A question about the actions of Large Players

[nickola.pazderic]

I have one question. Perhaps it has been answered, and I have missed it. I can miss things under my nose. My search is proving, however, futile. And I'm impatient enough with my progress that I bring the following question directly to the group:

"Is there an assumption in the book, Value in Time, that large institutions must leave a trail of LEV because they purchase or sell securities in relatively-- yet concealed-- concentrations? Is this an axiom of the EV system? Has this assumption been proven empirically or otherwise?"

Please excuse me if I've missed the data or the point in the book or elsewhere.

Many thanks,

Nickola Pazderic

[Pascal]

This is a good question because it goes back to the basic principle in the back of the EV method and the LEV/SEV separation (Large/Small players).

The idea is that if a fund wants to buy for 5 Million$ of a $20 company that trades about 1 Million shares per day, the fund cannot obviously do that on the open market in one day. What sorts of possibilities exist?

There are the "dark pools" type of exchanges, which are fund limited.
The fund can also order these shares at an average VWAP price for the next X days. The order will go to the marketmaker who will try whatever possibility to keep the price low while accumulating shares for his customer (the simplest strategy is "stop fishing").
The next possibility is to buy shares on a regular base on the open market, but do it is small enough quantities so as not to push the price up. for example, the fund could buy 5% of the exchanged shares every day for the next 20 days or 10% for the next 10 days. That sort of volume will leave traces, because it pushes the Demand/Supply always in the same direction and the probability that you will see price upticks on large volume is higher than seeing price downticks on large volume. Therefore, by sorting the up/down ticks by volume size, if the majority of the large volume traded is responsible for upticks or downticks, then we can conclude that there was a "will" to buy/sell some large volume.

What we do not know is the reason for such a decision or the culprit. It might be 500 individuals who made exactly the same analysis and who bought each for $10,000 of shares (very unprobable) or more probably one ior two fund managers who bought a big chunk.

So, to come back to your question, the book's assumption is not that large players have left a trace. The assumption is that there is a trace of accumulation/distribution and when that trace is "strong enough" and occurs at critical period in the price trend (during a trading range, on a pull-back, in a support/resistance area), then most often than not, this gives the direction of the future price move. It is a statistical analysis, not a "sure pattern".


Pascal

[nickola.pazderic]

Pascal--

Yes, I very much understand the methodology, which Dr. Elder has called revolutionary. And this methodology is based on the logic presented above.

Reading the book, I must confess to the biases of anthropology: in every instance we're professionally curious about what people think and do. If the book had come to me for review prior to its publication, I would have asked the editor to prod the author to offer some quotes, examples, and references to substantiate the logic of the project.

The book was never sent to me, of course. When it was published I was still teaching qualitative research methods and courses on neoliberalism. In short, I was teaching students to track down the effects of the global economy on the everyday lives of people and Taiwanese, in particular. The market was known only to me in a very abstract way. In fact, a brilliant graduate student introduced me to the stock market as something where people like her were involved. My first question to her: "What's that for?" To which she replied "To make money."

So now you know how slow I am!

Many thanks,

Nickola Pazderic

[mklein9]

Pascal,

Thank you for the detailed answer to Nickola's question. I have similar questions but not having a strong trading background don't have as good an idea of where to start.

I would certainly agree that "smart" players would carefully hide their transactions. Perhaps my primary question about EV methodology is why the large players (who we assume have all means at their disposal to hide their intentions) would cause a large change in price from minute to minute (compared to the high-low difference during that minute), which is what LEV/SEV separation is based on. Wouldn't they want to structure their transactions to produce a small price change at a high volume?

I think I am asking why you chose the Williams method as the basis for EV, as opposed to, for example, an OBV of some form, or even something like looking for the smallest price change at high volume as potential evidence for "big smart" transactions. Is there prior work that shows some basis for this model? I would certainly be interested in learning about the issues. Did you try other methods of detecting EV before writing your book?

Anyway, it may very well be that the details of the low level calculations are not as important as the averaging effect of 1000+ stocks.

[adam ali]

The comment below from the previous posting by a community member:

Perhaps my primary question about EV methodology is why the large players (who we assume have all means at their disposal to hide their intentions) would cause a large change in price from minute to minute (compared to the high-low difference during that minute), which is what LEV/SEV separation is based on.

Is this an accurate portrayal of the methodology? I thought EV calculates effective volume based on as small as a penny a share change from one minute to the next.

[Pascal]

Pascal,

Thank you for the detailed answer to Nickola's question. I have similar questions but not having a strong trading background don't have as good an idea of where to start.

I would certainly agree that "smart" players would carefully hide their transactions. Perhaps my primary question about EV methodology is why the large players (who we assume have all means at their disposal to hide their intentions) would cause a large change in price from minute to minute (compared to the high-low difference during that minute), which is what LEV/SEV separation is based on. Wouldn't they want to structure their transactions to produce a small price change at a high volume?

I think I am asking why you chose the Williams method as the basis for EV, as opposed to, for example, an OBV of some form, or even something like looking for the smallest price change at high volume as potential evidence for "big smart" transactions. Is there prior work that shows some basis for this model? I would certainly be interested in learning about the issues. Did you try other methods of detecting EV before writing your book?

Anyway, it may very well be that the details of the low level calculations are not as important as the averaging effect of 1000+ stocks.

The selection of the Larry Williams' adapted method is what looked best as I did not have access to tick data at that time. What I however did was to use as effective volume the total volume traded during one minute, as far as the minute was showing a price inflection. This method (OBV) was also good at shwoing accumulation/distribution. Larry Williams seemed to be more precise though. Today, I'd use tick data for sure instead of LW.



Pascal

[Pascal]

Paul,


There is a large block filtration algo inside of the method. It is not explained in the VIT book, but since a large block that does not impact the price is probably an "arranged" trade (for example between the MM and his customer), you want to filter this out, otherwise this sort of transaction "pollutes" the EV pattern. The filtration algo is to filter out the minutes whose traded volume is higher than 5% of the daily volume, but which does not impact the price by more than 1%.

[mklein9]

Is this an accurate portrayal of the methodology? I thought EV calculates effective volume based on as small as a penny a share change from one minute to the next.

Adam, you are right. I didn't give the complete picture: EV is the change in minute to minute price, divided by the difference between high and low during that minute (which can be modified by the previous minute's close if higher or lower), times the volume during that minute.

Maybe a more specific example would help.

In one minute a share price changes from 20.00 to 20.01 with high of 20.10 and low of 19.95, and volume of 100,000 shares. The EV for that minute is:

EV1 = (20.01 - 20.00 + 0.01) / (20.10 - 19.95 + 0.01) * 100,000 = 0.02 / 0.16 * 100,000 = 12,500

If we have a smaller volume minute but with a larger change in price we may end up with a higher EV. Let's say the price changed from 19.98 to 20.09 but at only 1/5 the volume of the previous example (and high and low the same). EV then would be:

EV2 = (20.09 - 19.98 + 0.01) / (20.10 - 19.95 + 0.01) * 20,000 = 0.12 / 0.16 * 20,000 = 15,000

Which of these two examples would we think is more likely to be "stealth" accumulation? That is my question.

(BTW, I don't know nor am implying I know the answer. I'd just like to be able to learn from what others may have done in this regard.)

-Mike

[TraderD]

I find it interesting (but not really surprising) that the EV method discussion gets directed towards tick-based volume analysis. Linnsoft's Investor/RT tool includes "Volume Breakdown" and "Cumulative Delta" capabilities for several years (and instructional videos on their site: http://www.linnsoft.com/vb) as well as courses offered by Fulcrum Trader (http://www.fulcrumtrader.com, previously active on EliteTrader.com under AMT4SWA nickname). I had some hands-on experience with system testing using VB principles in 2009 but the statistical edge using a single instrument turned out to be too slim to be of practical use for retail trading.

The VB analysis is reportedly most relevant to instruments that trade 24x7 and capture all traded volume (e.g. ES futures contract on Globex). Maybe this is where discrepancies in EV measurements produce less-than-ideal examples on a stock-by-stock basis. My own hunch (tho not proven) is that EV analysis shines due to the law of large numbers when statistics is aggregated across a large number of stocks over a period of days/weeks. In other words, if you look under a microscope, you're bound to find plenty of errors, but taken together, you get a much better signal/noise indicator.

Availability of tick-data history (unless you're a GS) is rather limited and would require considerable storage and data management efforts to carry out, compared with processing 1-min data. Saying it, if the EV method accuracy warrants it and can be translated into a non-trivial boost to EV robot performance, such effort would be quite worthwhile IMHO.

-TraderD

[Andrei]

FWIW, here is a company that provides historical tick data for equities, futures, options and so on...

http://www.tickdata.com/