Overwhelmed by Market Data?
Overwhelmed by Market Data?

Overwhelmed by Market Data?

| fractalerts | Blog

With stock price alerts pinging on your smartphone and trades being executed at high-speed frequencies, it seems unbelievable that just 40 years ago, stock market data was restricted to a few thousand financial gatekeepers. If you, the eager trader, wanted to know how IBM was doing post-earnings, or what the price of oil per gallon was, you had to call your broker, or, worse, wait for the next day’s newspaper.

Now, thanks to the Internet and large-bandwidth data streams, you can check stock quotes in real time, listen to earnings reports live, follow Asian markets, apply sophisticated technical analysis software to Indices charts, and hear endless predictions from market pundits on the radio, TV, and web.

Market prognosticators nearly always have an agenda, whether it’s selling their latest book or shorting an underperforming stock, so their predictions are hardly ever really objective.

Market data is constantly within eye and earshot. But there’s a problem with this incessant chatter—it never stops. And it’s overwhelming for traders, managers, or anyone to decipher. How do you filter the noise to find the true market signals?

Luckily, there are some things you can afford to stop paying attention to.

Mute the Market Forecasters

Wharton School economics professors, asset managers, Carl Icahn. They’re the bellicose bellwethers of Bloomberg, CNBC, and late-night TV ads. But what are their real motives?

From December of 1994 to summer of 1995, dozens of newspaper and financial forecasters sounded the “Dive, Dive!” alarm for investors, warning them to exit the market before it crashed completely.

“Every time all five of our indicators turned negative, we had at least a 20% decline,” opined a Growth Fund manager to Barron’s magazine at the time.

The Dow Jones Industrial Average sat at 4,208. But if traders had listened to this pessimism and pulled out, they would have missed the biggest 5-year bull run in history, as author Larry E. Swedroe points out. On January 14, 2000, the Dow closed up 7,000 points higher at 11,722.98.

“Astoundingly, one of the main reasons for the crash was the physiology of bankers, traders and fund managers”

Shrug Off Short-Term Corrections

When the Dow drops 300 points in an afternoon and Mad Money’s Jim Cramer is yelling, “Sell, sell!” are you able to stay true to your core trading strategy?

If so, you’re stronger than 99% of traders. Humans are hard-wired to be spooked by anxiety-producing events, like short-term market corrections, because of our natural “fight or flight” adrenaline responses.

Stressful events cause the production of cortisol, a hormone that triggers fear and self-preservation instincts. In the markets, that causes traders to engage in “risk-averse” behavior, such as dumping stocks when they should buy or stay the course, according to John Coates, a research fellow in neuroscience and finance at the University of Cambridge. Coates studies the biology of risk-taking and stress and measured the cortisol levels of actual floor traders during a two-week period of market volatility. He found these levels rose 68 percent during periods of acute market fluctuations.

He concluded that the U.S. market crash of 2009 may have been exaggerated by panicked sellers flooded with cortisol.

“Astoundingly, one of the main reasons for the crash was the physiology of bankers, traders and fund managers,” he wrote in his Cambridge report.

Squelch the Mega-Signals of Trading Platforms

Day-trading platforms have grown ultra-sophisticated, with flashy optimization and market simulation tools. But how important are all those colorful graphs? What do the oscillations, candlesticks, and flashing technical indicators mean anyway?

Most trading software packages include instructions and videos on how to operate these systems. But what’s missing is a solid statistical education and guidance on how to properly interpret the results. Some trading platforms will provide this training to you—for a hefty price.

In addition, the time-based charts can be so micro-focused on the market volatility in a minute, 5 minutes, or half a day, that any intraday rise or fall appears much more significant than it really is. Better to leave the blinking screens to X-Box and Nintendo.

So, now that you’ve filtered out some of the white noise, here are some sanity-saving checks and balances you can use:

1 – Make a Trading Checklist

Before being tempted by that sexy ETF, ask yourself some rigorous questions: does this trade fit in with my overall goal? Does it duplicate similar equities I already own? What are my entry and exit points? What is the (realistic) potential profit? What ranges can I tolerate? Is the profit worth the potential headache?

2 – Know Your Investment Biases

Do you always want to cut and run if your portfolio drops 10%? Do fluctuations in the dollar make you queasy? Burned once on crude futures and can’t bear to trade in that sector again? We’re all affected by our personal trading experiences. But once you identify your weaknesses, you’re better able to recognize and separate emotional impulses from disciplined trading strategy.

To uncover your personal investment biases, start a trading journal and log your entry and exit points, stressful events, and the thought processes behind them. Be frightfully honest; no one else will see these notes but you.

Within 6 months time, you’ll start to recognize patterns in your motives and trading. Some may be profitable, others not so much.

3 – Consider Unemotional Trading Alerts

With the advent of computers and data-mining, automated pattern-recognition software is becoming the Phillips screwdriver of a smart trader’s toolbelt. Moving averages, Fibonacci sequences, Four Percent Models and other technical analysis theories are useful, but can be difficult and time-consuming to apply yourself. They also have a steep learning curve.

Alternatively, fractalerts’ algorithms evaluate market price, volume, momentum and elapsed time to identify repeating fractal patterns in indices, commodities, and currencies. When the software recognizes a predictable fractal pattern, it instantly earmarks the precise point to buy or sell a position. These insights are catalogued and sent to you in an easy-to-understand alert, so you can plan accordingly.