Financial Education

If the weak form of the efficient market hypothesis holds, security market information should have no relationship with future returns. Technical analysis and trading rules should not allow investors to earn excess returns.

Researchers testing weak form market efficiency generally use one of two groups of tests when studying weak-form market efficiency.

1. Statistical tests of independence measure either the significance of positive or negative correlation over time (autocorrelation) or by comparing the number of runs (consecutive moves in the same direction) with that expected in a normal sample. In general, statistical tests of independence have shown no relationship between current and future price movements.
2. Tests of trading rules seek to mechanically simulate various trading strategies. For example, testing whether a strategy of buying when the stock price closes above the 50 day moving average and selling when the price closes below the moving average. In general, these tests have supported the weak-form efficient market hypothesis by showing no excess returns (after trading costs, compared to a buy-and-hold strategy) from following such rules. However, the results are not unanimous – some rules have been shown to offer superior returns.

Technical analysts criticize the existing tests as being too naive or simplistic to capture the

The weak form of the efficient market hypothesis assumes that current stock prices fully reflect all security market information. Security market information includes historical price and volume data, as well as other market-generated information such as odd-lot trades and short interest.

If the weak-form EMH holds, security market information should have no relationship with future returns. Technical analysis and trading rules should not allow investors to earn excess returns.

Internet message boards offer a forum for professionals and amateurs to discuss the relative merits of various stocks. In the Journal of Technical Analysis, Issue 64, Manuel Amunategui creates a technical indicator based on the total traffic and moving average of traffic to the Yahoo! Finance message boards for 550 NASDAQ stocks.

In one test, the author finds that modifying a moving-average crossover strategy to enter the market only on days when the number of message board posts is declining results in fewer trades, lower transaction costs, and higher profit per trade. The premise behind the added condition is that declining message board traffic indicates the stable conditions under which trend-following systems flourish.

In another test, a strategy of trading for a bounce after four consecutive down days is modified to enter the market only when the message board posts have increased from the prior day. The logic in this case is that the increased attention may signal the opportunity for a reversal.

Standardized unexpected earnings is a means of comparing earnings surprise to the company’s track record of earnings surprise. For example, Cisco was once said to consistently beat earnings estimates by a penny. Thus, if the company did beat by a penny it was hardly unexpected. A method frequently used in academic research to adjust for this factor is the standardized unexpected earnings, or SUE.

SUE = the earnings surprise at a given time divided by the standard deviation of earnings surprises measured over some historic period such as the previous 20 quarters.

Consider a stock that had a $0.03 earnings surprise, and that the standard deviation of past earnings surprises is $0.05. The surprise is smaller than normal, and the standardized earnings surprise would be $0.03/$0.05 = 0.6.

I was sent a pre-publication copy of Timothy Sykes’ book An American Hedge Fund and found it to be a quick and fairly enjoyable read.

The book recounts the improbable tale of how Sykes turned his Bar Mitzvah money into a multi-million dollar hedge fund, and reads as much like a trading diary as it does either a novel or a personal finance book. As to what it actually is, if you were one of those people offended by the “truthiness” of A Million Little Pieces you may want to steer clear. The book is billed as a memoir, categorized under Business/Personal Finance and described in the cover letter I received as a novel. Not to mention it was published under Sykes’ own “Bullship Press” label, so consider yourself warned if not every fact in the book is verified.

Personally, though, I could care less about whether a story is truth or fiction as long as it reads well. And here the book turns out to be quick and, assuming you are into the stock market, enjoyable. The biggest turnoff was that hardly a page goes by without a clinical description of the gain/loss on some trade that was made. I would have preferred a more general discussion of how Sykes learned from his successes and mistakes, with the trades serving as illustrations rather than the other way around.

Sykes is able to tell the story with the right mix of chutzpah and humility, fessing up to his mistakes – some of which he continued to make even after professing to learn from them. I find it particularly ironic that late in the book Sykes says:

Looking back, I had foolishly gotten into this industry thinking I could easily grow my operation to the $20 to $50 million asset range based on my performance alone. I would’ve saved a great deal of time, energy and money if somebody had written a book like this to warn me about the true nature of the industry.

Four pages later, he says:

I’d read up on the self-publishing industry and thought I’d found another niche market ripe with opportunity. If I went this route, I’d have total control over my book, quadruple profit margins, and I could distribute the truth to the general public within a few months.

Something tells me his next book will be an expose of the publishing industry.

Once an appropriate allocation between different investment types (for example, stocks, bonds and real estate) has been determined, individual securities (or mutual funds) must be selected within each investment type.
There are two basic approches to individual security selection: top-down and bottom-up.
In a top-down approach the analyst examines the overall economy and market and selects sectors (for example, healthcare or financial) that are expected to perform well in the current environment. Individual companies are then selected within each sector based upon desired characteristics.
In a bottom-up approach the analyst first idenifies individual companies with desired characteristics and then examines the prospects for those companies given current economic and market conditions.
Regardless of which approach is taken it is important that the economy, market and industry conditions are considered when making the desicion to invest in individual securites of any type.
In evaluating individual securities there are also two main approaches: fundamental and technical. Fundamental analysis deals with examining a host of data such as a company’s financial statements, ratios and management in selecting securites for investment. Technical anlaysis involves looking at past trends in market price and volume information to discern the underlying trend in a security. These trends reflect underlying supply and demand and investor behavior.Often these two techniques are viewed as mutually exclusive (some people follow one but not the other). Another view is that the approaches are complimentary, a company may look great fundamentally but technical analysis may indicate it is not the best time to buy.

Technical analysis involves a study of past price and volume data to discern underlying trends for a security or market. The price of any asset is partly a function of supply and demand factors. If demand exceeds supply the price should rise. Conversely if supply exceeds demand the price should fall. The underlying supply and demand as well as the behavior of all investors is reflected in charts of price and volume data. A technical analyst examines these charts to determine if the current trend is expected to continue or to reverse. Technical analysis can be useful in evaluating individual securities, industries and the market as a whole.

There are many technical indicators; we will discuss only a couple of examples. A support level is a point at which buyers step in an begin buying a security. When a stock falls to this level the buyers typically step in and the security should either stay at that level or rebound (if however, the price falls below a level which has represented a support level in the past this is a negative sign). Conversely, a resistance level is a level at which the security stalls when it is rising. At this point investors are selling. A moving average line is an average of a certain number of days of prior price data. If a price is below the moving average line and moves above it, this is a positive indicator. Conversely, if the price is above the moving average and moves below it this is a negative sign.