Category Archives: markets

Central Clearing can economize on collateral

Reforming the financial system involves not only the grand public battles over legislation and rulemaking, but also the substantial trenchwork that falls to staffers in the many agencies responsible for carrying out the mandates. And it is heartening to observe this work advance. One of the many interesting analyses being produced en route is a study by Daniel Heller and Nicholas Vause at the Bank for International Settlements (BIS), the international organization of central banks. The purpose of the report is to produce an estimate of the financial resources that Central Counterparties (CCPs) would need to safely clear interest rate and credit default swaps. Central clearing of derivative trades is one of the major mandates of the Dodd-Frank Financial Reform Act in the U.S. and of comparable reforms in Europe.

In a number of our previous posts, we have emphasized that end-users have much to gain from the central clearing mandate—see here, here, here and here. Central clearing creates the possibility to reduce the total amount of credit risk in the system, lowering the overall costs to the various parties using derivatives, including non-financial companies seeking to hedge their commercial risk. One reflection of how risks can be minimized, depending upon how the mandates are implemented, shows up in Graph 6 of this BIS study, reproduced below.

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Cash & Carry, #4: Other resolutions to the puzzle

We began this series of posts recapping the finding that a currency carry trade investment has historically produced high return relative to the low risk. This finding is not consistent with models in finance that focus on the correlation between an investment’s return and the return on some benchmark stock portfolio. Using these models, and looking at the historical distribution of returns, the carry trade looks like a good bet, even accounting for bad outcomes. Posts #2 and #3 in the series reported on one route of the research effort to explain the puzzle, which attributes the abnormal return to the “peso problem”. But other researchers have been pursuing different routes. To wrap up this series, we’ll quickly mention some of this work.

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Cash & Carry, #3: the Price of “Peso” Risk

In our previous post in this series, we highlighted a line of research by Burnside et al. that explains the profitability of the carry trade as a “peso” problem. That is, the historical data doesn’t completely reflect all of the bad outcomes that may arise. The as yet unobserved bad outcomes are known as “peso events”. The historical profitability of the carry trade, isn’t the complete story. It’s a biased sample. The few bad outcomes not yet observed resolve the puzzle. Investors are worried about these “peso events” and price the currencies accordingly.

In this post we want to delve a bit more into this issue of how investors may be pricing “peso events.”

There are two different aspects to pricing “peso events.” First, we must assess the probability of an extreme negative event. Second, we must assess the discount we want to apply to that negative event. This second aspect is what we want to focus on.

In finance all dollars are not created equal. Cash received in states when the investor otherwise has plenty cash is not worth as much as cash received in states when the investor otherwise is short cash.

The standard models for pricing risk – such as the CAPM, the Fama-French and the Carhart factor models, among others – are based on what is called a linear stochastic discount factor across all states. They assume a linear relationship between the discount factor and some underlying risk factor. In the CAPM, that would mean a linear relationship between the discount factor and the payoff on the market portfolio. But there isn’t any natural presumption in favor of linearity in the discount factor.

The argument made by Burnside et al. is that the discount factor is not linear. Instead, a very high discount factor is applied to the as yet unobserved “peso events.” And this very high discount factor is essential in making sense of the historic profitability of the carry trade strategy.

In order to make the argument more accessible, we have constructed a simple numerical example:

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Cash & Carry, #2: Pesos and Steamrollers

In a previous post, we reported on the evidence that the carry trade strategy – investing in currencies with high interest rates and borrowing in currencies with low interest rates – earns high returns with low risk. In this post we describe in more detail some of what is known about the risk and return tradeoff on a carry trade investment. Our focus is on the risk and the cost of risk.

The returns to the carry trade, like the returns on a number of other trading strategies, are sometimes characterized by the phrase “They take the stairs up, but the elevator down.” That is, the profits accumulate gradually, but once in a while there arises a very, very large loss. The figure below, taken from a recently published paper by Burnside, Eichenbaum, Kleschelski and Rebelo (here is the free working paper version), shows the distribution of returns to a carry trade strategy between 1987 and 2009. The shaded bars are the observed sample. The black line is a normal distribution with the same mean and standard deviation as the sample.

What you can see in the figure is that the sample has a fatter left tail than the normal distribution, as highlighted by the red circle. Those few bad returns are the events at issue. They are very bad, and although few, they occur much more often than is predicted by the normal distribution. And these few extreme events matter to the total return of the strategy: Harvard’s Jeffrey Frankel noted that “In one week of 1998 (October 4-10), the yen rose 16% against the dollar, thereby suddenly reversing years of profitable carry trade from the low-interest-rate yen into the higher-paying dollar.”[1]

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Cash & Carry, #1: Where to Park?

Holding cash is a key risk management tool, and corporations are holding more cash than ever. Where should the corporate treasury park that cash? In which currency should these balances be held–US dollars, Euros, Yen, Swiss Francs, Australian Dollars or what? The choice of the currency denomination of cash investments is the flip side of the problem of selecting the currency denomination of debt. Modern capital markets confront corporate treasury with a broad array of opportunities for borrowing and investing in various currencies.

Assuming the expected returns in all currencies are fairly priced for risk (i.e., Uncovered Interest Rate Parity holds), the answer will depend on the multinational structure of the company’s business and its exposure to fluctuations in the different currencies. Some companies will be better off stashing cash in dollar denominated securities because they anticipate future net cash outflows denominated in dollars, while others will be better off stashing cash in Euro denominated securities and others in Yen, and so on. Many companies will have an optimal mix of cash stashed in a variety of currencies. We’ll call the company’s optimal mix under the assumption of Uncovered Interest Rate Parity the company’s Benchmark currency portfolio.

Other factors will matter, too, such as international tax rules, concerns about capital controls and so on.

But what about that big assumption we made up front? What if expected returns in all currencies are not fairly priced for risk, so that Uncovered Interest Rate Parity does not hold? What if investments in certain currencies are generating big profits, while investments in other currencies are generating losses?

It is well documented that a speculative portfolio built by purchasing high interest rate currencies and selling low interest rates currencies—the carry trade portfolio—has been very profitable over many years.The figure below, taken from a recently published paper by Burnside, Eichenbaum, Kleschelski and Rebelo (here is the free working paper version), shows the cumulative return to an investment in the carry trade portfolio between 1976 and 2009 as compared against the cumulative return to an investment in US stocks and the return to an investment in US Treasury Bills.

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Central clearing lowers end-user costs

One of the most controversial aspects of the financial reform in the US and Europe is the mandate that many derivatives trades will have to be cleared in central counterparty clearinghouses (CCPs). CCPs stand behind the losses in the event that a trader defaults.  To protect the clearinghouse against trader defaults, users of derivative contracts processed in CCPs will need to post margins.

But margins are expensive; they require traders to have spare cash or unused credit capacity; and margins need to be explicitly accounted for. Opponents of clearing have directed their criticisms at these points, complaining that margins crowd out other corporate investment. They also argue that margins have negative implications at a more macro level: variation margins can trigger panics; and out of concentrating risk, CCPs will become dangerous dens of systemic risk. Altogether, clearing under the proposed rules won’t change things for the better, they argue.

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The unorthodox model of risk pricing behind the UK EMR #5: creating value out of thin air

The UK’s Electricity Market Reform White Paper claims to have quantified how offering low-C generators a hedge creates value:

In our central scenario, the FiT CfD reduces the cost of decarbonisation to 2030 by £2.5 billion compared to using the Premium Feed-in Tariff (PFiT) to deliver the same investment. ( § 2.3, p. 37)

Given that my previous post says there can be no net value at all, I find this claim startling and it should be informative to investigate exactly how this number is arrived at.

Bottom line: (i) they calculate the benefit of a hedge captured by the low-C generator, but, (ii) they completely ignore the cost to the taxpayer or ratepayer from providing that hedge.

Ignoring (ii), the cost to taxpayer or ratepayer, is obviously the big problem, and we could stop there. But let’s take the bait and go ahead to examine (i), how they calculate the benefit of hedge captured by the low-C generator.

The White Paper purports to have assessed how providing the hedge (in the form of a Contracts for Differences, or CfD) lowers the cost of capital for different types of projects. Here is Figure 7 from the White Paper with the results:

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The unorthodox model of risk pricing behind the UK EMR #4: no value to hedging

The UK’s Electricity Market Reform (EMR) White Paper suggests that providing low-C generation projects with a hedge of the wholesale electricity price can lower the cost of providing low-C electricity. Can this be?

No.

A fairly priced hedge changes both the project’s risk and it’s return. The first order effect of the two is to leave the risk-adjusted cost of the project unchanged. This is commonly known as the M-M Proposition of Hedging.

In an earlier post I showed a stylized graph of a low-C generator’s revenue, costs and profit margin, all unhedged, and associated with them a present value for each of the three cash flow streams using a simple risk-pricing model. Now, using the exact same risk-pricing model I can construct a fair value hedge. A fair value hedge is one with NPV=0. The hedge is a swap in which the low-C generator sells the floating cash flow, tied to the wholesale electricity price, and receives the fixed cash flow:

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The unorthodox model of risk pricing behind the UK EMR #3: toss out the principle of value-additivity

This post takes up the core theoretical issue behind the EMR’s advocacy for having public authorities assume risk from low carbon generators. The White Paper claims that the profit margin of a gas-fired generating station is naturally hedged because the price of electricity moves in line with the price of gas. In contrast, the profit margin of a low-carbon technology generators is exposed to electricity price risk, since the operating costs of a low-carbon generator does not fluctuate with the electricity price. Consequently, the White Paper claims,

(i) even if the levelized cost of electricity were approximately the same for gas-fired and low carbon technologies,

(ii) nevertheless, investors would prefer the former over the latter.

Can (i) and (ii) be true at the same time?

No. Not if we are operating in an orthodox model of risk pricing. Not if there are robust capital markets where each risk has a unique price. Not if the principle of value additivity applies — “If we have two streams of cash flow, A and B, then the present value of A+B is equal to the present value of A plus the present value of B.” (Brealey, Myers and Allen, Ch. 17).

To examine claims (i) and (ii) more carefully, I constructed the two figures below based on Newbery (2008) which is one of the background papers underpinning the EMR’s White Paper. Similar figures have been used in other academic papers underpinning the EMR’s White Paper.

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The unorthodox model of risk pricing behind the UK EMR #2: the government as derivatives dealer!

The central aspect of the UK government’s proposed Electricity Market Reform (EMR ) with which this series of posts is concerned is the desire to shift all risk from private investors in generation onto public authorities. One example of this is the recommendation that the public authorities get into the risk management business by selling electricity derivatives to low carbon generators. In the EMR these are called Contracts for Differences (CfD). In the finance world they’re called electricity price swaps.  The EMR bundles these swaps together with a price premium paid to low carbon generators–the Feed-in Tariff–and so calls the full package a FiT CfD.

The figure above is taken from the EMR White Paper and shows how this swap works. The swap has a strike price of £70/MWh shown at the top red line. The black line shows the realized wholesale electricity price. When the wholesale price is below the strike price, the public authority pays the generator the difference, shown in dark green. When the wholesale price is above the strike price — which in the diagram happens briefly late in the period shown — the generator pays the public authority the difference.

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