The VIT tools

[acepsut]

Hi Pascal,

I have just finished reading your book for the second time, and I found your work one of the best book I have ever read, if not the best one.

I really like very much the concepts you show and I have now a very clear view about how to look at the market: I want to thank you for disclosing your thoughts and methods.

I would like to code all the tools in my Java platform to be used for my own trades in the Italian stock market, and for this reason I have some questions just to be sure to code it properly because there are some things not really clear to me.

1) page 32 "What is effective volume flow?" is explaind as the simple sum of all the single effective volume: but it is then called "Total effective volume flow", then "Total effective volume".

I suppose all three statements means the same thing, the sum of all single effective volume, summed with its polarity ( + or -).

Am I correct?

2) page 32, about the PI number: this is not clear to me. Is PI the tick value for the stock to be analized? For tick I mean the minimum distance (step) the stock can move. Tick value change depending on the value of the stock: in example, a stock trading @ 20 € 1 tick = 0.01 € (20.00 then 20.01 and so on) while stocks trading @ 8 € has 1 tick = 0.005 € ( 8.000 then 8.005 etc.)

So my question is: should I always use a fixed PI = 0.01 or change the PI value according with the stock tick value?

3) pag 123, in order to verify my code, I have compared the EV result as from table 3.1 and it is all fine, but the EV value at the second row where you have a -5,057 value where it should be positive 5,057 since there is a price increase.

Is this a print error or I am missing something?

4) LEV SEV separation: I am using the equi power method as describe at page 54. The method is clear to me but still I have some doubt about how use the data to be anylized.

Should I use an incremental data method or a moving window data?

In order to be more clear, let's suppose I would like to perform an analysis on 1 day (1 minute data). Italian market open @ 0900 and close @ 1725 with 5 min extension for close fixing @ 1730. Live data ranges from 0900 up to 1725, that's 505 minutes per day since market stop any trading activities @ 17.25:00

Having set = 0 the first trading minute (0900), do I have to take all these 505 1 min data and compute the LEV SEV separation or do I have to use a moving window (in example, x data such as 100 or 200 1 min data) in which add the next data and remove the first one?

Page 214 describe the use of a moving window for the positive and negative EV, so I am a little confused for the approach to use.

What if we would analyze more data, in example, 3 or more consecutive days? Should I have to separate LEV SEV based on the whole three 1 minute days?

Do I have to set = 0 any of the three 0900 min or do I have to start a new separation for any day? If so, I should have a gap between last day value and the next day.

As last question, I wonder if I can have a feedback on my data: attached are two txt data both 1 min time frame, would be very happy to have a xls or txt result with EV, TEV, LEV and SEV separation using the equi power method.

Data is in ddmmyyyy with ; fields delimiter and . as decimal delimiter: I can upload as different date and delimiters

My result for 1 day (EniJul24) is as follow, all three plotted



and only LV plotted



Thank you very much for your support and help!

Regards,

Alberto

[Pascal]

1) page 32 "What is effective volume flow?" is explaind as the simple sum of all the single effective volume: but it is then called "Total effective volume flow", then "Total effective volume".

I suppose all three statements means the same thing, the sum of all single effective volume, summed with its polarity ( + or -).

Effective Volume is by definition the volume that is necessary to move the price up or down from one minute to the next.

Effective Volume Flow is the cumulative sum of the minute effective volume

Effective Volume can be separated into LEV and SEV. The total Effective Volume : SEV + LEV.

Now, on every day use, if skip the word "Flow" and use EV for the cumulative pattern.

2) page 32, about the PI number: this is not clear to me. Is PI the tick value for the stock to be analized? For tick I mean the minimum distance (step) the stock can move. Tick value change depending on the value of the stock: in example, a stock trading @ 20 € 1 tick = 0.01 € (20.00 then 20.01 and so on) while stocks trading @ 8 € has 1 tick = 0.005 € ( 8.000 then 8.005 etc.)

So my question is: should I always use a fixed PI = 0.01 or change the PI value according with the stock tick value?

You need to use what is used in the Italian market. If the tick chnages with the value of the stock, then you also adapt your calculation. The PI value however does not make much difference.

3) pag 123, in order to verify my code, I have compared the EV result as from table 3.1 and it is all fine, but the EV value at the second row where you have a -5,057 value where it should be positive 5,057 since there is a price increase.

Is this a print error or I am missing something?

You are right, it is a typing error

4) LEV SEV separation: I am using the equi power method as describe at page 54. The method is clear to me but still I have some doubt about how use the data to be anylized.

Should I use an incremental data method or a moving window data?

In order to be more clear, let's suppose I would like to perform an analysis on 1 day (1 minute data). Italian market open @ 0900 and close @ 1725 with 5 min extension for close fixing @ 1730. Live data ranges from 0900 up to 1725, that's 505 minutes per day since market stop any trading activities @ 17.25:00

Having set = 0 the first trading minute (0900), do I have to take all these 505 1 min data and compute the LEV SEV separation or do I have to use a moving window (in example, x data such as 100 or 200 1 min data) in which add the next data and remove the first one?

Page 214 describe the use of a moving window for the positive and negative EV, so I am a little confused for the approach to use.

What if we would analyze more data, in example, 3 or more consecutive days? Should I have to separate LEV SEV based on the whole three 1 minute days?

Do I have to set = 0 any of the three 0900 min or do I have to start a new separation for any day? If so, I should have a gap between last day value and the next day.

To calculate EV, you only operate day by day on the full data from the start of the day until the minute of calculation. No rolling windown for EV. Rolling windows are used for divergence, and LER.

Yes, you need a new separation every day.

As last question, I wonder if I can have a feedback on my data: attached are two txt data both 1 min time frame, would be very happy to have a xls or txt result with EV, TEV, LEV and SEV separation using the equi power method.

Data is in ddmmyyyy with ; fields delimiter and . as decimal delimiter: I can upload as different date and delimiters

My result for 1 day (EniJul24) is as follow, all three plotted

I am sorry, but I do not check other people's code. I do not have the necessary time to offer that type of service.


Pascal

[acepsut]

Thanks,

but if I perform a new separation every day, I will come to have that every new day the LEV and SEV will start from zero, so if for example previous day ended with LEV = 400 it should restart with LEV = 0, thus producing a quick jump to zero value.

So, if I want to perform a LEV SEV separation on 10 or more day data, I will have 10 or more jump back to zero value in continuous data.

There are no such example of zero back in VIT book: the fig 1.19 page 44 shows the separation on 20 days, but it is all continuous and it seems there is no new separation for each day.

Is this example based on one separation only for all 20 days data?

[Pascal]

Thanks,

but if I perform a new separation every day, I will come to have that every new day the LEV and SEV will start from zero, so if for example previous day ended with LEV = 400 it should restart with LEV = 0, thus producing a quick jump to zero value.

So, if I want to perform a LEV SEV separation on 10 or more day data, I will have 10 or more jump back to zero value in continuous data.

There are no such example of zero back in VIT book: the fig 1.19 page 44 shows the separation on 20 days, but it is all continuous and it seems there is no new separation for each day.

Is this example based on one separation only for all 20 days data?

You can separate LEV/SEV on a day basis but sum up the values that result from the calculation on 20 days or more.


Pascal

[acepsut]

You can separate LEV/SEV on a day basis but sum up the values that result from the calculation on 20 days or more.


Pascal

Thank you very much!