Swing Trading in Two Sentences

May 26, 2011
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Want the essence of swing trading in two sentences?

Here goes:

In uptrending markets, buy weakness as it returns to strength. In downtrending markets, sell strength as it returns to weakness.

There is plenty more to it than that (obviously). But think about what is packed into that encapsulation.

Why does it hold true? In part because of inertia. A body in motion tends to stay in motion. Trends are likely to persist.

Imagine a trend of 100 days duration. Now imagine you are watching the trend unfold, without foreknowledge of how long it will last. How many times will a countertrend move within that trend revert back to the original direction? Likely a fair number of times. And how many times will a turn in that trend be THE turn that ends or reverses it? Just once.

Reversion to the mean is a key factor here. An uptrend that has taken a breather — experiencing a period of weakness in doing so — is likely to revert to its dominant state (back to strength) after a logical consolidation period has passed. The same holds in reverse for a downtrend.

But in terms of taking action, and finding attractive reward to risk entry points, you need confirmation — some form of turning point identification or probabilistic identifier — to get your best shot at a solid R multiple on the trade. Hence acting on empirical evidence that the countertrend is ending — that the near-term correction period is exhausted.

In uptrending markets, buy weakness as it returns to strength. In downtrending markets, sell strength as it returns to weakness.



What about breakouts?

Sometimes, and oftentimes in certain environments, it is better to buy or sell a pattern breakout versus waiting for the end of a countertrend within a trend. But a breakout still counts as a transition of sorts: One could say that breaking through a price ceiling means freshly minted strength (a transition from weakness). Or one could say that falling through a price floor means newly established weakness (a transition from strength).

This also plays into what the behemoths do. When a large institutional player wants to accumulate shares of a company for a sizable position, or a commercial end user needs to put on a big commodity futures hedge, how do they do it? How do they get into that position?

The answer is, they get in carefully and methodically — buying and selling over time. This could mean a stream of block orders over days, or even weeks.

Furthermore, the trading desk staffer at MegaMutual Fund Inc. isn’t just going to buy or sell willy nilly. He (or she) will consistently work to get the best prices available. That means buying a little more in periods of weakness, or selling a little more in periods of strength. (Though this luxury is not always available.)

This dynamic has been around for a very long time. Richard Wyckoff captured it nearly 100 years ago:

Large interests are practically always in the market. They usually have their scale orders in on both sides so that they buy on declines and sell on rallies. They always have money with which to buy on declines, because they sell on the rallies.

They thus realize a profit as well as supply funds for the next decline. If the public would learn to do this, there would be fewer stock market fatalities.

Unpacking a little more, here’s a Wall Street “secret” that is hidden in plain sight:

The elephants of the business are forced to establish long-range positions based on murky fundamental convictions. Sheer bulk, conventional restraints, and committee oriented market-timing restrictions force them to do this.

These big, heavy, beta chasing managers have to peer into a muddy crystal ball and pretend they have table-pounding clarity over laughably extended time frames — a sense of false sureness as to what XYZ company or ABC industry will be doing over a long period of time. This is not optimal — the world is too complex — but it is a necessity, so manufactured convictions are embraced with gusto.

“Who knows” is not an acceptable answer for most elephants — even when it is the honest answer, and the only sane one — and “short term” is not an acceptable time horizon.

Manufactured conviction, in other words, is the dull gray elephant’s lot in life. As a rule they are too weighted down to be anything but slow, and too beset by career risk to be anything but conventional.

As a result of this — and the fact that trillions of dollars are run this way — you get plodding moves into institutionally fashionable trends, with lots of post-facto rationalization to justify whatever view is prominent at the time.

(This further explains why so many managers go on CNBC or wherever, to speak with conviction on what will happen in six, twelve or eighteen months time, even when extreme uncertainty is the order of the day and the weatherman can’t get you a good forecast for next week. It’s a confidence racket, with the elephants bolstering themselves as much as their clients.)

Swing traders can have fundamental convictions too, of course. And they do!

But nimble market participants are not slaves to their fundamental beliefs. No trader worth his salt feels imprisoned by the need to “always have a view.” Market agnosticism is a far more palatable option for those with neither boards to impress nor benchmarks to chase.

What’s more, the swing trader has the ability to get liquid (go to cash) or otherwise turn on a dime very quickly. This capability lets conviction — ALL conviction — get filtered through the lens of price action, thus reducing risk (via proper risk management) and enhancing long term results through consistent pursuit of high R multiple scenarios.

In uptrending markets, buy weakness as it returns to strength. In downtrending markets, sell strength as it returns to weakness.

The ability to add or subtract exposure in a heartbeat constitutes a major performance edge, in the context of outsized annual returns with tightly managed risk, in that speed and dexterity are what allow a trader to exploit attractive opportunities in the first place.

When you are nimble, you have multiple shots at great setups with the ability to cut losses quickly if the position doesn’t work out. Over time, this works out as more return for less risk.

The hidebound elephants are mostly too big to perform as described above. They have to accumulate (or distribute) shares over extended periods of time, contending with benchmark comparisons and “decision by committee” or “judgement of one’s peers” influences all the while. This makes for slow going — except when the whole herd gets frenzied and stampedes (which is always fun).

Shifting tack a bit, we can think about another big driver here: Capital Flows.

Many managers run off an allocation target. Say, for example, that MegaMutual Fund Inc. has determined the best portfolio mix contains 75% equities, 20% bonds, and 5% cash.

If MegaMutual gathers an extra $100 million in assets via its new marketing campaign, what is the manager going to do with it? Three quarters of that cash will be spread out over the names already owned, more or less, in order to keep the “75% equities” target.

This is a flow process, with new money coming in pushing up the same names day after day (the elephants love to ape each other). This flow process can be largely oblivious to charts, rallies and declines (except to the extent the desk can do a little better, execution wise, via purchase or sale at opportune times).

Perhaps now you have a better picture of why markets can go up and up and up. Flows drive that process.

If your typical elephant likes Home Depot at $35, maybe he likes it even more at $40 etcetera. The valuation process is laughably far from rational. A set of base convictions is the starting point, coupled with the need to “have a view” and put capital flows to work.

But it isn’t a one-way street. Think about the reverse situation — when capital flows are net negative, and money is flowing OUT of MegaMutual.

What happens when these same elephants get net redemptions, week after week and day after day?

As money flows out, they are forced to sell the favored names they were indiscriminately buying. Sticking to the percentage target is the same on the flow downside as it was on the flow upside. More redemptions, more selling, more pessimism, more redemptions.

This is how feedback loops create downtrends that can persist and persist, much as bulls would love to abolish them.

This same dynamic further applies to macroeconomic trends and large scale macro adjustments.

To paraphrase trend follower John Henry, for example, central banks don’t just “raise” interest rates. They raise, raise, raise, raise, raise. Nor do central banks simply “lower” interest rates. They lower, lower, lower, lower.

Actual and perceived adjustments to the macroeconomic landscape take time to reach fullness, often with perception lagging — and create trends in doing so.

In uptrending markets, buy weakness as it returns to strength. In downtrending markets, sell strength as it returns to weakness.

Winston Churchill once said: “From intense complexities, intense simplicities emerge.” That could have been a statement about trading.

As directional traders with a global macro overlay, we pay keen attention to fundamentals — ideas, industries, sectors, groups and themes. But the uncluttered mandate of seeking out inflection points in well-defined trends, as described in those two sentences, remains at the heart of what we do. This “core simplicity” helps put all the follow-on complexities of day-to-day execution in perspective.

JS

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4 Responses to Swing Trading in Two Sentences

  1. Bob Spear on May 26, 2011 at 7:40 pm

    "a solid R multiple on the trade"
    Are you referring here to Chuck Branscomb's R multiple idea?

  2. Jack Sparrow on May 27, 2011 at 6:57 am

    Not familiar with Chuck Branscomb. As far as I know the R multiple concept has been around a very long time — Van Tharp comes to mind. It is simply a condensed description of Reward vs Risk on the trade. So if a trade has realistic 5R potential, that means you could make $5 for every $1 of planned risk. A 3R trade would be $3 for every $1 of planned risk. A historical winning trade average of 2.7R would mean $2.70 in profit for each $1 of initial planned risk, and so on.

  3. SirG on May 27, 2011 at 11:05 am

    Yep, that was Branscomb who originally stumbled upon that idea after realizing expectation in $ terms was useless data. He and Tharp worked together in the mid-90s on that stuff, wrote about it for Tharp's newsletter and then was part of Tharp's book from what I recall. This was covered on Curtis Faith's site years ago.

    • Jack Sparrow on May 27, 2011 at 11:33 am

      Interesting, thanks. Bottom line being, R is a useful way to express reward to risk profile in shorthand, which is probably why the terminology has survived.

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