There are many who confuse these two: trading and investing. Some even offer trading disguised as investing. Even worse, some try to convince us that we should do one or the other. This clash is mostly motivated by marketing and an effort to increase passive investing fund inflows.
Investing is usually associated with passive (strategic) portfolios. The objective is to realize an annual return that is as smooth as possible. The lower limit to this is investing everything in Treasury bonds and keep them to maturity. Risk is minimized but also return is lower. There is no loss of capital unless the government defaults. The upper limit is investing all the money is stocks. Risk is maximized and so is return, at least theoretically but there are times this fundamental relationship does not hold. A more sensible approach is finding the optimal allocation between stocks and bonds for a given risk profile. For example, the 60/40 portfolio in stocks/bonds is a popular choice with superior risk-adjusted returns that match equity returns longer-term but at a much lower risk, as shown in the chart below:
It may be seen from the above chart that the Sharpe ratio of the 60/40 portfolio is much higher than that of a passive investment in large cap stocks since 1986. More importantly, worst year is -7.25% versus -37.5% for buy and hold.
Now, market price series are not stationary and we have no basis for claiming that the 60/40 portfolio performance will be maintained in the future. However, in the absence of clairvoyant ability, looking at past performance and drawing inferences about the future that are as realistic as possible is the only thing we can do. But this is not even the main point here. The main points are two:
- Given the historical performance of the 60/40 portfolio, all other proposed schemes, including momentum, diversified portfolios, etc, are irrelevant. Actually, they may be problematic due to data-mining bias. The 60/40 portfolio is not a data-mined anomaly; It is a theoretical model of longer-term market performance. The performance of some allocations based on buzzwords such as cross-sectional momentum is probably due to data-mining bias. Therefore, investors who skip the 60/40 portfolio and go for more complicated schemes to gain a few basis points of annualized return may be assuming disproportionate risks.
- No strategic allocation will make anyone rich. The objective of investing is capital preservation with an excess alpha. Therefore, people who already have funds to invest, including those who are already rich, can grow their portfolio at lower risk. Instead, trading is a vehicle for (potentially) becoming rich. And since not everyone can be rich by virtue of limited resources (capital and securities), some become rich but more lose money in trading. Note that financial trading is a zero-sum game while investing in equities is not a zero-sum game.
Therefore, the false dichotomy arises when some market professionals start comparing investing and trading when these two are essentially different endeavors with different goals. Most do that because of competition and they want to convince traders to become passive investors. In a way they have succeeded in recent years with help from central banks but these traders who became passive investors must know that they will never become rich from this particular activity, although it is true that has low probability anyway. However, the probability of becoming rich via passive investing is exactly zero if you are not already rich.
There many different ways of trading the markets that use different tools. Below is a table with chances of success.
|Type of trading||Chances|
|Intraday with charts||Zero|
|Intraday with model||Very low|
|Short-term with chart||Very low|
|Short-term with models||Low|
|Trend-following with charts||Very low|
|Trend-following with model||Low|
|Esoteric methods||Very low|
Although my favorite method is trading rare events, which is described by Nassim Nicholas Taleb in his fantastic book Fooled By Randomness, I do not have a model for that. However, this can be the most lucrative trading method if one has a model for determining the probability of rare events, or is lucky. In essence, a trader can become very rich with the correct application of this method while market exposure is kept to a minimum.
Chartists in any timeframe have no chances to ever make money. I have talked about this several times in this blog. Trend-followers can become rich if they have a proper model but as recent data show, this is becoming more difficult. News and sentiment trading and some esoteric methods, for example based on astrological aspects, also have zero to very low chances because of the low signal to noise ratio.
A viable alternative is short-term trading via a robust model and use of Kelly leverage or Kelly position sizing. However, developing such a model is difficult. Most models based on unique hypotheses (not suggested by the data) about market structure and operation cannot provide any alpha due to arbitrage. Traders must use data-mining and machine learning to identify models suggested by the data and this is a process that is subject to high bias. This is why chances of success are low.
The main idea with short-term models is to identify mispricings in markets and exploit them before anyone else does. There are armies of quants in hedge funds trying to do this, unfortunately (or even fortunately depending on perspective) most do it the wrong way and end up with spurious correlations. But if a model can be identified that has reasonable drawdown, it can be leveraged and generated substantial profits.
Below is an example of a strategy developed by DLPAL (Deep Learning Price Action Lab) that is currently running in Quantopian contest. The strategy was developed in 2013 with DIA ETF in-sample data from inception to 12/31/2009. The chart shows both in-sample and out-of-sample equity performance:
Out-of-sample CAR is 14.1% versus 12.1% for buy and hold but Calmar is 0.64 versus 0.23 for buy and hold. This is quite promising. Note that this system was not rebalanced since 2013.
The year-to-date return of this long/short strategy (but not market neutral) is 21% with a maximum drawdown of -3.31%, as shown in the chart below:
Maximum drawdown is the most important metric given positive performance. If drawdown is small, then the strategy can be leveraged to generate substantial returns.
This is the idea but it is difficult to implement it in general unless one is prepared to put some serious work, while there is possibility of total ruin when leverage is involved. But this is one way of becoming rich trading and to have the luxury of then investing the money in a 60/40 portfolio. Investing versus trading is a false dichotomy.
Trading with models is not easy and there is possibility of total loss of capital and even in excess of initial investment. This high risk translates to a low but real probability of substantial returns. Please read the disclaimer below.
If you have any questions or comments, happy to connect on Twitter: @mikeharrisNY
Charting and backtesting program: Amibroker
Technical and quantitative analysis of Dow-30 stocks and 30 popular ETFs is included in our Weekly Premium Report. Market signals for longer-term traders are offered by our premium Market Signals service. Mean-reversion signals for short-term SPY traders are provided in our Mean Reversion report.