One of the biggest hurdles that the individual investor faces in trying to create a nimble, smart portfolio is the competition.
Investment bankers, quants, mutual fund companies, and big Wall Street firms are employing Ph.D. researchers with degrees in everything from finance to physics to create model portfolios. They use the latest and most powerful technology to guide their buys and sells.
The little guy doesn’t have a chance.
That’s what I thought, until last week. George and I had a chance to see a demonstration of Chaikin Analytics, probably one of the most complete set of investment tools and stock market model-building technology that’s available for the money. Or at least I’ve ever seen.
The Chaikin Analytics Dashboard
How does Chaikin level the playing field?
Business Strategy, Internet, Investing, Money, US Economy
The whole philosophy of using machine learning and artificial intelligence in investing is that machines can make trades quickly and without being burdened by emotions.
It’s the last bit that I’ll talk about today. Emotions — like fear and greed — skew the decision-making processes of the investor, causing him or her to but too high or sell to low based purely on feelings. A good example: you would probably pay more for food if you’re hungry than if you just had a big dinner.
Therefore — and this conclusion is inescapable — machines that do not have emotions can trade better.
Except, this logic is totally wrong. Well, not wrong. But it forgets the most important variable. The market and the economy runs on emotions. Even if every investor was an emotion-less cyborg, the rest of the economy, which underlies all stocks and commodities, runs on desires and emotions.
A successful investment system can not possibly rule out emotions. In fact, the most successful investment system would totally understand emotions, but not ruled by them. This system would understand how desire for something quickly turns to the desire to not lose something — fear. Likewise, it would be able to sense when the momentum of fear turns into a buying opportunity. It could sense that the greed in the real estate market was becoming too frothy, or that the fear of a recession was starting to bottom out.
In short, the best investment system understands emotions. It just isn’t ruled by them.
Investing, Money, Online Investing AI
Each day, machines, not humans, are plowing through statistics and crunching numbers trying to devise trading algorithms to make money in stock markets, futures markets, commodities markets, and any other place that traders can turn a dime.
They’ve been successful.
But not totally successful. And not successful for long stretches.
The stories of trading strategies failing are just as common as stories of amazing machine-learning success in the market.
Why is that?
I’ll take a stab. I believe that most machine learning and artificial intelligence programs are essentially created short-sighted. To build an automated trading system, you “train” the program to understand data. This data can be technical or fundamental, or a range of other data sets. The program learns the relationships between the data and the market. When factor x goes up, the market reacts with a y, let’s say.
But, this data is not an object, per se, but is really a shadow of currents in a broader economy. So, the program ends up not be predictive at all. It is reacting to a reactive set of data.
Accelerating Technology, Automated Trading, Investing, Money, Online Investing AI, Success
Good looking waitresses could be bad for your assets. (Creative Commons.)
Can the number of good looking waitresses in a restaurant tell you something about the state of the economy?
Could Big Mac sales help you trade currencies?
They just might. You can check out The WSJ Guide to 50 Indicators by Simon Constable and Robert E. Wright for these–and a lot more financial forecasting devices.
Not all the indicators are as fun to research as waitresses and Big Macs. In a serious, but highly readable style, the authors introduce you to a wide-range of the most important portents of coming economic conditions.
The book does a good job of introducing a range of indicators–from macro-economic to micro-economic and from established to esoteric. There is the well-known Libor indicator, but there’s also, for instance, the aforementioned “good looking waitress”–or Vixen–indicator. Here’s how the latter works: Count the number of good looking waitresses–the more there are the worse the economy is.
Although, the authors also tell you that’s a risky trade and, depending on your marital status, a risky practice.
Internet, Investing, Money
Photo courtesy Creative Commons
Depending on who you talk to, the economy, the stock market, and the world as we know it is either in a free-for-all dive into oblivion, or is simply in a correction stage with the continuation of the bull market to continue.
Then there was the S&P 500 downgrading American debt. That should make for an interesting Monday morning for traders. I bet there’s a lot of Maalox sales at groceries stores around Wall Street.
(Here’s a good recap on the situation by Monevator.)
What do I believe about the sitch?
That wouldn’t be any fun. I would much rather show you what some other people–people a lot smarter than me–have to think. Here’s a list of what I’ve been reading about the stock market swan dive and debt status.
Internet, Investing, Money, US Economy
Image courtesy Creative Commons
I remember a guy who used to come in a local watering hole with a tattoo on his forearm in a shaky font that read, “Born to Lose.”
I always thought it was a rather depressing statement and to etch it on your skin is a real statement. Because the guy was big and known to use a pole stick to squelch a lot of questions, I decided not to press him on the deeper meaning of the tattoo. But it made me think…
Are we destined to be losers?
Are we hardwired to do stupid things–like get ugly tattoos and buy stocks in hyped-up companies?
I don’t have the answer to those questions, but Carl Richards at Behavior Gap certainly thinks we have some psychic tattoos on our investment souls that make us born to lose money.
Investing, Money, Success
is either an economic revolution or another foray into the internet-based currency trap.
Technically, it’s a person-to-person virtual currency network. When you use bitcoin, you’re actually receiving protected digital keys that you can use to exchange for goods and services from other folks who accept or use Bitcoin.
If you buy an item, that coin transfers to the next person, just like passing on a dollar at the grocery story.
However, Bitcoin takes a different tack from early attempts at virtual coins.
Business Strategy, Internet, Money
Recent news from the housing sector is not good.
In fact it stinks–stinks worse than ever.
Despite all the best efforts (or maybe because of the best efforts) of the government to prop up the housing market, the price of a home has fallen to its lowest point in nearly eight years. And, yes, that includes points during the “Great Recession”–or the pending “Great Double-Dip Recession.”
That means the housing market is officially in a double-dip recession pattern.
Prices fell 3.6 percent in March. And prices have dropped in all 20 major metropolitan markets, except one.
You’re dying to know which one, aren’t you. Well, if you’re wondering if the stimulus program worked, it sure did. If you’re a homeowner in Washington D.C. Prices rose 4.3 percent.
The market pretty much shrugged off this news. What about you? Should you be worried about a double-dip housing recession?
Yes and No.
Investing, Money, US Economy
After reading this fascinating article over at Digital Trends, I started thinking about how cool it will be to have my own jetpack. Way cooler than a Segway, for sure!
What I like about this idea is that it shows how quickly a wacky idea can become real. Many people may think that the jetpack will be too expensive or impractical, but I think that point of view is shortsighted. After they go on sale, those problems will gradually get solved.
Accelerating Technology, Dreams Come True
Many people think that stock markets are unpredictable and random. It turns out that they are in fact somewhat predictable and not random at all. They exhibit what is known as complex, or emergent behavior.
Emergent behavior comes from the interaction of many actors. The behavior appears to be random and unpredictable, as if it were determined by very complex rules. Yet in fact this emergent behavior is generated from very simple rules. The rules for each actor are very simple; the behavior that emerges from the interaction of the actors is complex.
What does this have to do with trading?
Accelerating Technology, Great Books