Creation (i.e. algoritms used) of Indicative data...
Hi,
I was wondering if anyone out there knows the techniques or algorithms used to create indicative data? As you're probably aware, the data provided by MetaQuotes (via their download function) is indicative data, as opposed to real (or specific broker) data. For those who don't know, indicative data is quote data supplied by a number of different brokers that's combined to form a "representative" data set. Since currencies aren't traded on a central exchange, every broker's quotes vary slightly.
But to get back to my original question, does anyone have any idea as to how this data is created? It seems to have a higher volatility compared to real data. Is this because when the data is combined, the highest from all the data sets is used for the high and the lowest low from all the data sets is used as the low? How is the open and close calculated?
If anyone can shed some light on this, I would greatly appreciate it.
I was wondering if anyone out there knows the techniques or algorithms used to create indicative data? As you're probably aware, the data provided by MetaQuotes (via their download function) is indicative data, as opposed to real (or specific broker) data. For those who don't know, indicative data is quote data supplied by a number of different brokers that's combined to form a "representative" data set. Since currencies aren't traded on a central exchange, every broker's quotes vary slightly.
But to get back to my original question, does anyone have any idea as to how this data is created? It seems to have a higher volatility compared to real data. Is this because when the data is combined, the highest from all the data sets is used for the high and the lowest low from all the data sets is used as the low? How is the open and close calculated?
If anyone can shed some light on this, I would greatly appreciate it.
Most of brokers who allows automated trading offers filtered datas (less ATR on small TFs) to avoid scalping. But, as they are not tradable, there is no need to filter indicative datas.
Hi MichelB,
Thanks for your response.
Just wondering what you mean by your explanation of filtered data? Are you saying that the brokers reduce the average true range of the price quotes? And what does "TFs" mean?
I would have thought that brokers would have liked scalpers as it means lots of trades and hence, lots of commissions for them. Am I wrong in assuming this?
Thanks for your response.
Just wondering what you mean by your explanation of filtered data? Are you saying that the brokers reduce the average true range of the price quotes? And what does "TFs" mean?
I would have thought that brokers would have liked scalpers as it means lots of trades and hence, lots of commissions for them. Am I wrong in assuming this?
I would have thought that brokers would have liked scalpers as it means lots of trades and hence, lots of commissions for them. Am I wrong in assuming this?
Yes, this is really wrong ! at least for the retail brokers (most of the MT4 brokers); You are not trading on the interbank market, you are in a little private casino : in two words, if you loose, the broker win and if you win, the broker loose. Scalping is a tremendous powerfull way to win a lot of money with very little risk, thus no one broker likes that very much.... Most of the time, if your trades are considered as scalping, they will be canceled, or your account closed in matter of hours, use of EA disabled, or you will be puted on "manual desk" i.e. 5 minutes to open a position and so on ... So first, ask your brok what precisely he means by "scalping", what is allowed and what is not so everyone is happy.
And what does "TFs" mean?
Timeframes
Are you saying that the brokers reduce the average true range of the price quotes?
Yes, I mean that. Just compare the feeds of several brokers, and an "indicative datas" feed, or even an interbank feed like Dukascopy or MBTrading, you will understand...
Hi MichaleB,
Very interesting! I knew that brokers settled trades internally as much as possible, before settling them with their external bank (i.e. essentially playing market maker between their clients). I thought that the quotes would vary slightly from the "market" (whatever that may be) price between brokers because of these internal market making activities but I didn't realise that they actually tweaked the quotes themselves.
So you're saying that they actually reduce the ATR of quotes? Do you know at all which time periods this tweaking would affect? I can imagine that this tweaking would show up in 1m, 5m, 15m charts - how about 1h, 4h, daily charts etc? As you suggested, I had a look at the Dukascopy website and found that they display the daily ranges. I checked a few of the Dukascopy daily ranges with a MetaQuotes broker's daily ranges and they were pretty much identical (1-2 pip difference).
I could imagine that they average out a number of interbank market ticks (say, 10 ticks) and then feed you this average tick as "their" tick, rather than feeding you every incoming interbank market tick. This would certainly slow down the scalpers. Are you sure that it's not this that they're doing?
Thanks for the info thus far - much appreciated!
Very interesting! I knew that brokers settled trades internally as much as possible, before settling them with their external bank (i.e. essentially playing market maker between their clients). I thought that the quotes would vary slightly from the "market" (whatever that may be) price between brokers because of these internal market making activities but I didn't realise that they actually tweaked the quotes themselves.
So you're saying that they actually reduce the ATR of quotes? Do you know at all which time periods this tweaking would affect? I can imagine that this tweaking would show up in 1m, 5m, 15m charts - how about 1h, 4h, daily charts etc? As you suggested, I had a look at the Dukascopy website and found that they display the daily ranges. I checked a few of the Dukascopy daily ranges with a MetaQuotes broker's daily ranges and they were pretty much identical (1-2 pip difference).
I could imagine that they average out a number of interbank market ticks (say, 10 ticks) and then feed you this average tick as "their" tick, rather than feeding you every incoming interbank market tick. This would certainly slow down the scalpers. Are you sure that it's not this that they're doing?
Thanks for the info thus far - much appreciated!
Dukascopy provides also free charts for every timeframe (starting from 10 sec and even tick charts), check this page http://www.dukascopy.com/swiss/english/data_feed/webproducts/charts/ .
I am not a broker, so I do not know what algo they are using, but ofcourse only low timeframes are concerned.
One can see is for sample that if a M5 bar Dukascopy has 3 top-bottom runs, there is only one on Ibfx; Also the ATR is lower, but on the H1 bars prices are pretty the same; things like that...
I am not a broker, so I do not know what algo they are using, but ofcourse only low timeframes are concerned.
One can see is for sample that if a M5 bar Dukascopy has 3 top-bottom runs, there is only one on Ibfx; Also the ATR is lower, but on the H1 bars prices are pretty the same; things like that...
Hi MichelB,
Thanks again for the info - much appreciated! It's great talking to someone who has a bit of in-depth knowledge about these things....
Thanks again for the info - much appreciated! It's great talking to someone who has a bit of in-depth knowledge about these things....
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I was wondering if anyone out there knows the techniques or algorithms used to create indicative data? As you're probably aware, the data provided by MetaQuotes (via their download function) is indicative data, as opposed to real (or specific broker) data. For those who don't know, indicative data is quote data supplied by a number of different brokers that's combined to form a "representative" data set. Since currencies aren't traded on a central exchange, every broker's quotes vary slightly.
But to get back to my original question, does anyone have any idea as to how this data is created? It seems to have a higher volatility compared to real data. Is this because when the data is combined, the highest from all the data sets is used for the high and the lowest low from all the data sets is used as the low? How is the open and close calculated?
If anyone can shed some light on this, I would greatly appreciate it.