Chapter 2
IN THIS CHAPTER
Considering different trading strategies and styles
Understanding technical analysis: charts, trends, and indicators
Figuring out fundamental analysis: catalysts, growth stocks, and value stocks
As a soon-to-be swing trader, how do you uncover promising opportunities? And after you uncover those opportunities, how do you time your entries and exits? Very good questions, and I’m glad you asked.
Like all traders, swing traders rely primarily on two main strategies:
So which strategy should you use? I encourage you to use both strategies. After all, understanding why stocks move and which ones are likely to move can be just as important as knowing which stocks are moving. After spending years trading and managing money, I believe a swing trader should be well rounded in his or her approach.
In addition to determining whether you’ll be a swing trader that uses technical analysis, fundamental analysis, or both, another question to consider is whether you’ll be a discretionary swing trader or a systematic one. Some swing traders are discretionary — they use technical and/or fundamental analysis to evaluate each potential trade and make decisions based on the rules they’ve outlined for themselves. Other swing traders are systematic or quantitative — they use either or both forms of analysis and make trades using an automated system (they rely on a computer to execute their strategies).
In the last few years, an important trend has taken hold in the management of institutional assets (for example, pension plan money, sovereign wealth funds, and so on). Whereas in the past many of these funds invested via discretionary managers, an increasing number is investing via quantitative funds. Think of these funds as computers managing vast amounts of money. Typically, the people running the funds have advanced degrees in mathematics, physics, engineering, and other sciences. They use computer models to study past behavior and then develop models to execute trades based on the historical success of these models.
This chapter introduces you to both strategies (technical and fundamental analysis) and both styles of trading (discretionary and quantitative). Only you can determine what kind of trader you want to be based on your interests and expertise.
Devoid of calculations, reading, or other time-intensive research, technical analysis allows a swing trader to examine any security — be it stock, commodity, currency, or something else — and make a decision on its likely short- or long-term direction (depending on whether the chart being analyzed is a short-term chart, such as a chart where each bar represents an hour or day, or a long-term chart, such as a chart where each bar represents a week or month). Swing traders relying on technical analysis don’t care about what a company does, how it makes its money, or whether the CEO graduated at the top or bottom of her class — they care for nothing but the ticker tape (the running list of trades of a security, similar to what you may see on financial news networks at the bottom of the screen). After all, swing traders earn profits based on a security’s price, not how many widgets a company sells or the academic pedigree of its board of directors.
The swing trader who relies on fundamental analysis is a different breed. This trader wants to know what line of business a company is in, whether that industry is on the rocks or gaining momentum, when a company reports its earnings, and what those earnings expectations are. The swing trader using fundamental analysis isn’t interested in every detail of a company’s balance sheet. After all, if you’re looking at trading stocks of ten companies in the coming week, you don’t have the time to read those companies’ annual reports cover to cover. Instead, a high-level overview is enough. Intricate modeling in Excel, though useful, isn’t practical for a swing trader who buys and sells stocks over a period of days.
Swing traders relying on fundamentals may be categorized as event-driven traders. Event-driven traders wait for specific events and then trade a security based on their expectation of how this event will drive a security’s price.
For example, assume that Apple unexpectedly announces that the sales of its latest iPhone are above expectations. An event-driven trader might look at which companies will benefit from Apple’s success — perhaps a supplier of Apple products. Or perhaps a major retailer announces disappointing earnings due to competition from e-commerce. An event-driven trader might buy shares of e-commerce companies in anticipation of a strong earnings report that will send their shares higher.
Newcomers to swing trading are typically attracted to technical analysis, for a couple reasons:
There is no one right answer. Some successful traders use one or both forms of analysis. What’s important is that you know which method you enjoy using and which method plays to your strengths.
Regardless of which approach you take, you should also think about whether you want to be a top-down swing trader or a bottom-up swing trader. A top-down trader finds securities by beginning at a macro level and drilling down to an industry and then to a particular company. A bottom-up trader finds securities by beginning at the bottom (that is, with individual companies) and then selecting the company that has the best industry group and macro-level fundamentals.
Discretionary swing traders evaluate potential trades based on their trading plan. They use either fundamental or technical analysis to determine whether each trade meets their requirements. Although the discretionary trader’s rules are written down, he or she may pass on or take trades based on experience or gut. The discretionary swing trader doesn’t follow a program such as, “If A, then B.” Instead, he or she synthesizes all available info, weighs items, and then makes a call.
Quantitative swing traders are very different. They map out trading strategies that a computer can execute. The quantitative system can be based on technical inputs (like price, indicators, and so on) or fundamental ones (such as earnings surprises, sales growth rates, and other corporate events). The strategies are programmed into a computer software program that tests them on historical market data. The quantitative swing trader analyzes those results to determine whether the strategy is worth pursuing — if it produces higher profits than the overall market, for example.
As you may’ve guessed, the two approaches both have advantages and disadvantages:
Discretionary trading allows for a fresh look at each situation and the ability to pass on trades when external data that may not be easily captured in a computer program indicates decreased chances of success. The future isn’t always similar to the past, and discretionary traders can understand how markets change over time and incorporate such changes into their trading plan.
This approach does have its drawbacks: Discretionary traders must make a decision on each buy or sell, and they’re more prone to falling in love with trades, becoming emotionally attached or failing to follow the trading plan.
Quantitative trading largely takes the human out of the equation. A computer program executes the trades as programmed. Of course, the swing trader executing this program developed the program based on the historical success of applying certain rules (for example, buy a stock when it makes a new high for the first time in 20 days). After the program is set, the swing trader isn’t making a decision on each trade. The quantitative trader can step back and watch the computer work its magic.
But quantitative trading systems also have their drawbacks. Can a system be designed to capture all contingencies or possibilities that may arise? Of course not. Moreover, even though a certain strategy worked in the past, there’s no guarantee it will continue working in the future. When losses occur, the quantitative swing trader must determine whether the setback is a temporary part of the system or whether it represents a change in the market environment, requiring development of a new quantitative model.
That doesn’t mean discretionary trading is superior to quantitative trading. Only that each approach requires a different skill set. I’m a discretionary trader because I believe my experience in the markets can’t be easily programmed, I enjoy using discretionary trading, and I have developed a system over time. But if you incline to quantitative trading methods and are experienced in programming or want to find out more, I recommend accessing other resources focused solely on quantitative trading methods.
Technical analysis is the art of reading a security price chart with volume and determining the security’s likely direction based on the strength of buyers and sellers. Technical analysis can range from the simple (interpreting a chart pattern) to the complex. Basic chart interpretation is an important skill, but swing traders typically rely on indicators and intermarket analysis.
The technical analyst is principally concerned with the following questions:
To help make sense of whether technical analysis is right for you, I cover the theory behind technical analysis as well as the major pros and cons of using this approach in the coming sections. Finally, I wrap up with a more detailed explanation of reading chart patterns and using technical indicators.
So why does technical analysis work? How can examining past price history possibly provide insight into future price movements?
Market participants have memory. Traders, investors, and other market participants have reference points when they buy or sell securities. The price they pay when they buy a security affects when they’re likely to sell that security (even though it should have no bearing on that decision). They remember their purchase price and, naturally, want to either make a profit or break even. If the security price swoons after they purchase shares, they’re likely to feel pain. And if the price recovers to their original purchase price, many will be happy to sell to break even. What these traders and investors often don’t realize is that hundreds, if not thousands, of others are experiencing these same emotions. This fact is why certain price levels are more significant than others. Securities tend to find support (a level at which security prices stop falling and begin to rise) and resistance (a level at which security prices stop rising and begin to fall) at round numbers.
I’m amazed at how often traders place buy-limit or sell-limit orders at round price figures. Don’t they realize that many other traders may be doing the exact same thing, and that their actions may prevent the price from ever reaching that level? Quite simply, a sell limit of $100 isn’t too bright, because other traders or investors likely placed orders at that same round number. And their orders may prevent yours from ever getting executed (the overwhelming supply of shares at that level will force the stock to retreat before reaching $100). On the other hand, a sell limit of $98.71 is smart, because it’s unlikely that other traders placed an order at that specific price, and you have a much better chance of your order getting executed.
Smart investors’ actions show up on the chart. Smart money often refers to investment money made by institutional investors who have greater resources than individual investors (for instance, access to research, staff, and so on). Institutional investors invest their money with specialized managers who can visit a company’s headquarters and pay for expensive research. Smart money also constitutes insiders at a firm who have an information advantage over other market participants and may trade on that information.
Dumb money, on the other hand, refers to investment money made by amateurs who buy or sell securities for the thrill of investment or without proper diligence. Dumb money doesn’t necessarily mean individual traders; it can include retirement plans or corporate plans that divest securities that no longer meet the plans’ criteria. This selling pressure pushes prices down for no good reason. Dumb money can also include institutional investors who buy or sell stocks because they fall in love with their investments. Believe it or not, institutional investors are subject to the same whims and emotional swings experienced by all traders.
Because the price chart shows all available public and private information, technical analysis can really shine bright when prices diverge from their fundamentals. Opportunity is greatest when you’re in the minority, but right. If everyone, including you, expects shares of Twitter to do well, you won’t make much money because others have already come to the same conclusion and positioned themselves according to that expectation. However, if you think Twitter will surprise investors to the upside and everyone else is on the other side, you stand to make a large profit if you’re right and the crowd has to correct its collective opinion by buying shares.
For example, shares of Enron were tumbling in late 2000 despite what appeared to be stellar fundamentals. Price drops were met by upgrades and buy recommendations by Wall Street analysts who, using all available public data, determined that shares represented significant value.
But prices kept falling. A swing trader using technical analysis would conclude that something wasn’t right. If everything was peachy, why were shares falling? Something must be up. And sure enough, something was up — something mischievous indeed. Investors using fundamental analysis, on the other hand, are often alerted of underlying cracks in a company’s financial position after it’s too late.
Technical analysis can also be useful for new markets. For example, what is the appropriate price for Bitcoin? I have no idea; it’s simply too new to understand this asset class. But technical analysis can assist you in determining when (or if) to buy and sell a cryptocurrency. Some of the major advantages of technical analysis are that it
But technical analysis also has some glaring weaknesses. For example, it
This book covers the two major aspects of technical analysis: charting and using technical indicators. Reading charts and using indicators are of equal importance to the swing trader who uses technical analysis, so you should be adept at both. (Keep in mind that technical indicators are largely unhelpful if you don’t understand basic chart pattern interpretation.)
Charting, which I cover in Chapter 4, is the analysis of securities based on patterns, which security prices trace, as well as volume. The appeal of stock charts for many is their ease of use. Even fundamentals-based investors who don’t believe in or use technical analysis bring up a stock chart before buying a new position just to see where the security has been recently. Managers with no background in charting whatsoever still use it to some extent. As a swing trader, you can use dozens of chart types, including line charts, bar charts, and candlestick charts.
In this book, I break the discussion of patterns in two, though I cover both topics in the same chapter:
A technical indicator is like a compass: It helps steer you in the right direction. The act of using technical indicators, which I cover in Chapter 5, is a two-step process:
Apply technical indicators to security prices.
Technical indicators are mathematical formulas that, when applied to security prices, flash either buy or sell signals. They largely remove subjectivity from the analysis of chart patterns. Technical indicators primarily fall into two categories: trending and non-trending.
Not all indicators tell you whether a security is in trending mode or non-trending mode, but relying on the ones that do is useful. Not all indicators are appropriate at a single point in time. Technical indicators are subject to user inputs. These questions partly explain why no indicator is always going to give the correct signal. Many swing traders seek out a trading system that yields the correct signals every time, but no such indicator exists. You must rely on your understanding of the security in question and apply indicators judiciously.
Analyze the strength of the security relative to the overall market.
Relative strength analysis involves comparing the performance of a security to an overall market or industry by looking for divergences between the price of the security and the overall market, which you can see after applying technical indicators. A divergence occurs when a security’s price moves to new highs or new lows, and the technical indicator doesn’t confirm that strength or weakness. The indicator is signaling that the security price isn’t telling the whole story. Divergences are powerful signals because they communicate information contrary to the perceived trend.
If you start to sweat when you hear the phrase fundamental analysis and get anxious when you consider all the tough work that goes into analyzing a company, don’t worry. I follow the K.I.S.S. (Keep It Simple, Stupid) approach when it comes to fundamental analysis.
The material on fundamental analysis that I present in the following section (and in this book) won’t prepare you for your MBA. Rather, it will guide you through the key parts of a firm’s fundamentals that have the biggest impact on share prices.
The fundamental analyst is constantly asking the following questions:
When you find the answers to these questions, you begin to get an idea of what price the company’s shares should reasonably trade at and, more importantly, what events will drive the security’s price in the short-term. You’re not going to arrive at the intrinsic values that Wall Street analysts slave over calculating (intrinsic value refers to the true value of a company and is distinguished from market value, which is the value the market is currently assigning to the firm). But you don’t need to know the value of the shares you trade down to the cent. If shares are valued at $15, and you know shares should be between $25 and $32, do you really need to spend dozens of hours calculating the exact figure? Nope.
Understanding how fundamental analysis works is a bit easier than understanding how technical analysis works. Here’s why this strategy is effective:
The higher the earnings of a company, the more others will pay for a piece of that company. If you own a condo that produces $1,000 in income each month, how much would you value that cash flow? Different people would value the condo differently, depending on their risk tolerance levels and the certainty of that cash flow continuing. But obviously, if the condo were producing income of $2,000 per month, it would be worth double what it was worth when it was producing $1,000 per month (holding all else equal).
Fundamental analysis isn’t that different, except that instead of producing rental income of $1,000 per month, companies produce earnings and report them quarterly. Of course, shareholders don’t usually receive a firm’s entire income because much of it is reinvested in the business and little, if any, profit is distributed (such as in the form of dividends). But the point is, fundamental analysis works because it measures a company’s value based on its expected future earnings.
Okay, you’re convinced that fundamental analysis has merit, but can you benefit from it in your swing trading? The answer is yes. But you should be aware of its limitations and how you can address them:
Unlike technical analysis, you can’t uniformly apply fundamental analysis to securities. A swing trader who understands how to interpret chart patterns and technical indicators goes through the same process whether he or she is trading corn, cotton, gold, oil, stocks, exchange traded funds or cryptocurrencies. The chart analysis is the same, and resistance and support both apply because market participants behave in similar ways regardless of what they’re trading.
Master the fundamental analysis of cotton, however, and you aren’t much better off when you come to trading oil. Master the fundamental analysis of real estate companies, and you’ll face a new ballgame when it comes to technology companies. Differences persist between market fundamentals and how you analyze them. For this reason, swing traders who rely on fundamental analysis often must specialize in a few markets.
Fundamental analysis has its pluses and minuses. Some aspects, such as its emphasis on industry dynamics and competition, make it well suited for the swing trader; other aspects, such as its focus on value realization over the long term, make it a poor swing trading tool.
The advantages of fundamentals are centered on the focus on value — what a firm is actually worth. Fundamental analysis
Of course, fundamental analysis also has its shortcomings because it
Fundamental analysis is principally concerned with a company’s value (or perhaps more accurately, what a company’s value appears to be). But even a company that is undervalued may stay undervalued unless some catalyst occurs to cause other investors to revalue shares higher.
To help make up for the main weakness of fundamental analysis — the issue of timing — swing traders rely on catalysts. Catalysts are fundamental events like mergers, acquisitions, new products, and earnings release dates that affect short-term price movement and spur the market to correctly value a company’s shares. Event-driven trading can be thought of as catalyst-driven trading. These catalysts can be internal or external, and you should pay attention to both.
As a swing trader, you should look for opportunities to trade when a firm’s fundamentals change because of one of these events — or when the perception of a firm’s fundamentals changes (such as when a company surprises Wall Street with its earnings report, or for the more advanced, when a company in the industry or sector reports results that will have an effect on another company, such as a supplier or customer of company). For example, Bitcoin became a rage in 2017 after climbing more than 1,400 percent in one year. A clever swing trader would have looked at who benefits from such a rise and traded those shares. In the case of Bitcoin, graphics card maker Nvidia was a prime beneficiary because Bitcoin “miners” needed intensive graphics processing units to mine Bitcoin. Nvidia returned 82 percent in 2017 (versus the S&P 500’s return of 21 percent) and returned more than 22 percent in the first six months of 2018 (compared to the S&P 500’s return of 3 percent).
Fundamental analysts usually classify companies as either growth firms or value firms (though many ardent investors argue that growth and value investing are two sides of the same coin). Even though growth investing and value investing are associated with long-term investing, swing traders need to be aware of the differences, because growth stocks and value stocks outperform each other at different times.
During some years, value is in the lead; during other years, growth is out front. Trading growth stocks when value is in favor, or vice versa, can be like fighting a schoolyard bully with one hand tied behind your back. If you’re a great fighter, you can pull it off. But it’s not easy.
Is it simply enough to know which horse is in the lead? Unfortunately, just because growth or value has performed well in recent months does not mean that performance will continue. How about forecasting whether growth or value should lead? Unfortunately, forecasting is extremely difficult and rarely works.
I remember meeting with investment consultants many years ago who quizzed me on whether value stocks would outperform growth stocks in the coming year. In truth, I had no idea. I knew that it was growth’s turn to lead because value had been in the driver’s seat for several years, and the valuations were compelling on the growth side of the divide. But the market doesn’t always agree with my analysis. The only reliable way I know to trade the growth/value divide is by using technical analysis. (In Chapter 6, I cover using relative strength analysis, which can help determine whether growth or value is in the driver’s seat.)