Asset Allocation and Diversification
What's the best way to minimize your risk while trading? We look at how asset allocation can be combined with technical analysis to ensure a strong trading portfolio.
Last updated
What's the best way to minimize your risk while trading? We look at how asset allocation can be combined with technical analysis to ensure a strong trading portfolio.
Last updated
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The term “asset allocation” describes the money management strategy that designates how capital should be distributed within an investment portfolio. Generally, this involves identifying how much of the portfolio should be distributed into various asset classes or broad investments such as stocks, bonds, commodities, and cash.
Asset allocation aims to optimize the mix of the investments into different asset classes to maximize the return of the investment portfolio while minimizing the potential risk. This optimization is based on your timeframe, risk tolerance, and long-term investment goals. Evidence suggests that certain asset classes perform better or worse depending on economic conditions, market forces, government policy, and political influence. An asset allocation strategy aims to identify these conditions and allocate resources appropriately.
A concept that is closely associated with asset allocation is “diversification.” In practice, these terms are often used interchangeably.
Asset allocation is principally concerned with allocating capital into different asset classes. For example, a typical asset allocation strategy might dictate that your portfolio should have 50% invested in stocks, 30% in bonds, 10% in commodities, and 10% in cash.
Diversification is typically associated with allocating capital within asset classes such as stocks, bonds, and commodities. For example, within the stock allocation of a portfolio, you could allocate 50% to large-cap stocks, 20% to mid-cap stocks, 10% to small-cap stocks, 10% to international stocks, and 10% to emerging market stocks. The concept of diversification involves the distribution of assets within individual asset classes. Because risk is distributed among the asset classes of the overall portfolio, diversification reduces risk within each asset class.
Below is a hypothetical example of asset allocations in a typical vs a diversified portfolio.
Utilizing asset allocation strategies as risk management is not a new concept. The idea of “not putting all of your eggs in one basket” is something we learn as children and has been around for thousands of years. Yet, the term asset allocation did not exist within the investment community until recently. Even before the advent of modern financial markets, people understood that one's assets should be divided among different classes, such as land, ownership of a business, and reserves (cash). That conception of asset allocation as a fact of life stayed relatively unchanged until the middle of the 20th Century.
The diagram below represents early forms of portfolio diversification.
So, what changed to create the asset allocation models we are familiar with today? In 1952, an American economist named Harry Markowitz wrote a paper in the Journal of Finance entitled “Portfolio Selection,” in which he developed the first mathematical model emphasizing volatility reduction in a portfolio by combining investments with different patterns of returns. This paper was the basis for the standard in portfolio management known as “Modern Portfolio Theory.”
Before Markowitz's contribution to portfolio asset allocation, diversification focused on the return and risk characteristics of individual securities irrespective of how the returns correlated with one another. After Markowitz created his mathematical models for portfolio construction, his ideas quickly became accepted in academic circles. Much research was published verifying the benefits of asset allocation, and it rapidly became popular among financial professionals.
In 1974, the Employee Retirement Income Security Act (ERISA) was enacted as a federal law establishing minimum standards for investment allocations in pension plans. After ERISA became law, asset allocation and modern portfolio theory became standard practices for portfolio managers required to be in compliance with the Act when allocating investor capital in pension plans.
Modern Portfolio Theory (MPT) has significantly impacted how portfolio managers construct investment portfolios. The concept of MPT is reasonably straightforward. However, it requires the investor to make several assumptions about the financial markets; additionally, the mathematical equations used to calculate correlation and risk can be somewhat complex.
The basic premise of MPT is simple: by combining securities from different asset classes together that are not highly correlated, you can reduce the volatility of the portfolio and increase risk-adjusted performance. In other words, combining assets that aren't correlated will produce the most efficient portfolio, one that delivers the greatest return for a given amount of risk.
Asset returns don't have to be negatively correlated or non-correlated to provide diversification benefits. They just cannot be perfectly correlated. For example, in the chart below, international stocks (represented by the iShares MSCI EAFE Index) are compared to US domestic stocks (represented by the S&P 500 index). Using the Correlation Coefficient indicator, you can see that the correlation is positive for most of the five-year period. However, it isn't perfectly correlated (a correlation coefficient of 1.0).
There are periods of low correlation and even negative correlation within this period. So, suppose you invested in US domestic stocks and international stocks. In that case, the overall volatility of your portfolio can be decreased since correlation varies enough between the two asset classes to provide meaningful diversification.
The concept of MPT illustrates that adding a volatile asset to a portfolio can still decrease overall volatility if the returns have differences in correlation. This is an intriguing concept—that overall portfolio volatility can be decreased by combining asset classes that have returns with higher volatility.
The assumption is that by combining asset classes that aren't perfectly correlated, when one asset is declining in value, another asset in the portfolio increases in value over the same period. So even if all asset classes are highly volatile by themselves, when combined together in one portfolio, the volatility is reduced.
The following chart shows an extreme example of negative correlation: the US Dollar Index ($USD) compared to the price of Gold ($GOLD) over the last five years. If an investor invested in both these volatile assets, the portfolio's overall volatility would have been lowered significantly due to the negative correlation.
As mentioned earlier, MPT requires that the investor make certain assumptions about the financial markets in order to calculate the theory's potential benefits. The principal assumptions are:
Financial markets are efficient.
Market returns are randomly distributed.
Investors are rational.
These assumptions are necessary for accurately calculating standard deviation and correlation using a normal distribution or bell curve.
Using a normal distribution function (which defines risk as the standard deviation of returns), risk and correlation can be mathematically calculated for individual assets and portfolios. However, if, in reality, markets are not entirely efficient, then asset returns don't necessarily follow a normal distribution, and the correlation and risk calculations used in MPT may be flawed. With the extreme market volatility seen during the “dot-com” bubble of the early 2000s and the financial crisis of 2008–2009, the assumptions used in MPT have been highly scrutinized.
Although the assumptions of Modern Portfolio Theory are most likely flawed to a certain extent, asset allocation using MPT is still a proven method for reducing volatility in an investment portfolio. A simple example using two separate investors can help explain the value of diversification.
Our first investor, investor A, has his entire portfolio invested in just one company's stock. By comparison, investor B has her portfolio invested equally in the stocks of 30 different companies. Both investors carry the risk that the entire stock market could go down and negatively affect their respective portfolios. However, investor A also has risks associated with the one company whose stock he owns. If something specific happens to that one company (i.e., an earnings disappointment, product recall, investor fraud, etc.), investor A could lose a significant portion of his investment.
In contrast, if this exact scenario happened to one of the thirty stocks in investor B's portfolio, it would not be devastating to the value of the whole portfolio. In a worst-case scenario, investor A could lose his entire investment if the company goes out of business. Investor B would only lose 1/30th of her portfolio.
The preceding example identifies the two types of risk associated with investing in the financial markets. The first type of risk is associated with the entire market or systematic risk. Systematic risk affects all of the stocks in the entire market together, as a whole, and cannot be diversified away within that market. For example, if the entire U.S. economy is weakening, it will affect all stocks within the S&P 500 to some extent. Diversifying your portfolio with other stocks within the S&P 500 will not significantly decrease the overall risk in the portfolio because other stocks share the same characteristic of being stocks.
The other type of risk is the risk specifically associated with the individual security, or non-systematic risk. Non-systematic risk is easily diversifiable, as shown by the earlier example of diversification. If you had invested equally in the stocks of 30 different companies, and one of those companies went out of business, the loss to the overall portfolio would only be 3.3%.
Asset Allocation can be applied to portfolio management in different ways. Most asset allocation techniques fall within two distinct strategies—strategic asset allocation and tactical asset allocation.
This is a more traditional approach to asset allocation that utilizes the tenets and assumptions of Modern Portfolio Theory in a passive investment style. The goal of strategic asset allocation is to create a portfolio based on the investor's investment goals and risk tolerances. Changes in the investment portfolio are usually only made when the portfolio becomes “unbalanced” due to fluctuations in the market or the investor's risk/reward profile changes, requiring an adjustment in the allocation.
Making changes to the portfolio when it becomes “unbalanced” is consistent with a “value investing” philosophy that chooses investments due to their perceived low valuation versus an estimated intrinsic value. For example, if the international stock allocation of the portfolio underperforms the domestic stock allocation, then, over time, the international allocation will make up a smaller portion of the overall portfolio because fewer unrealized gains are contributing to the total dollar investment. To reallocate the portfolio and return to the original asset mix percentages, you must sell some domestic stock and purchase more international stock. This is consistent with value investing, as you would buy stock that is out of favor (possibly undervalued) while selling stock that is in favor (perhaps overvalued).
This is similar to strategic asset allocation but with a few noteworthy differences. Like strategic asset allocation, tactical asset allocation is based on the assumptions of Modern Portfolio Theory. However, unlike strategic asset allocation, it uses a more active investment approach involving the concepts of relative strength, sector rotation, and momentum. Instead of reallocating the portfolio when it becomes unbalanced due to market fluctuations, the allocation is purposely over-weighted in market sectors that outperform the overall market.
A tactical asset allocation strategy differs from value investing in that instead of buying underperforming stocks, you purchase or add to positions that are outperforming the broad market. So, in a tactically allocated portfolio based on relative strength, you can be significantly concentrated in particular market sectors. The idea behind this type of asset allocation is to remain somewhat diversified but concentrate more of the portfolio on improving areas of the economy. Studies have shown that when one sector of the economy is outperforming the overall market, there is a tendency for that sector to outperform for an extended period.
The following chart shows the performance of the 11 sector ETFs (representing the 11 S&P 500 sectors) compared to the performance of the S&P 500 index over a one-year timeframe.
The top-performing sectors are Communication Services and Technology. The two worst-performing sectors are Real Estate and Staples. An investor using a tactical asset allocation strategy can use this information to choose investments that outperform the broader market and avoid investments that underperform the broader market.
Even with all of its benefits, asset allocation as a risk management strategy has limitations. Awareness of these limitations will help investors realize when other tools may be used to minimize portfolio risk.
One major criticism of asset allocation is that “black swan” events (unexpected events with catastrophic consequences) seem to occur more often in the financial markets than would be statistically expected if the markets followed a normal distribution. If this is true, using standard deviation as a measure of risk may be misleading, and statistical correlation between asset classes may be distorted. Also, correlation tends to increase between asset classes during a crisis period, which would make asset allocation less useful as a risk management strategy precisely when it is needed most.
Another criticism of asset allocation is that it does not tell the investor when to buy or sell a security. Buy and sell decisions are based on reallocating the portfolio (usually arbitrarily) when it appears to need rebalancing due to the investor's risk parameters, without regard to changing market conditions. Tactical asset allocation strategies can address some of the timing of buy and sell decisions, which are usually not part of strategic asset allocation investment decisions.
Finally, asset allocation as a risk management tool does not address the risk of portfolio drawdown. Drawdown is defined as the minimum value of a single investment or investment portfolio reached following a previous peak in value. During secular bear markets, portfolio drawdown can be significant. Simply spreading one's investments across multiple asset classes may not provide adequate risk protection.
Many technical analysis tools can be used with asset allocation strategies to provide a comprehensive risk management plan for an investment portfolio. Fortunately, utilizing protection strategies available through technical analysis can minimize many of the shortcomings of traditional asset allocation.
One of the most valuable tools available for risk management is the protective stop. Stops are used to exit a position when a predefined profit target is achieved, or a predefined loss limit is reached. Using stops eliminates many of the pitfalls of asset allocation since it minimizes drawdown to a predefined amount, no matter what effect outside influences have on the portfolio.
For example, the correlation between different asset classes became uncharacteristically high during the recent financial crisis. Due to this increase in correlation, traditional asset allocation strategies were ineffective from a risk management perspective. However, protective stops placed at predetermined levels would protect investors from a catastrophic loss.
Stops placed before the severe downturn in the market would have been executed at levels acceptable to the investor ahead of time and provided the risk management needed to keep the portfolio drawdown from being excessive.
The chart below shows how a simple moving average stop loss strategy would have worked well as a risk management tool during the last two major bear markets. This hypothetical example shows the S&P 500 SPDRS (SPY) with a 20-period simple moving average over 20 years. If an investor had sold or decreased his position (stopped out) when it went below the 20-period moving average and then bought it back when it went back above the 20-period moving average, portfolio drawdown would have decreased significantly.
Another valuable use of Technical Analysis is to calculate potential trade entry and exit points before you enter the position. Predefining where entry and exit points should be can provide information on the potential reward and risk of each position. This helps the investor identify attractive trade setups and investment opportunities prior to committing capital.
One question often asked is how much capital you should risk in each position. Using a fundamental asset allocation approach, you would diversify across multiple asset classes based on individual timeframes and risk tolerance. After deciding on an appropriate asset mix, the portfolio would remain fully invested throughout the determined period, regardless of changing market conditions. Using this passive strategy, the portfolio could simply “ride out” the corrections in the market and hopefully regain any losses during market advances.
Many methods are available to determine individual position size for actively managed portfolios. These include comprehensive methods such as the Kelly criterion (or Optimal f) and the Risk of Ruin Formula, or a simple rule of thumb like not risking more than 2% of the entire portfolio on any one position. For example, if you have a $250,000 portfolio, no more than $5,000 should be invested in any one security under the 2% max position size rule.
Exchange Traded Funds (ETFs) are another excellent tool for investors who want to actively manage their investment portfolios. ETFs can be traded like individual securities. However, they contain a basket of securities that provides diversification within the ETF. When choosing ETFs, due diligence is required by the investor since some ETFs are well diversified and others can be highly concentrated in a few positions. Also, some ETFs carry other risks, such as leverage and tracking errors.
One last consideration on risk is deciding how much of the portfolio should be actively traded and how much should simply be allocated to passive, long-term investments. This is why developing a rules-based trading system and maintaining a trading journal to track your performance are essential components of active trading or investing. If you are just starting out, you should only trade the amount of your portfolio you are willing and able to lose. Once you gain confidence as a trader and can quantify your abilities with a bona fide track record, you may begin managing an increasingly larger portfolio segment.
One of the most difficult aspects of trading is managing your emotions and objectively critiquing your own trading abilities. If you cannot consistently outperform a buy-and-hold strategy, actively managing a larger portion of your portfolio is probably not a good idea. If you do not enjoy trading and cannot separate your emotions from your trading, then it may make more sense to let a professional manage your investments or invest passively using mutual funds or ETFs.
Being honest will also help you develop a trading strategy that fits your personality. Each individual trader or investor is different, and while one style of trading may be appropriate for one person, it may not be appropriate for another. A key component to developing a strategy is that it should be easy for the trader to conceptualize and follow the trading plan. Most of all, it needs to be enjoyable for the trader and not conflict with his or her core values.
