How to invest in the stock market like a professional
Unfortunately, we humans are subject to emotional responses that can result in some spectacular investment misadventures. It turns out there is a part of our brain that detects and directs us to avoid danger, and another, separate region, that recognizes and pursues opportunities. In other words, fear and greed control centers. Unfortunately, these control centers don’t talk to each other and, because of the speed at which they react, they don’t negotiate or take prisoners either. These dueling controllers cause us to sell during a scary market drop and then turn around and buy aggressively when the markets rise dramatically.  In the good old days, investment advisers could ignore the phone to help panicky investors ride out a market crisis, but today the same technology that gives us instant access to our investments makes it easy for us to act impulsively on these fear and greed emotions.
We are also subject to behaviors called cognitive biases which are patterns of poor judgment. It’s possible that these behaviors led to a greater chance of survival or reproductive success in our ancestors or maybe our brains just can’t physically process some types of data very well, but they are not helpful to us as investors.
Wikipedia maintains a disturbingly long list of these patterns of poor judgment. Here’s just a few:
- The Bias blind spot is the tendency not to be aware of or compensate for cognitive biases.
- The Bandwagon effect or herd mentality is the tendency to follow the crowd. This causes investors to buy into bubbles when they are near the top and to sell after everyone else has sold on the way down.
- A Confirmation bias is the tendency to seek out conformational information or interpret information in such a way that it confirms what we thought we already knew. This bias tends to lead to overconfidence.
- Loss aversion is the tendency for people to strongly prefer avoiding losses to obtaining gains. This can cause investors to sell off their best performing investments to buy more of their worst performing investments hoping to recoup their losses.
- Outcome bias is the tendency to judge a decision by its outcome instead of on the quality of the decision when it was made.
On top of the emotional impulses and cognitive biases that can cause us invest poorly, there are other decision blind spots which can undermine what appear to be carefully thought out investment strategies.
The Observation Selection Bias
When we mistakenly focus only success stories, we risk overestimating historical investment performance. For example, many beginning investors invest in penny stocks (i.e., stocks that sell for less than a dollar) believing that they will make more money on the winners than they can lose on the losers. After all, the losers can only go down to zero but there is no limit to how far the winners can go up. However, they are almost always basing this assumption on tests with stock data that has a survivorship bias. 
In other words, they have selected what they assumed was a random sample of penny stocks from 5 or 10 years in the past that survived until the present, and concluded that they could have made a considerable amount of money. Unfortunately, there was no way to have known at the time the selection was made that the stocks selected would survive 5 or 10 years into the future.
Unfortunately, this observation selection effect undermines decisions on a large scale every day. Everyone knows that, over long periods of time, stocks have outperformed bonds. This is the basis for the investing strategy known as buy-and-hold. An observation selection effect bias is at least partly responsible for this apparent superiority of stocks. Although most historical stock data favors owning stocks, the data is typically from the American and British exchanges, which have been unusually stable. If we examine all stock exchanges, we see that wars, political upheavals, and currency collapses have actually destroyed quite a few of them. From 1921 to 1996, while U.S. equities returned about 5 percent, all other equities from 39 different markets had returns of only about 1.5 percent. 
Moreover, if we look at a longer time frame, the unusual stability of the American and British stock exchanges is even more dramatic. Examining financial crises going back eight centuries, researchers have observed that serial defaults (i.e., a succession of defaults, one after the other) are actually the norm for developing countries, and these defaults can and have led to financial crises worldwide repeatedly. Although one or two decade long lulls between defaults were not uncommon, each lull was always followed by a new wave.  In fact, market crashes have described by some researchers as “a hearty perennial” due to the regularity of their occurrence over long time periods. 
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The Data Mining Bias
Also known as data-snooping, a data mining bias occurs when an investigator proposes a hypothesis after noticing a correlation in historical data instead of postulating a hypothesis first and then testing it on unseen historical data. Typical tests of statistical significance assume that the data has not been seen prior to the test. If this is not the case, a model may appear to be strongly supported by the data when, in fact, it is just a chance correlation and it doesn’t hold up on new data.  In developing a trading or investing strategy, a developer will always have previously examined historical data or, if using their own experience, they will have already noticed some correlation they want to take advantage of. When they test their strategy on historical data, the strategy is likely to do well, but, going forward, the correlation probably won’t hold up. 
Passive Investing Strategies
The average investor needs a fundamentally sound, non-biased investing strategy that they can commit to stick with even when their control centers are attempting mutiny. Strategies based on the unusual stability and performance of the U.S. and British markets (for example, long term buy-and-hold) are not supported by the aggregate of stock data from all markets over long time periods. Strategies based on fitting models to historical data such as “stock picking” or mechanical trading systems are prone to data mining biases which, in some cases, make them worse than doing nothing. As a result, the strategy used by passive investors (investors who are not frequently churning their investments) is called asset allocation, which relies on diversification among uncorrelated assets and rebalancing to generate returns rather than attempting to predict future prices.
To understand asset allocation, it is helpful to understand the sources of risk in a portfolio because, in the end, it will be desirable to spread our risk out over all of these buckets. There are typically said to be four, somewhat uncorrelated, market risk factors that determine the typical portfolio’s risk: 
1.) Equity risk is the risk that stock prices will drop.
2.) Interest rate risk is the risk that interest rates will change against you.
3.) Currency risk is the risk that foreign exchange rates will change against you.
4.) Commodity risk is the risk that commodity prices will change.
The Classical Mean Variance Diversification Theory
Harry Markowitz mathematically formalized the observation that if you combine a number of assets that aren’t correlated you can reduce your portfolio risk.  From this he defined an optimal portfolio, in terms of risk to reward at a given level of reward, called the mean-variance portfolio. The mean-variance portfolio for a particular investor will depend on the investors risk tolerance and the historical returns and variance of returns for each asset in the portfolio. An example of an asset combination is the stocks and bonds portfolio which is typically recommended by investment advisors for retail investors. By adjusting the ratio of stocks to bonds (for example, 70% stocks with 30% bonds or 50% stocks and 50% bonds) one can adjust the amount of risk (sometimes referred to as variability of returns or volatility) of a portfolio and the risk can sometimes be reduced dramatically for only a small performance penalty.
Before continuing, I should mention that studies have shown that somewhere around 90% of the variability of portfolio returns is determined by asset allocation.  The variability of returns should not be confused with portfolio’s average returns. Average returns are almost entirely dependent on the asset allocation because portfolio managers, on average, don’t beat the market.  Typically, an asset allocation that has made more money in the past will also have had a higher volatility.
When uncorrelated assets are combined in a portfolio, the ratio of each asset to the total tends to drift as some assets will almost certainly outperform others and alter the risk characteristics of the portfolio. To maintain their risk protection, the investor will need to periodically sell off some of the outperforming assets to buy more of the underperforming assets. Unfortunately, Markowitz didn’t specifically address how to do this. One study examined the effect of different rebalancing schemes on a 50% stocks and 50% bonds portfolio and found that monthly rebalancing was slightly better than quarterly and only a tiny bit better than yearly over the 1968 to 1991 time period. Rebalancing based on thresholds (for example, any one equity exceeds +/- 5% of its target) were roughly equivalent to quarterly rebalancing.  A theoretical study found that periodic and threshold rebalancing strategies perform similarly as long as they are performed more frequently than every two years or have tolerance thresholds less than 10% (for a two asset portfolio anyway).  So, while rebalancing is needed in order to keep a portfolio’s risk/reward balance intact, the exact methodology does not appear to be critical.
Under some conditions rebalancing significantly increases returns beyond the geometric mean of the individual asset returns in a portfolio. This “rebalancing bonus” is most pronounced for assets that are volatile and negatively correlated. When highly volatile and weakly correlated assets are present in a portfolio, it may be more beneficial to use a threshold strategy to capture this bonus. 
Adding Gold to a Portfolio
Many investors include some gold in their portfolios, although typically no more than 10-15%, as a means of increasing the diversification of their holdings or as a safe haven (i.e., to add diversification in times of extreme market stress). Gold is also thought of as a hedge against inflation and currency fluctuations. As the dollar goes down in value relative to other currencies, or inflation increases, the price of gold (in dollars) tends to go up. Additionally, gold may add some protection to stock holdings against black swan events (infrequent, unexpected, negative market events such as market crashes, currency devaluations, wars or natural disasters) albeit only for a limited time historically (so investors should consider rebalancing within a few weeks of the event).  The addition of gold to a stocks and bonds portfolio has historically increased returns and reduced risk. 
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The Talmud or 1/N Portfolio
The Talmud is a record of rabbinic discussions or debates on a wide number of topics, one of them being an asset allocation strategy recorded around 1500 years ago which is known as the 1/3 rule, or, more generally, as the 1/N rule for N assets.  The original asset classes suggested were land, business interests and reserve funds (probably meaning coins). A modern version of the 1/N portfolio which has been reportedly used successfully holds real estate investment trusts, stocks and U.S. bonds.  In spite of it’s seemingly naïve nature, the 1/N rule has been found to outperform sophisticated mean variance strategies on the majority of real data sets studied, especially when N is small.  The reason for this may be that the strategy doesn’t assume that past return volatility predicts future volatility, unlike the mean-variance method which tries to predict the best allocation using historical prices. The mean-variance method also assumes that returns follow a gaussian distribution – when we know for a fact that they don’t.
The Permanent Portfolio
The permanent portfolio, first published by Harry Browne , is a specific 1/N portfolio which builds on the stocks/bonds/gold portfolio by adding cash as a forth component. Basically, the underlying theory is that one should hold four equally weighted assets – gold, cash, stocks, and bonds- which tend to move in different directions during different stages of the four economic cycles: inflation, deflation, prosperity and recession. During times of inflation, gold tends to do well, during deflation bonds tend to do well, during times of prosperity stocks soar, and during recessions, cash is best. This portfolio has returned about as much as the overall stock market in terms of returns in the 1974 to 2008 time frame but with dramatically lower volatility,  perhaps due to the remarkably low correlations of its components.  The strategy certainly worked well recently for Icelanders – whose country defaulted on its debt in 2008 – by returning a profit of 28% while the Icelandic stock market suffered a 90% loss.
Diversification Beyond the Permanent Portfolio
There are numerous other real assets that can be used to diversify a mean-variance or 1/N portfolio beyond the assets previously mentioned. Examples of real assets are art, antiques, rare coins, land, and commodities such as oil, timber, rice, industrial metals, livestock, etc.  Because of the difficulty of buying and selling small amounts of many of these assets, they are typically only used by very wealthy investors. Beginning investors should be wary of commodity exchange traded funds (aka ETFs) because they may not track the underlying commodity futures prices very well,  and there is an unfortunate history of price manipulation of some of the underlying assets. 
Many sophisticated investors also hold what I call conviction stocks. A conviction stock is one that you have high expectations for in the long run for a good reason. You may have some (legal) insider information (you may work for the company or work for a supplier, for example) or you may have done research and have concluded that the company’s prospects are potentially spectacular. Best case, the price of the stock will be driven primarily by something other than the general market and will thereby add some additional diversification to your portfolio. Most advisors would probably recommend that no more than 10 to 15% of a portfolio should be in conviction or employer stocks because the risk will begin to dominate the potential rewards beyond that.
Which investment strategy is best?
The “best” strategy depends on the investor. How much risk the investor is willing to take, how much money they have to invest, and how well the investor can control their emotions during tough times, among other things, determine which strategy is the best. And most people don’t even know how much risk they can stomach until that day of wild swings arrives.
The best investors probably aren’t as much smart as they are disciplined.
The problem with unconventional portfolios like The Talmud and the Permanent Portfolio is that most investors will bolt after a couple of years of underperforming the market – which is certain to happen.  Non-conventional portfolios are probably utilized primarily by wealthy investors whose advisers have taken the time to thoroughly educate them and who are willing to accept sub-market returns for years in exchange for the likelihood of preserving their wealth when the inevitable financial crisis erupts. 
Should you get an investment advisor?
Small investors who are self-educated and disciplined can also easily take advantage of the portfolio strategies on this page without an advisor. Investment advisers have been found to, on average, push investors into funds that benefit the advisor, not the client.  And even if they see a crisis coming, they may not be able to warn you: 
Bernstein, the chief strategist, has actually been bearish for much of the past decade. Given his recent disposition toward market pessimism, I asked him why he didn’t tell Merrill’s clients to dump their equities seven months ago. “I said it as best as I could within reasonable professional standards,” he said. “I’m not going to yell ‘Sell, sell, sell!’ I’m not going to go out and be irresponsible.”
- Investment Portfolio Examples
- Effect of Adding Gold to a Portfolio
- Example of a Talmud Portfolio
- The Permanent Portfolio
- Adding Growth Stocks to a Portfolio
R. Gibson, Asset Allocation, 4th Ed, McGraw-Hill; 4th edition (December 20, 2007)
W. Bernstein, The Intelligent Asset Allocator: How to Build Your Portfolio to Maximize Returns and Minimize Risk, McGraw-Hill; 1st edition (September 22, 2000)
 D. Lenick, K. Jordan, Financial Intelligence: How to Make Smart, Values-Based Decisions with Your Money and Your Life, FPA Press, April 21, 2010
 R. Kan, G. Kirikos, Biases in Evaluating Trading Strategies, Nov. 1995 [pdf]
 P. Jorion, W. Goetzmann , A Century of Global Stock Markets, Yale School of Management Working Paper No. F-55, 1996
 C. Reinhart, K. Rogoff, This Time Is Different: Eight Centuries of Financial Folly, Princeton University Press; 1st Edition (September 11, 2009)
 C. Kindleberger, R. Aliber, Manias, Panics and Crashes: A History of Financial Crises, Sixth Edition, Wiley, 5th edition (October 4, 2005)
 J. Ioannidis, Why Most Published Research Findings Are False, PLoS Medicine 2(8) 2005
 Wikipedia Market Risk
 Markowitz, H.M., Portfolio Selection, The Journal of Finance, 7 (1): 77–91, March 1952
 G. Brinson, B. Singer, G. Beebower, Determinants of Portfolio Performance II: An Update, Financial Analysts Journal, May/Jun 1991; 47, 3
 R. Ibbotson, The Importance of Asset Allocation, Financial Analysts Journal, Vol 66, No. 2
 Robert D. Arnott and Robert M. Lovell, Rebalancing: Why? When? How Often?, The Journal of Investing 2, No. 1 (Spring 1993): 5.
 Y. Si, The Benefits of Portfolio Rebalancing and How They Can be Achieved, Feb. 27, 2009 [pdf]
 W. Bernstein, The Rebalancing Bonus: Theory and Practice, efficientfrontier.com website
 D. Baur, B. Lucey, Is Gold a Hedge or a Safe Haven? An Analysis of Stocks, Bonds and Gold, The Financial Review, Eastern Finance Association, vol. 45(2), pages 217-229, 05
 iShares.com Gold Benefits Calculator
 R. Duchin, H. Levy, Markowitz Versus the Talmudic Portfolio Diversification Strategies, The Journal of Portfolio Management Winter 2009, Vol 35, No. 2, pp 71-74
 J. Grote, The Talmud Strategy: A couple rely on ancient principles to build a thoroughly modern clientele , Financial Planning, Sept. 1, 2001
 J. Tu, G. Zhou, Markowitz Meets Talmud: A Combination of Sophisticated and Naïve Diversification Strategies, April, 2009
 H. Browne, Fail-Safe Investing: Lifelong Financial Security in 30 Minutes, St. Martin’s Press, 2001
 G. Considine, What Investors Should Fear in the Permanent Portfolio, Advisor Perspectives website March 22, 2011
 Crawling Road blog, December 22, 2008
 W. Bernstein, Wild About Harry , efficientfrontier.com website 2010
 European Permanent Portfolio blog, June 16, 2010
 Real Assets and Inflation Hedge Investing, E. O’Donnell, NEPC, LLC [pdf]
 P. Robison, A. Loder & A. Bjerga, ETFs Imperil Investors as Contango, Pre-Roll Conspire, bloomberg.com, Jul 22, 2010
 W. Cohan, A Conspiracy With a Silver Lining, The New York Times, March 2, 2011
 S. Mullainathan, M. Noeth, A. Schoar, The Market for Financial Advice: An Audit Study, NBER Working Paper No. 17929, Issued in March 2012
 J. Goldberg, Why I Fired My Broker, The Atlantic, May 2009