The standard approach of the efficient markets concept dangerously underestimates the risks in the financial system. The long-term capital management crash of 1998 is one of many examples of the disastrous effects of market risk underestimation. In the 1970s and 1980s, this approach became ?...the guiding principle for many of the standard tools of modern finance . . . taught in business schools and shrink-wrapped into financial software packages... [It] is a house built on sand.? (Mandelbrot 2008). The efficient market theory promised ?expected? returns through clear, simple risk assessment and profile models based on risk aversion. In this model, option markets flourished and structured finance boomed (CDOs...). This model was adopted by financial markets, economics department and business schools who trained students on the basis of the modern portfolio theory (MPT), which attempts to maximise returns for a given amount of risk, or, alternatively, minimises risk for a given amount of return.Professor B. Mandelbrot (1924-2010) changed the way we view the world by introducing the fractal geometry of nature. He gave us a tool to describe different systems with common characteristics. Applied to finance it allows us to understand market instability as described by Professor H. Minsky (1919-1996). Wild prices, fat tails (that is, heavy-tailed market distributions that exhibit extreme skewness or kurtosis), and the long-term memory effect, led Mandelbrot to view the financial series as fractal series.Fractals are everywhere from cauliflowers to our blood vessels. Fractals have helped model the weather, measure online traffic, compress computer files, analyse seismic tremors and the distributions of galaxies. Mandelbrot hope was to build a stronger financial industry and an enhanced system of regulation. He developed a multifractal model with variable market time, exponential price distributions, and fractal generators. Some say that Mandelbrot described the financial system without explaining it, but no one can elucidate it. He was a wise observer and had a special way of scrutinizing objects and nature... thinking in a fractal way in finance is about observing, analysing and trading opportunities out off the markets anomalies! His hope was that people will accept the reality of risky markets and stop pretending otherwise. By identifying markets structures, what we essentially learn from B. Mandelbrot is that markets risks can be modelled so that people can avoid big losses - the question he left unanswered is how to do this in practice. A measure of risk should take into account long term price dependence or the tendency of bad news to come in flocks. Our focus shouldn't be on how to predict prices; but on how to foresee risks. Understanding the nature of the market allows us to use the clustering property of volatility as a tool to measure and forecast risk, ?opportunities are in small packages of time, large price changes tend to cluster and follow one another. If there was a large price change yesterday, then today is a risky day.? (Mandelbrot 2008,p.233). We may not be able to forecast direction, but with this understanding we can get out of the market at its clustery periods and reduce the chances of loss.

It is really not so complicated. We live in a sort of binary world. Either things go as expected, or all coordinated plans fall apart. It is possible for people to make adjustments, so that things can fall apart in smaller increments.So what can we say about the probability that things will fall apart tomorrow, and the size of the increment before a new arrangement is settled? We can say a lot more than nothing. We can say that what will happen tomorrow is associated with what happened today and yesterday.The only problem has been the manner in which the association between tomorrow and today has been modeled. People say a stock which has moved 1 today and 1 yesterday, is likely to move the square root of 2 over the next two days. It is a nice model, but simply not calibrated with as many influences as are available.It is extremely basic, and a nice first step, to predict the next two moves in a single time series off previous moves in the same time series. But to get useful result, you have calibrate the model onto the larger class of stocks and other asset prices at different times. A stock is not just like itself recently, but also similar to many additional things, such as other stocks and assets at other times.Put differently, you can predict the volatility of something not by using random guess for tail thickness, but by assuming it is like the price of other things at other times. So tomorrow it could be like itself yesterday. Or it could be like wheat in 1979. I don't think anyone is pursuing certainty, rather they feel they are pulling stuff out of a hat when they plug the price of wheat in 1979 into their models.

If all risk were gone we would all case to exist!Eat risk for breakfast, lunch and dinner and you will stay alive! What is a volcano with no chance of erupting? A dead volcano, or at least half dead!Risk is the life blood of mortals!

Last edited by Collector on November 2nd, 2011, 11:00 pm, edited 1 time in total.

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QuoteOriginally posted by: CollectorIf all risk were gone we would all case to exist!But there are a couple of sure things in life for which all hedging is fruitless.

Step over the gap, not into it. Watch the space between platform and train.

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Finance ain't physics. To properly quantify risk one must assume something is known about the future. Thus all risk management is relative to some standard assumptions.

Volatility has 2 main characteristics, it clusters and reverts to the mean. we can use that knowledge to improve our risk metrics and avoid big losses. however we cannot time it. market timing is the mystery and nothing can be done about it. The mystery of the financial markets is key to its existence, understanding it is key to our survival.

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