back start next
[start] [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46] [47] [48] [49] [50] [51] [52] [53] [54] [55] [56] [57] [58] [59] [60] [61] [62] [63] [64] [65] [66] [67] [68] [69] [70] [71] [72] [73] [74] [75] [76] [77] [78] [79] [80] [81] [82] [83] [84] [85] [86] [87] [88] [89] [90] [91] [92] [93] [94] [95] [96] [97] [98] [ 99 ] [100] [101] [102] [103] [104] [105] [106] [107] [108] [109] [110] [111] [112] [113] [114] [115] [116] [117] [118] [119] [120] [121] [122] [123] [124] [125] [126] [127] [128] [129] [130] [131] [132] [133] [134] [135] [136] [137] [138] [139] [140] [141] [142] [143] [144] [145] [146] [147] [148] [149] [150] [151] [152] [153] [154] [155]
99 * ApproximateJy 90% of al] new mutual fund sales in 1997 had Morningstar 4 or 5 star rankings, testifying to the enormous influence of this publication. church itself. The field has been so indoctrinated and dogmatized that only those who promoted the leading model from the start are allowed to destroy it. The academics also devised measures to adjust risk by dividing performance by volatility. I might return 15% a year and my competitor 30%, but if her portfolio were much more volatile than mine, I would have the better risk-adjusted retums. It tums out it could all come from the Wizard of Oz. But why is that a su rise? Beta gives the appearance of being a highly sophisticated mathematical formula, but is constmcted while looking into a rearview mirror. It takes inputs that seemed to correlate with volatility in the past, then states they will work again in the future. This is not good science. Because some variables moved in step with volatility for a number of years, does not mean that they initiated it. Most often, such correlations are sheer coincidence. I wrote almost two decades ago that betas, built as they were on spurious correlations with past inputs, were unlikely to work in the future. This is precisely what has happened. This is notjust ivory tower stuff, as weve seen. Beta and other forms of risk measurement decide how hundreds of billions of dollars are invested by pension funds and other institutional investors. High betas are no-nos while the money manager who delivers satisfactory retums with a low-beta portfolio is lionized. A billion-dollar industry, selling beta and similar measurements, has grown and prospered. The academic definition of risk is almost universally used by legions of mutual fund advisers and pension fund consultants. They advise clients on the mutual funds to buy, or the money managers to hire or fire, by the volatility of their investment retums. Take Momingstar, for example; the largest service monitoring mutual funds. Although it is an excellent and easily readable source that I refer to often, its concept of risk is problematical. Momingstars "five stars," its top ranking, widely followed and much sought after, is anchored on dubious assumptions of how you should measure risk.* The returns of a mutual fund are calculated every month against the interest eamed on a 90-day T-bill or other "riskless investment." If a fund falls behind this benchmark-or worse yet has the misfortune of unde erforming the market for relatively short periods-it is branded as "risky." In fairness
to Momingstar, it cautioned its readers not to treat its rankings as gospel. Other ranking systems have not taken this step. Which leads us back to the dollars you shell out for risk ratings today. While I respect Momingstar as a storehouse of mutual fund information, I believe its rankings, and others like them, built as they are on some variation of volatility, are dangerous to you. They can steer you away from some of the finest value funds, just as you should be looking at them, and guide you to pricey ones with weak finances because they are temporarily shooting out the lights in a sizzling sector. This is exactly what happened with aggressive growth funds that owned stocks priced in the stratosphere from 1995 through July of 1997. Many billions poured into these funds, which invested in a limited portfolio of small-cap growth stocks. Until they plummeted. Not a few had high ratings from the various consultants and ranking systems that measured risk in terms of volatility. Yet, looking through the rearview mirtor is exactly what almost all of these risk measurement services do. Investors have been hurt when low risk ratings were awarded to money market funds, such as Piper Jaf-freys, that then fell apart. The ranking systems had no way of picking up the fact that the funds, by using derivatives, were as dangerous an investment as the most speculative stock fund. The point is that when you are told what is risky and what is not, read the fine print of the ranking agency very carefully. If its based on beta or volatility measurements such as Ive described, stay well clear of the advice. This brings us to an important mle. RULE 32 Volatility is not risk. Avoid investment advice based on volatility. The simplisdc risk measurements commonly used today can get you into trouble, or cause you to miss opportunities. Sometimes even the bluest of blue chips tumble sharply and become very volatile for a while (as the banks and the pharmaceuticals have done in this decade). This volatility is not something to shy away from, its the gift of opportunity. For the value buyer, the more a stock is driven down by panic selling, the better. People wamed away from this volatility lost enormous potential profits. The rearview mirror approach also cannot detect either of the two key risk measures that we looked at in chapter 12, which allow you to avoid stocks that are overpriced or those that are weak financially. More than a few high rankings have gone into the tank as a result. Many more, par-
Other Risk Measurements We have seen that volatility, and its crowning achievement beta, do not work, although beta is still the risk measurement most widely followed by consultants and mutual fund advisors. The question then is what else is out there? Actually, there are some good looking new models that measure risk. One of the popular tickets today is called semivariance. Semivariance measures the performance of your portfolio only in a down market or in down quarters, to see how it holds up relative to the market. The theory behind it states that investors are happy enough to beat the market when it is rising, but want to see their portfolios fall less than the averages when the bear growls. Youd be surprised at the acrimony of the academic debate about whether to accept this sensible-seeming measurement instead of volatility. Some researchers consider outperformance (or volatility) of the market on the upside equally distasteful to investors as their portfolios dropping more than the market on the way down. The theorists may know some hidden secrets we dont, but Ive yet to meet an investor who, watching his portfolio move briskly ahead of the market, considered it more risky. You might recall we used semivariance in all our contrarian tests of down markets. Regardless of which value benchmark we tried, each contrarian portfolio passed the semivariance test by outperforming the market in down quarters. However, although I think semivariance is a better measure than volatility, I am not happy with it as the basic definition of risk, because it still states that investors assume risk is price volatility alone. Price fluctuations are only one of the risk factors that investors face. As we have seen, there are risks endemic to both the investment and business worlds that cannot be put into a neat litde statistical package that measures volatility and retums-nor can the impact of inflation on your investment results in the future. Lets tum to what I believe is a better approach to assessing risk. The Riskless Investments During most of American financial history, preservation of capital, rather than appreciation, was the most important criterion of investment ticularly of the emerging growth or aggressive growth variety, are on their way.
[start] [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46] [47] [48] [49] [50] [51] [52] [53] [54] [55] [56] [57] [58] [59] [60] [61] [62] [63] [64] [65] [66] [67] [68] [69] [70] [71] [72] [73] [74] [75] [76] [77] [78] [79] [80] [81] [82] [83] [84] [85] [86] [87] [88] [89] [90] [91] [92] [93] [94] [95] [96] [97] [98] [ 99 ] [100] [101] [102] [103] [104] [105] [106] [107] [108] [109] [110] [111] [112] [113] [114] [115] [116] [117] [118] [119] [120] [121] [122] [123] [124] [125] [126] [127] [128] [129] [130] [131] [132] [133] [134] [135] [136] [137] [138] [139] [140] [141] [142] [143] [144] [145] [146] [147] [148] [149] [150] [151] [152] [153] [154] [155]
|