Taking A Long-Term View On Stocks
Posted by admin in Easy money on July 17th, 2009
The market is definitely ping-ponging and investors are either running for the hill or celebrating the potential for a bottom. It may seem one day that the news is all gloom and doom and the next day there are numerous positives about the economic situation listed heralding a market bottom. What can you believe? If you’re taking a long-term view of your investments, it really doesn’t matter. If you have money to invest, now is definitely the time to invest as any long-term strategy will give your money time value the more you wait to cash in.
Ten Years Or More
Let’s assume that the bottom of the market isn’t reached in 2009. It might still come in 2010, or maybe even 2015. At any rate, if you have at least 10 years before retirement and you’re trying to cash in on the great value and low prices of some quality stocks out there, now is the time to do it. Once the rebound happens, you may be priced out and it will be too late to invest then. That’s why many investors will continue to buy in down markets as they know that just waiting out the ups and downs to a later date has historically been one of the easiest ways to make money in this financial system.
Think Value
What’s going to happen in the year’s ahead? Does anyone know for sure? You may not be a fortune-teller, but some trends are clear. Pick stocks that can provide an increase in value over time. This can be stocks from emerging markets like Asia. It can mean investing in commodities like agricultural stocks and oil. Look for companies that are well-positioned to survive the downturn and have a quality product. As their competitors go bankrupt, those customers will be forced to find a new vendor, thus increasing the likelihood that the survivor gets a larger market share. If you hold stock in that company, your stock is likely to increase in value too
Division of Agricultural Sciences and Natural Resources
Posted by admin in Easy money on May 18th, 2009
Economic development concerns the creation, attraction, expansion, and retention of jobs and income. A community or region can pursue many avenues when attempting to encourage economic development. Economic development usually means improving or expanding existing business or attracting new business and industry.
There are several reasons why attracting new business or industry is a popular approach to economic development.
1. New business or industry can provide needed expansion and diversification to a community’s or region’s economic base.
2. Recruiting business and industry, as opposed to assisting existing business development, is an easy concept for community leaders and the general public to understand and support.
3. New business and industry can have a quick, highly visible impact with new jobs, income, families, and potential community leaders.
4. Recruiting business and industry is an accepted, traditional approach that has an established support system in the development programs of state governments, utilities, and other organizations.
Forward and Futures prices
For all financial instruments, it is important to be able to determine whether the price available in the market is an appropriate one. Hence, we engage in the process of “pricing” the financial instrument. A major objective of this post is to determine the appropriate price of a futures contract. Given the similarity between futures and forward prices, however, we can benefit from studying forward contract pricing, which was covered in former posts. But first, we must look at the similarities and differences between forward and futures contracts. Recall that futures contracts settle daily and are essentially free of default risk. Forward contracts settle only at expiration and are subject to default risk. Yet both types of contracts allow the party to purchase or sell the underlying asset at a price agreed on in advance. It seems intuitive that futures prices and forward prices would be relatively close to each other. The issues involved in demonstrating the relationship between futures and forward prices are relatively technical and beyond the scope of this post. We can, however, take a brief and fairly nontechnical look at the question. First let us ignore the credit risk issue. We shall assume that the forward contract participants are prime credit risks. We focus only on the technical distinction caused by the daily marking to market.
The day before expiration, both the futures contract and the forward contract have one day to go. At expiration, they will both settle. These contracts are therefore the same. At any other time prior to expiration, futures and forward prices can be the same or different. If interest rates are constant or at least known, any effect of the addition or subtraction of funds from the marking-to-market process can be shown to be neutral. If interest rates are positively correlated with futures prices, traders with long positions will prefer futures over forwards, because they will generate gains when interest rates are going up, and traders can invest those gains for higher returns. Also, traders will incur losses when interest rates are going down and can borrow to cover those losses at lower rates. Because traders holding long positions prefer the marking to market of futures over forwards when futures prices are positively correlated with interest rates, futures will carry higher prices than forwards. Conversely, when futures prices are negatively correlated with interest rates, traders will prefer not to mark to market, so forward contracts will carry higher prices.
Because interest rates and fixed-income security prices move in opposite directions, interest rate futures are good examples of cases in which forward and futures prices should be inversely related. Alternatively, when inflation is high, interest rates are high and investors oftentimes put their money in such assets as gold. Thus, gold futures prices and interest rates would tend to be positively correlated. It would be difficult to identify a situation in which futures prices are not correlated with interest rates. Zero correlation is rare in the financial world, but we can say that when the correlation is low or close to zero, the difference between forward and futures prices would be very small.
At this introductory level of treatment, we shall make the simplifying assumption that futures prices and forward prices are the same. We do so by ignoring the effects of marking a futures contract to market. In practice, some significant issues arise related to the marking-to-market process, but they detract from our ability to understand the important concepts in pricing and trading futures and forwards.
STOCK INDEX FUTURES CONTRACTS
One of the most successful types of futures contracts of all time is the class of futures on stock indices. Probably the most successful has been the Chicago Mercantile Exchange’s contract on the Standard and Poor’s 500 Stock Index. Called the S&P 500 Stock Index futures, this contract premiered in 1982 and has benefited from the widespread acceptance of the S&P 500 Index as a stock market benchmark. The contract is quoted in terms of a price on the same order of magnitude as the S&P 500 itself. For example, if the S&P 500 Index is at 1183, a two-month futures contract might be quoted at a price of, say, 1187.
The contract implicitly contains a multiplier, which is (appropriately) multiplied by the quoted futures price to produce the actual futures price. The multiplier for the S&P 500 futures is $250. Thus, when you hear of a futures price of 1187, the actual price is 1187($250) = $296,750.
S&P 500 futures expirations are March, June, September, and December and go out about two years, although trading is active only in the nearest two to three expirations. With occasional exceptions, the contracts expire on the Thursday preceding the third Friday of the month. Given the impracticality of delivering a portfolio of the 500 stocks in the index combined according to their relative weights in the index, the contract is structured to provide for cash settlement at expiration.
The S&P 500 is not the only active stock index futures contract. In fact, the Chicago Mercantile Exchange has a smaller version of the S&P 500 contract, called the Mini S&P 500, which has a multiplier of $50 and trades only electronically. Other widely traded contracts in the United States are on the Dow Jones Industrials, the S&P Midcap 400, and the Nasdaq 100. Virtually every developed country has a stock index futures contract based on the leading equities of that country. Well-known stock index futures contracts around the world include the United Kingdom’s FTSE 100 (pronounced “Footsie loo), Japan’s Nikkei 225, France’s CAC 40, and Germany’s DAX 30
When managing risk, diversify (part 4)
Posted by admin in Risk management on April 6th, 2009
The CAPM establishes a logical relationship between expected rate of returns and portfolio volatility. The greater the latter, the greater should be the mathematical expectancy of high returns. The CAPM shows that the expected returns for a portfolio should exceed that of a risk-free investment; this may be attributed to a risk premium whose amount is proportional to the beta coefficient.
However, empirical studies do not exactly confirm this theory. In a study dating from 1992, two American researchers, Fama and French, considered the monthly returns of stocks quoted in New York from 1963 through 1990.30 These stocks were distributed into 10 portfolios in accordance with their beta coefficients. The first contained those stocks whose beta was weakest; its volatility was assessed at 0.8. The volatility of the second portfolio was assessed at 0.9 and so on. The last portfolio’s volatility was rated at 1.7. Returns should have grown at the same rate as the relative degrees of volatility. Nothing of the sort took place; no correlation emerged. In a more recent study (June 1999) another researcher, John Cochrane, demonstrated that even though a correlation does in fact exist, ‘‘small cap’’ shares provide returns that are higher than their volatility would convincingly lead us to believe.
The trouble with these theories is that statistical tests on returns obtained after the fact fail to render them perfectly justifiable. Practice shows that professional investors base their choices first on historically attested volatility and second on expectations of returns. Portfolio theory is regularly applied. That said, investors often anticipate in an erroneous manner. If they expect prices to rise and choose volatile portfolios in order to make profits, a market downturn will aggravate the effects of disappointing results. It is not because the expected return on a portfolio is 15 percent that it will supply such sizable returns. Risk justifies the fact that an investor demands higher returns than is the case with risk-free rates, and quite rightly so. The CAPM shows us that the more risks are incurred, the higher the returns an investor must demand. However, this is not tantamount to asserting that the higher the risk, the more favorable the returns obtained! Were this the case, it would behove us to take a maximum number of risks, to run up debts and to invest borrowed money in a market portfolio clearly reflecting systemic risk. In the long run, each and every gambler would make a fortune! One would be better off going for broke and putting borrowed money into play on the roulette wheel or on horse races. Were rewards proportional to the risks incurred, gambling would invariably be the best bet. Statistical tests apply to history-based returns or volatility; as for the model, it functions with expectations of returns rather than time-based averages and with estimates of responsiveness instead of past volatility. Expectations of returns may indeed prove to be proportional to the risk incurred, and yet obtained returns may turn out to be disappointing.
Another criticism is that such tests ought not be restricted to stock market securities. When calculating the beta coefficient, the reference market needs to include all the financial instruments and all assets in which the fortune of the world may be invested: unquoted equities, real estate, raw materials, precious metals, the art market and so on. That said, such criticism is basically technical.
More criticism should rather be addressed to the hypotheses that underpin the CAPM. As we saw above, this reasoning is predicated on a strong hypothesis according to which everyone has the same vision of the future. All investors are said to form identical anticipations; as a result, there supposedly exists but only one envelope of efficient portfolios. This assumption is also part and parcel of a well-known economic framework in which markets are always in equilibrium. This basis for CAPM does not hold water. Markets are never well-balanced; any equilibrium is always shifting. Equilibrium between supply and demand is achieved through prices; continual changes in the latter reflect a perpetual displacement of the point of equilibrium.
The second basis for the CAPM logic consists in the would-be existence of a single efficient envelope of portfolios, the set of all the superior portfolios possible in Markowitz’s framework. Yet in order for this envelope to be unique, it would be necessary for all investors to hold the same predictions. However, if everybody shared the selfsame vision of the future, there would be neither buyers nor sellers! In reality, when we talk about markets we evoke transactions; any transaction features the divergent viewpoints of the buyer and the seller. So there can be no single efficient envelope of portfolios. In practice, many investors believe that their idea of the future is more prescient than that of their neighbors. They do not invest in the same portfolio as the rest of the market. Moreover, when there are several points of view, there also exist several portfolio envelopes. One may even wonder whether the number of efficient envelopes is not equivalent to the number of investors, in so far as each of the latter foresees the future differently. If this is the case, one must admit that portfolio structures may differ greatly among particular investors, which does not necessarily call into question the analytical frame of reference. We must not forget that investors have differing horizons; while some of these are short term, others are long term.
Predictions for the future are relevant to a given horizon of investment. When you think of investing over two to three years, you formulate hypotheses on that time span. But if you are a long-term investor (+ 8 years), you tend to rely on trend analysis. When there are sellers and buyers, there also exist several points of view. And if there is a market, sellers and buyers do exist. The market arbitrates their differences. There is no such thing as a consensus about the future. At any given point in time, one may find many efficient envelopes of possible portfolios.
When managing risk, diversify (part 3)
Posted by admin in Risk management on March 26th, 2009
It has been shown that portfolio risk is reduced by introducing shares from emerging countries, whose volatility is nonetheless much greater than that of industrialized countries. The key to the mystery is that the shares of the former are only weakly correlated to those of the latter. Portfolio performance is enhanced once shares of emerging countries are brought into the mix. At least that is the case in normal times. Financial crises occasionally breed correlations that foil the best-laid mathematical schemes.
During a stock market crash in a given country, it often happens that the local currency also bites the dust. Losses for a foreign investor are even more agonizing than those suffered by a domestic investor; this is due to the correlation that appears in times of financial crisis between exchange rate risk and overall market risk. In the Mexican crisis from December 1994 to March 1995, shares dropped by about 30 percent. That said, over the same period an investor who had acquired Mexican stocks with dollars would have endured a loss of 65 percent – 35 percent more – on account of the devaluation of the Mexican peso in relation to the American dollar.
A financial crisis makes correlations appear in places where they were not expected. The ‘‘tequila’’ effect of the Mexican crisis made investors massively sell off their shares in emerging countries. So it was that the crash spread to numerous Latin American countries and also had a ripple effect across the Pacific, in Indonesia, Thailand and the Philippines.
In fact the risk of a security is composed of two distinguishable sets of risks. Systematic risk is that which cannot be eliminated through diversification strategies. It is the risk inherent to the system, the market risk. Specific risk is proper to the financial asset under consideration. It is a reflection of the risk that something happens and affects the asset (and the asset alone). This risk disappears by dint of diversification.
These two risks are independent; their correlation coefficient is 0. Total risk is the sum of the two. Three experts – William Sharpe, John Lintner and Fisher Black – have put this observation to work by building the Capital Asset Pricing Model (CAPM). The CAPM indicates the price of risk. You may recall that Louis Bachelier established that: ‘‘The mathematical expectancy of the speculator is zero.’’ As for the CAPM, it establishes a simple rule on the basis of two hypotheses: markets are in equilibrium; all investors believe in Markowitz’s theory and they choose their investment out of the same set of efficient portfolios. The rule postulates that the mathematical expectancy for an investment in a security or a portfolio must be proportional to the systematic risk. Since specific risk may be eliminated by diversification, it will not be remunerated by the market. On the other hand, the value of a portfolio has to include remuneration for the investor of an amount in proportion to the degree of systematic risk.
Market risk is attributable to the ongoing evolution of financial assets; it dictates the fluctuation of a given security. Some stocks react strongly to market movements; others do not. The degree of sensitivity to overall market fluctuation proper to a given security is known as the beta coefficient (the estimated coefficient of independent variables in a regression equation). It historically measures the systematic risk proper to a given security on the basis of comparison between the price fluctuations of the security and the fluctuations of the financial market taken as a whole. A security with a 1.0 beta presents the same risk as the market. With a beta lower than 1.0, its risk is also lower than that of the overall market; the security attenuates market fluctuations. With a beta higher than 1.0, the security tends to amplify market fluctuations. With a beta of 2.0, the instrument moves twice as much as the market. If the market rises by 10 percent, it goes up by 20 percent; when the market falls, it goes just as precipitately down. Yet for a given security, the beta does not necessarily hold steady. In other words, it takes on different values in accordance with the periods for which it is measured. On the other hand, the beta value of a market portfolio shows more stability over the course of time. It measures the responsiveness of this portfolio to market fluctuations; it quantifies its volatility.
When managing risk, diversify (part 2)
Posted by admin in Risk management on March 5th, 2009
It is often supposed that investors do not like risk; they are convinced that the good surprises fail to compensate for the bad ones. They would consequently prefer the same returns while incurring a lower degree of risk.
The more the correlation coefficient is negative, the more one endeavors to diminish average risk by applying negatively correlated instruments. If the investor is indeed ‘‘risk-averse’’, he will make sure that the latter are as negatively correlated as is feasible. Then again, the mere fact that the financial instruments are not strictly correlated enables diversification to play an appreciable role.
The correlation of two financial instruments takes on a value between – 1 and + 1. The lower the correlation between a financial asset and a portfolio, the more the volatility of the latter is diminished once the former is added to the portfolio. If one adds securities that are negatively correlated with the portfolio, then the volatility of the latter will be very much diminished. If the new financial assets have no correlation with the portfolio (its coefficient correlation is 0), adding such a security will nonetheless reduce the volatility of the portfolio. Even with a positive correlation coefficient, provided that it is less than 1, adding a supplementary asset diminishes the risks incurred by a portfolio. If we limit ourselves to stock portfolios, studies show that maximal risk diversification is attained with at least 20 shares of firms operating in heterogeneous industrial sectors. Needless to say, if you specialize in stocks for skis, ice skates, fur jackets and 17 shares in industries related to cold weather, your portfolio will be poorly diversified notwithstanding your 20 shares! In contrast, you must try to introduce shares that are not positively correlated. It is also necessary for the probability distributions and the degrees of correlation between them to remain stable for a sizable length of time. The more we study long periods of time, the less reliable are the available statistics. How long is long enough? During calm spells studies by institutional investors analyze and survey the degrees of correlation that may exist between the different categories of financial assets: the stocks of large-scale groups, medium-sized companies, government bonds, corporate bonds, junk bonds, real estate, hedge funds and so on. One must remember that securities that are riskier than a portfolio when taken individually may, in spite of everything and provided that they are not correlated with the portfolio, reduce the overall risks of the latter.
Such factors help to explain the interest in international diversification; it can be expected that economic crises will not take place simultaneously in every country. This approach is supported by the observation that in each country, stocks evolve as a function of the ups and downs of the local economy. Money flows likewise introduce negative correlations between stock market performances and exchange rates. Lowering risk through international diversification largely compensates for the risk linked to exchange rates. Yet with the ongoing internationalization of the activities of quoted companies, the impact of purely local or national factors tends to diminish. A French economist, Bruno Solnik, has shown that for an internationally diversified firm, asset returns are determined to a significant extent by non-domestic (rather than domestic) factors. Moreover, the sensitivity of individual company returns to non-domestic factors is integrally linked to the scope of their international activities, as represented by the relative importance of foreign sales in relation to total sales.
When managing risk, diversify (part 1)
Posted by admin in Risk management on February 14th, 2009
When he drastically modified the risk theory of financial markets, Markowitz reasoned in terms of a portfolio. A portfolio is a whole group of financial assets. Its overall profitability is the sum total of the return on each asset weighted in terms of the proportion represented by its value with regard to that of the entire portfolio. Portfolio profitability is the weighted average of returns on the securities included in it. Yet the risk incurred is another story entirely. A portfolio’s volatility is less than the average volatility of the securities from which it is constituted; that is why diversification is basically praiseworthy.
Markowitz’s singular contribution consisted in providing precise instruments to measure diversification. These instruments allow for the constitution of a portfolio supplying optimal returns for minimal risk; Markowitz terms this an efficient portfolio. No efficient portfolio is superior to any other. Each is simply the best in its category of risk; it offers the highest expectations of returns for a given risk. And in a rigorously equivalent manner, it offers minimal risk for a given expectation of returns. If an efficient portfolio offers comparatively higher returns, it must also present more risks.
Instances of random deviation have a tendency to cancel each other out in a portfolio. This is called diversification. There is an important parameter known as the correlation coefficient, whose role is to assess the benefits obtained through diversification. The correlation coefficient measures the degree of correlation between two variables. The greater their tendency to move in concert at the same time, the higher their correlation coefficient. The range of values this takes is between – 1 and + 1. If the phenomena are perfectly correlated, the coefficient is +1. If they are inversely correlated, the coefficient is – 1. If they are not correlated at all, the coefficient is equal to 0. As for two positively correlated shares, the periods of strong returns for the first correspond to the periods of strong performance for the second; the same for poor performance. When the shares are negatively correlated, underachievers accompany overachievers. When there is no correlation at all, A’s performance has nothing to do with B’s.
Diversification brings together two random variables that are not strictly correlated and thereby diminishes average risk. The interest of Markowitz’s theory basically consists in his having mathematically expressed the fact that the important parameter is the correlation coefficient and that what matters is to estimate correlations involving multiple phenomena.
Stock prices fluctuation, part 6
Posted by admin in Stock prices on January 6th, 2009
Financial theory tends to focus on a notion of risk limited to what we might be termed ‘‘trivial perils’’, those having to do with price fluctuations liable to appear in a relatively stable overall environment. Doesn’t history frequently show that radical alterations in the environment provoke price variations comparable to mood swings? Maybe we just do not know how to analyze major risks. Maybe we do not know how to prevent them.
Examples have demonstrated that rather than base their expectations on past mathematical averages, investors tend to detect correlations between past events. At the beginning of his chapter on ‘‘the state of long-term expectation’’, Keynes wrote:
It would be foolish, in forming our expectations, to attach great weight to matters which are very uncertain. It is reasonable, therefore, to be guided to a considerable degree by the facts about which we feel somewhat confident, even though they may be less decisively relevant to the issue than other facts about which our knowledge is vague and scanty. For this reason the facts of the existing situation enter, in a sense disproportionately, into the formation of our long-term expectations; our usual practice being to take the existing situation and project it into the future, modified only to the extent that we have more or less definite reason for expecting a change.
How is such a judgment to be formulated? Investors tend to make a fetish out of economic ‘‘factoids’’, such as for how many months, at some time in the past, did the market anticipate and predict economic recovery. And yet they interpret such anecdotal data by connecting the ‘‘dots’’ that get their attention in accordance with the ‘‘paths’’ they map out. As with the Impressionists (and most especially with Georges Seurat), investors spend a great deal of their time connecting details. The brain is organized in order to detect correlations. Numerous studies have shown that investors revise their predictions by overemphasizing new information in relation to pre-existing and long-term data.
Curiously enough, the mechanism of risk analysis is altogether different. Rather than behave as they do when forming expectations, investors often use historical (mathematical) volatility to assess the risk of a possible investment. Experience shows that volatility constitutes an excellent basis for risk evaluation; what skyrockets may plummet just as precipitately.
That said, the relationship between risk and return is not as fluid as theory would have it (we shall return to this point). The connection between risk and return is not a detail. It is not because a portfolio presents high risk that one may reasonably expect to win the ‘‘sweepstakes’’. Moreover, unforeseen correlations do crop up; they merely were not noted in the past. Last but not least, volatility evolves along with time. One may think that the dispersion of returns (additional volatility) would increase in times of economic and political uncertainty. The sensitivity of a financial asset to market variations may be estimated historically, but this should only be the basis of ongoing anticipation. Volatility also must be anticipated.
Stock prices fluctuation, part 5
Posted by admin in Stock prices on November 11th, 2008
Untimely surprises are especially dangerous when one is counting on the income drawn from one’s portfolio. Capitalization is based on the principle that all such revenues are reinvested and that values may consequently be compared at several points in time. In reality, investors will want to redeem earnings or liquidate a portion of their investments before the date of termination. One may be (or at least feel) compelled to sell off one’s investments at a time when prices are low, which is a disagreeable surprise. If investors regularly liquidate a portion of their investments in order to remain afloat, they will be especially aware of the risk of doing so at a time when prices are heading downwards. Stock market crises compress the per-share value of a portfolio to such an extent that more shares have got to be sold in order to draw the same revenues. Once prices rise again, it will be that much more difficult to compensate through capitalization for the transfers conceded when prices were low.
Let’s take as an example an investor who retired at the end of 1998 at the age of 60 with e300,000 invested in a stock-indexed fund (a fund that follows a market index; see Chapter 9). Suppose that this recent retiree had the intention of eking out an existence thanks to the e18,000 annually withdrawn from his portfolio. If the latter had provided a regular annual return of 8 percent, it would have produced e24,000 each year in dividends and capital gains, and he would have been able to cope with the withdrawal of e18,000 per year. But from 1999 through 2001, the stock exchange went down by about 40 percent! By the end of 2001 the portfolio would have been worth only e180,000. It would have taken annual returns of 10 percent over the following period to allow for the withdrawals. Quite obviously, everything would have been different had the crisis taken place 20 years later. During that period the portfolio would have been enriched by e24,000 – 18,000 = 6,000 per annum, that is 2 percent per year. It would have increased by 50 percent and a 40 percent loss in 2020 would still have left e270,000 in the portfolio. Average 8 percent returns would have permitted scheduled payments of the required annuities. The one way to survive a stock market crisis that comes too early is to diversify one’s portfolio and employ financial instruments that do not all go down at the same time. Such diversification limits portfolio volatility.
Does historical volatility measure the risk of investment for the future? Fluctuations in the vicinity of the average may give a precise idea of the risk, but this is the case if – and only if – the law of probability remains unchanged. If observations of the past are to prove useful when forecasting the future, it is necessary for the law of probability to be stable in time. Is this the case? Just like the laws of mortality, the law of probability is not a known quantity; it can only be estimated on the basis of past series. Compare the probability of stormy weather. Tomorrow’s skies may be predicted as a function of meteorological parameters, provided that the climate is not fundamentally altered. Consider global warming; weather forecasting is of little avail in the event of a phenomenon rendering history obsolete! And in a stock market crisis, investors may have the impression that everything is crashing. From 1989 through 1999 at the Paris Bourse, 95 percent of reported monthly returns ranged from +12.75 percent to – 11.25 percent, which means that 5 percent of the time, returns were greater than +12.75 percent or lower than – 11.25 percent; hence there had been a monthly loss greater than 11 percent for 2.5 percent of the time (or once every three years). In some cases losses become downright catastrophic – in October 1987 shares plummeted by 22 percent in a month; in September 2001 it took just a week for them to lose 18 percent of their previous value. That is twice as much as the lower limit of the range of confidence over the 10 previous years! Yet up to now, the market has always recovered. Even if stock market performances are approximately akin to a random walk and even if their distribution resembles a normal law, this is not what happens at the extremes. Pronounced monthly highs and lows, bubbles and crashes occur, not as often as the normal law indicates, but more often than the normal law can possibly foresee. As Bernstein states:
At the extremes, the market is not a random walk. At the extremes, the market is more likely to destroy fortunes than to create them. The stock market is a risky place.