Author Archive

A big thank you to Dave Evans and Mrkt_Rewind for starting an educational video series on trading DV_indicators at the Quantum Indicators YouTube Channel!

Following is a video by Dave Evans using the rapid development MS Excel tools that are part of the DV_Indis Research Service to develop a Silver (SLV) Exchange Traded Fund system:

The acronym “LTR” simply stands for the Livermore Trend Ranking. The concept was inspired by literature on Jesse Livermore as well as legendary speculators like Nicholas Darvas. Both traders tended to favor stocks that were predictable and trended smoothly. Livermore was indifferent to direction- he was equally likely to short in bear markets, while Darvas preferred only those stocks that moved up. Both speculators wanted to be able to pyramid on their positions. Pyramiding means that they wanted a stock to “prove itself” by going higher/lower following purchase. At this point they would add to their positions in the direction of the trend. Having tried this strategy a long time ago, I realized that many stocks would simply pull back by the time I added my biggest position—leaving me at an immediate loss. I was beginning to experience the transition from trending markets to mean-reverting markets.


I realized that in order to find stocks that would be suitable for trend-based strategies or pyramiding, I would have to consider the “noise” in their daily behavior. I noticed by looking at price charts that stocks with smoothly trending price closes (and high/lows) seemed to have a higher tendency to follow through—that is an up day would tend to be followed by an up day, and breakouts had higher odds of success. This did not mean that a “trending” stock must go up—often this is a big point of confusion with high LTR stocks. Most people associate trending with going up. In fact a high LTR stock only means that the stock has less noise, it has nothing to do with relative strength or the probability that a stock will go up.


The calculation of LTR is highly proprietary, but is the best single measurement of a stock’s noise factor that I have tested. Intuitively it looks at the close to close volatility with respect to momentum. Academics (and option traders!) have long confused volatility as a pure proxy for risk. There is a big difference between “good” and “bad” volatility. If you look at high momentum or high relative strength stocks they have substantial “volatility” but typically they have less actual risk in most market conditions (with the exception of bear markets). The predictability of momentum stocks makes them easier to trade. The riskiest stocks are in fact are volatile stocks with little relative strength. If you were to buy and hold the most volatile stocks, you would in fact lose money and suffer much lower trade winning percentages than if you bought and held stocks with low volatility. That said, highly volatile stocks can be effectively traded with short term timing strategies. CXO Advisory recently reviewed an academic paper on this same topic: http://www.cxoadvisory.com/volatility-effects/combining-realized-volatility-and-simple-moving-averages/. The caveat here is that the volatile stocks that perform well with moving averages are not the ones with low momentum in relation to volatility. Furthermore, correlation also is a major mitigating factor as I will present in future research. Nonetheless, this academic paper indirectly lends support to the thesis that high LTR stocks tend to trend—and this effect is robust across stocks, not just for large caps.


[A full Livermore Trend Ranking report for both OEX and NDX stocks is provided weekly exclusively to DV_indis Research Subscribers]