Tharp's Thoughts Weekly Newsletter (View On-Line)
Reflective Learning by Ali Moin-Afshari
A Market That is Neither Risk-On Nor Risk-Off by D.R. Barton, Jr.
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Many people hold a wonderfully romantic belief that great traders are born with a God-given talent for trading. I don’t think so. But then what is talent? It could be defined as how someone is hard-wired, apart from knowledge or skills. Talent dictates someone’s moment to moment reaction to the environment, a unique instinctiveness, a immediacy implied. Talent results in consistently recurring patterns of thought or behavior. To deviate from those patterns requires conscious effort, and such deviations are difficult to sustain.
On the other hand, traders spend a lot of time working alone, time thinking about various aspects of our work. The root of success in everything, from trading to leadership to personal relationships and elsewhere is thinking; whether it’s thinking disguised as intuition or good values or decision making or creative problem solving - it’s all thinking. So, one supportive aspect of developing talent is to be able to think in a structured manner.
In learning something new, talent can be considered as nothing more complex than extreme interest. Extreme interest in what you are doing keeps the inner flame blazing, which creates an open mind, prevents you from getting bored, and keeps your mind actively engaged in the learning process. Talent is also the neuro-network you build in your brain-body as you learn more, analyze constantly, and develop interrelationships between isolated pieces of information. Extreme interest is the key to keep you learning aggressively by looking in all directions and staying hungry for information. It also keeps the brain engaged in constant analysis of new information to find new relationships with past experiences and concepts that are already learned. Over time, your acquired knowledge reaches a critical mass at some point which then enables you to think outside the box.
Quality learning plays an important role in a trader’s development. Surprisingly, the basic methods for thinking more clearly, more innovatively, more efficiently, are fundamentally the same in all areas of life – including trading. Maybe more surprisingly, methods of effective thinking can be described, taught, and learned. We will briefly look at the mechanics of the best method, reflective learning or reflective practice, and then explore how it could be applied to trading and how Tharp Think methodology incorporates these concepts into a streamlined trading practice.
Reflective learning is the process of reflecting on action for continuous learning. According to Wikipedia - “Reflective Practice was introduced by Donald Schön in his book The Reflective Practitioner in 1983, however, the concepts underlying reflective practice are much older”. Kolb’s reflective model highlights the concept of experimental learning and centers on the transformation of information into knowledge. After a situation has occurred, the practitioner reflects on the experience, gains a general understanding of the concepts encountered and then tests these general understandings in a new situation. Previous situations provide lessons that are continuously applied and reapplied building the practitioner’s knowledge or developing talent.
Graham Gibbs discussed the use of structured debriefing to facilitate the reflection involved in Kolb's "experiential learning cycle". I believe Gibbs model is more efficient for traders and easier to use because of its interactive debriefing style.
Let’s use a trading example to see how this model works. When I was learning to day trade the S&P 500 e-mini contract (ES), the amount of information I had to process to make trading decisions overwhelmed me. I needed help (outside ideas) and a method. I adopted Ken Long’s RLCO system as the method, but I couldn’t convince myself to take all the signals that the system generated. For example, staying in a strong trend with the RLCO system is not readily possible because price fluctuations cause the faster regression line to cross the slower regression line (a signal to get out or reverse) despite the trend regularly working its way higher (or lower).
I used Gibbs model to help me resolve the issue:
How to avoid RLCO false signals in a trend?
Observation: Price fluctuations produce RLCO crossovers which cause premature exits during strong trend moves.
Feelings during trading: Surprise, suspicions that the system is broken, frustration, and a sense of conflict when price action on the chart contradicts the RLCO exit signal.
Post trading observations: Shape, position, and relation of regression lines to other chart elements are distinctly different between a reliable exit signal versus a poor or false exit signal.
- What is good?
- RLCO can get me into a new trend quickly with little chart reading overhead, so it is a good workload reduction tool.
- RLCO generates optimum exit signals that help me maximize my gains.
- I can use RLCO to automate my scanning to find trading candidates quickly.
- What is bad?
- Premature exit signals prevent me from taking full advantage of the trend I am in.
- Exit signals are not always accurate.
- Such inaccuracies make it difficult to trust the system and bring about extra processing cycles which cancel out the efficiency advantages.
What sense can I make of it? I’d like to keep using RLCO, however some fix is required: extra information, techniques, or maybe more observation.
What is really going on?False signals happen with two simultaneous or separate occurrences:
- Price movement weakens,
- A retracement or pullback forms on the chart.
What do other people think about a trend?
This is where I started reading and referring to other sources. Three ideas seemed promising:
- Measuring volatility dynamically on the instrument’s price chart could be helpful. I decided to try Bollinger Bands.
- Measuring momentum with a price oscillator that visually summarizes the number of up bars versus down bars could be helpful.
- Plain old price action analysis might also be helpful. I decided to use Dr. Al Brooks techniques for analysis of price action in strong trends.
Next week, in part two of this article series, we’ll further the analysis with a price chart and see what conclusions we can draw from this applied experiential learning process.
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A Market That is Neither “Risk On” Nor “Risk Off”
I’m hearing from lots of traders that they’re getting “chopped up” in the post QE3 markets. They’re not alone. The world of managed money is doing no better. Institutions and hedge funds are telling me and my colleagues that it’s all they can do to hold onto gains made earlier in the year.
The “sure things” like Apple and Google have taken hits recently. The lovely uptrend that lasted from the June lows until just before U.S. elections has given way to a choppy sideways market that is just enough volatile to take out stops on swing trades for both the long and the short sides. Basically, things have gotten ugly for those trying to find “outperformance” or alpha in this market.
What’s more striking is that the “risk on” vs. “risk off” paradigm has not been working. Back in May and June of this year, I wrote an article series on how this phenomenon had changed the way institutional traders look at the market. In essence, portfolios and trades were being swung from “risk on” (things that work well when markets are moving higher) to “risk off” (those instruments that are relatively better in down markets) in an almost binary or yes/no fashion.
Risk On / Risk Off becomes “Risk Undecided”
One of the pages that I keep in my charting package is labeled “Risk On – Risk Off”. It contains a series of charts that track the ratios of classic pairs of risk on vs. risk off assets. I thought it might be instructive to give you a glimpse of what I’m seeing when I looked at those charts as of the close of Monday (12/10). Let’s start with Small Cap stocks, represented by the Russell 2000 (risk on) vs. the large cap stocks of the S&P 500:
The chart is fairly self explanatory – risk on asset at the top, risk off asset in the middle, and the ratio of the two at the bottom. When the ratio heads up, that indicates risk on behavior. The ratio dropping equals risk off. For almost two weeks the ratio has been going sideways telling us “risk undecided”…
In the bond world, when we look at riskier (high yield) bonds vs. U.S. Treasuries, we see a similar picture:
Once again, we see that neither side can gain the advantage. How about on the currency side? The classic combo is the Australian dollar for the risk on side vs. the Japanese yen for risk off:
Let’s look at one last chart – silver (higher risk) vs. gold (lower risk):
We can see that after silver gained some ground on gold, the ratio has been flat since late November.
For the past several weeks, all of these charts indicate similar behavior: there has been no flight to quality, nor has there been any desire to jump into the riskier asset.
What Does It Mean?
We’re in a market that can’t decide which way to go. Perhaps a resolution for the much discussed fiscal cliff will give the market some directional movement. But until then, the market doesn’t want to pick sides between the various risk assets. Unless you have some keen insight into where the fiscal cliff debate will end up, this may be a good time to keep your powder dry. As always, I welcome your comments and feedback. Send them to drbarton “at” vantharp.com
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