Risk in trading and speculation, whoops!, excuse me, risk in “investing” is often spoken about, but rarely defined inside the conversation. Thankfully “risk” isn’t as nebulously and stupidly used a word as “alpha” is, but it still behooves us to ask ourselves what we mean when we talk about risk. I gave it some thought and came up with seven key definitions of risk that apply to trading and speculation, whoops!, there I go again, I mean, seven key definitions of risk that apply to “investing.”

Risk is the Volatility of an Individual Position.

Some stock speculators, large and small, use an options overlay strategy, such as selling covered calls, in order to mitigate the day-to-day mark-to-market of their individual stocks. In this way, they hope to eliminate the volatility of each holding’s equity.

One common technique is to use recent historical volatility, perhaps a multiple of the width of a Bollinger Band or the Average True Range (ATR) to set the position size. When setting position size via this method, the trader puts a theoretical limit on the day-to-day dollar variance of the position’s value. If the trader can scale the position continuously to adjust for changes in the price volatility, they can have a lot of control on the dollar variability of the position value.

When a commercial enterprise like a manufacturer needs a supply of some basic material, say copper, that enterprise is exposed to the spot price of copper at the time it is needed. Through buying and selling speculative contracts on the metal, or options on those contracts, the manufacturer can, over long stretches of time, smooth out their costs of obtaining copper. This is true for producers as well, since they can smooth out their product delivery price enough to make forecasts and manage their own operating costs which might involve energy contracts for the power needed to mine and transport their copper. These entities are concerned about the volatility of a single position (an input or output) and are participating in the speculative market to control that “risk.”

Risk is the Volatility of a Portfolio.

The futures contract speculator is the liquidity provider to the manufacturer and producer hedgers listed above. They get paid, on net, because the hedgers are more interested in smoothing returns than in generating positive income from their activities, and the inherent leverage of the contracts makes it far more potentially worthwhile than it would be on a cash basis. The mechanized trend-follower who speculates on futures typically uses large baskets of contracts, 20+ or even a hundred different contracts, in order to smooth their results for the portfolio. Think of this as an exercise in blending non-correlated systems.

When trading individual equities, there is a significant risk to any one stock; there could be lawsuits, catastrophes that impact a packing plant, economic outlook changes, or a simple miss of expectations for revenues or earnings. Provided that the overall method of selection has a statistical edge, the speculator can start using the “law of large numbers” by selected many stocks that hold the same selection criteria. Of course, there may be diminishing returns in the selection criteria as it gets less stringent to allow for more choices. A classic “old school” example is Ben Graham’s “Cigar Butt” methodology, which clearly dictates holding upwards of two dozen (if possible) of these NCAV “values” at any one time, because only a few will make it good and pay for the rest.

Some of the more quantitative shops may use something like the “black box” covariance matrix from the “Barra U.S. Equity Long-Term Risk Model” to limit the intercorrelation of their various positions, so that they don’t wind up holding 3 different equities that tend to move together, thinking they’ve mitigated risk – when they haven’t.

Read more about the benefits of diversification.

Risk is the Downside Potential of an Individual Position.

This is similar to viewing risk as the volatility of an individual position, except only the downside variability is counted as a negative.

The “old school” Ben Graham’s “Enterprising Investor” and “Defensive Investor” methodologies would buy stocks only after careful examination of several years’ balance sheets, income statements, and the like. The idea was to find, not just companies that were cheap relative to their current earnings potential, but to find good quality companies where the risk of the stock going to zero was reduced. It’s the value speculator’s, damn! there I go AGAIN, the value “investor’s” concept of “margin of safety.”

Another “trick” used by value-type guys is capitalizing on forensic accounting methodologies. Read more about fundamental analysis for solvency and earnings quality.

The purely technical discretionary trader accomplishes limiting the downside risk through selection of opportunities. Clearly-defined risk/reward parameters emerge, such as pullbacks to current support/prior resistance after a breakout, bounces off of significant moving averages, and the bottoms of breakaway gaps, when one is looking at charts all day. Now, regardless of the predictive value (or non-value, in many people’s opinions) of these levels, it is plain that the levels indicated by the charts present “cut and run” points of price action that DO limit the technical trader’s downside risk on that position.

Risk is the Downside Potential of a Portfolio.

Once again, this is similar to another perspective, but only counting downside variability as a negative. I love the actuarial phrase for this definition: “risk of ruin.”

Mechanized system traders in the futures world think of this number as “heat.” Using an R (risk per position) of 0.5 (percent of equity), a system may dial up the “heat” by having more positions with tighter stops and more leverage, or they may keep the same number of positions and relative stop size, and increase the leverage to have more R than 0.5. In this case the number of positions multiplied by the risk per equals the “heat.”

VAR (value at risk) is one measurement of this “heat” notion that many quants and hedgies use.

Anyone trading unleveraged instruments, like stocks or ETFs from the long side, has the theoretical downside potential capped at their invested equity; using margin accounts to go more than 100% long, or to go short, increases that theoretical risk. Using leverage exacerbates this amount, especially if trading near the minimum margin allowed in a futures account. More than one discretionary trader caught his wanker in a zipper at 10-to-1 leverage during last January’s equity slide! That’s what happens when you don’t know your leverage, you wind up increasing your “risk of ruin.”

When I look at maximum drawdown in backtest, as compared to backtested CAGR, I’m really comparing one measure of downside portfolio risk (drawdown) to one measure of return (CAGR). It’s similar to Seykota’s “bliss ratio.”

Risk is a Mistaken Position.

If the retail schlump “value investor” doesn’t understand the company he’s researching, he might run into this; perhaps it’s an electronics retailer that, on closer inspection, also invests in synthetic fuel plants for the purpose of getting the associated tax credits. In this case, if the “value investor” bought that stock, they introduced the risk of a mistaken position.

The institutional analogy might best be described as “style drift.” They wanted a mid-cap value fund, but the fund manager drifted into holding mostly large-cap growth stocks.

Risk is Third-Party.

The counter-party to your complex derivatives transactions blows up.

The source of your hedge fund’s leverage is in financial trouble and puts the kibosh on your borrowing, forcing a margin call at an inopportune time.

The retail schlump’s broker goes bust. Yes, there are legal protections here up to certain account sizes, but what happens to those with active strategies and open positions?

Risk is Not Achieving My Benchmark.

Of all the risks discussed, this is probably the one that needs the most thought, from the perspective of a retail schlump with an absolute benchmark. Unfortunately, most people don’t give a lot of thought to their benchmark, and don’t understand the difference between an absolute and relative benchmark, much less why they should use an absolute one. Oh, bother.

For the retail schlump who hasn’t yet evolved past comparing himself to the index return, that index’s return is a Mendoza Line that must be crossed. After all, it’s hard to justify the pain and expense of being an active trader if one can’t beat “buy and hold the SPY.”

The institutions seem to have devolved into comparisons to the index, because when they select managers, that’s exactly what they are usually happy with; beating the benchmark index, even if that means losing just less than the S&P 500 loses. Even when using more complex strategies overall, they’ll select the relative benchmark outperformance where they can find it, regardless of absolute performance, and then allocate assets to other classes through cheap index funds or through derivative strategies. Maybe they just never evolved past that …

The most sophisticated retail traders are looking at performance from an absolute perspective, based on either backtested results for their strategy, a necessary return on investments based on careful budgeting, or both. This is where most, darn near all, of the retail schlumps are missing the boat, because you can’t eat relative performance when the index sucks, and they abandon their (occasionally) carefully-crafted strategies when they have periods of underperformance.

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