Dynamic hedging only has the potential of working on deep markets.
Arbitrage pricing can reveal proper prices in smaller less liquid markets if there are larger, more liquid markets to compare against. The process cannot work in reverse, except by accident.Leon Cooperman Likes These Real Estate, Credit And Private Equity Funds
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The recent case of JP Morgan’s hedging activities bring to light an observation that should be clear to all but isn’t. Hedging only works when you are small relative to the markets in which you hedge.
Let’s consider tranched credit index default swaps. We can create models where the prices of each tranche can be calculated given default frequency and severity. But default is not a constant beast. Defaults come in waves, and when incidence is high, so is severity of loss. Vice-versa when incidence is low, leaving aside fraud.
We might have a good idea of where credit default should trade for a basket of corporate debtors “credits” so long as we look at the thing as a whole, and don’t carve it up. In general, a basket of borrowers is easier to predict than individual borrowers.
But the basket gets difficult when we split it up into first loss, second loss, third loss, etc. claims where different parties lose their capital at differing levels of total loss. Yes, in theory, we can come up with prices. We can even come up with hedge ratios that show the theoretical tradeoff between tranches as losses increase or decrease, which might work, might, if you are a small player in that market.
Woe betide you, if you do anything too fancy, and you are big relative to the market. Because you are big, you have affected the prices of the market. Price relationships that were normal before you arrived have shifted and reflect your interests, which in the short-run makes your accounting look better. As the bubble grows, those investing in the bubble look better. But as the bubble expands, those that have invested in it find a wave of cash fighting against them, but it doesn’t matter, because momentum investors are still buying.
At the end, the large investor amid the bubble finds himself stranded. The market knows his positions, and he can’t make trades to extricate himself, because the terms are onerous.
Look, I used to trade small-issue lesser-known bonds. I only bought stuff that I knew would be money-good, i.e. pay off. In that case, you have the option of speculating when spreads are wide, and selling when they get tight. But if you do that with bonds that you don’t know whether they will likely pay in full, the ability to hedge is meaningless, because your hedge could break in a default.
And so it was for JP Morgan. When you get too big relative to the market, it had better be when you are the buyer or seller of last resort, and you are catching the turn. But in normal markets, bigs are pigs, and are likely to be slaughtered.
It doesn’t matter what your model says is the right tradeoff if you are too big relative to the market. Your own actions have poisoned the signals that your models receive.
Amaranth fell into this same bucket, with a talented energy trader who understood how the market generally worked. As his success grew, so did his size, and he didn’t realize that the size of the fund was distorting market prices. At the end there was one unlikely scenario that was unhedged, and that was the scenario that occurred, and the results led to the collapse of the fund.
If Amaranth had been smaller they could have traded out of it. At their size, they were “elephants in an elevator.”
Size matters, and for investment purposes, smaller is better. And for the most part, less complex is better too. Don’t demand liquidity from markets, or you will lose. If liquidity come to your door, and it seems to be a good deal, wave it in.