The toxic assets that continue to occupy the balance sheets of most key US banks, and that as a result make these firms a no go area for many investors, are still central to the continuing problem in the US financial system. Solutions have been slow in coming as the crisis is now entering its third year.
The idea that Obama and Geithner are pushing, in essentially enticing investors to take on the risk from the banks, is hardly revolutionary policy. However, given how CDO technology works, now is the very first time it has been sensible to push this solution - any time prior to this and the volatility of many of these assets would have scared away anyone but the most foolhardy of investors. Not to mention the banks themselves were struggling with generating a meaningful valuation. However, it seems that Obama's timing, by accident or design, is possibly perfect. The opportunity in this 'toxic' asset giveaway is a fabulous one for an investor willing to do a little homework now that the first grass shoots of stability in the US housing market have appeared.
There are three key hazards to negotiate before this opportunity becomes a good one. And if you do this properly, the opportunity could be an excellent one:
1. Do your homework on the mortgage pool - some 'subprime' pools are more rotten than others. Finding a subprime mortgage pool with a fundamental supporting market and solid reasons for a stabilising of house prices is key. Some subprime areas, where all the neighbours were borrowing money they couldn't afford, could well become ghost towns. Prices in areas like this are trapped in a race to the bottom. For these pools, any signs of recovery are more a pause before the downward march is resumed rather than a turnaround. Other pools, where subprime mortgages have a fundamental floor on account of solid surrounding economic support, are the pools you need to identify. This requires local analysis. If you can't find a pool you like, stop right there.
2. Once you feel you have a good idea how your chosen mortgage pool is likely to behave, you need to value the CDO derivative correctly. Conventional valuation tools do not work for these securities in volatile markets. Indeed, many CDO tranches generate an effect which is the opposite of diversity - hence why they are so risky. You need to develop a more fundamental approach to valuing these assets and play through some different scenarios from now to asset maturity to frame the risk you are taking on. If you use quantitative techniques you don't fully understand, it is likely they will lead you up the garden path.
3. The Treasury is committed to extending a floor to your asset - it is likely they will value this floor very generously giving you an asymmetric pay off. Governments are not always known for their financial acumen and they also need to price this stuff to sell. The value in this floor is a function of you fully understanding the last two hazards.
If you understand your mortgage pool, how your CDO will behave for different forward scenarios, and then combine this knowledge with a generous Treasury floor, these assets will be a fabulous opportunity. However, get on the wrong side of one of these issues, and it could be very painful one.
And bid low ! Let your scenario analysis drive the size of what you will pay for the asset ensuring that if your price is filled that you make money even if we see further house price falls and rising default rates from today. This is as much a giveaway as an auction. No-one will be bidding aggressively.
Happy hunting,
Andy Shaw
Sunday, March 29, 2009
Saturday, March 14, 2009
Fundamentals vs Technicals
Hi,
A quick steer for those having trouble in this volatile market environment. When you buy an equity, you are in essence buying primarily 'speculation', particularly in a market like this. As the price of a stock evolves through time, solid fundamentals in a company will help push this speculation in your direction if you are long the equity. However, in a market as volatile as this, the equity will be moved less by fundamentals and more by technical flows whether they are driven by fear or speculation. In an environment as saturated in fear as we are, 'speculation' is a very volatile commodity to trade. The uncertainty around equities currently is huge and no matter how much homework you do, or how well you know a stock, you can never confidently predict the short term capital flows, or technicals, that will push the price of your stock around.
If you can cope with taking short term MTM losses then now is a great time to pick up some equity bargains in solid, fundamentally sound businesses. However, if the idea of 10 - 20% swings in price keeps you awake at night in sweats, and you want a more stable reward for doing your homework, your opportunities are to be found in shorter dated corporate bonds.
Shorter dated corporate bonds have their price anchored to a fundamental event on a definite date in the future - the bond's maturity date. If you know a stock well, you'll know the balance sheet well, and if you know the balance sheet well, you should be able to predict with accuracy whether or not the notional of the bond will be repaid. Beware companies with volatile business models that have a large percentage of their debt redeeming in the near future. If you are looking for a maturity sweet spot, try 2 - 3yrs with the total notional of debt redeeming inbetween now and then being less than 20% of the company total. For those with even less of a risk appetite, go for maturities less than 2yrs.
Using fundamentals to help you in an environment where technicals are causing huge swings in perceived company health is a savvy investment approach. The market will one day calm down, and the balance of what primarily moves stock prices will move back towards fundamental perfromance and away from panic selling. But not for a while.
One other option is to use equity derivatives to put boundaries in value around your investment. If you understand how derivatives work, they can be a very powerful tool in dampening uncertainty in your portfolio. But take caution, in the wrong hands, derivatives can cause more problems than they solve. Just ask a CDO salesman.
Happy hunting,
Andy Shaw
A quick steer for those having trouble in this volatile market environment. When you buy an equity, you are in essence buying primarily 'speculation', particularly in a market like this. As the price of a stock evolves through time, solid fundamentals in a company will help push this speculation in your direction if you are long the equity. However, in a market as volatile as this, the equity will be moved less by fundamentals and more by technical flows whether they are driven by fear or speculation. In an environment as saturated in fear as we are, 'speculation' is a very volatile commodity to trade. The uncertainty around equities currently is huge and no matter how much homework you do, or how well you know a stock, you can never confidently predict the short term capital flows, or technicals, that will push the price of your stock around.
If you can cope with taking short term MTM losses then now is a great time to pick up some equity bargains in solid, fundamentally sound businesses. However, if the idea of 10 - 20% swings in price keeps you awake at night in sweats, and you want a more stable reward for doing your homework, your opportunities are to be found in shorter dated corporate bonds.
Shorter dated corporate bonds have their price anchored to a fundamental event on a definite date in the future - the bond's maturity date. If you know a stock well, you'll know the balance sheet well, and if you know the balance sheet well, you should be able to predict with accuracy whether or not the notional of the bond will be repaid. Beware companies with volatile business models that have a large percentage of their debt redeeming in the near future. If you are looking for a maturity sweet spot, try 2 - 3yrs with the total notional of debt redeeming inbetween now and then being less than 20% of the company total. For those with even less of a risk appetite, go for maturities less than 2yrs.
Using fundamentals to help you in an environment where technicals are causing huge swings in perceived company health is a savvy investment approach. The market will one day calm down, and the balance of what primarily moves stock prices will move back towards fundamental perfromance and away from panic selling. But not for a while.
One other option is to use equity derivatives to put boundaries in value around your investment. If you understand how derivatives work, they can be a very powerful tool in dampening uncertainty in your portfolio. But take caution, in the wrong hands, derivatives can cause more problems than they solve. Just ask a CDO salesman.
Happy hunting,
Andy Shaw
Thursday, March 12, 2009
Risk management and statistical models
Hi,
http://business.timesonline.co.uk/tol/business/columnists/article5871007.ece
More articles appearing in the press about risk management and the failings of financial risk models. I've addressed some of these topics in a previous blog already but thought I'd comment on this article specifically. The authors are barking up the right tree but are missing a few key issues.
Risk models don't make mistakes, risk managers make mistakes. This is a little like the maxim, "guns don't kill people, people kill people". You could have all the possible statistical models in the known universe but they will be of little help as you'll probably just confuse yourself in a fog of model output and make even more mistakes. The more models you have, especially if they are very technical, the more bogged down in maintaining the model's integrity you will become and the less time you will have for managing your risk. A sweet spot for the number of risk models you need is a maximum of 2, minimum of 1. Pick a couple of models you understand well rather than commissioning the latest unproven research from a crackpot, neural networking, aerodynamicist turned risk manager. If you don't understand how a model works, how can you undestand when to use its output or when to ignore it?
Once you have your tools, then you're ready to play. And this leads onto the next key point. The clue here is in the name, 'risk manager'. Risk managers aren't risk observers. They are risk 'managers'. There are a variety of instruments out there for them to manage risks with. Risk managers earn their money by deploying clever and cost effective hedging strategies which support the company's business strategy.
Remember, markets are the collective will of all those people able to deploy capital on any particular day. Or, in alternative terms, the market will move in response to the volume of buyers and sellers in any particular product. No model in the world will ever capture this effect accurately given the idiosyncratic whims and flaws of human nature.
So once you are efficiently hedged, it doesn't matter how irrationally crazy the rest of the investing world gets, and it can get pretty crazy when you look at some of the recent peaks and troughs of certain assets. Through clever hedging you have turned your downside from an unexpected unkown, based on the whim of the market, to a number you know regardless of whatever scenario the market throws up. And businesses love known knowns. Just ask Rummy Rumsfeld.
Simple huh. Yet I haven't seen one article out there that outlines this point.
Happy hunting
Andy Shaw
http://business.timesonline.co.uk/tol/business/columnists/article5871007.ece
More articles appearing in the press about risk management and the failings of financial risk models. I've addressed some of these topics in a previous blog already but thought I'd comment on this article specifically. The authors are barking up the right tree but are missing a few key issues.
Risk models don't make mistakes, risk managers make mistakes. This is a little like the maxim, "guns don't kill people, people kill people". You could have all the possible statistical models in the known universe but they will be of little help as you'll probably just confuse yourself in a fog of model output and make even more mistakes. The more models you have, especially if they are very technical, the more bogged down in maintaining the model's integrity you will become and the less time you will have for managing your risk. A sweet spot for the number of risk models you need is a maximum of 2, minimum of 1. Pick a couple of models you understand well rather than commissioning the latest unproven research from a crackpot, neural networking, aerodynamicist turned risk manager. If you don't understand how a model works, how can you undestand when to use its output or when to ignore it?
Once you have your tools, then you're ready to play. And this leads onto the next key point. The clue here is in the name, 'risk manager'. Risk managers aren't risk observers. They are risk 'managers'. There are a variety of instruments out there for them to manage risks with. Risk managers earn their money by deploying clever and cost effective hedging strategies which support the company's business strategy.
Remember, markets are the collective will of all those people able to deploy capital on any particular day. Or, in alternative terms, the market will move in response to the volume of buyers and sellers in any particular product. No model in the world will ever capture this effect accurately given the idiosyncratic whims and flaws of human nature.
So once you are efficiently hedged, it doesn't matter how irrationally crazy the rest of the investing world gets, and it can get pretty crazy when you look at some of the recent peaks and troughs of certain assets. Through clever hedging you have turned your downside from an unexpected unkown, based on the whim of the market, to a number you know regardless of whatever scenario the market throws up. And businesses love known knowns. Just ask Rummy Rumsfeld.
Simple huh. Yet I haven't seen one article out there that outlines this point.
Happy hunting
Andy Shaw
Monday, March 2, 2009
The future of economics research - Chaos theory and behavioural psychology
Hi,
http://www.timesonline.co.uk/tol/comment/columnists/article5689642.ece
In recent weeks, journalists and market pundits, like Anatole Kaletsky at The Times, have predicted that economic research is going to branch out into a number of different areas, leaving behind the 'flawed' principles that have driven much of recent economic study. Bell curves/ normal distributions or Monte Carlo VaR models, as tools for risk managers, have come in for particular criticism. 'Chaos Theory' and 'behavioural psychology' are two of the more popular topics that have been suggested as new avenues for economists to explore. I'm not going to dwell on what Chaos Theory is, or any other new theory for that matter, (search on wikipedia if you'd like a general explanation) but what I am going to address is how these theories, and the implications taken from them, aren't actually new and have been used in a handful of areas of the financial system for a number of years now.
Recently, I've heard statements from Wall St. CEO's saying that the markets are in chaos. If markets are indeed 'chaotic', and 'Chaos Theory' will be to economics what The Theory of Relativity was to Physics, what implications does that have for real world practitioners? Pension funds still need to match assets and liabilities despite this chaos. Insurance firms who have minimum capital requirements remain exposed to risk but must meet these restrictions despite the huge amount of uncertainty flooding our economic system.
The good news is that you don't need to rewind all the way back to Poincare and restart your education in Economics from scratch. You also don't have to wait for new 'chaos' research to start being published to take advantage of the findings that will come out of this new research. The reason is this: the conclusions one can draw, given the fact that markets present as chaotic, and the conclusions one can draw from the fact that markets are driven by human beings rather than bell curves, have been utilised in certain pockets of the financial system by cutting edge risk managers for a number of years. These methods are relatively new and they have recently been thoroughly tested through the ravages of the credit crunch, and, put simply, they work. The expertise and the experts are already out there if you know where to look.
One problem, however, is that these new techniques were far from ubiquitous as the credit crunch struck. In fact, they were very rare. Had they not been, many firms would have been in a much better position to cope. During the past two decades, as the complexity of financial products has exploded, many risk managers and many senior financial managers made the mistake of believing that the bell curve inspired statistical models they used to measure a firm's risk were somehow so sophisticated as to be able to predict the future. This led them to accept risk they didn't fully understand because it fit into their model.
Now, if markets present as chaotic, and you are measuring risk using a bell curve model, you should realise that, amongst other things, you are leaving yourself exposed to a sudden change in market environment. Bell curve Monte Carlo models might be sophisticated maths but they aren't magic. They also can't predict the future and in fact, they are quite poor at predicting the future. To set large amounts of strategy and risk appetite based off of bell curve Monte Carlo model output, without further risk analysis, is a big mistake if you believe markets are chaotic.
Of course, risk managers will learn. One crucial lesson they must embrace is this: any statistical risk model (and not just the popular bell curve Monte Carlo ones) MUST be seen for what it is - nothing more than help for a company to understand the economy in which it is operating, and most importantly the changing face of the risks to which it is exposed. Fortune tellers these models are not. There are occasional market environments when these models should be ignored. A risk manager's skill comes in knowing when to ignore the model to make his decision or knowing when to use his model output to shape his decision.
These risk and capital models, whether Bell curve inspired or otherwise, are one bullet in the risk manager's arsenal. The weaknesses and failings in the model must be fully understood and planned for. The key lesson is to change attitude from an unthinking and unquestioning strategy based on flawed models to the following:
1. A desire to push the boundaries of understanding with regards to the niche you hold in the economy. Statistical models of a variety of different types are needed to do this but they must be pulled apart and questioned by the risk managers who built them. Risk managers need to be some of the smartest people in their company.
2. Once your niche is understood as much as possible, you can set about formulating a strategy based off of market expectations and ALSO dynamically hedging this strategy to defend against unexpected events. And you will have many unexpected events.
Chaotic markets present excellent opportunities as well as problems, and any business strategy must be dynamic and flexible enough to change as the market environment dictates. One lesson this crisis has taught us is that the moment you think the dust has settled and you know what is around the corner is the moment you're surprised.
Happy hunting,
Andy Shaw
http://www.timesonline.co.uk/tol/comment/columnists/article5689642.ece
In recent weeks, journalists and market pundits, like Anatole Kaletsky at The Times, have predicted that economic research is going to branch out into a number of different areas, leaving behind the 'flawed' principles that have driven much of recent economic study. Bell curves/ normal distributions or Monte Carlo VaR models, as tools for risk managers, have come in for particular criticism. 'Chaos Theory' and 'behavioural psychology' are two of the more popular topics that have been suggested as new avenues for economists to explore. I'm not going to dwell on what Chaos Theory is, or any other new theory for that matter, (search on wikipedia if you'd like a general explanation) but what I am going to address is how these theories, and the implications taken from them, aren't actually new and have been used in a handful of areas of the financial system for a number of years now.
Recently, I've heard statements from Wall St. CEO's saying that the markets are in chaos. If markets are indeed 'chaotic', and 'Chaos Theory' will be to economics what The Theory of Relativity was to Physics, what implications does that have for real world practitioners? Pension funds still need to match assets and liabilities despite this chaos. Insurance firms who have minimum capital requirements remain exposed to risk but must meet these restrictions despite the huge amount of uncertainty flooding our economic system.
The good news is that you don't need to rewind all the way back to Poincare and restart your education in Economics from scratch. You also don't have to wait for new 'chaos' research to start being published to take advantage of the findings that will come out of this new research. The reason is this: the conclusions one can draw, given the fact that markets present as chaotic, and the conclusions one can draw from the fact that markets are driven by human beings rather than bell curves, have been utilised in certain pockets of the financial system by cutting edge risk managers for a number of years. These methods are relatively new and they have recently been thoroughly tested through the ravages of the credit crunch, and, put simply, they work. The expertise and the experts are already out there if you know where to look.
One problem, however, is that these new techniques were far from ubiquitous as the credit crunch struck. In fact, they were very rare. Had they not been, many firms would have been in a much better position to cope. During the past two decades, as the complexity of financial products has exploded, many risk managers and many senior financial managers made the mistake of believing that the bell curve inspired statistical models they used to measure a firm's risk were somehow so sophisticated as to be able to predict the future. This led them to accept risk they didn't fully understand because it fit into their model.
Now, if markets present as chaotic, and you are measuring risk using a bell curve model, you should realise that, amongst other things, you are leaving yourself exposed to a sudden change in market environment. Bell curve Monte Carlo models might be sophisticated maths but they aren't magic. They also can't predict the future and in fact, they are quite poor at predicting the future. To set large amounts of strategy and risk appetite based off of bell curve Monte Carlo model output, without further risk analysis, is a big mistake if you believe markets are chaotic.
Of course, risk managers will learn. One crucial lesson they must embrace is this: any statistical risk model (and not just the popular bell curve Monte Carlo ones) MUST be seen for what it is - nothing more than help for a company to understand the economy in which it is operating, and most importantly the changing face of the risks to which it is exposed. Fortune tellers these models are not. There are occasional market environments when these models should be ignored. A risk manager's skill comes in knowing when to ignore the model to make his decision or knowing when to use his model output to shape his decision.
These risk and capital models, whether Bell curve inspired or otherwise, are one bullet in the risk manager's arsenal. The weaknesses and failings in the model must be fully understood and planned for. The key lesson is to change attitude from an unthinking and unquestioning strategy based on flawed models to the following:
1. A desire to push the boundaries of understanding with regards to the niche you hold in the economy. Statistical models of a variety of different types are needed to do this but they must be pulled apart and questioned by the risk managers who built them. Risk managers need to be some of the smartest people in their company.
2. Once your niche is understood as much as possible, you can set about formulating a strategy based off of market expectations and ALSO dynamically hedging this strategy to defend against unexpected events. And you will have many unexpected events.
Chaotic markets present excellent opportunities as well as problems, and any business strategy must be dynamic and flexible enough to change as the market environment dictates. One lesson this crisis has taught us is that the moment you think the dust has settled and you know what is around the corner is the moment you're surprised.
Happy hunting,
Andy Shaw
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