In my previous post I suggested three different approaches to using PositionBook data other than directly using this data to create new, unique indicators. This post is about the first of the aforementioned ideas: modifying existing indicators that somehow incorporate volume in their construction.
The indicators I've chosen to look at are the Accumulation and Distribution index, On Balance Volume, Money Flow index, Price Volume Trend and, for comparative purposes, an indicator similar to these utilising PositionBook data. For illustrative purposes these indicators have been calculated on this OHLC data,
which shows a 20 minute bar chart of the EUR_USD forex pair. The chart starts at the New York close of 4 January 2024 and ends at the New York close on 5 January 2024. The green vertical lines span 7am to 9am London time and the red lines are 7am to 9am New York time. This second chart shows the indicators individually max-min scaled from zero to one so that they can be more easily visually compared.
As in the OHLC chart, the vertical lines are the London and New York opening sessions. The four “traditional” indicators more or less tell the same story, which is not surprising since their calculations involve bar to bar price changes or open to close intra-bar changes which are then multiplied by bar volume. Effectively they are all just differently scaled versions of the underlying price movement, or alternatively, just accumulated sums of different fractions of the bar volume. The PositionBook data version, called Pos Change Ind, does not use any OHLC information at all but rather uses the accumulated difference(s) between position changes multiplied by volume. For most of the day the general story told by the Pos Change Ind indicator agrees with the other indicators; however during the big run up which started just about 9am New York time there is a significant difference between Pos Change Ind and the others.
In hindsight, by looking at my order levels chart
and volume profile chart
it is easy to speculate about what market participants were thinking during this trading day, especially if the following PositionBook chart is taken into account.
For the purpose of the following brief “stream of consciousness” narrative imagine it's 7am New York time and looking back at the day's action so far it can be seen that the downward drift of the day seems to have halted with a mini double bottom, and we are now moving up with some new heavy tick volumes having accumulated over the last hour or so, forming a new volume profile point of control (POC). Over the next hour prices continue the new slight drift up with accumulating long positions and at about 8.30am we see a doji bar form on the 10 minute chart at the level of the rolling vwap for the day. Suddenly there is the big down bar, which could conceivably be a shake-out of the recently added longs, targeting the stop orders below, which finishes with an extended lower wick. This seems to be an ideal set-up for a long trade targeting either the old POC, which also happens to be the current high of the day, or the accumulated orders which happen to coincide with the level at which, currently, the greatest proportion of long positions have been entered.
Of course it can seen, in hindsight, that this was a great set-up for an intra-day trade that could have caught almost the entire high-low range of the day as a profitable trade, dependent of course on exact entry and exit levels. This set-up is a synthesis of observations from the volume profile chart, the order levels chart and the position levels chart, along with the vwap indicator. The Pos Change Ind indicator does not seem to add much value over that provided by the more traditional, volume based indicators in the set-up phase.
This is not necessarily the case for the exit. It can be seen that the Pos Change Ind indicator turns down sharply several bars before all the other indicators, and this movement in the indicator is evident by the close of the bar with the long upper wick which makes the high of the day. This sharp downturn in the indicator shows that there was a mass exit of longs during the formation of this bar, made clearer by the following chart which shows the two components of the Pos Change Indicator, namely the
“Outside Change” and the “Inside Change.” The outside change shows the total net position changes for the price levels that lie outside the range of the bar and the inside change is the net change for price levels that lie within the bar range. The greater change of the two is obviously the (red) inside change, and looking at the position levels plot we can see why. The previously mentioned level of “greatest proportion of long positions” suddenly loses that distinction – a large number of the longs at this level obviously liquidated their positions. This is important information, which shows that sentiment favouring long positions obviously changed, and it can be surmised that many long position holders were happy to get out of their trade at more or less break even prices. Also noticeable in the position levels chart is the change in blue shade from darker to lighter at the price levels within the range of the large price run-up. This reduction in colour intensity shows that those traders who entered during the run-up also exited near the top of the move. Taken together these observations could have been used as a nice short set-up targeting, for example, the then currently lower level of vwap, which in fact was subsequently hit with the day closing at this level.
As I had previously suspected, there is value in PositionBook data but it is perhaps tricky to operationalise or to easily automate within a trading system. It can be used to indicate a directional bias, or as above to show when traders exit positions. Again, as shown above, it can be used to put a new, useful twist on existing indicators, but in general it appears that use of this data is primarily visual by way of my PositionBook chart and subsequent, subjective evaluation. Whilst I am pleased with the potential insights provided, I would prefer a more structured, algorithmic use of this data, as in the third point of my previous post.
More in due course.
