A Discounted View

Over the past year, investors have been lulled into a complacent state by the exceptional returns in the market accompanied by low volatility in price action. However, as of Tuesday the S&P 500 (SPX) experienced its largest recent one-day drop of -1.09%. Daily Perspective On the daily chart today’s drop in SPX is clearly defined as it deviates from the uptrend that has formed since the beginning of 2018. While we navigate through earnings season, the gap-down in SPX represents a meaningful difference in sentiment among market participants relative to the rest of January. As constituents of SPX continue reporting earnings, expectations are being repriced into the index. In the meantime, there are some noticeable developments on the daily chart . For example, the gap lower was so pronounced that the daily Relative Strength Index (RSI) finally closed below its overbought level which SPX had maintained throughout all of January 2018. At the very least this sign...

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 chronologi...

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 characteristic...

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....

In Mebane Faber’s paper, “Quantitative Approach to Tactical Asset Allocation,” he builds a quantitative market-timing model that employs a trend-following strategy with built-in risk management. Specifically, he utilizes a moving-average-based trading system which is the most commonly used trend-following method. The system rules are simple and are as follows: Buy Rule: Buy when monthly closing price > 10-month Simple Moving Average (SMA) Sell Rule: Sell and move to cash when monthly closing price is < 10-month SMA At most, this system will rebalance monthly if a market is range-bound. However, when using the 10-month SMA (near equivalent to the 200-day SMA) as a trading signal, systems generally have a propensity for less turnover than other actively managed strategies. The converse, and one basis for comparison, of an actively managed strategy is a passively managed system. Faber’s research compares the model against a buy-and-hold (i.e. long) allocation to the S...