On May 6, 2010, at about 2:30 PM, a "flash crash" in the US stock market sent the Dow plummeting by almost 999 points -- the deepest intra-day plunge ever recorded.

The Dow recovered by about 600 points. During the flash crash some individual stocks collapsed to pennies and then rebounded. For the day as a whole, the market closed down 350 points.

This unprecedented shock galvanized the Securities and Exchange Commission into action to identify the cause and devise mechanisms to prevent recurrence. At first, it was thought a "fat finger" error might have sent computerized trading into a tailspin. However, it soon became evident the scale and speed of trading abnormalities could not have been caused by a single misplaced finger.

To its chagrin, the SEC found its antiquated computer capabilities could not capture the volume and speed of transactions in today's markets. Moreover, there was no coherent data center that encompassed the reporting systems of nine separate U.S. exchanges, the "dark pools," and the activities of new ultra-fast, computerized high-frequency trading platforms.

Theoretically, it could take months to rerun that day's records in ultra-slow motion to identify market malfunctions or possible manipulations. The SEC does not have the manpower or technical capability to carry out such a task.

High-frequency trading has truly revolutionized how stock markets function in the United States. High-frequency trading enterprises are not giant corporations or brokerages. They are simply a set of computers functioning according to computer "codes" written by mathematical model builders. The high frequency traders argue they provide substantially increased liquidity to stock market trading and they improve efficiency by driving down buy-sell spreads to tiny fractions of spreads that prevailed a decade ago. Such arguments initially sound appealing.

However, high-frequency trading liquidity turns out to be illusory, totally dependent on the willingness of high-frequency trading platforms to remain active during all trading hours. When several high frequency traders disconnected their computers from the markets on the afternoon of May 6, the result was a temporary implosion of liquidity and a crash in innumerable buy and sell orders. What has been learned from this event is that high-frequency trading platforms not only enhance market liquidity, but they can also threaten massive melt-down, or systemic risk.

Does high-frequency trading (HFT) increase the overall share prices that investors pay over time simply because provision of seemingly limitless liquidity increases transactions demand? High-frequency trading does have an amplifying effect on market moves, but it would be simplistic to consider HFT's the sole cause of upward bias. We are experiencing weakness in trading of U.S. equities, with thin volumes in comparison to historical performance. Unemployment and slow growth may discourage equity investing, but there have also been more seismic changes in the makeup and activity of market participants.

In past decades the market benefited from economic expansion and an increasing cadre of "natural buyers," including pension plans, endowments, foundations, insurance companies, and individual investors.

With economic expansion, one would expect an ever-increasing number of companies to become publicly traded, but that has not been happening. Instead, there are now only about 5,400 publicly traded companies on the major US stock exchanges, half the number prevailing a decade ago. Less choice and thin trading volume would seem to create a situation where valuation becomes skewed by other factors, such as the illusion of new liquidity generated by computerized trading turbo charged by high-frequency trading.

Shrinkage of "normal buyers" in a context of continuing rallies taking place on thinner and thinner volume suggests that high-frequency trading is hiding more weakness than is recognized.

The upward bias from high-frequency trading on rapid buying and selling pushes equity markets higher while providing a false sense of market strength.

For decades, professional investment advisers have continued to teach reliance on "value investing" and "buy-and-hold" as long-term guides to successful investment. Chief economists and market prognosticators for financial institutions continue to urge us to keep focused on "market fundamentals" rather than sell when jostled by disruptive events, expecting "efficient markets" to generate a "fair price" in the whirlwind of market trading.

Technology may now have overridden such investment concepts.

In effect, individual traders are confronted with overwhelming momentum-driven forces that are unrelated to performance of individual businesses.

A "fair price" may exist, but high-frequency traders are not seeking fair prices—they are they are seeking transaction volume boosted by momentum they can generate to maximize profits. Unfortunately, high-frequency trader interaction with computerized algorithms of large-cap financial institutions also provides opportunities for high-speed, virtually undetectable market manipulation.

Where there is opportunity to "shape" the market for advantage, it is likely that such opportunity will be exploited.

In an environment where the range and speed of price movements is ever-increasing, fundamental valuation of a company becomes increasingly arbitrary without ability to distinguish accelerated price movement from actual value.

In conclusion, continuing advances in computerized trading pose challenges for regulators throughout the world—and leave individual investors marginalized. Regulators need to take into account the ability of high-frequency traders to play global regulatory arbitrage in microseconds. Regulators should not only seek to assure that markets are able to continue to function under stress, but they also need to devise remedial actions that protect individual investors who have fundamentally different objectives from the high-turnover objectives of computerized high-frequency traders.

[An extended article-length version of this column appeared in the Summer 2010 edition of International Economy and has been widely circulated in English, Japanese, and German.]