Financial Information

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Share picking is akin to weather prediction - no one can predict with certainty five hours from now if the price will rise or fall, much less five years from now.

Nevertheless, there are indicators that help to reduce the risk and increase the odds of profiting over the long term. After all, historically stocks have returned over 10%, as measured by the growth of the S&P 500.

The first step is to get educated. Learn not only about dividends yields and earnings per share, but also some basic accounting. Reported figures have an air of authority but the sad fact remains that those numbers are arrived at, in part, by accounting methods which are not cut and dried. 

The Enron case (case in which the executives of Enron manipulated their earnings figures to appear to be much more
successful than they were) is extreme, but even ordinary procedures involve judgment calls on the part of financial officers and auditors.

Next, commit to continuing research about stocks both inside and outside your intended portfolio, and update it as you buy and sell. There’s a broad spectrum between exact prediction and throwing darts blindly. In the long run, those who do their homework do far better and almost all day traders lose money.

Research both prospective buys and intended sells. Many investors put considerable time and effort into analyzing a buy, but then only watch for some price to be reached in order to sell. Knowing when to sell is just as important, and a target should be selected before the share is bought.

RESEARCHING BUYS

Obtain the latest, and some historical, financial statements. The SEC provides these free (www.sec.gov) in their EDGAR database, but other exchanges have similar arrangements.

Analyze the quarterly statements covering two to three years, looking for EPS (earnings per share) and revenue trends. Calculate dividend yields, if the company pays dividends.

Compare the company’s P/E (Price to Earnings) ratio to others in the same economic sector. Look at P/S (Price to Sales) ratios, too. Sales growth is easier to predict than earnings and less volatile than P/E ratios. 

Examine general economic factors. Interest rates affect share prices as well as bonds (though less directly), since almost every company borrows money. Even when they don’t, their competitors, suppliers, and customers do. Interest charges reduce profits for all but the lenders, for whom it’s income. 

Even when researching a bank, though, high interest rates increase short-term profits, but can reduce the number of loans and cause certain current ones to be repaid early. High interest rates aren’t necessarily good for banks either, therefore.

Use some of the more common technical indicators, such as MA (moving averages) and RSI (Relative Strength Index, which compares the number of days a share finishes up versus down). An RSI of 70, or above, for example, does tend to indicate a stock which is overbought and due for a fall in price.

RESEARCHING SELLS

Pick a target price, which amounts to deciding how much profit (in dollars or percentage terms) you seek then sell at that price, unless your continuing research has turned up significant new information.

Consider selling if the price has dropped substantially or remained unchanged for several months. Losses are hard to bear, but consider that you can’t always pick winners and while you’re invested in one share, you’re forgoing potential profit from another. That profit could help reduce or more than make up for the loss from the sale.

Continue to monitor the company’s fundamentals by obtaining updated filings. Re-evaluate them by updating earnings trend calculations, significant management or general economic changes.

You can ease the difficulty of performing calculations (which is a useful exercise at least once) by finding Internet sites that provide objective data and go easy on the “here’s how to pick winners” sales talk.

And remember, ‘on the street’ opinions are a dime a dozen - including mine.

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Probably you know by now that the big boys don’t play nice. In the stock market, institutional and other investors with large sums have much more influence on events than the average trader. One way they do that is through the use of something called ‘program trading’, the purchase (or sale) of a group of stocks, usually by automated buy/sell orders.

Originally the term had little to do with ‘computer program’. Program Trading got its name when index funds and other institutional investors embarked on large-scale trading to replicate a share index. Before long, clever statistical analysts joined hands with even more clever arbitrageurs to try to ‘beat’ the market through the use of sophisticated trading algorithms, assisted by (then) new, high-speed computer programs.

Fundamental analysis met technical analysis and introduced themselves to software. The rest is rather bumpy history. In one famous case, though some studies deny this, it may have contributed heavily to the well-known Black Monday of October 1987 when the market dropped by over 20% in one day.

While not the largest drop in history (a larger percent decline occurred in 1914 and later a larger point drop, in 2001), nevertheless within one day, 500 billion dollars evaporated from the Dow Jones index. And, the event continued in markets around the world. Hong Kong shares fell over 45% (some say this happened before the U.S. decline - accounts differ) and London over 26%.

Out of favor for, oh say maybe a day, program trading continued - albeit after a few software tweaks. New SEC rules were devised and major market players altered thresholds to slow or halt trading when certain percentage declines are reached.

While the NYSE defines a program trade as a basket of 15 shares or having a total value of $1M (or more), trades can be executed in small lots (100-300 shares, for example). In theory, this allows orders to be completed before other investors get wise, and helps avoid large price movements before positions are solidified or liquidated.

As finance professors and large-firm specialists develop ever more sophisticated methods of taking advantage of small price discrepancies across global markets, program trading becomes ever more complex. In many cases, the individuals involved don’t themselves understand well the consequences of implementing a particular strategy.

Program trading now comprises over 50% of NYSE volume on average and it can introduce large swings in a few stocks or large portions of the market. Clearly, the big boys wouldn’t bother unless they believed - backed now by decades of studies - that there was an advantage in using the technique.

But whether villain or savior, it’s here to stay. Over 50% of the volume on one exchange that trades over 1.6 billion shares a day is a huge amount of arbitrage activity. That effect can work against the average investor or for him, but only if included in a trading strategy that pays attention to where those trades are going.

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Once upon a time there was no Internet. OK, now take a deep breath. It’s alright because there is one now. For several decades (roughly from 1960 to 1990), large companies such as Merrill Lynch and Morgan Stanley were able to trade among themselves electronically, but these trades took place over private networks.

In 1978, the Intermarket Trading System (ITS) opened for business, providing an electronic link between the NYSE and competing exchanges, enabling brokers to access several markets. But still, only for the ‘in-crowd’.

Then in 1994, Aufhauser Securities (now owned by Ameritrade) created the first Internet trading system. As Internet trading grew dramatically, companies developed systems allowing individual investors to not only trade, but access information once available only to those large companies.

The world has never been the same since.

Trading commissions fell to negligible territory. Twenty years ago, it was common to pay $100 or more on a $1000 trade; online trading fees are less than $10 today. Yet, despite the considerable drop in prices, brokerages are making enormous profits, thanks to the increase in trading volume.

Peak volume in 1824 on the NYSE was 380,000 shares, though less than 10,000 was the norm in 1835. Unfair comparison, too far back? Fine. In 1992 average daily volume was 200 million shares. Today, it’s over 1.6 Billion. Peaks as high as 3 billion have been seen.

Along with lower prices and increased volume, trading times have shortened from an hour or half a day, to a few seconds. And you wonder why the floor brokers are always yelling at one another on the share exchange.

Research, once available only to specialized analysts in large brokerage firms, is now accessible to the average investor with an online trading account - often for free. And the research itself has grown from simple Earnings Per Share and Dividend Yield data to a bewildering array of Relative Strength Indexes (RSI), Moving Average Convergence Divergence (MACD), Bollinger Bands and others even more arcane.

Networked trading, along with other computer technology, has made exchanges international and in some cases global. Only a few years ago the Amsterdam, Brussels, Lisbon and Paris exchanges merged into Euronext - a single trading exchange for countries with widely differing backgrounds. Efforts continue to bring the London stock Exchange into partnership with Euronext or FWB (Frankfurter Wertpapierbörse, the major German exchange), or both.

As a consequence of the emergence of merging exchanges, trading has improved not only for members but the individual investor as well. It isn’t just citizens of the countries involved in Euronext who can trade there. Exchanges the world over are now open to almost any investor anywhere. Now anyone, not just London’s professional traders, can enjoy the effects of sleep deprivation monitoring and trading on exchanges that cross every time zone on the globe.

All this change, while difficult to absorb, has one overriding goal and result - you can now make (or lose) a lot more money a lot faster, in a lot more places, than your father. That ought to produce at least a few interesting family dinner conversations.

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