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Forecasts and Risk assessments. Can we predict the future?

Posted by Adrian on November 28, 2007

Over the last year some of the biggest losses in financial history have occurred within the banking sector, especially the investment banks, hedge funds and larger retail banks. As discussed on morbius glass “finance and economy strategy and society”, the majority, if not all of these losses have occurred from mortgage debt. Attributed by the massive loan defaults of the American mortgage market in the last 12 mths from 2006 through into late 2007.

The question is could this crisis in the banking sector be avoidable? I have briefly discussed this topic in ‘Wall Street risk management and judgment comprised by blindness, madness and greed’, and also ‘The complexities of Wall Street and the simplicity of the boom bust cycle’; the easiest answer to give, in respect to the huge errors, overestimations and over enthusiasm, especially in rating investment debt, selling various SIV’s (Structured Investment Vehicle’s) from the mortgage market, was greed. It would seem that greed blinded everyone involved in the packaging of investment vehicle’s like CDO’s (Collateralized Debt Obligations). The greed that occurred, seemed to be an arrogant optimism of ‘boom’ economics, a convenient mental removal of boom bust cycles, in which risk management went out the door, literally. Replaced by a bizarre mix of blind optimism, arrogance and a detachment from reality. But, if that was the case, and the human flaws were somewhat calculated into a mathematical formula, from a risk management team – why didn’t the computer mathematical models pick up what humans may conveniently have overlooked?

In my opinion it would appear that there was too much reliance on a streamlined computer models to gauge the markets, in other words the technicality of the financial markets became supreme as far as risk evaluation. From computerworlduk.com “Greed, analytics and the mortgage lending crisis”:

“If you had to pinpoint one area where analytics really was a factor, it would be the rating agencies” that rated mortgage-backed securities, says Beardsell (Mike Beardsell, director of risk model analytics at Loan Performance). These “innovative” mortgage products presented a challenge. The agencies’ statistical models, which relied on historical records of how traditional mortgage loans performed, had to be adjusted. But “the market was changing faster than the models could keep up,” argues Beardsell. And the users of those models made a fatal assumption “

Technical analysis is extremely helpful tool, but it still relies on your own judgment and assessment outside from a mathematical formula. For stocks, FX, option and other derivative trading, 50 day and 100 day averages, overbought and under bought signals play an important role, more particularly the CCI type gauges. But all technical gauges and analysis can show a limited, non emotional and at times subjective indicator of the markets. Subjective in the sense, you can by human intervention overly manipulate technical signals. I have seen this in FX trading and Option trading, more particularly I have seen time frame shifts (on trading platforms) from 1 min to 15 mins to one day, on a broad perspective this can make a trading platform look different to other trading platforms trading the same derivatives, at the same time with the same risk. This can cause a messy overestimation of markets, especially when one can pick and choose the ‘platform’, as traders do jump from time frames to gauge the markets. This is a risk and in someways they are trying to conceptualize their own perspective, which is possibly clouding good objective judgment. This is from a traders perspective, but what of the Subprime mortgage defaults. Why was risk so broadly overlooked from their analytical programs and platforms? From: computerworlduk.com “Greed, analytics and the mortgage lending crisis“:

“In the subprime market, many borrowers could not afford the payments on adjustable rate loans two or three years later, once the low teaser rates expired. The reset rates on those loans created large rises in monthly payments, and some borrowers are now seeing their monthly payments increase by $1,000 or more. Lenders were fully aware that borrowers could not afford those payments. But in a booming housing market where values were increasing at double-digit rates, lenders just assumed that borrowers would always have more than enough equity to refinance later.”

“The value was determined by statistical models. And those models assumed that home values would continue to rise. In fact, such an assumption was critical to the marketing of the structured securities based on those mortgages. “The economics of the securitisation would be negatively impacted by a zero growth assumption,” Beardsell says, never mind a negative one.”

My point is, statistical models and graphs can show you what you want to see, thus deceptively convincing one that the process is correct. This was caused by a blinding greed factor which tuned off natural risk assessment in a person. If there wasn’t such a mad race for profits, the natural risk assessment in a person would in turn reevaluate the data. This didn’t happen.
So, it appears the computer models did get it wrong and in some ways have increased the likelihood of a wider economic crash, from “The anatomy of a crash: What Market upheaval of 1987 say about today”:

“Markets are different now. Average daily volumes on the New York Stock Exchange alone have increased tenfold since 1987, the venues on which stocks can be traded have proliferated and the speed of trading is unimaginably faster. The range of hedging opportunities using derivatives is much larger than it was.

The view from the floor is that the improvements in technology will not prevent crashes. “But it will help them happen that much faster,” says Mr Cashin, the veteran broker.

Andrew Lo, an economist at the Massachusetts Institute of Technology, argues that these developments have also made crashes more likely. “We have a much more well-integrated and well-connected set of financial markets. Disruption in one market can very easily spill over into other financial markets.”

He draws comparisons with recent events, which saw a number of quantitatively managed hedge funds – which use complex mathematical algorithms to trade swiftly among different stocks and asset classes – suffer huge losses in August amid the fall-out from the credit crisis. Portfolio insurance, Mr Lo suggests, was “a microcosm of what we see today, writ large”.

But what if it is impossible to predict anything, let alone predicting the rise and fall of financial markets. According to Nassim Nicholas Taleb, the author of The Black Swan: The Impact of the Highly Improbable. You can’t predict the world, or the changes that occur in it. It is a pure random set of errors and luck, and how one applies their luck when presented with opportunity. I have not read The Black Swan, but I have visited his website and I have read many articles about his philosophy. Which I believe holds some merit, but unfortunately does not convince me that we live in complete uncertainty, to the point that risk analysis is, according to Taleb “charlatans” who think they can map the future.”

I believe as I suspect Taleb does, that people generally are unprepared for a crisis, possible relying on too much ‘order’, or a comfortably believing that an inflexible strategy is the right path. But never the less, learning from history and anticipation of events is what human beings are good at; but unfortunately any intuition or a learned ‘gut instinct’ (from life experience) has been removed at an early age of a child’s development and replaced by a belief structure, or power structure of authority and ‘their’ analysis and forecasts. Which every human is capable of doing, if taught and encouraged – which in turn is likely to give rise to strong independent thought and decision making. So in that sense we would not rely on an analyst that works at Merill Lynch. In fact we would probably dispute it and re-analyze his or her data, and look at it with a degree of skepticism, due to the fact the analyst is working for an investment bank, and he/she works with the banks interest coming first.

The fact is when risk is presented and put on the table, one should anticipate how that is going to effect them. In a sense forecast that risk, or the problems associated with it. According to Taleb no one could anticipate September 11 2001 terrorist attacks on the World Trade Center in NYC, I agree to a point. But, one could assume that attack was going to occur eventually. In fact I remember the day it happened and a family member said at the time, ‘I am not surprised’. With growing provocative policies from neo conservatives in the West, mixed with a reemerging of Islamic fundamentalism, something was going to give – when it was going to occur was the ‘guess’. Although it could be argued the arrogance of ‘it can’t happen’ here mentally , created a lapse of real threat analysis of potential attacks on US soil. Also a bad habit of short memories occurred too when the World Trade Center was targeted once before in 1993 by an Islamic terrorist group, quote from BBC ‘on this day article’,

A suspected car bomb has exploded underneath the World Trade Center in New York killing at least five people and injuring scores more.The bombing has shocked America which had seemed immune from acts of terrorism that have plagued other parts of the world.”

Maybe the ‘guess’ or ‘assumption’ of a another pending attack could have been narrowed to specifics, due to the fact the building was targeted again with the devastating September 11 2001 attacks.

But as a review of The Black Swan (in the Telegraph.co.uk) indicates, Taleb refers to events like September 11, and my relative who saw it coming (on a broad perspective) as a Black Swan event in which the human mind then normalizes the events,

“The trouble is, we can’t cope with these Black Swans, and so we normalise them in our minds. When something bizarre happens, we tell ourselves, retrospectively, that it was bound to happen. We just didn’t see it coming. And then we brace ourselves in case it happens again. But then something else happens, again completely out of the blue. Taleb says: ‘the sources of Black Swans today have multiplied beyond measurability. In the primitive environment they were limited to newly encountered wild animals, new enemies, and abrupt weather changes.’

The problem with that assertion, in context to the September 11 WTC attacks, is that the event did happen before in 1993 albeit a smaller event, but nevertheless a possible precursor or indicator to a larger attack (it happened again in 2001). Could the event of 1993 WTC attacks have been memorised, or at least registered in my relatives brain. So he drew a correlation to the bigger, far more destructive event of 2001 attack. In which constituted to his ‘lack of surprise’?

I am more inclined to believe in the recursion theory, or Chonesthesia (Mental Time Travel). A relatively new theory based in psychology, in which our mind records data from the past to project possible futures. As our minds are constantly returning to the past to see what outcomes could be made in future events. According to Endel Tulving, PhD from apg.org “What makes mental time travel possible?” “…allows people to update information critical to surviving, thriving and dealing with changes in their world.”

The recursion aspect of the Chonestheisa theory is the repetitive mental visits of past events to project a future outcome. I remember once when I was younger and I was going to start at a new school, the night before starting at the new school I dreamt of the school, the kids, the teachers and how I thought the first day was going to be like – as I was nervous the night before and according to the chronesthesia theory, the human mind collects past events and tries to formulate a future scenario. This is needed, according to the theory, so that you can prepare for situations that may lie in front of you in the future event.

From apa.org “What makes mental time travel possible”?

“You don’t need mental time travel to remember a chemical formula or your mother’s maiden name,” he explained. “You can know a lot of things without mental time travel, but you can’t remember events from your past, or anticipate your future, without it.”

Tulving went on to explain how and why humans have adapted chronesthesia–a learned capability absent in other animals and human infants–to advance their survival. And he urged other psychologists to help build a research base on its workings.”

An interesting theory and one worth looking into further in regards to cognitive and theory of the mind studies. I’ve always remembered that quote from Taoist teachings, “know before knowing” and the classic Sun Tzu Art of War quote, “Know your self, and don’t know the enemy, you win one and lose one. Know yourself and know the enemy you will win every time”.

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4 Responses to “Forecasts and Risk assessments. Can we predict the future?”

  1. […] The point I am trying to make here is the continued equilibrium in everything just doesn’t exist, for some reason we don’t accept that things will come to end. I discussed this in an older post I wrote at the end of 2007 called Forecasts and Risk assessments. Can we predict the future? […]

  2. […] a comment » Back in November 2007 I wrote a blog post in morbius glass titled Forecasts and Risk assessments. Can we predict the future? The post it’s self was written in light of the mortgage market collapse in the US, forecasts […]

  3. […] more harm than good. As a society and humanity are intermixed with calm and turmoil. As discussed Forecasts and Risk assessments. Can we predict the future?, I actually believe that humans are very good at adapting to environments when they change […]

  4. Ego-W said

    Ego-W…

    […]Forecasts and Risk assessments. Can we predict the future? « morbius glass[…]…

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