NOTE: Quantext is not a registered investment advisor.  No information on this website should be taken as advice to buy or sell any asset.  Any and all information obtained from Quantext is on an "AS IS" basis.   Newsletter and Forum We have an email newsletter that will alert you when new articles are published  To subscribe, email to: news-subscribe@quantext.com Note: we have been having trouble with SPAM filters on the newsletter, so you may want to check back here periodically We have a discussion forum on the use of quantitative methods for portfolio planning Quantext Discussion Forum   Introductory Materials We have a validation study that demonstrates the ability of QPP's portfolio analysis in a blind (out-of-sample) test over nine years.  The analysis was performed by a third-party analyst, Peter Manhardt, and we wrote the analysis together. For a general overview of quantitative methods in portfolio planning and how QPP has proven its worth, see this article Here is a list of Frequently Asked Questions (FAQ) About Monte Carlo Simulation for Financial Planning For two articles that cover a broad-based perspective on portfolio planning, see these: The Humble Arithmetic of Portfolio Management and Choosing Your Portfolio Risk Tolerance Or, for some discussion of the basic statistics of portfolio planning: Personal Portfolio Management This monograph covers basic statistics for portfolio management applications.  Introduces Monte Carlo tools and explains why they are important.  This is a very basic overview.  For more advanced topics, see the articles and white papers below.   Articles and White Papers The Volatility Shock of 2008 The enormous rise in volatility in 2008 was predicted by a number of reliable models well before it occurred--including our own.  This article links to these leading resources (the original articles dating back well before 2008) and discusses how the proposed solutions worked out.  Portfolio planning that accounted for the probability of a big increase in volatility provided considerable porotection to investors--including those who stayed long in the market.  The Road Ahead This article, written in March 2009, is my quantitative analysis of where things are heading in the near-, intermediate-, and long-term. Seeing Risk Ahead While it has become popular to blame risk management models for the terrible returns many funds experienced in 2008, our research shows that good risk management models added considerable value in flagging risky strategies. What is Diversification Worth? In this article, I compare estimates of the amount of additional return that effective diversification can provide.  The benchmark against which this is judged is a mix of domestic stocks and bonds.  Using sources including David Swensen of Yale and Ibbotson, as well as our own model, I conclude that really well-designed portfolios can provide a diversification benefit as high as 2.5% a year.  Individual stocks can improve this further, not least because of the less-than-ideal market cap asset weightings in major stock indices.    Risk Management Lessons from Bear Stearns Using the criteria suggested in my article below, I examined the evolution of Bear Stearn's projected worst loss, as calculated by QPP.  QPP projected a massive increase in default risk for BSC by the end of January of 2008, well before the actual collapse in Mid-March.  Investing in Individual Stocks and Default Risk Investors are often told that individual stocks are 'too risky' because of the chance that a company will go bankrupt.  I wrote and published this article prior to Bear Stearns collapse.  Quantext Portfolio Planner's risk outlooks capture very much the same information as Moody's credit ratings--as shown in this article.  These results explain how individual investors can manage the default risk associated with owning individual stocks.  Portfolio Theory Vindicated It was more than two years ago that I published my first article on modifying a standard asset allocation using Quantext Portfolio Planner to maximize return by diversifying more effectively.  I revisit this portfolio to see how it has performed.  As the model suggested, this portfolio has generated more return, with less risk. Two articles on Seeking Alpha by Phil DeMuth A Practical Demonstration of the Value of Portfolio Theory (Part 1)  and Global Giants and Diversifiers to Supercharge a Portfolio (Part 2) These two articles take model portfolios from the recent book with Ben Stein that were designed using QPP and examines how they have performed during the market decline.  The first article shows slightly modified asset allocations and the second article shows a more radical all-equity portfolio.  The results speak for themselves. Black Swans, Portfolio Theory and Market Timing The responses to my article on 'Black Swan' events suggested that this topic was worth exploring further.  This article explains the origins and meaning of 'Black Swan' concepts in finance and how this relates to asset allocation and market timing.  In particular, this article explains that while there are unpredictable events in the world (the black swans), and they can be very important, this does not detract from the fundamental utility of a good quantitative portfolio model.  This is a long review article which includes many links to related articles. Insight on Portfolio Planning from Yale's David Swensen Analyzes David Swensen's statements about the goals for Yale's endowment in the context of portfolio planning methods.  Mr. Swensen's stated goals for the Yale portfolio are remarkably consistent with analysis from Quantext Portfolio Planner that suggests that the best that an investor should plan for is roughly a 1-to-1 ratio between expected return and annualized portfolio volatility in a well-diversified portfolio. Black Swans, Real Estate and Financial Stocks Nassim Taleb's book, The Black Swan, has gained great notoriety for asserting that financial modeling is a massive failure.  My assertion in this article is that he does not do good financial models justice.  I show that a good portfolio tool (our QPP) predicted the scale of losses that we have seen in real estate and financial stocks ahead of time.  This is easily reproduced by any user of our software, using all default settings.  Mr. Taleb is no doubt correct that quantitative models cannot predict the odds of events like 9/11, but they certainly can predict events at the scale of the sub-prime meltdown.  To ignore this powerful capability of portfolio models is to miss the ability to plan with the risk of extreme events in mind.  Computer Models for Retirement Planning This article is more of a thought piece on computer modeling as part of the financial planning process, with a focus on the Pension Protection Act of 2006. Outlook for Some Sector ETF's Quantext Portfolio Planner projects risk and return for specific holdings.  QPP's projections can be compared to trailing performance to give a sense if an investment has been generating unsustainably high returns over recent years.  We show examples of this approach for a range of broad sectors in this article.  Getting The Most Return for Your Risk, Part 2 The critical issue that resides at the core of all of portfolio planning is how to build a portfolio that is likely to deliver the most return for a given level of risk. A related question is as to the realistic bounds on return that can be planned for on a forward-looking basis. Every investor will benefit from having a portfolio that provides solid diversification benefits across asset classes, but what is the best that we can realistically plan on?  This article compares analysis from Quantext Portfolio Planner (QPP) to research from Ibbotson Associates and Bridgewater.  The topic is determining how much return a well-designed portfolio can realistically be projected to provide going forward.  There is remarkable agreement between QPP, Bridgewater, and a series of models developed at Ibbotson.  Making Sense of Trailing Performance This article is inspired by a question that I received from a trial user of our portfolio planning software. This person likes a mutual fund called the American Funds Capital World Growth and Income Fund (ticker: CWGIX). This fund, currently rated five stars by Morningstar, has generated annualized returns over the past five years (through8/31/2007) of 20.7% per year. This is, as it name implies, an internationally focused fund, and world stock indices have done very well over this period---but this fund has out-performed the indices against which Morningstar benchmarks it, and this is the cause of the five star rating. Fair enough. The investor was analyzing this fund as part of a portfolio using Quantext Portfolio Planner, a planning tool and he felt that he had found a paradoxical result in QPP’s forward view. The issue with this particular fund bears on the far larger issue of how to treat trailing performance of a fund. Value of Individual Stocks in a Fund Portfolio Let’s start from the premise that you understand that most investors will underperform the S&P500 in their investing because they (1) pay too much in fees, (2) chase hot funds and asset classes, and (3) do not carefully manage their tax exposure. Given this, John Bogle advocates that index funds are the best solution. Fair enough. For the average retail investor, buying some index funds will probably produce better results than he/she is currently getting. That said, I believe that this still leaves us a long way from the idea that simply buying the S&P500 to gain our equity exposure is the best approach.  Our analysis suggests that there is a great deal of value in meaningful allocations to individual stocks. Some Core Themes for Portfolio Planning This article looks at a series of important themes raised by Rob Arnott that also relate to articles that we have written.  Real Estate: How Far, How Fast? Does Tracking Error Matter? Estimating Future Stocks Returns Portfolio Management in Increasingly Volatile Markets Rethinking Rebalancing Judging Fund Performance: Part 2 Judging Fund Performance: Part 1   Investing in China China seems to have captured the imagination of investors, and with good reason.  The flip-side of the enormous potential in China is the levels of volatility that Chinese markets have had historically and also the high volatility that the options markets imply will eventually manifest itself again.  Asset Allocation and the All-ETF Portfolio This article shows a model portfolio that is made up entirely of ETF's.  The discussion focuses on key issues in designing an all-ETF portfolio.  Projecting Portfolio Return and Volatility We routinely test how the forward-looking projections for risk and return from QPP and QRP fare in a range of different market conditions.  This article shows a new set of tests and compares this round of tests to earlier validation studies.  These tests can be reproduced by users of QPP and QRP.  This new series of tests examines risk and return projections for a portfolio made up of twenty stocks over seven three-year periods.  The Cost of Volatility Many investors do not understand how the volatility of their investments really impacts their long-term compounded gains.  This article discusses this issue--commonly known as 'volatility drag' or 'risk drag' The Do-It-Yourself Market Neutral Portfolio A common topic in portfolio management is 'market neutral' investing, which means developing portfolios that are not driven by the movements of the market as a whole.  While it is most common to build a market neutral portfolio using both long and short positions, you can build a remarkably good market neutral portfolio by simply buying a set of stocks that have low correlation to each other and to the broader market.  This article describes how this might be done and how to test such an approach. The Income Glide Path: Implications for Asset Allocation While most articles on portfolio allocation focus on a highly simplified model for rates of investment and subsequent withdrawal from a portfolio in retirement, the specific details of this process can be very important.  QPP and QRP can now incorporate customized rates of investment and income in conjunction with Monte Carlo analysis.  Our analysis demonstrates the relationship between an investor's life cycle of investing and the best asset allocation to meet his or her needs. Why Volatility and Beta Matter There is widespread complacency about the risks associated with stocks and this is very dangerous.  Volatility and Beta are only statistics, but they are important statistics.  People who ignore these statistical measures are, I believe, doomed to repeat the past--and this article explains the reasoning. Stock Portfolio to Weather a Volatility Shock This article, a follow on the one below, shows a portfolio of stocks that is well-positioned to deal with a substantial increase in market-wide volatility. Preparing for a Volatility Shock There is a broad consensus that volatility in global markets is due to a rise--really just a reversion to normal historical levels.  This has important implications for asset allocation and portfolio management. Investing in a Greenhouse World There is considerable evidence that broad regulation of Greenhouse Gases (GHG's) is gaining momentum.  This article discusses the issue and how a portfolio can be positioned to be ready for this eventuality. Google Employee Stock Options - Part II After my first comments on Google's stock options program, I got a lot of interesting feedback--overwhelmingly positive and seeking more information on the broader issue of how to consider stock options in the context of portfolio management.  This article addresses some of the core questions. Investing in Real Estate: REIT's and Your Home The party in real estate seems like it is over.  This article is written to provide a broad overview of the returns available to homeowners and how to reconcile the high returns that we have seen in both residential and commercial real estate over the past 5-10 years with a long-term view.  The evidence suggests that we will see considerably lower long-term returns from real estate and also that the high returns that homeowners have achieved through the use of financing to leverage their returns also carry considerable long - term risk. Note: Bill Gross just came out with a new essay addressing many of these topics, too.  Google Employee Stock Options: A Case Study This article is a review of Google's new program that allows employees to sell their stock options grants via an internal auction.  The buyers are approved financial institutions.  While this program has been lauded by the press as a perk for employees, I feel that there are some interesting questions raised.  Perhaps the most important issue is whether the employees know enough about the inherent value of their options to make their best choices in this regard.  When employees sell their options in this market, they are often going to be selling at a substantial discount to 'fair value' and Google stands to benefit from this.  This case has important implications for employees who own stocks options and for investors in firms that offer options as part of compensation.  Looking Forward, Looking Back: Prospects for Selected iShares ETF's Morningstar ratings are predominantly a measure of trailing performance.  Most retail investors choose their investments just this way: they look for whatever has been out-performing.  This approach leads to poor returns.  This does not mean that investors should be contrarian, however.  Some asset classes that have delivered high returns can be expected to do so in the future.  This is what happens when you invest in a high risk / high return asset.  When an asset's returns exceed what can reasonably be expected based on the risk/return profile of that asset, it is a good idea to be concerned.  This article looks at a series of iShares ETF's in this light.  Because a number of these funds are sector/index-specific, this analysis also provides an outlook for some broad sectors.  How Wealthier Americans Invest A recent survey of 1,000 investors with $1 Million or more in invested assets (average of $3 Million) provides very interesting insight into how the wealthier tier of Americans invests.  The broad features of the asset allocations of these wealthier Americans are consistent with the types of allocations that Quantext Portfolio Planner suggests can generate the highest returns relative to risk for the predominant age ranges of investors in this survey.  Generating Meaningful Outlooks for Portfolio Performance This paper demonstrates how a Monte Carlo model can generate forward-looking portfolio outlooks that add substantial value in planning.  In our previous article (below), I showed that Quantext Portfolio Planner generates good projections for volatility.  In this article, I show how QPP generates good predictions for the average return and risk on a portfolio of stocks for a series of three-year periods from 1972-2005.  The predicted portfolio risk and return is shown to be far superior to generating expected returns and risk from trailing historical performance.  This article also shows that QPP balances between long-term risk/return characteristics of capital markets and more recent data.  QPP's projections are not biased towards heavier allocations to assets that have recently out-performed.  Foreign and Domestic Market Risk: Outlook from February 2007 One of the largest factors that determines whether an investor will be able to reliably draw long-term income against his or her portfolio is portfolio volatility.  This means that planning tools must generate realistic forward-looking projections of market volatility.  Quantext Portfolio Planner and Quantext Retirement Planner generate these forward-looking projections of volatility for portfolio components and for the total portfolio.  We benchmark these tools' projections against the best available measures.  QPP and QRP are in agreement with the 'smart money' that volatility is going to be considerably higher in coming years.  This has major implications for all investors, but especially for Baby Boomers. Looking for Value in Active Management This article is a follow-up to the one below, and looks at how an investor can attempt to calculate the value of active management in a fund.  This is a real challenge when many funds have mixed 'styles' and can include asset classes that are outside the basic index against which they are benchmarked.  When a fund that is benchmarked against the S&P500 includes foreign assets, for example, the fund may appear to generate market-beating performance.  This type of 'alpha' is really not worth paying for, however, because it is available to any investor for free--simply by diversifying.  The real 'alpha' that investors in actively managed funds are looking for must go beyond this.  Financial Screens and Fund Performance Measurement While many investors and advisors narrow down the universe of potential investment opportunities using 'financial screens,' institutional investors look at what is called performance attribution.  In this article I analyze a portfolio of funds that are in the top 20% of their style categories over the last ten years (determined from the use of financial screens).  To examine whether this portfolio of actively-managed fund shows manager skill, I apply a form of performance attribution using Quantext Portfolio Planner.  The performance attribution shows that these funds have performed no better than an equivalent basket of index ETF's on an absolute and risk-adjusted basis.  Further, a forward-looking analysis shows the same result.  This result demonstrates why the 'smart money' uses performance attribution.  Foreign Index Funds as Defensive Assets It is common to read analysis that suggests that foreign investing will provide protection against a broad domestic decline in the stock market.  This article uses Quantext Portfolio Planner to analyze this concept from a quantitative standpoint.  Sadly, broad foreign index funds do not provide nearly as much cover as many investors believe.  The (Irrational) Economist Just when you think the world can get no less rational, there is further proof.  This is a short note pointing to what I see as a case of terribly flawed investment reasoning from a source, The Economist, that I expect to know better.  Beat The Market This article looks at the evidence against efficient markets and shows how investors can reasonably expect to out-perform the broad indices using forward-looking asset allocation strategy.  The arguments against efficient markets are fully consistent with modern financial theory.  The 'No Direction' Portfolio This article analyzes a portfolio submitted to us by a user of Quantext Portfolio Planner.  The portfolio focus is on making a portfolio that is not sensitive to swings in broader U.S. markets.  Using both historical and forward-looking Monte Carlo analysis, this portfolio is remarkably insensitive to what the broader market does. Getting to the Right Level of Portfolio Risk This paper examines how to choose the right balance of risk and return for long-term planning and related issues.  Discusses 'target date' mutual funds.  Unique Diversification Benefits of Utilities Electrical utilities have some very special qualities in terms of diversification.  These effects are the result of physical, financial, and regulatory properties of electricity and natural gas and their transmission / transportation. Getting The Most Return For Your Risk As investors think more critically about asset allocation, it is useful to have a sense of the realistic limits to the amount of return that can be generated for the levels of risk that individual investors will want to bear.  This article discusses an article by Ray Dalio, the founder of Bridgewater Associates, in conjunction with a range of analyses using Quantext Portfolio Planner.  Mr. Dalio agrees with the conclusion that I have drawn from a series of forward-looking analyses that it is possible to develop a strategy that will can be projected to generate about 10% per year if you limit risk to an annualized standard deviation in return of around 10%.  This 1-to-1 ratio between average annual return and standard deviation (in this risk range) is, I believe, the best that investors can realistically plan for.  A Quantitative Look At Stock Picking Lists This article looks at expert stock picking lists from a quantitative perspective. Safe Portfolio Withdrawal Rates: Beyond The Four Percent Solution Many investors have run across the proverbial 'four percent solution' that suggests that you can draw an inflation-adjusted annual income from your portfolio in retirement that is equal to 4% of the value of your portfolio in the year that you retire.  If you have a portfolio worth $1M, you can draw $40K per year and index that up with inflation and thereby provide reliable income for the rest of your life.  This results when you account for portfolio risk and you assume that you are simply investing in a portfolio that is 60% in a stock market index fund and 40% in a bond fund.  I believe that you can do a lot better than this type of simple-minded portfolio by being more strategic in your asset allocation and planning.  This paper discusses why it is possible to do better and how to determine a more realistic withdrawal rate for your situation. Foreign Investing and Diversification Lessons from Berkshire Hathaway Warren Buffett has often espoused gaining international exposure with U.S. companies that have a substantial amount of their revenue from foreign sales in local currency.  When I recently read an article about Berkshire Hathaway loading up on some Johnson and Johnson stock (see paper below), I wanted to look at the impact of this strategy.  Low-Beta Portfolio Strategies Many signs point towards slowing in the broader U.S. economy.  While many investors are trying to insulate their portfolios from sensitivity to the U.S. equity markets by investing more heavily in foreign stocks and commodities, it is possible to build a model that is remarkably insensitive to swings in the U.S. stock market using a judicious selection of solid U.S. stocks.  We show a portfolio that has generated remarkably stable and good returns during the past several years, as well as during the recent bear market.  The key is to combine stocks with low correlations to one another and to the market as a whole.  Can You Afford to Underestimate Risk by 50%? This article reviews the types of assumptions made in standard portfolio planning applications and how these assumptions impact what these tools can tell you.  Users need to understand that the different tools may be appropriate for some portfolios but not for others.  Targeting Low-Correlation Assets for a Portfolio Discusses the concept of correlation and how investors can thinkg about correlation and effectively exploit correlation effects in building well diversified portfolios Perils of Using Asset Allocation Tools This article discusses the potential risks in using planning and asset allocation tools.  Some tools use such simplistic representations of assets -- by lumping holdings into generic asset classes -- that the results from the models can badly mis-represent actual diversification across holdings and can substantially mis-state portfolio risk levels.  We explore this issue in the context of the asset classes used in a standard model that is used by many investors. Risk Outlook for Country-Specific Funds Consensus opinion is that future prospects for growth are higher outside of the U.S. than in domestic markets.  Emerging markets, in particular, have seen an enormous rally over the past several years.  As funds have emerged that focus on specific countries, it is more and more important to be aware of country-specific risks.  This article provides some background and shows projections and historical data on country-specific risks. Limited Value of P/E Ratios in Choosing ETF's While screening stock selections on the basis of price-to-earnings ratios has some value, P/E ratios are of very limited value in selecting ETF's for two reasons.  First, P/E ratio calculations for ETF's are not standardized and, depending on the components of the ETF, can be very deceptive--typically being biased so as to make P/E ratios look lower than they really are.  Beyond basic issues of calculation, P/E ratios don't necessarily tell you much about the underlying value.  This article examines a series of low P/E ETF's provided via a Yahoo! Finance screen.  These ETF's all have P/E's more than 20% below the market as a whole.  Running these ETF's through Quantext Portfolio Planner (QPP) suggests that these funds do not look under-valued at all.  Monte Carlo Analysis of Major Berkshire Hathaway Holdings Monte Carlo simulations from Quantext Portfolio Planner (QPP) provide measures of the attractiveness of a portfolio.  We decided it would be interesting to look at what QPP would indicate about a portfolio made up of Berkshire Hathaway's top twenty equity holding--with their relative weightings matching their weights in Berkshire Hathaway.  The portfolio analysis using the Monte Carlo analysis provided some very interesting insights.  The results from QPP make this portfolio look like an attractive and value-driven selection of stocks.  The portfolio looked like the exact opposite of a momentum driven strategy.  Best Practices for Computer Models for Portfolio Planning There are a number of 'computer models' and Monte Carlo simulations for helping individual investors and their advisors plan for the future.  This article lays out a hierarchy of capabilities for these models to be considered to meet 'best practices' in computer-driven portfolio simulation.  Predicting Risk and Return for the NASDAQ A forward-looking Monte Carlo simulation can yield considerable insight into the future performance of even a single index.  In this short article, we show how conditioning the expected future return of an index on its volatility can yield valuable insight. Risk vs. Return for a Sample of ETF's and Implications for Portfolio Management This article looks at the volatility and average returns for all of the iShares ETF's that have at least three years of history.  There are 74 of these funds and we examine the basic balance of risk and return across this broad family of ETF's.  While individual funds exhibit a wide range of relationships between risk and return, when we aggregate the funds by risk there is a very consistent balance (on average) between risk and return over a period of only three years.  This relationship is far less robust if we use Beta as a risk measure.  Future Volatility for the U.S. and Emerging Markets One of the key sources of value from using a good Monte Carlo tool is that it generates a meaningful outlook for future volatility across portfolio assets.  The volatility outlook maye be very different from historical volatility.  How do you know that the volatility outlook is better than just looking at history?  The answer is explained in this article.  This article is a high-level introduction to benchmarking Monte Carlo tools and how you can tell if they are plausible representations of the future.  The article below is a companion. Testing Monte Carlo Risk Projections - August 2006 This article shows that Quantext Portfolio Planner's projections of future risk (volatility) in domestic and emerging markets are consistent with the implied volatility in long-term options markets.  The general process is also explained.  This approach is standard in professional risk management. Predicting Sector Performance Using Momentum and Volatility This article follows the conceptual path laid out in the article below, but looks at a series of asset classes over a 12-year period to examine the relative contribution of momentum effects vs. volatility in determing future performance.  The results reinforce the earlier conclusions.  Momentum provides additional returns.  Trailing volatility also can predict higher future returns (a precept of risk-return balancing).  When a sector has generated trailing average returns relative to risk that are out-of-balance, however, the future expected returns will be below average.  Predicting Fund Performance Using Momentum and Risk-Return Balancing This article discusses the relative contributions of momentum and risk in determining the future expected returns on a cross section of ETF's.  The analysis is accomplished using the Quantext Portfolio Planner (QPP).  Momentum effects are real, but when a fund has generated returns that are out-of-balance with the risk (volatility) in that fund, there is likely to be a correction ahead.  QPP's Risk-Return Balancing accounts projects future returns such that the long-term balance of risk and return are consistent with long-term markets.  In this way, QPP's projected future expected returns on assets helps investors to avoid the 'follow the leader' syndrome that costs the average mutual fund investor 1-2% per year. Making Monte Carlo Tools Useful While our most recent articles have focused on applications of Monte Carlo portfolio planning, this article looks at a more basic issue: the kinds of basic tests and analysis that make sense for building confidence that these models are reasonable.  The inspiration for this was a recent article in The Journal of Portfolio Planning that raised some questions about how one might establish confidence in the results from Monte Carlo tools. Why a Mix of Individual Stocks and Funds is Usually Preferable to an All-Fund Portfolio This article discusses an important consequence of portfolio theory: the ability to get maximum benefit from diversification is often diminished in an all-fund portfolio.  Investors in all-fund portfolios may be giving up 1% to 2% per year in total return for a given level of risk if they ignore this effect.  This is somewhat subtle but important nonetheless. July 2006. Case Study for A Sophisticated Individual Investor: Stress Testing Your Outlook In this article, we analyze a model portfolio submitted by a client.  The focus of this article is on 'stress testing' your portfolio outlook.  July 2006. Growth vs. Value in Asset Allocation This article discusses the seemingly perpetual debate of the relative merits of asset allocation to value vs. growth oriented funds.  This discussion examines the evidence for and against the long-term out-performance of value funds and concludes that standard 'value' funds offer no advantage over 'growth' funds.  We also show examples with Quantext Portfolio Planner (QPP) that project the same return for a set of growth funds as for a set of value funds, once the portfolio risk is matched for each class of funds.  This is notable given the dramatic out-performance of value funds over the past several years.  QPP automatically discounts recent out-performance of assets and this is a case in point.  June 2006. The Equity Risk Premium -- What It Is and Why You Should Care This article discusses the best current analysis of the future premium that investors may realistically expect for bearing the risk of investing in stocks.  The assumed equity risk premium has a major impact on projected future portfolio performance so it is worth understanding the basis for this critical factor.  Case Study for Coffeehouse Investor - Part I  and Case Study for Coffeehouse Investor - Part 2 In these two companion articles, we developed a case study based on information provided by a reader and registered user of Quantext Portfolio Planner (QPP).  The reader (John Doe) is looking for a solid portfolio for his retirement assets and had been reading a book called The Coffeehouse Investor.  He wanted to know what QPP would suggest about a 'model portfolio' in this book.  In Part I, we develop a portfolio that generates substantially higher historical and forward-looking returns than the model portfolio with no additional risk.  In Part 2, we further adjust the portfolio to allow more short-term risk, with the goal being to maximize John Does' ability to successfully fund his retirement.  Put another way, we allow QPP to suggest the appropriate risk level for his particular scenario.  Through the use of improved asset allocation in portfolio design, and allowing QPP to find the risk/return balance that would increase John's probabilities of funding his retirement, QPP yields a portfolio that adds an estimated 16 years of retirement income to John's portfolio.  June 2006. Evolving Risk Profile of a Model Portfolio This article discusses how the risk profile of a given asset allocation can change dramatically as overall market volatility increases.  We are in a market environment in which we are seeing and can expect to continue to see increasing market volatility.  A portfolio that has been very well behaved in the past several years may see its volatility / risk level increase more than many investors realize.  May 2006. Tracking Market Volatility for Portfolio Planning Most investors have portfolios that are largely driven by broader market returns.  This article discusses how to follow and conceptualize market risk, with a focus on the Volatility Index (VIX).  You can chart VIX using your favorite charting site (such as Yahoo Finance!) and keeping an eye on VIX provides considerable insight.  This paper explains VIX and how it relates to the variables that are commonly used for portfolio planning.  May 2006. Comparing Portfolios of ETF's and Mutual Funds One of the compelling value propositions for Exchange Traded Funds (ETF's) is that you can create a portfolio that is essentially identical to a portfolio of index funds, but at lower cost.  This makes sense, but is it true?  I wanted to look at the actual differences in performance--on a risk and return basis--between a model portfolio of index funds and the same allocation into ETF's.  The results serve as a validation of the equivalence of a set of ETF's with similar index mutual funds, but also highlights some important considerations about looking at historical performance.  Monte Carlo simulation provides a more robust basis for comparing portfolios than looking at historical performance.  May 2006. Similarities of Tech and Emerging Markets I see some real similarities between the current rally in emerging markets and what happened with tech stocks in the late 1990's.  To explore this, I have run our Monte Carlo simulation for a popular emerging market fund and also done an analysis as if we were standing at the end of 1999 for a tech fund.  The potential for similar outcomes is striking.  Read this article and then see if you can completely discount the possibility that we are in the midst of an emerging market rally with some real bubble potential. May 2006. Portfolio Effects of Foreign ETF's This paper explores the similarities and differences in the portfolio impacts of investing in foreign funds vs. investing in tech funds.  There are some striking similarities.  Even though both often have high Beta and high volatility, there are some key differences in portfolio impacts.  Also, just in case you still think that foreign funds are not well correlated to U.S. markets, you will be surprised.  May 2006. Accounting for Total Portfolio Diversification Most people think that they understand basic principles of portfolio diversification, but many of the portfolios that we see suggest that this is not the case.  This paper explains how diversification relates to correlation in returns between assets.  Correlation between assets or asset classes is driven by two sources: correlation of assets to the market as a whole and correlation between assets that is not related to market as a whole, so-called non-systematic correlation.  Understanding and accounting for market-driven and non-market correlations between portfolio components can dramatically improve the degree to which a portfolio effectively exploits diversification opportunities.  Better diversification means less aggregate risk for a certain level of return and portfolio theory has shown us that this is the easiest and most effective way to get a higher return and lower risk in the total portfolio.  Quantext's Portfolio Planner not only calculates non-market correlations across assets, but accounts for both sources of correlation in analyzing and simulating the entire portfolio using Monte Carlo.  We have developed a basic measure of diversification effectiveness called the Diversification Metric (DM) that quickly shows how well the assets in a portfolio actually provide a diversified portfolio.  The illustrative examples will surprise many investors and advisors! April 2006. Dividend-Focused ETF's vs. Alternative Portfolios In this article, we delve deeper into the analysis of dividend-focused ETF's and the alternatives that are available.  We compare a tailored portfolio including high-yield stocks to the projected historical performance of two dividend-focused ETF's for the ten-year period from 1995 through 2005.  The ETF's are designed to track indices for which long historical records are available, so that even though the ETF's have been around for less than three years, we can analyze how they would have performed over longer periods using the indices.  We compare published analysis of how these ETF's would have performed to a simple portfolio of high-yield stocks in a broadly diversified portfolio.  While the dividend-focused ETF's outperform the S&P500 on an absolute and risk-adjusted basis (and are projected to continue to do so in a Monte Carlo simulation), these ETF's suffer from 'over diversification' effects that limit the ultimate benefit of high-yield stocks.  Our results suggest that it is possible to do markedly better by selecting a strategic allocation of high-yield stocks in a broadly diversified portfolio.  April 2006.  Using the Market to Assess Risk in Stocks The volatility of historical returns can provide fairly accurate estimates of how risky a stock might be in the future.  We have analyzed the stock of Montepelier Re, a property and casualty firm that saw enormous declines in it's stock due to high exposure to hurricane risk in Florida and the enormous costs of Katrina and other storms in 2005.  It is of great interest to note that the projected volatility of Montpelier Re derived using a Monte Carlo simulation predicted that the level of declines in that stock was quite possible, using only historical market data available prior to the start of 2005.  The market was signaling that this level of loss was possible before hurrican season started.  This finding is consistent with a relatively efficient market in assessing stock-specific risk.  April 2006.  Risk-Managed High Dividend Portfolio In our previous article on a portfolio of high dividend stocks, we found that many high dividend stocks are also very risky which diminishes their appeal to the income investor and inserts a note of caution into the current enthusiasm for high dividend stocks.  In this article, we take a set of high-dividend stocks that are not leveraged--that are paying out dividends that are entirely covered by earnings.  Once again, historical and Monte Carlo analysis suggest that a dividend-focused approach is a good strategy for building a portfolio, whether or not you are going to take the dividends as income or reinvest them.  We show that the Monte Carlo projections for both risk and return are consistent and stable during both up and down market conditions and that the projections would have provided valuable guidance in navigating the market downturn during the early 2000's.  March 2006. Monte Carlo Analysis of a Portfolio of High Dividend Stocks In this article, we analyzed a potential portfolio of high dividend stocks as possible components of a portfolio.  These stocks provided very high dividends and high trailing returns, but the Monte Carlo model and related statistical analysis demonstrate that a portfolio constructed from these stocks will tend to be very volatile.  The resulting portfolio is also projected to provide high future returns, but all but the most aggressive investors will want to manage the volatility downwards using other portfolio components.  The trailing and projected volatility are so high in part because these companies are paying out dividends beyond their earnings and this 'leveraged' dividend strategy is itself inherently risky.  These points notwithstanding, the Monte Carlo model projects that dividend-focused strategies will tend to outperform on a risk-adjusted basis--an effect that has been shown to exist over long periods.  March 2006. Tailored Portfolio of iShares for a Moderately Aggressive Investor Portfolio design needs to be customized to an individual's situation for best results.  In this article, we examine the case of Jane Doe, a 40-year old who wishes to retire at age 65.  We show alternative portfolios using iShares ETF's and suggest that Jane may be better off with no bonds in her portfolio.  Appropriate risk/return balance can be achieved through the use of low-Beta ETF's in the energy and health sectors.  Comparing Portfolios with Different Asset Components and Allocations There are many possible portfolios that can provide an optimal return for the level of risk.  Two portfolios that have the same risk/return balance may contain very different assets and asset classes.  In this paper we show how to use a small set of iShares ETF's to replicate the risk/return profile of some model portfolios that have quite different components.  With a set of ten iShares ETF's it is quite simple to create a portfolio that relicates the risk/return profile of a wide range of portfolios.  Evenr more, you can create these equivalent portfolios whilespecifically holding out certain asset classes.  We show, for example, cases in which we entirely exclude focused energy exposure that are equivalent to the risk/return profiles of some energy-heavy model portfolios.  Similarly, while we have tended to de-emphasize international funds in some articles, we show a portfolio with a concentration in international funds.  There are many ways to create equivalent portfolios that are made up of very different allocations--and this is where a fundamental view of sectors and specific investments comes to bear. How Risky is That Stock or Fund (Really)? The ‘rational investor’ needs three critical pieces of information: 1) Estimate of expected future return, 2) Estimate of future volatility (range of future returns), and 3) Estimate of correlation of an asset to other assets. People spend an awful lot of time thinking about the first of these three (analyzing how well a stock or fund will do) and very little time on the other two of the three.  When you are analyzing a set of decisions with uncertain outcomes (i.e. like investing), all of modern finance and statistics (and their cousin game theory) teaches us that items two and three are as important as item one.  Investing is about risk and return, but the majority of investors do not understand the rudiments of risk and this means that many investors are ultimately likely to have less than ideal portfolios, no matter how good they are at stock picking.  Try the little risk quiz in this paper--you may be surprised. Portfolio Analysis: By Style or Statistics? Since my firm's release of our Monte Carlo portfolio analysis software, I have become more acutely aware of how differently different people think about portfolio analysis.  This point has become increasingly evident in the dialogs that have evolved from my articles on using Monte Carlo portfolio planning tools for portfolio allocation.  The contrasting schools of thought may be described as fundamental analysis and statistical analysis.  In practice, most people can and should do some of both. When More Risk is Less Risky One basic mistake that people make in asset allocation is properly factoring in their current portfolio, investment time horizon, and other personal factors in determining how much risk they should be carrying in their portfolios.  You don't want too much risk, but you also do not want to be so conservative that you reduce your chances of building sufficient wealth.  I think of long-term risk in terms of the probability of running out of funds in retirement.  You may find that investing in a higher risk / higher return portfolio substantially decreases your long-term risk of an under-funded retirement.  This situation is demonstrated using Monte Carlo analysis for the Agile Investing model portfolios.  This paper shows why it is so important to use Monte Carlo planning tools that are set up with personal and specific information.  February 1, 2006. Analysis of Sample ETF Portfolios from Agile Investing This paper is a case study of three portfolios proposed by Agile Investing, an investment advisory firm (www.agileinvesting.com).  These three portfolios, aimed at three different risk tolerance levels have been analyzed using our Monte Carlo portfolio model and the results are impressive.  The three portfolios make good use of strategic asset allocation in getting the best returns available for the level of risk. January 26, 2006. Risk Outlook 2006 for the S&P500 and NASDAQ 100 A reasonable way to determine an estimate for future volatility in a stock or fund is to look at options prices and back out the implied volatility.  If you have a portfolio simulation tool, you can run the simulation, price options from the simulation, and (if levels agree), you can look at the projected market volatility in the portfolio model.  This is a good way to sanity check a Monte Carlo model, as well as providing insight.  We have compared put and call option prices on SPY and QQQQ in the market to simulated prices from Quantext's Retirement Planner (QRP), a Monte Carlo (MC) portfolio simulation.  The results provide valuable insight into market risk over the next 2-3 years.  January 19, 2006. Improving a Style-Based ETF Portfolio Using Individual Stocks This paper takes a sample ETF portfolio submitted to us and looks at how to improve the overall portfolio properties by re-balancing around the initial list of ETF's.  The second step in the analysis is to look at how to add individual stocks to the ETF portfolio in order to imptove the total portfolio performance.  The analysis is performed using the Quantext Portfolio Planner.  January 16, 2006. Tuning a Portfolio of ETF's This paper examines a basic portfolio of ETF's and how it can be evaluated objectively and then tuned to achieve better asset allocation.  The original and final portfolios are examined using a Monte Carlo model to determine how improved asset allocation impacts the ability of the portfolio to provide income over an extended period.  The impact of improved asset allocation is to increase the viable survival rate of a sample portfolio by 5-10 years.  This paper was excerpted and discussed on ETFinvestor.com.  January 2006. International Investing and Portfolio Diversification This paper follows on from the discussions in the article above and on ETFInvestor.com.  The primary issue in the paper is the degree to which investing in international ETF's or mutual funds actually provides diversification in the form of offsetting risks in a portfolio.  Surprisingly, many of the best-known international ETF's actually increase a portfolio's exposure to U.S. markets rather than providing offsetting effects.  January 2006. Building a Balanced Portfolio with iShares ETF's Provides samples of portfolios with various mixes of iShares ETF's and the resulting portfolio risk and return characteristics.  The portfolios are examined historically and using a Monte Carlo analysis to project forward.  December 2005.  Personal Portfolio Management This is a mini-text about personal portfolio management.  The text describes how to determine required savings rates and appropriate asset allocation for specific individualized cases.  Covers portfolios that include stocks, mutual funds, and bond funds, and also accounts for employee stock options.  This book explains Monte Carlo portfolio management and shows a series of cases.  The book also covers key statistical concepts for portfolio management and asset allocation.  Note:  This book discussed basic topics.  The other articles and white papers on this site provide additional depth. Testing Monte Carlo Risk Projections While articles about Monte Carlo models for retirement planning and portfolio management abound, this paper looks at a topic that receives almost no attention:  how can you determine if the risk projections used are reasonable?  This paper examines Quantext's QRP and shows how the projections for market volatility can be tested by looking at where options are trading. Fall 2005. The Writing on The Wall: What Portfolio Management Tools Can Tell You This paper looks at the ways that Monte Carlo portfolio planning tools can help in making better asset allocation and risk management decisions.  Fall 2005. Safe Portfolio Withdrawal Rates in Retirement: Comparing Results from Four Monte Carlo Models This paper, written by Quantext, examines how much you can reasonably expect to draw from a diversified portfolio of stocks and bonds in retirement.  The discussion looks at results from four Monte Carlo planning models, including the Quantext Retirement Planner. Monte Carlo Portfolio Planning with Employee Stock Options This paper shows results from the most recent version of QRP which includes treatment of employee stock options. Case Study: Sun Microsystems Employee Stock Options and Portfolio Management This paper looks at a series of employee stock options grants using real historical strike prices and expirations for Sun stock.  The paper looks at how we we determine fair value for options and how to manage risk exposure with options.  There is also a brief discussion of how our valuation approach is consistent with FASB's suggested approach.   NOTE: Quantext is not a registered investment advisor.  No information on this website should be taken as advice to buy or sell any asset.  Any and all information obtained from Quantext is on an "AS IS" basis.    Other Useful Links Conservative Wealth Management CWM is an investment management firm run by Phil Demuth, Ph.D.  Phil is a registered investment advisor (RIA) and his perspectives on money management represent a best-in-breed approach for the conservative investor.  Ben Stein - Phil Demuth Homepage Ben Stein and Phil Demuth are the authors of a best-selling series of personal finance books.  This site provides information on their books, etc. MoneyChimp Provides a very readable introduction to quantitative issues in investing The Retirement Calculator from Hell: Part III This paper by William Berstein is a lucid explanation of planning that accounts for risk.  The article includes links to the earlier papers (parts I and II) by Bernstein on these topics.  Online Asset Allocation Resources from William Bernstein