + "-" monChg );
    
VarSet("SumChgMon"monChg NzVarGet("SumChgMon"mon ) ) );
    
VarSet("SumMon" monNzVarGet("SumMon"mon ) ) );
 
    
MaxMoProfit MaxMaxMoProfitChg );
    
MinMoProfit MinMinMoProfitChg );

    
LastMoValue eq];
  }
}

/////////////////////////////////////////////////
// Drawing code & helper functions
////////////////////////////////////////////////

GfxSetOverlayMode);

CellHeight = (Status("pxheight")-1)/(LastYr FirstYr ); 
CellWidth = (Status("pxwidth")-1)/14
GfxSelectFont"Tahoma"8.5 ); 

GfxSetBkMode);

function 
PrintInCellstringrowCol 
{
 
Color =  ColorRGBIIfrow == || col == || col == 13220255 ), 255IIfrow 2255220 ) );
 
GfxSelectSolidBrushColor   );
 
GfxRectangleCol CellWidth
                    
row CellHeight, (Col ) * CellWidth 1
                    (
row ) * CellHeight  1); 
 
GfxDrawTextstringCol CellWidth 1
                    
row CellHeight 1
                    (
Col ) * CellWidth, (row ) * CellHeight32+); 



YOffset 25;
XOffset 15;

function 
DrawBartextbarnumbarsyMinyMaxy )
{
 
BarWidth = (Status("pxwidth") - XOffset )/( numbars ); 
 
BarHeight Status("pxheight") - YOffset;
 
relpos = ( Miny ) / (Maxy Miny );

 
xp XOffset + ( bar 0.5 ) * BarWidth;
 
yp YOffset BarHeight * ( relpos );
 
xe XOffset + ( bar ) * BarWidth;
 
ye YOffset BarHeight * ( - ( -miny )/( maxy miny ) );
  
 if( 
)
 {
 
GfxGradientRectxpyp
                  
xe ye,
                  
ColorHSB70255 relpos255 ), ColorHSB7020255 ) ); 
 }
 else
 {
 
GfxGradientRectxpye
                  
xe yp,
                  
ColorHSB020255 ), ColorHSB0255 * ( relpos ), 255 ) ); 
 }
 
GfxTextOuttextxpye );
 
GfxTextOutStrFormat("%.2f"), xpyp );
}    

function 
DrawLevelsMinyMaxy )
{
  
range Maxy Miny;

  
grid 100;
  if( 
range 10 grid 1;
  else 
  if( 
range 20 grid 2;
  else 
  if( 
range 50 grid 5;
  else 
  if( 
range 100 grid 10;
  else 
  if( 
range 200 grid 20;
  else 
  if( 
range 500 grid 50;

  
_TRACE("grid = "+grid +" range "+range );
  
  
width Status("pxwidth") - XOffset;
  
height Status("pxheight") - YOffset;

  
GfxSelectPencolorBlack1);
  for( 
grid ceilMiny grid ); <= grid floorMaxy grid ); += grid )
  {
    
yp =  YOffset Height * ( -  ( Miny ) / (Maxy Miny ) );

    
GfxMoveToXOffsetyp );
    
GfxLineToXOffset width yp );
    
GfxTextOut""yXOffset widthyp );
  }

  
GfxSelectPencolorBlack1);
  
GfxMoveToXOffsetYOffset );
  
GfxLineToXOffset widthYOffset );
  
GfxLineToXOffset widthYOffset Height );
  
GfxLineToXOffset YOffset Height );
  
GfxLineToXOffset YOffset );
}

MonthNames "Jan,Feb,Mar,Apr,May,Jun,Jul,Aug,Sep,Oct,Nov,Dec";

function 
DisplayProfitTable( )
{
 
Header "Year,"+MonthNames+",Yr Profit%";
 for( 
Col 0; (Colname StrExtractHeaderCol ) ) != ""Col++ )
 {
  
PrintInCellColName0Col );
 }

 
Row 1;
 for( 
FirstYr<= LastYry++ )
 {
  
PrintInCellStrFormat("%g"), Row); 
  
PrintInCellStrFormat("%.1f%%"VarGet("ChgYear" ) ), Row13 ); 
  for( 
1<= 12m++ )
  { 
   
Chg VarGet("ChgMon" "-" m);
   if( 
Chg 
     
PrintInCellStrFormat("%.1f%%"Chg ), Row);
   else
     
PrintInCell"N/A"Row);
  }
  
Row++;
 } 

 
PrintInCell("Mon. Avg"Row);
 for( 
1<= 12m++ )
 { 
   
PrintInCellStrFormat("%.1f%%",  NzVarGet("SumChgMon" m)/VarGet("SumMon" ) ) ), Row);
 }

}

function 
DisplayYearlyProfits()
{
 
Bar 0;
 for( 
FirstYr<= LastYry++ )
 {
   
Chg VarGet("ChgYear" );
   
DrawBar""+yBar++, ( LastYr FirstYr ), ChgMinYrProfitMaxYrProfit );
 }
 
GfxTextOut("Yearly % Profit chart"1010 );

 
DrawLevelsMinYrProfitMaxYrProfit ); 
}

function 
DisplayMonthlyProfits()
{
 
Bar 0;
 
 
MinAvgProf MaxAvgProf 0;
 for( 
1<= 12y++ )
 {
   
Chg VarGet("SumChgMon" ) / VarGet("SumMon" );
   
MinAvgProf MinMinAvgProfChg );
   
MaxAvgProf MaxMaxAvgProfChg );
 }

 for( 
1<= 12y++ )
 {
   
Chg VarGet("SumChgMon" ) / VarGet("SumMon" );
   
DrawBarStrExtract(MonthNamesy-), Bar++, 13ChgMinAvgProf MaxAvgProf );
 }
 
GfxTextOut("Avg. Monthly % Profit chart"1010 );

 
DrawLevelsMinAvgProf MaxAvgProf ); 
}

///////////////////////////
// This function checks if currently selected symbol
// is portfolio equity
//////////////////////////
function CheckSymbol()
{
 if( 
Name() != "~~~EQUITY" )
 {
  
GfxSelectFont"Tahoma"20 ); 
  
GfxSetBkMode);
  
GfxTextOut("For accurate results switch to ~~~EQUITY symbol"1010 );
 }
}

////////////////////////////
// Main program - chart type switch
////////////////////////////
type ParamList("Chart Type""Profit Table|Yearly Profits|Avg. Monthly Profits");

switch( 
type )
{
 case 
"Profit Table"
         
DisplayProfitTable();  
         break;
 case 
"Yearly Profits"
         
DisplayYearlyProfits();
         break;
 case 
"Avg. Monthly Profits"
         
DisplayMonthlyProfits();
         break;
}

CheckSymbol();


Figure 1. Profit chart in table mode

Profit chart example 2

Figure 2. Profit chart in yearly mode

Profit chart example 3

Figure 3. Profit chart in monthly mode

Profit chart example 4

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