After two weeks of modest losses, the S&P500 reversed course and rose 1.4% last week. Volume was modest. But volatility dropped; the VIX index dropped back down to multi-year lows, suggesting that once again, investors are setting all worrying aside and putting all their faith into the central banks of the world.
The primary drivers of last week’s rally, aside from technical reasons (the market was over sold on a short-term basis), were a couple of upside surprises in the economy. But there were caveats with each. First, the ISM indices beat expectations. However key components within these indices were still quite bearish. For example, prices paid rose within the ISM’s—pushing the indices higher—but the reality is that higher prices lead to lower corporate profits or lower wages, which could hurt the economy in the longer run.
Then the unemployment rate surprised everyone by plunging to 7.8% from 8.1% just in time to boost the president’s election chances. However, key problems remain in effect. Almost all of the improvement in the headline rate came from a historic surge in part-time workers, who seemingly came from nowhere to suddenly take on sub-optimal employment. So the most broad measure of unemployment, U-6, remained stuck at an dismally high rate of 14.7%. Meanwhile, factory orders kept on plunging and construction spending fell, instead of rising as expected.
After all the focus on the open manipulation of the equity markets (up), the bond markets (yields down) and the dollar market (down) by the Federal Reserve, it’s easy to forget that there are other major risks lurking beneath the surface of the capital markets.
One of the most sinister, yet still perfectly legal, forces of market manipulation comes from high frequency trading. And now over two years after the Flash Crash in May 2010, this industry has just kept on growing. Today, it’s responsible for 70% of all transactions on US stock exchanges.
Computer algorithms, or machines, have virtually taken over the US stock markets. And this presents several problems. One is that these programs cheat everyday individual and institutional investors out of money. Algos, for example, due to their speed advantage, can front run normal traders and take money away from them.
A second problem is that their supposed liquidity tends to vanish when it’s need most—eg. times of market stress. Instead of supplying liquidity when normal “human” investors get stressed, computers simply shut off, usually in a flash, leaving the markets they were formerly trading vulnerable to massive plunges.
Luckily, regulators outside the US are beginning to rein in these predators. And hopefully this will set an example for the SEC in the US, where they have still not conclusively demonstrated how and why the Flash Crash occurred in 2010.
While, according to the NY Times, the SEC is beginning to invest in research to better track computer trading, it’s still a long way away from doing anything about it.
And this means that in addition to all the other major risk factors already threatening risk markets, it’s important not to forget that algorithmic trading is another home-grown risk that we face every single day.