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Blog / Position Size Selection

Position Size Selection

2013/04/06. - 14:09

 

In this writing  I try  to highlight  some aspects of  position size.

This  is Not equal to Position Management  before and during market participation.

It might be  quite different from person to person and strategy to strategy and time- to time-frame how we build up and tear down our positions.

As a predictor player  having overnight positions I  found  for this purpose to build Up  the position  mostly in one  buy / sell order  and in less than 10 % of the cases  in two  orders.

Having a position overnight  I found  the best results  could be achieved  by closing that  position  in two  orders, or sometime (Less than 15% of the  cases in three orders) and  occasionally in one order, especially if  need to act quickly to  limit losses occasionally.

 

This article  makes a few considerations about possible  factors, that impact  our decision making, when  we think about position size, before opening a position as a result  of  our analysis   considering  predictor  data  and other market  analysis.

 

Position size should reflect our  confidence  in our trading decision.

It can have multiple  factors or aspects, but  best if  we try to stay  objective, depend on  available data,  though we might  also add  psychological factors, like our perceived mental strength at the time of  position  opening, especially if we are daytraders.

 

The available funds for market participation is  our starting point and also impact the  risk, that we  accept to bear.

From this  two we can usually  get  two numbers:

1.       The Maximum position size, that we  would take in the best case. (MaxPos)

2.       The Minimum position size,  that we would take in the least confident situation.

(MinPos)

 

Most of the time our actual position size  will be between MinPos and MaxPos.

We introduce  PSC, Position Size Coefficient,  that will be a measure of our actual position,

Between MinPos and MaxPos.

PSC can be   the result of an equation, that takes into account the different position-size related  parameters that we consider important. We will detail  a possible construction of  PSC later.

 

No matter what  are those parameters,  PSC will have a Maximum value, PSCMAX  in  the best situation and a Minimum value PSCMin in the least confident situation.

See the chart below for illustration:

.

With the introduction of the above the Actual Position Size (ActPosSize)  could be calculated  something like the following:

 

 

Pos_Size_Sel_2 

 

To  visualize it  lets say we have a Minimum Position Size of MinPos $ and a Maximum Position Size of  MaxPos $.

With these data I created  the following   chart  to demonstrate  visually the  Actual Position Size Selection.

 Pos_Size_Sel_1

 

ActPSC, the Actual Position Size Coefficient  could be calculated, taking into account the most important  parameters.

The following is only one example, that  those, who rely on the predictionwizard  generated win probabilities for the Daily and  / or Weekly  predictions of a specific Index:

 

ActPSC = A * B * C * D where

 

A:   Prediction Win Probability related parameter

This parameter is related to either the Daily prediction win probability Or the Weekly prediction win probability or a combination of both, depending on our preference and time – frame, that we intend to play.

 

A (Actual)  = A(Min) + (A(Max) – A(Min)) *  (Pwin – Pwin(Min)) / (Pwin(Max) – Pwin(Min))

Where:

Pwin is the actual win probability, calculated by the predictor system (It is the Daily win probability if we use only that  in our calculation, but  we also could use  the weekly and / or the monthly predictor  generated, actual win probability if we trade different time frames.)

 

Pwin(Min) is the Minimum win probability that is generated by the system and we use for our trading purposes.

 

Pwin(Max) is the Maximum win probability that is generated by the system.

 

A(Min) is the Minimum parameter  data that we would like to get (It is our decision)  for this parameter.

A(Max) is the Maximum parameter  data that we would like to get (It is our decision)  for this parameter.

 

If we would like to have  the “A” win probability   related parameter to have a bigger  impact on the ActPSC (Actual Position Size Coefficient), than we select  A(Min) and A(Max) in such a way, that  A(Max) / A(Min)  ratio  is bigger, and if we would like the  win probability  related parameter to have a smaller impact on ActPSC, than we compress  that A(Max) / A(Min)  ratio,  and select that  to be smaller.

The following chart  try to show  the two scenario:

 Pos_Size_Sel_3 

Note  that we could select A(Max)- A(Min) range in such a way, that  the  medium of the range is equal to one,  and when   A = 1 than  we can say that  the Actual prediction win probability  will not alter  the final  position size coefficient  in this calculation sequence.

 

It is easiest  to select  A(Min) to be one, and A(Max) to be slightly bigger than one.

Lets say we  would like  the win probability  - related parameter alone to have a 50 [%] impact on the ActPSC, meaning that this parameter alone might alter ActPSC by 50 [%], than  we select   A(Min) and A(Max) so that   A(Max) / A(Min) = 1.5

So for example we  can set A(Min) = 1   and   A(Max)  = 1.5

 

A will be A(Min), when the predictor win probability will be minimum (Say 55 [%])  and A will be equal to A(Max) when  the  actual calculated win probability of the system is equal to the maximum (Pwin = Pwin(Max)   Say it is 83 [%]  for the NASDAQ Daily prediction (We can get this from the  downloadable prediction   history data for all indices, which is available in Excel spreadsheet format.)

 

Note  that this is the same transformation function,  that we used to  transform one specific  data range into another at the beginning of this article.

 

But  in our case, we have  four  parameters, A, B, C and D  multiplied by each other, so  the final impact  on ActPSC will be the multiplication of each individual parameter, A, B, C, and D so if we want to decrease the impact of any one of them, than we need to transform  that specific parameter data range  into a smaller range.

 

B:   Trend Direction related parameter

This parameter takes into account the information, that  the predictionwizard works in such a way, so that the actual win probability,  will slightly depend on the trend direction.

If  predictionwizard predicts  a direction and   that direction  is the same as the current  short – to mid  term trend direction (10 Day to 3 Month), than  the Actual Win probability is slightly higher than the calculated  win probability and If  predictionwizard predicts   a direction  which is the opposite  of the short – to mid – term trend direction, than the Actual win probability is slightly lower, than the calculated one, presented on the WEB – site.

(The  calculated win probability does Not take into account the actual short – to mid term trend direction, it is an aggregate, taking into account multiple years of data, regardless of trend direction.)

So  with this we can calculate B  as follows:

 

B = ( 1 +  Kt)  where

Kt   is a constant that we select. For example  from the 0 … 0.5 range.

If the predicted direction is  the same as the short – to mid term trend direction, than Kt is greater than zero.

Kt is zero,   if the predicted direction is the opposite of the short – to mid – term trend direction.

For example If Kt  =  +0.3   then    B = (1 + 0.3)  = 1.3  (Predicted direction is the same as the trend direction.)

 

If Kt = 0, then   B = (1 – 0) = 1  (Predicted direction is opposite of the trend direction.)

In this case the  maximum impact of  “B”  for the final Actual position size coefficient (ActPSC)  is:   (1.3 / 1 * 100 – 100) =  30 [%]

 

If we would like the Trend Direction related parameter to have smaller impact on our trading position size coefficient, than we select  Kt as 0 / 0.2  for example.

 

In this case the impact  of this parameter would be: 

((1+0.2) / 1 * 100 – 100)  = 1.2 / 1 * 100 - 100 =   20 [%]

 

C:  Market volatility – related parameter.

If we plan to  have relatively smooth P/L curve  on a long-term period, than this must be represented in our position size selection.  So many traders  go bust just because of this simple  phenomenon.  This  parameter can be multiple things, like something, related to the  Daily Average Range for the past N Days or  a  simple indicator, that is widely available, the VIX.

Obviously  If the market volatility is high,  than we need to decrease our trading position size accordingly so the  position size – VIX relation is inverse.

 

The Average of the VIX  during the past many years was between 20  and 25.

 

The Maximum VIX value during the last 10 years was above 80, the minimum  was about 11 so the ratio  between Max and Min is about 7.

This is way too much,  but even during the past  three  years,  the ratio of the  VIX(Max) / VIX(Min)  was about  4.

Yes we need to  allow the VIX to have a relatively big impact on our position size selection, especially  for those periods of extreme volatility, but still probable smaller, than the actual  ratio of the VIX(Max) / VIX(Min)

If we want  to  transform the VIX impact  to the “C” parameter in such a way, when  the ratio between the C(Max) / C(Min)  = 3,  than we can select  for example:

C(Min)  = 1

C(Max) = 3

This will make it possible to alter the normal position size coefficient by 200 [%].

The reason  to decrease the impact of the  variability of VIX for the position size coefficient  could be that  over time and with some experience  the brain and thinking process could adopt  to the increased volatility  slightly and  intuitive traders learn to handle the increased risk.

But still we need this to restrain our trading during heightened risk in the market.

The following chart demonstrate the  transformation of the VIX to the defined “C” parameter, and  the equation  below the chart describes   the calculation of the Actual C parameter value, knowing the Actual VIX value.

 

 

Pos)Size_Sel_4 

D:  Other Market-related or Technical  indicator – related parameter.

This could be anything that  we consider  important for position size calculation.

It  could be one specific technical indicator, like overbought / oversold condition, momentum indicator, strength indicator or a combination of indicators.

We can also include  a Mental Strength Indicator  if we are trading intraday, and we would like to have that represented.

It can be a continuous function,  a step function or a set of data, that we define from  other indicators, something like this:  (Very Supportive, Supportive, Neutral, Against position, Strongly against position with corresponding data representation as  of  5, 4, 3, 2, 1)

 

To clear up this a bit I  present  a few examples:

 

- The Daily prediction for the NASDAQ and the Omega prediction  gives a Long signal.

- For this “D” parameter calculation we decide to use the CCI indicator (Commodity

  Channel Index), call it TechParam, and   the value of this will be the following, in support  of a Long (Bullish) position:

TechParam = 5  If   the CCI  was below the -100 level during the past few days, but just turning upward Today  and is about to cross  the -100 level. (For CCI indicator users this is a Bullish  situation.)

TechParam = 4  If   the CCI  was below -75.

TechParam = 3  If   the CCI  was between -75 and +75.

TechParam = 2  If   the CCI  is above +75 but the direction of the indicator is Upward.

TechParam = 1  If   the CCI  is above +75. but the direction of the indicator is Downward.

 

The D parameter, which can take five distinct value,  can be viewed on the following chart.

 

 

Pos_Sel_5

 

Another example for  a Technical indicator is that we  use a channel (Which could be a trading range   in a range market  and a trend channel in a trending market.)

We split this channel  into five  equal size regions.

In the midst  of a range market in the past few weeks let’s  assume, that the predictor gives a Long signal.

Now in this case If the market index  is in the top 20 [%]  of the range, meaning that it is close to strong resistance levels from which the market turned back down,  we  enter a value for this TechParam = 1 as it is not supporting the Long position.

In case of a trending market  it is more probable that the market participants will not interpret the  top 20 [%] range as resistance, as  the market  moved higher  recently in similar situations.

If the market  is in the bottom 20 [%]  area of a market range, than we enter 5 for this TechParam in a range market, as  it is more probable, that  the recent market behavior will prevail, and  the market  will find  support at current levels and  will turn  upward  with a higher probability.

 

Only our imagination limit the possibilities here.

 

All this might look  a bit complicated, but it really does not.

To make the whole idea easier to understand  I created a Demo Excel file and  implemented  “A”,  “B”,  “C”  and “D”  parameter there as  potential impacts for our position sizing.

You can download this  Excel file from HERE.

The name of the Excel file is Pos_Size_Calc_Tool_Demo and it can be downloaded from the predictionwizard download area:

http://www.predictionwizard.com/admin.php?p=downloads&act=downloads&parent=765

 

Please read the comments first, and after that you can experiment with it  as you like.

It might be ideal to save the original file with a different name first and do  your own experiment on a copy and not on the original file.

You can modify or tune it to your  preference  if you find it  valuable for yourself.

It is a general purpose Demo Tool,  that could be  valuable for those, who consider  position size  and position management  extremely important as I do.

 

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