Risk is probably the most interesting part about investing. Understanding what it is, where it comes from, and most importantly, how to measure it, is really a lifelong study. I find it is truly where the art of the craft lies, where the hypothesis is formed for the main architecture of your trading strategy. This usually takes a lot of reading, experimentation and iteration to get right, at least for me.
Stocks of a Feather…
Since I trade only a subset of US securities, specifically stocks and sometimes ETFs, I’m not really diversified when it comes to type of investment or location. What that means is no matter how few or many stocks I own, I’m exposed to the risk of the overall market. For example, the book How to Make Money in Stocks by William O’Neil states that 75% of the movement of a stock is market-driven, while the remaining is related to the perceived value of the stock itself, where even some of that quarter may be due to the strength or weakness of its specific industry or sector. This implies stocks are pretty correlated, especially with their underlying market.
Parker Hannifin ($PH) performance vs the S&P 500. Note how they almost always move in the same direction together, although $PH shows significantly better relative strength. (http://stockcharts.com/freecharts/perf.php?PH,$SPX&n=3816&O=011000)
What’s more gruesome is that you’ll start to notice after a few complete market cycles that when stocks go down, they tend to all go down together. That is, the movement of stocks tend to be more correlated during downtrends; this is especially true during a market crash. Panic seems to spread viciously and readily into the minds of retail and institutional investors, alike. No one is immune! However those whose strategies are rule-driven, especially around mitigating loss of capital during these negative events will likely come out relatively unscathed, as long as they have the will power to follow said rules.
Preserving your capital for the next bull run is absolutely crucial.
NASDAQ and its 200-day MA. Note that except for the 1987 crash, “Black Monday”, there is quite a bit of time spent under to 200-day MA prior to a major downfall. (http://stockcharts.com/h-sc/ui?s=%24COMPQ&p=W&st=1986-1-1&en=2015-12-31&id=p88334107040)
How do we trade around these events? One common and relatively simple hypothesis centers around the use of a what is the 200-day Moving Average (MA). What this does is measure the average of the last 200 days of whatever major market you are trading (I use the S&P 500 for instance). This average is recalculated every day and can be charted along with price. What you will see is that the average will appear to be a very smoothed-out curve relative to the market movement. If you look at a long-term chart as the one above or below, you will see a very obvious pattern:
- When the recent market prices are mostly above the 200-day MA, the market tends to trend upwards, sometimes for years at a time!
- When the recent market prices are mostly below the 200-day MA, the market tends to trend downwards for shorter periods of time, but usually much more viciously
- Most stock crashes tend to occur after the market price has already been under this price for an extended amount of time
S&P 500 with respect to its 200-day MA. (http://stockcharts.com/h-sc/ui?s=%24SPX&p=W&st=1986-1-1&en=2015-12-31&id=p70836100443)
Meb Faber captured it best in his blog, with an excerpt of Tony Robbins interviewing Paul Tudor Jones (one of the most famous hedge fund managers, famous for predicting the 87 crash known as Black Monday). Jones espouses the value of the 200-day average:
[Tony Robbins]: So my next question is, how do you determine the trend?
[Paul Tudor Jones]: My metric for everything I look at is the 200-day moving average of closing prices. I’ve seen too many things go to zero, stocks and commodities. The whole trick in investing is: “How do I keep from losing everything?” If you use the 200-day moving average rule, then you get out. You play defense, and you get out.
Time to Experiment
So let’s put our money where our mouth is and actually measure this. Assuming no commissions, assume we trade the S&P 500 and the NASDAQ over the last 30 complete years.
If we were simply to buy on the first trading day of 1986 and sell on the last trading day of 2015, this is how we would have performed using the classic buy-and-hold strategy:
Buy-and-Hold Strategy Performance Per Market
|Market||Total Profit||Maximum Drawdown||Yearly Rate of Return|
|S&P 500||863 %||56 %||7.8 %|
|NASDAQ||1404 %||78 %||9.5 %|
So while you make some pretty good money over the 30 years, you’ll notice that even for the quieter S&P 500, you still need to suffer through losing over half your money at a certain period of the market. The NASDAQ, although returning 15 times your money, would cause you to suffer through losing over three quarters of your hard-earned cash!
Even if you consider yourself to be extremely tough and emotionally sound, or you’re really good at ignoring your portfolio over the course of decades, you might find yourself traumatized at suffering those kinds of losses. Worse, that maximum drawdown could occur right when you need that money the most, forcing you back to work if you were planning on retiring, or postpone that renovation, or pay back that school loan early!
Now let’s consider using this moving average as a buy/sell strategy:
- If the market is usually bullish above the MA, we buy.
- Otherwise, we sell because the market is deemed bearish.
How would this do?
Simple Moving Average System
|Market||Total Profit||Maximum Drawdown||Yearly Rate of Return|
|S&P 500||588%||28 %||6.6 %|
|NASDAQ||1105 %||49 %||8.7 %|
Noticing something? Although the return has decreased somewhat, the drawdown has decreased even more. A lot more people can tolerate a 28 % to 49 % drawdown over the buy and hold strategy. And the commissions would be almost negligible if you buy the market’s equivalent ETF. It proves that most of the return occurs above the line, which fits the hypotheses noted above while about half the drawdown occurs when the market is below average.
There is also another form of risk that is prevalent in such an on-off strategy, the whipsaw effect. This is when the market you trade moves around the moving average several times in a short time creating many useless buy and sell signals, forcing you take many small losses which can eat away at capital. This can be mitigated by waiting a few days or so before committing to buying or selling after you get a buy or sell signal, however again you will be balancing risk vs. reward, drawdown vs. annual return.
Another thing to note is how the example performances above prove that properly taken risk eventually gives due reward over the long term. Just check out the graph below:
Moving Average (MA) and Buy-and-Hold (BnH) strategies for both the NASDAQ and S&P 500.
So while you can eliminate risk, you will also eliminate potential reward. How you balance that is up to your personality and personal tolerance for losing money. Although the above rule-based system is very crude, and you can get a much better return-to-drawdown ratio by adding just a little bit of sophistication, it seems to clearly illustrate the value of risk and how it can be put to work to make you money as long as you wield it carefully.
If we get back to stocks now, and the notion that three quarters of their price movement is due to the underlying market, we can then further postulate that we should only buy stocks when the market is bullish. If this holds true, your stock purchases should be relegated to only when there is a high probability of your stock going up. Since the market has such a large influence, you can use this as a proxy to the bullishness of the stock. This is the notion of using market-timing to reduce overall risk.
Taking this one level further, you could apply this moving average or any other signal and apply it to stocks themselves. You could establish this as the minimum criteria for even considering buying a stock. Let’s say you want to trade stocks only listed in the S&P 500, but you also only want to consider bullish stocks. In this case the moving average can be used as a filter to eliminate all the bearish stocks. Combine this with market-timing, and you can trade safer knowing you are buying only bullish stocks during bullish market conditions.
Sounds easy? We’ll look next time at how we can apply market-timing and stock filtering to a simple stock strategy.