Wednesday, January 24, 2018

The "Reversal" Play: A Study of Company Size, Industry, and Sector

In technical analysis, the “reversal play” is a well-known strategy used by traders to take advantage of imbalances in momentum. The strategy roots itself in the idea of mean-reversion, large decreases in the share price of a stock are typically followed by a period of increases as the value roughly regresses to a mean. From a fundamental point of view, the investor assumes that a sudden spike in share price (which this data looks at) is not accompanied by an immediate fundamental change, therefore, the company has become undervalued.

This phenomenon has been heavily researched before showing that this strategy is capable of producing excess returns. Marc Bremer and Richard Sweeney in “Reversal of Large Stock-Price Decreases” (1991) found that “extremely large negative 10-day rates of return are followed on average by larger-than-expected positive rates of return over following days.” Bremer and Sweeney found that the recoveries they studied were relatively slow and “inconsistent with the notion that market prices quickly reflect relevant information.” This conclusion seems to question the legitimacy of the efficient market hypothesis, a rule that is often rebutted by the existence of reversal plays.

MIT researcher Wesley Chan published “Stock Price Reaction to News and No-News: Drift and Reversal After Headlines” (2001) documenting reversals accompanied by news. His results lead to two conclusions, “first, investors are slow to respond to valid information,” and “second, investors overreact to price shocks, causing ‘excess’ trading volume and volatility.” Once again, academic research suggests that the efficient market hypothesis can’t explain these plays which show a pattern of excess return.

It is in this spirit of a loose interpretation of the efficient market hypothesis that this paper is written. Information asymmetry and a wide variety of valuations help fuel movements in a stock’s price that doesn’t seem fueled by fundamental shifts. This research will look at these movements across different sectors, industries, and company sizes to bring to light any trends of the reversals within those subcategories.


The data was collected from Alpha Vantage which provides stock price data going back to 2000. In particular, this data looks at 1,824 different companies with market capitalizations above 2 billion dollars. This constraint on company size has been enforced because of the volatility of smaller companies with low share prices that move in erratic manners not representative of the technical environment in which reversals occur. These companies are organized in 11 sectors and 70 industries based on their main line of business. In total, 110,404 data points of share price drops in the range of 3 percent and 50 percent were used. Table 1 shows the distribution of these points by sector.

Data Points
Basic Materials
Communications Services
Consumer Cyclical
Consumer Defensive
Financial Services
Real Estate
Table 1. Size of data set and tickers used for each sector.

Data Distribution

For each of the drops observed, measures of price movement 5-days, 10-days and 20-days were recorded to determine the development of the reversal. These values could take on negative or positive values of varying magnitudes. In all sets of the rebound data for most sector, large right tails developed and formed skewed distributions. The average skewness of each sector’s rebound set (5-day, 10-day, and 20-day rebound) is shown in Table 2.

Basic Materials
Communications Services
Consumer Cyclical
Consumer Defensive
Financial Services
Real Estate
Table 2. Average skewness of rebound data sets of 5-days, 10-days, and 20-days. Positive values represent skewness to the right.

The skewness of the datasets shows which sectors are prone to above average returns when a reversal develops. Technology has the largest right skew reflecting its accelerated movement in the current stock market. As illustrated by the boom and bust in the early 2000’s, these stocks are prone to speculation and, therefore, volatile movement. However as technology grew fundamentally strong, the reversals became stronger. Energy and Industrials were the next highest skewed with their dependence on fluctuating commodity prices. Movements in commodity prices can often cause unbased drops in a stock which is otherwise fundamentally strong. The Utilities and Consumer Defensive sectors came in as the lowest as these stocks typically move slower than the market and are shielded from speculation. Reversals are typically tepid on the positive side in these sectors.
It is interesting to note that the distributions of the rebound sets are not just skewed but lognormal. The rebound data sets can be transformed into a roughly normal data set, through the following calculation. After this transformation, the skewness of each distribution is update in Table 3.

Basic Materials
Communications Services
Consumer Cyclical
Consumer Defensive
Financial Services
Real Estate
Table 3. Average skewness of rebound data sets of 5-days, 10-days, and 20-days after transformation

After the logarithmic transformation, the distributions’ skewness falls dramatically and even become negative. This shape only occurs in instances of a heavy positive tail suggesting that reversal developments have smaller negative extremes relative to the positive extremes. While negative outcomes are still likely, the magnitudes of these observations are significantly lower. This is an important observation to be made by an investor looking to reduce risk of large drawdowns and increase the chances of an extremely positive result.


This paper seeks to identify various sector and industry trends within the reversal data. To do this, one can observe the recorded average drops and average 5-day, 10-day, and 20-day rebounds. For the following analysis, visuals can be found on the author’s Tableau workbook titled, “Average Share Price Drop and Rebound By Sector and Industry.” Chart 1 is an extract from the workbook showing the average drop and 5-day rebound of all the industries.

Chart 1. Drop and 5-day rebound by industry (colored by sector).

There is a low positive correlation between average drop and average 5-day rebound when organized by industry. A few outliers stick out. Biotechnology within Healthcare had drops that averages 7.52 percent in magnitude and an average 5-day rebound of 3.28 percent. Volatility in this industry is significantly higher than its peers within Healthcare due to pharmaceutical trials that, more or less, determine a company’s future. Although, this is mostly true for smaller-sized biotechnology companies. Communication Equipment in Technology is another industry that showed drops and similar swings of high magnitude.
Of the most resilient industries, Specialty Insurance within Financial Services and Homebuilding and Construction within Consumer Cyclical were the most. Within 5-days, Insurance had recovered more than half lost in an average drop while Homebuilding and Construction had almost recovered two-thirds of the average drop. Interestingly enough, both industries might be the ones that are affected by natural disasters the most. Natural disasters are the ideal event for a reversal as, typically, a company’s fundamentals do not change and the negative effects are temporary and often exaggerated.
Industries that had the strongest drift from 5-days out to 20-days out (20-day-5-day spread) included Insurance, Biotechnology, Communication Equipment, Coal, Airlines, and Metals and Mining. Coal is an irrelevant case because of its unwinding over the past decade. Three of the industries with the largest spread are those already identified as the most vulnerable based on the 5-day rebound number, therefore it makes sense that these are seeing strong drift. The interesting observations are Metals and Mining and Airlines. Metals and Mining and Airlines grew 1.89 percent and 2.29 percent from 5-days after to 20-days after. Both industries tend to be capital intensive and have large barriers of entry.

Chart 2. Average 5-day, 10-day, and 20-day rebound by market capitalization.

The chart above shows each average rebound measure by market capitalization. Three size groups are represented in the data, mid-capitalization ($2 billion - $10 billion), large-capitalization ($10 billion - $50 billion), and mega-capitalization ($50 billion and over). Following the general observation that smaller stocks tend to be more volatile, the data shows this trend to be true for reversals as well. The 5-day rebound averages are relatively equal, but the drift to 20-days is strongest in mid-caps. This is also explained by a larger amount of extreme positive rebounds that pull the mid-cap data higher.

Tuesday, January 9, 2018

2018 Stock Market Outlook

It's January again, and that mean's another year of trading opens in 2018 closing out the 52 weeks assigned the 2017 label. A new year brings new investment opportunities and closes out others. Rallies and rotations look to be extended, but traders know anything can happen. In 2016, for example, the stocks welcomed investors into the new year with a 220 point drop in the S&P 500 before rebounding over 400 points to end the year in a rally. The rally continued, and 2017 did not disappoint.

From Yahoo Finance

Like a smooth ramp, the top 500 companies in the United States (the S&P 500) grew steadily this year breaking record after record. Only a few red days in April threatened to slow the rally, but those were easily trumped by the green days the followed. The S&P 500 returned 19 percent, the Dow Jones Industrial Average returned 25 percent, the NASDAQ returned 28 percent, and the passive investor once again grinned cheekily. The astonishing bullish sentiment has active investors scrambling to not be left behind, and ETF investing on the rise. In 2017, ETF inflows totaled $475 billion breaking the 2016 record of $287.5 billion. ETF assets are now worth $3.4 trillion with most of that capital landing in U.S. equity funds.


2017 was no doubt a good year, but as mentioned above, it's a new year of trading, and the only way to look is forward. Where else to start but earnings. The well-known Shiller PE Ratio currently sits a 26.2x. The valuation metric continues to grow as price rallies continue to overwhelm earnings growth. With the Trump administration one year old, traders still speculate that EPS numbers will catch up to the prices they at which they trade. The passing of the tax bill has brought abounding optimism in the words "corporate tax cut" that certainly helps Wall Street (Main Street standby). Despite varying opinions on the legislature, a weak general consensus sees a higher national debt and slightly higher gross domestic product. However, the economic jury still deliberates and trades on these hopes could be labeled as speculation.

From Conference Board
The Conference Board provides a nifty little view of the picture that economic data paints of the economy. Based on the historical chart, the indicator has proven itself to be pretty timely in its movements. The last six recessions were preceded by a drop in the Leading Economic Index. Entering 2018, the indicator is back on the rise after what looked like a threat of flattening. The strongest numbers that supported it in November were: the ISM New Order Index, Leading Credit Index, 10-year federal funds rate spread, and consumer expectations for business conditions. In summary, businesses and consumers are continually feeling more optimistic about the economy with new orders growing and expectations improving. Additionally, rising interest rates are supporting the financial services industry and helping margins recover after the long period of flat rates.

NYSE New Highs - NYSE New Lows from
With the exception of high valuations, most measures of stock market sentiment are pointing towards optimism. However, that optimism is as frail as its ever been. Both political and financial pitfalls threaten to send the market into turmoil. Essentially, in 2018 there's more downside than upside. Over the past five years, stocks have consistently been posting record numbers with widespread new lows rare. However during periods of shakiness in the market, the number of new lows skyrocketed over a few trading days. And so, fragility remains, and there are a handful of things that look like they could end the nine-year run of the bulls:

  • Nothing says stock market crash like "thermonuclear war," and scary enough, those words aren't too far from the lips of the most talked about (and arguably the most talkative) leaders, Donald Trump and Kim Jong-Un. While realistically, "thermonuclear war" is an extremely unlikely outcome of the conversation between the leaders of North Korea and the United States, the build-up and excessive deterrence can have a negative impact on the stock market in the way of volatility. In 2017, these moments were not absent and have shown investors that even something as simple as a nuclear missile test can cause a red day.
  • Again, political risks arise as a reason the U.S. stock market could crash, but instead of foreign political risks like the previous point, domestic political risks are the reason here. President Trump shocked the system with his surprise election in 2016 and looks to continue to push his agenda going into 2018 after a radical attempt to repeal the Affordable Care Act and the passing of Republican-supported tax reform. Investors have put a lot of money on the pro-business tactics of the Trump administration spurring on the "Trump rally." To extend those gains, Trump must follow through on his antics as well as successfully renegotiate dozens of trade deals he finds unfit. But with Democrats winning some key elections in 2017, the domestic political pendulum could swing heavily to the left side.
  • Another danger that could cause the stock market to crash is a major slowdown in an emerging economy like China or Brazil. As projected, emerging economies have become a huge source of global growth and enormous demanders of commodities and industrial goods. PIMCO saw a small recovery in Brazilian and Russian GDP in 2018, but a large part of those forecasts are based on the improvement in commodity prices. Weakness in agricultural commodities can pose problems to Brazil's economy, and a tumble in energy commodities could threaten Russia's economy. Additionally, PIMCO says that China's economy is not expected to "disrupt" the global economy, but the Chinese credit expansion over the past couple of years still leaves some risks to consider. Like seen in late 2015 and early 2016 with China, weakness in a major emerging market can create shocks.
  • The Federal Reserve and interest rates continue to be in focus as 2018 rolls around. Not only do investors have to consider where the Federal Funds rate might be by December 2018, but they must also consider what the new Fed chair Jerome Powell could bring to the table. CPI Inflation rates have recovered from only 0.1 percent in 2015 but still haven't reached the 2 percent inflation target. Currently, the Federal Reserve sees a median of 3 rate hikes in 2018 which is justifiable considering the optimism in economic numbers. However, with the amount of debt in the economy, any unfavorable policies or adverse reactions to policy plans could cause emotions to take over.
So in 2018, expect to walk a path similar to the one in 2017. The Trump trade continues to roll stocks higher as earnings slowly trudge behind prices. The fragility of the situation is not to be underestimated as shares reach all-time highs and buying opportunities appear less and less. Nevertheless, a smooth 2018 should coax stocks even higher with technology leading the way (once again).

2018 S&P 500 Performance: 15%
2018 Dow Jones Industrial Average Performance: 17%
2018 Nasdaq Performance: 20%