A Discounted View

Atlassian Corp (TEAM) had its initial public offering (IPO) in December 2015. Since that time the price has displayed interesting behavior from a long perspective . During the beginning of 2016 TEAM declined rapidly along with the rest of the market  as global economic fears were pervasive among market participants. Since that decline, TEAM found support  in early February 2016 as seen by the two reversal candlesticks  on the weekly chart.  The weekly reversals in price  were accompanied by an increase in volume both weeks which indicated that $20 is a meaningful level of support  from a weekly bar perspective. In mid-May 2016 TEAM formed a higher low around $22 and also exhibited a reversal candlestick at this level. Upon clearing prior resistance  in June 2016 volume accelerated again for four weeks indicating conviction in the move higher . Zooming in one order of magnitude shorter, the daily chart shows that after the breakout out above previous resistance between

The price of ResMed Inc. (RMD) recently broke out of a resistance barrier on multiple timeframes. First, the monthly chart shows a clear break of resistance near the $60 level. Historically, this behavior in RMD and other stocks is constructive for a long set up . You can see from the past 10 years of monthly price data that RMD has a tendency to trend, consolidate for a while, and then trend again . At the point of breakout, a long position was unconfirmed by MACD, a trend indicator , but with further price improvement it exhibited a bullish crossover. Additionally, comparing RMD’s lows in its most recent range bound consolidation with MACD-H confirms its advance leading up to its breakout. Second, after zooming in one order of magnitude  shorter to the weekly time frame you can see a more granular view of the breakout from the monthly chart. From a trend perspective  we now see the price above its 40-week moving average ( 200SMA ) and a fairly consistent bottom left to t

Nicolas Darvas was a professional dancer turned stock market speculator. He happened to stumble upon investing when one of his employers opted to pay him in stock instead of cash. As it turns out, Darvas could not make this particular show but in a gesture of professionalism offered to buy the shares from the venue owners. This decision ultimately changed the course of his life and led him to write his well-known book “How I Made $2 Million in the Stock Market.” Despite the trite title, the experiences shared by Darvas are invaluable to an aspiring trader . Moreover, William O’Neill of Investor’s Business Daily and Market Wizards fame built his proprietary CANSLIM process mirroring most of the Darvas principles. While still effective and useful today, the principles conveyed in this book are well-known and shared openly online. Instead of touching on those aspects of the book, it will be valuable to examine the emotions experienced  by Darvas in his trading journey. In particu

During a market downturn the VIX is a commonly referenced indicator. The value of the VIX is derived from the price of out-of-the-money S&P 500 (SPX) put options and will increase as SPX declines. Given this behavior in the VIX, it can be used as a valuable trading tool  on its own and in combination with other indexes or indicators . For example, one of the most common strategies  is buying put options on the SPX when prices begin to top or decline. In other words, the VIX can be used for a simple equity market hedging strategy . This buying of SPX put options will cause the implied volatility to rise, resulting in higher premiums for the options. Since the VIX measures implied volatility of SPX index options, it will move inversely with the SPX. That is, as prices fall there is more put option buying which results in higher VIX levels. Not only does VIX increase as SPX declines, but it also has a tendency to increase more quickly the faster and farther the SPX declin

Momentum is a very unique trading style. Cliff Asness defines it as “a phenomenon where securities that have performed well relative to peers (winners) tend to outperform. Additionally, securities that have underperformed peers (losers) tend to continue to underperform” (Fact, Fiction, and Momentum Investing). Momentum is different from, and should not be confused with, Trend Following . Momentum ranks securities relative to peer performance, whereas Trend Following focuses on absolute price changes . Moreover, momentum takes no position on a market direction when it ranks securities by recent performance. Conversely, Trend Following is a useful tool that can be used to identify the trending behavior of a market . In the investment business, momentum is one of the newest strategies. It was officially discovered in the academic community in 1993. Given this recent discovery by academics there remains much skepticism around momentum’s efficacy as a viable trading strategy .

Bubbles are a naturally occurring phenomenon in financial markets. However, while academics and subscribers to the Efficient Market Hypothesis will argue that a market inefficiency, such as a bubble, could not exist, practitioners  see differently. After all, anyone with money at risk  in their own account or for clients will say that the market did not behave rationally during the recent credit bubble in 2007-2008 or the Dot-com bubble in 1999-2000. Bubbles have existed for centuries with the most infamous dating back to Tulipmania in the 1600’s in Holland. Human nature and our inherent behavioral biases  fuel the rapid rise in asset prices that accompanies a bubble’s expansion phase. This unsustainable growth in investment leads to an eventual dramatic decline that happens nearly as fast the popping of a balloon. While the peak and end of a bubble are easily identifiable in hindsight, the stages of a bubble can be further classified into five chronological categories

No matter how hard you try to fight it, trading will test your emotional stability. It simply cannot be avoided. We as human beings are wired with an emotional, reptilian brain that will over-rule our rational and probabilistic thinking especially when dealing with money. Moreover, Alexander Elder  states “Thinking about money interferes with decision making” (The New Trading for a Living). New traders look at open profits and think about the ways they can spend the money they just made in the market. Elder continues by saying “ Professionals focus on managing trades ; they count money only after trades are closed.” In other words, professionals focus on process not outcome .  Additionally, when a novice trader is experiencing a large drawdown or a series of losses he or she is more inclined to hold losing positions below initial stops with the hope that the prices will recover. The inability to sell a losing position stems from our emotional brain. For example, emotional trad

In his book, Trading Systems and Methods, Perry Kaufman provides some simple, non-mathematical rules that all traders should employ when running a trading program. While there is a purpose and time for using statistics and more advanced mathematical concepts to manage risk, these guidelines will help keep your trading on the path to profitability.   Only risk a small amount of total capital on any one trade . This suggestion echoes the teaching of Dr. Alexander Elder who popularized the 2% Rule . Simply put, when trading you should never exceed a particular amount of risk in any one position that could compromise your performance. In the futures industry, risk-based position sizing algorithms  are commonly used to determine the ideal position size or Optimal f. Know your exit conditions in advance . Kaufman states that “There should be a clear exit criterion for every trade, even if the exact loss cannot be known in advance.” In other w

The art of professional portfolio management  experienced a revolution after the concepts in Harry Markowitz’s seminal paper explained how investors view risk and return. In his work, he derived formulas used to calculate volatility and expected return of a diversified portfolio with the ultimate goal of his to find the best portfolio allocation to maximize return for a given level of risk. His work is based on three assumptions: 1) Investors are generally risk-averse, 2) investors base their portfolio decisions on risk and expected return only, and 3) investors measure risk as the variance (or standard deviation) of expected returns. The third assumption led Markowitz to conceive the idea of a portfolio being “mean-variance” efficient when no other portfolio offers a higher expected return at a given level of risk, or lower level of risk for a given expected return. Creating portfolios that have higher mean-variance efficiency depends on certain statistical characteristics of

Harry Markowitz, the founder of Modern Portfolio Theory, once said that “diversification is the only free lunch.” Decades since his seminal work in developing mean-variance efficient portfolios that maximize return for a given level of risk, this adage still holds true in most market environments. It is common practice for fund managers to diversify among asset classes based on Markowitz’s findings. However, diversification with his methods can be taken one step further .  While diversifying your account in all suitable asset classes is worthwhile, a trader can also diversify an account with different trading styles which will create uncorrelated return streams. For example, Perry Kaufman suggests that a well-diversified trader has an ideal mix of three, maybe four, unique strategies. Generally speaking, these three trading styles can be categorized as Trend Following , Mean Reversion , or  Pattern Recognition . Furthermore, styles can be differentiated by time horizon.  For examp