When your trading results are becoming more correlated, your self-coaching will lead you to ask whether the correlations are due to biases in your trade selection or due to shifts among the markets. In the first instance, you can make special efforts to seek out uncorrelated ideas; in the second, you may want to reduce the size of each of your trades so that you have less concentrated risk. What you want to avoid are situations in which all your trading and investment eggs are in a single package. That can produce fine returns for a while, but leaves a trading business vulnerable when market conditions change.
My coaching experience with traders suggests that they most often achieve sound diversification in one or more ways:• Blending intraday trading with swing trading or blending longer-term trading/investing with shorter-term swing trading.
• Blending directional trading (being long or short a particular instrument) with relative value trading (being long one instrument and short another, related one).
• Blending one strategy (such as trading around earnings events) with another (trading opening range breakouts).
• Blending the trading of one market or asset class (such as a currency pair) with another (U.S. small cap stocks).
For example, a trader might be long high-yielding stocks as one idea. A second idea would have the trader selling the front end of the yield curve and buying the long end, perhaps in anticipation of yield curve flattening ahead of Fed tightening. A third idea would have the trader short value stocks and long growth issues, anticipating that a historically wide spread in performance between the two will revert to its norm. A fourth idea might be a short-term long trade on small cap stocks. The good thing about spread/pairs trades, such as ideas two and three, is that they can work regardless of the direction of the underlying market, providing a measure of diversification. Trading horizons widen considerably when you don’t just ask if a market is going up or down, but start to think about what will go up or down versus other things.
High frequency day traders will tend to achieve diversification and low correlation in other ways. They will demonstrate a relatively even mix of long and short trades over time. They may also manage positions over different time frames or place different trades in different stocks and sectors. The risk for the day trader is getting caught up in fixed opinions about the market, biasing trades in a single direction. If the day trader is diversified, the correlations among returns from his different setups and the serial correlations of returns among trades (and among returns across times of day) should be relatively modest over time. Each trade or type of trade for the day trader should, in a sense, be a separate product in the business mix.
You don’t have to diversify by trading many markets. You can diversify by time frame (longer-term, shorter-term), directionality (long, short), and setup pattern (trending, reversal).
Is your trading business adequately diversified? Is its diversification expanding or narrowing? If you’re like most traders, you don’t know the answers to these questions. The data, however, can be at your fingertips. All you need is to divide your trades by strategy, track the results of each strategy daily, and enter the information into Excel. From there, it’s simple to calculate correlations over varying time periods. And if you don’t trade every day and hold most positions for days? No problem: simply calculate the returns of each strategy as if you had sold all positions at the end of each trading day. That will tell you if your trades are moving in unison or independently. And that will tell you if you have many profit centers supporting your business or only a very limited few.
COACHING CUE
It is not too difficult to turn good directional ideas into good pairs trades. Once you determine that an index, sector, commodity, or stock is going to go up or down, ask yourself what related indexes, sectors, commodities, or stocks are most likely to maximize this move. You would then buy the instrument most likely to maximize the move and sell the related one that is likely to lag. For instance, you might think the S&P 500 Index is headed higher. You note strength in the NYSE TICK ($TICK) relative to the Dow TICK ($TICKI) and so buy the Russell 2000 small caps and sell the Dow Jones Industrials in equal dollar amounts. This gives you an idea that can be profitable even if your original idea about directionality in the S&P Index doesn’t work out. As long as there’s more buying in the broad market than among the large caps in relative terms, you’ll make money. Learn to think and trade in terms of relationships so you increase your arsenal of ideas.
LESSON 77: CALIBRATE YOUR RISK AND REWARD
I recently used Henry Carstens’ P/L Forecaster (www.verticalsolutions.com/tools.html) to simulate possible equity curves under scenarios for two small traders:1. Trader A has a small negative edge - The trader wins on 48 percent of trades and the ratio of the size of winners to losers is 0.90.
2. Trader B has a small positive edge - The trader wins on 52 percent of trades and the ratio of the size of winners to losers is 1.10.
I viewed the simulation as tracking returns over a 100-day period. The average size of winning days was $100 in both scenarios. That means that, if we assume that the traders began with a portfolio size of $20,000, that the daily variability of their returns was somewhere around 50 basis points (½ percent, or $100/$20,000). If the traders averaged just one trade per day, then it’s plausible that they were risking roughly 2 S&P 500 emini points per trade and making about that much per trade.
By running the scenarios 10 times each, I was able to generate an array of returns for the two traders:
What we see is that small edges over time add up. When the small edge is negative, as in the case of Trader A, the average portfolio loss over 100 days is around 3 percent. When the edge is positive, we see that Trader B averages a 100-day gain of about 3 percent.
Clearly, it doesn’t take much to turn a modest positive edge into a modest negative one: the distance between 52 percent and 48 percent winners and the difference between a win size that is 10 percent smaller versus larger than the average loss size are not so great. Just a relatively small change in how markets move, how we execute our trades, or how well we concentrate and follow our ideas can turn a modest winning edge into a consistent loser.
You don’t need to have a large edge to run a successful trading business; you do need to have a consistent edge.
Had we tracked results every single day, we would have found that Trader A had some winning days and Trader B had some losers. Over a series of 100 days, however, the edge manifests itself boldly. There are no scenarios in which Trader A is profitable and none where Trader B loses money. Just as the edge per bet in a casino leads to reliable earnings for the house over time, the edge per trade can create a reliable profit stream when sustained over the long run. Once you have your edge, your greatest challenge as your own trading coach is to ensure your consistency in exploiting that edge, every day, every trade.
But let’s take the analysis a step further and explore risk and reward. Our Traders A and B are not great risk takers: they are only trading one ES contract for their $20,000 account. This provides them with average daily volatility of returns approximating 50 basis points, which is not so unusual in the money management world. We can see, however, that the 3 percent return for Trader B over 100 days would amount to about 7.5 percent per year (250 trading days). While that’s not a terrible return, it is before commissions and other expenses are deducted. The consistent small edge does not produce a large return when risk-taking is modest.
So how could our Trader B juice his returns? A simple way would be to trade 3 contracts instead of 1. Assuming that this does not change how Trader B trades, the average daily variability of returns would now be 1.5 percent, with an average win size of $300. The return of over 20 percent per year would now look superior. If you take more risk when you have a consistent edge, this certainly makes sense, just as betting more makes sense at a casino makes sense if the odds are in your favor. You simply need to have deep enough pockets to weather series of losses th
at are expectable even when you do have the edge. When I ran the scenarios for Trader B, peak to trough drawdowns of $700 to $800 were evident. Multiply that by the factor of 3 and now Trader B incurs drawdowns of 12 percent.
But what if Trader B took pedal to the metal and traded 10 contracts with a small edge? The potential annual return of 75 percent looks fantastic. The potential drawdowns of more than 40 percent now seem onerous. That small, consistent edge suddenly generates large losses when risk is ramped to an extreme.
The variability of your returns will tend to be correlated with the variability of your emotions.
In that aggressive scenario, Trader B would ramp the variability of daily returns to 5 percent. Average daily swings of that magnitude, particularly during a slump, are bound to affect the trader’s psyche. Once the trader becomes rattled, that small positive edge can turn into a small negative one. Amplified by leverage, the trader could easily blow up and lose everything, all the while possessing sound trading methods.
The size of your edge and the variability of your daily returns (which is a function of position sizing) will determine the path of your P/L curve. Management of that path is crucial to emotional self-management. Your assignment is to utilize Henry’s forecaster in the manner illustrated above, using your historical information regarding your edge and average win size to generate likely paths of your returns. Then play with the average win size to find the level of risk, reward, and drawdown that makes trading worth your while financially, but that doesn’t overwhelm you with swings in your portfolio.
Few traders truly understand the implications of their trading size, given their degree of edge. If you know what you’re likely to make and lose in your trading business, you’ll be best able to cope with the lean times and not become overconfident when things are good. Match your level of portfolio risk to your level of personal risk tolerance for a huge step toward trading success.
COACHING CUE
Doubling your position sizing will have the same effect on the path of your returns as keeping a constant trading size when market volatility doubles. This process is a dilemma for traders who hold positions over many days and weeks, but is also a challenge for day traders, who experience different patterns of volatility at different parts of the trading day. It is common for traders to identify volatility with opportunity and even raise their trading size/risk as markets become more volatile. This greatly amplifies the swings of a trading account, and it plays havoc with traders’ emotions. Adjusting your risk for the volatility of the market is a good way to control your bet size so that a few losses won’t wipe out the profits from many days and weeks.
LESSON 78: THE IMPORTANCE OF EXECUTION IN TRADING
You can have the greatest ideas in the business world, but if they’re not executed properly, they won’t be worth much. A great product marketed poorly won’t sell. A phenomenal game plan by a top coach won’t work on the basketball court if the players don’t pass well and can’t establish position underneath the basket for rebounds. The quarterback can call a great play, but if the line doesn’t block, the pass will never get off.
So it is with trading: execution is a much larger part of success than most traders realize. The average trader spends a great deal of attention on getting into a market, but it’s the management of that trade idea that often determines its fate. When you are the manager of your trading business, you want to focus on day-in and day-out execution, just as you would if you were running your own store.
A trade idea begins with the perception that an index, commodity, or stock is likely to be repriced. For example, we may perceive that a stock index is trading at one level of value, but is likely to be trading at a different level. Our rationale for believing this may be grounded in fundamentals: at our forecasted levels of interest rates and earnings growth, the index should be trading at X price rather than Y. Our rationale might be purely statistical: the spread between March and January options contracts on the index is historically high and we anticipate a return to normal levels. Too, we may use technical criteria for our inference: the market could not break above its long-term range, so we expect it to probe value levels at the lower end of the range. In each case, the trade idea takes the form: “We’re trading here at this price, but I hypothesize we’ll be trading there at that price.”
What this suggests is that a fully formed trade idea includes not just an entry setup, but also a profit target. Too often that target is not made clear and explicit, but still it lies at the heart of any trade idea. A trade only makes sense if we expect prices to move in an anticipated way to an extent that is meaningful relative to the risk we are taking.
Just as businesses set target returns on their investments, traders target returns on their trade ideas.
It is in this context that every trade is a hypothesis: our belief regarding the proper pricing of the asset represents our hypothesis, and our trade can be thought of as a test of that hypothesis. As markets move, they provide incremental support for or disconfirmation of the hypothesis. That means that, as trades unfold, we either gain or lose confidence in our hypothesis.
Any good scientist not only knows when a hypothesis is supported, but also when it is not finding support. A hypothesis is only meaningful if it can be objectively tested and falsified. The outcome that would falsify our trade hypothesis is what we set as a stop-loss level. It is the counterpart to the target; if the target defines the possible movement in our favor, the stop-loss point captures the amount of adverse movement we’re willing to incur prior to exiting the trade and declaring our hypothesis wrong.
The trader who lacks clearly defined targets and stop-losses is like the scientist who lacks a clear hypothesis. You can trade to see what happens, and scientists can play around in the laboratory, but neither is science and neither is likely to prove profitable over the long run. A firm hypothesis and objective criteria for accepting or rejecting the hypothesis advances knowledge. Similarly, a clear trading idea and explicit criteria for validating or rejecting the idea can guide our market understanding. Frequently, if you get stopped out of a seemingly good trade idea you can reframe your understanding of what is going on in the market. After all, scientists learn from hypotheses that are not confirmed as well as those that are.
With the target and stop-loss firmly in mind, we now have the basis for executing our idea. Good execution mandates that we enter the trade at a price in which the amount of money we would lose if we were wrong (if we’re stopped out) is less than the amount of money that we would make if we were right (if we reach our target). When traders talk about getting a good price, this is what they mean: they are entering an idea with relatively little risk and a good deal more potential reward. A good way to think about this is to think of each trade as a hand of poker: where we place our stoploss level reflects how much we’re willing to bet on a particular idea.
Many traders make the mistake of placing stops at a particular dollar loss level. Rather, you want to place stops at levels that clearly tell you that your trade idea is wrong.
Let’s say my research tells me that we have an excellent chance of breaking above the prior day’s high price of $51 per share. We are currently trading a bit below $49 after two bouts of morning selling took the stock down to $48, which is above the prior day’s low of $47.50. A news item favorable to the sector hits the tape and I immediately buy the stock at $49, with $51 as my immediate target. My hypothesis is that this news will be a catalyst for propelling the stock higher, given that earlier selling could not take out yesterday’s low. I’m willing to lose a point on the trade (stop myself out at $48) to make two points on the idea (target of $51).
Suppose, however, that the stock was trading at $50, rather than $49 when the news came out. Now my risk/reward is not weighted in my favor. If I’m willing to accept a move back to $48 before concluding I’m wrong, I now have two points of potential loss for a single point of targeted profit. While the idea is the same, the execution is quit
e different. It is difficult to make money over the long haul if you’re consistently risking two dollars to make one. If, however, you’re risking a dollar to make two or more, you can be right less than half the time and still wind up in the plus column.
Good execution means that you calibrate risk as a function of anticipated reward.
Execution provides proactive risk management. If you control how much you can win and lose based on your price of entry, you keep your risk known and lower than your potential reward. You can track the quality of your execution if you calculate the amount of heat you take on your average trades. Heat is the amount of adverse price movement that occurs while you’re in the trade. If you’re taking a great deal of heat to make a small amount of money, you’re obviously courting disaster. When your execution is good, you should take relatively little heat compared to the size of your gains. Your assignment for this lesson is to calculate heat for each of your recent trades and track that over time. This assignment will tell you how successful you are at executing your ideas, and it will provide a sensitive measure of changing risk/reward in your trading.
Good execution, psychologically, is all about patience. To get a good price, you will have to lay off some trade ideas that end up being profitable. Like the poker player, you want to bet when the odds are clearly in your favor. That means mucking a lot of hands. Similarly, a business doesn’t try to be all things to all people. A business owner passes up certain opportunities to sell products in order to focus on what she does best. When you’re running your trading business well, you don’t take every conceivable opportunity to make money; you wait for your highest probability opportunities. The clearer you are about risk and reward, the easier it will be to stick to trades that offer favorable expected returns.
The Daily Trading Coach Page 34
