Top Recommendations by “the most profitable Bank”

Recently, following recommendations have been provided:

• Long Ringitts, SGD and Taiwanese dollars – all funded by USD.
• Sell pound-sterling against yen.
• Sell gold.
• Borrow in CAD, GBP, USD and buy BRL, RUB, CZK.
• Sell 10-year CAD bond futures and receive fixed on 10-year CHF swaps.

How the "Masters of the Universe" think about Exchange Rates!

In a recent excellent, if perhaps deliciously short, report issued by the most profitable bank this year entitled "The Foreign Exchange Market" -- one of the sub-reports attempts to forecast the exchange rates for the coming year. What struck me about it is -- other than the predictions they make (I have my issues with that... see below) -- is the elegance of the underlying method. The way do is as follows:

1. Changes in Terms of Trade (= price of exports divided by price of imports) is a function of changing commodity prices (energy, industrial metals, agriculture, live stock).
2. Extract sensitivity estimates (the coefficients in a regression) to predict terms of trade.
3. Changes in Real Exchange Rates ( = price of one unit foreign currency in domestic currency * ratio of foreign and domestic price levels) is a function of two key parameters.
   
• Terms of Trade
• Relative productivity levels -- measured by, say, per-capita output per hour etc.,
  
4. Perform regressions on #3, using #2 to arrive at new estimates for real-exchange rates.
5. Convert real exchange rates into nominal exchange rates.

Amongst key predictions are USD-CAD = 1.10; USD-INR = 50.1. i.e., their model supposedly predicts that the the Canadian dollar is expected to depreciate from the present levels, and so is the USD expected to appreciate against the Indian Rupee. Since, they do not explicitly mention all the concerned control variables in the exchange rate attribution -- it is difficult to really validate their claims, even intuitively.

My own guess is that there are three key parameters that affect the short term exchange rate fluctuations:

1. Global capital flows -- that chase the second-order effects anticipated changes in terms of trade.
2. Changes in US deficits (budgetary and trade) -- this is particularly accentuated by the coming US electoral-cycle.
3. Idiosyncratic events -- particularly emerging market macroeconomic instabilities.
   

So, I suspect their analysis are largely driven by "true" long term economic factors, while the intermediate fluctuations are more complicated beasts -- and therein lies, as Shakespeare writes, the rub.

Mathematics for Derivatives

Often while reading about financial derivatives -- a lot of terminology comes to fore. Some are financial while the more esoteric ones are often mathematical. This document has some of them. Probability(errors) = 1 almost.surely.

Risk in the Times of Reversal

Standard Black Scholes pricing assumes a constant vol. The underlying implication being that the logarithm of the returns is normally distributed – and thus contained in it, a constant standard deviation (the constant volatility). In the market, there are other factors are play – such as supply/demand, risk-premia etc., -- all that contribute to, what Keynes memorably called “animal spirits” in the option pricing market. Typically, if the market expects a greater likelihood of the underlying exchange rate to go past the strike, the calls on the currency tends to get priced more expensively than the puts.

An option on call USD–CAD put refers to the call on the USD and the put on the CAD. So, the holder of the option has the right to buy the USD (convert the CAD notional at a prespecified rate). Equivalently, the holder of the option has the right to sell the CAD at a prespecified rate.

A spot price of 0.97, i.e., one USD can be exchanged for 0.97 CAD; with a strike of 1.01 on a call USD-CAD put refers to the right to buy one USD in exchange for 1.01 CAD. Tersely, the spot is 0.97 and the strike is 1.01 with a CAD-put. On the expiry date if the spot prices are 1.00, then the buyer of the call (with say 101 CAD in his account) would not exercise his option to buy a USD at 1.01 CAD when he can easily buy the same USD at 1.00 CAD. In this example, the USD is anticipated to appreciate. So, the call option on the USD-CAD is evidently ‘worth more” than a corresponding put option. i.e., if an appreciation is anticipated the corresponding call is priced at a higher level. This supply-demand forces are not a part of the Black Scholes derivation. Since, most parameters are fixed – the only “tweak-able” parameter is the vol – or the implied vol.

A 25-delta call refers to a call option where the strike above the spot (thus an out of the money option). So, in the above – it is clear that a 25-delta call has different implied vol than a 25-delta put. The “25” in the above refers to the fact if the underlying exchange rate increases by 1, the corresponding the call option value rises by 0.25. So, to arrive at a delta-hedge a corresponding position has to be taken in the underlying. The market convention of 25-delta is agreed upon – as one that is sufficient to capture the expectations regarding changing underlying prices. Of course, you can have 10-delta, 50-delta and so on.

A risk reversal is thus, the difference in implied vols between, ceteris paribus, out of the money calls and out of the money puts. Quoted thus, a rise in the risk-reversals means that as the currency appreciates, the volatilities are likely to rise. Instead, if risk-reversal are quoted as put – call. Then a rise in risk-reversal refers to the fact that as currency depreciates the vols are likely to rise.

A useful example of the trade flow is as follows: (courtesy gfmi.com)

Assume an appreciation of the USD against the CAD over the next 3 month period (mean-reversion??). 3-month 25 delta USD-CAD risk reversal of 0.15 -.28% at a vol of 8.5% means:

1. Buy the 25 delta USD call/CAD put at 8.65% and sell the USD put/CAD call at 8.5%. The trader shells out 0.15%. i.e., he is paying a skew-premium of 0.15% in anticipation of a USD rise.

2. Sell the 25 delta USD call/CAD put at 8.78% and buy the USD call/CAD put at 8.5%. The trader earns the .28% spread.

On option desks, rules of thumb Rule! So, to extract the implied skewness, it is pretty standard to (a) calculate the risk-reversal (b) calculate risk-reversal per-unit of ATM vol. Risk reversals.

The big challenge is what to do when appreciations have different vols than depreciations. If you know how to deal with that – then there is some money to be made and a heck-of-career to be had!

Dollar Got the Blues... by Clarence "Gatemouth" Brown

CAD, Crude and Risk Aversion... A conjecture

There is a whole lot of play in the financial press that claims the rising oil demands are due to (a) increased consumption by BRIC and EM (b) lack of refinery capacity (c) rising cost of production of crude in the Persian Gulf (d) geopolitical tensions etc., No doubt some, if not all of these forces are at play in the market.

However, it must be noted that the oil markets across the globe are quoted in USD. So, there is no doubt a linkage between crude, USD values. To think about this more visual, I have plotted the relationship here. Typical the Swiss franc is the defacto currency of choice, when global uncertainity rises. i.e., Investors tend to flock to the Swiss franc or Gold, when they assume the value of the USD is on a decline. I have used USD-CHF exchange rate along with Crude prices -- to arrive at the following. (Note correlation is not causation... but this is pretty interesting). A more formal analysis should control for risk-aversion (proxied by USD-CHF), growth in consumption etc.,

Nevertheless, on a trading floor -- I would be very surprised if the marginal gains from more sophisticated regression analysis are any better over a short period of time. In the long run, of course, more sophisticated analysis might reveal much -- but, by then the underlying structural parameters have changed...

In this simple case, fitting a simple straight line through the data points from 2006 onwards, we get the simple results. At a USD-CHF = 1, the crude prices are expected to be around 97.4. Today the Swiss Franc is around 1.123 and the crude (WTI Cushing) is quoted at 94.09.

Here is the key point. If one assumes that exchange rates tend to overshoot -- i.e., because of rigidities elsewhere in the economy (supply and demand of contracts done in the past), the fastest readjustments tend to happen in temporary misalignments of asset prices. So, if you think the USD-CHF has overshot in its depreciating trend, then one can make a plausible argument that the crude prices have shot through as well.

In essence, the tenuous (but I think, fairly justifiable) relationship is between global risk-aversion (vis-a-vis USD) and crude prices. If risk-aversion rises (i.e., USD appreciates) then crude prices must fall. If risk-aversion decreases, the crude prices must rise. If Jim O'Neill at Goldman is correct (rising capital flows into EM) -- I would read it as fall in risk-aversion.

Presumably then, Crude prices above 100 are to come soon; and ineluctably then the CAD is to rally again.

Loonie Tunes...

I first heard about the TarSands, courtesy the ever generous Leigh Shankland. He was super excited about it, but I was in highschool and I had other things to be excited about. The latest NewYorker has an wholesome piece about the TarSands in Alberta. It deals with the energy costs in producing a barrel of oil (around 1/3 a barrel! -- without dipping into the subtleties...); the environmental impacts (pollution, cancer) and the GoldRush spirit at work that trampels most voices. There are clear reasons why this phenomenon will last. Extracting oil from tarsands costs between 30-40USD per barrel, around 174 billion barrels of recoverable oil, etc etc., While reading, it is clear that this phenomenon is here to stay -- over the next 30-50 years. And to some extent, it is suffice to say that the TarSands are only getting started -- there are other firms coming into the mining industry, firms keen on supplying energy to the mining firms, firms that are laying pipelines and so on and so forth. Over 3/4th of a percentge of Canadian GDP is expected to be spent in 2008. It is fair to say, I think, before the lifetime of most readers of this note the long term impact of the TarSands -- environmentally and in raising global supply of oil is dramatic.

One area where the effects are demonstrably clear is the exchange rate. Rising investments in the TarSands coupled with rising commodity costs -- causes increased profitability of Canadian firms. The financial herd comes chasing the possibility of a superior return which puts an upward pressure on the CAD. On top, the speculative capital anticipating this upward pressure on the CAD follows through as well, hoping for a quick turn around before month end P&L numbers are issued. There is the obvious sense that the rising CAD affects other Canadian exports -- and to a reasonable degree this is true. However, the rising CAD affects, in the short term, only those purchases made on the margin (for eg., that extra software license from a Canadian firm for eg.,). However, the rising exchange rate over a two-three year period can and will distort the capital formation of the Canadian economy. New investments will divert itself from existing manufacturing base and move towards the paraphernalia required for the oil industry. It is of course critical to distinguish between the dying industries of Canada and the ones forced to close out due to the rising exchange rate. Perhaps, it might be possible to wean that information from the manufacturing data etc.,

My own sense is that that is seems the loonie has found a new home in the 1.05-1.10 USD range. But, this is only a resting point. Over the next six months -- as oil prices continue their climb upwards and US housing numbers deteriorate along with growth -- one should be surprised if the loonie kisses 1.15-1.20 USD.

If I were a Canadian firm earning USD six months, I would be buying some CAD forwards...

Hugo Chavez and Cristina Kirchner: Hot or Not Hot?

Venezuela and Argentina are different countries (duh!); but for the credit-markets and emerging markets portfolios, they are reasonably close and different! Sort of like the Cain and Abel of the Latin-American fixed income portfolios. Who's who, who knows. They are all (grand) children of God (or at least, Simon Bolivar). And in recent times, one has been more volatile than the other -- depending on what time-frame you investigate.

As per credit market data, the 5-year CDS for Argentina and Venezuela are trading at the same premium rates (around the band of 240bps). Over the past year and half, in order for you buy protection against the possibility of Venezuelan credit event on its loans as opposed to Argentina credit event – the spreads between the two have converged. This convergence in CDS spreads was caused by a greater confidence in Argentina and declining macroeconomic sentiments in Venezuela.

In fact, up until December 2006, Argentina’s spread seems to mimic the directionality of Venezuela’s spread movements. This tango, of sorts, meets an abrupt end in late December when Venezuela begins its nationalization of oil companies. Subsequently, the possibility of Venezuela pulling out of the IMF led to an increased spike in its premiums as well. The credit market fears in late summer led to a serious liquidity crunch (overnight rates climbed to 90%!!). Add to this political tomfoolery by Hugo Chavez (opposition arrests, indiscreet pressuring of central bank officials, closing of television stations etc.,). From a spread in July 2006, of 140bps on notional; today the spread is around 260bps – an approximate increase of 85%. All of this has occurred when oil prices were rampaging from around 55USD per barrel to the approximately 95USD per barrel. i.e., despite the filling of coffers in Venezuela, the credit markets were increasingly apprehensive of the possibility of “some” credit event, or even worsening of credit quality.

In contrast, Argentina has made gingerly adjustments to “normalcy”. This has come in the form of political stability, some swallowing of the bitter financial pill (staying out of the financial markets for a year after paying around 35 cents on the dollar for bonds – for 140bn., bonds!) thanks in part to Nestor Kirchners’ hard nosed bargaining, helped with generic boom in internal aggregate demand as opposed to aggregate global demand (13% of growth) etc., All this said, there is still uncertainty – most keenly evidenced by Argentines emigrating out to Spain, Canada and even Mexico. Unemployment rate has fallen to around 8.4%, inflation hovers around 8-9%. The real story is that year or year surplus has declined by around 60% compared to last year. (i.e., Spending increased. Is it me or do I see a relationship between government spending the election of Cristina Kirchner!)

In essence, the question is – who will the credit markets bet against! A loopy and statist petrocracy run by a junta or preternaturally prone to crises democracy. What has seemed obvious in the past few months is that – (a) every time Venezuela does something silly (claim to nationalize even more industries in the name of the people), the spreads have increased by 10bps or more, only for the rates to stay up there (b) the markets are willing to let Argentina have a pass, (Is it the democracy factor?) and has increasingly found itself comfortable with the non-Washington consensus based policies of the Kirchners. A subtle, but difficult to reason-out-completely-point, is that increasingly the largest holder of on-the-run Argentine bonds are the Venezuelans. So, in some sense, Argentine government spending is financed by the petrocrats in Caracas.

So, now what?

The primary bet are on the following events, and the subjective probabilities:

• Chavez goes to nationalize some more: About 40-60%

• Kirchner can’t control spending: About 60%

• Oil prices rally to 120USD in next six months About 45%

• Political turmoil in Venezuela About 10%
  

Over the next six months, I would bet on Venezuela’s spreads rising in the market – and the Argentine spreads trailing behind. So, sell Argentine protection and buy Venezuelan protection. It is imperative to note that in Argentina, one is dealing with credit risk that works its way through government finances. In contrast, in Venezuela one is dealing with “event” risk. So, in the strictest sense – it is not the same underlying propagating mechanism.

This is imperfect knowledge; and hence precisely more fun!

Decomposing Credit & Systemic Fears

A useful measure of how to think about how the market prices two key "unknowns" -- idiosyncratic credit risk and system wide disturbance -- is to use the TED spreads. The TED spread can be created by trading Futures positions in US Treasuries and Eurodollar markets. Implicit in the prices quoted (via the IMM convention) are interest rates implied. So a Eurodollar quoted at 98, implies a rate of 100-98 = 2%. The USD TED Spreads are thus created by going long US Treasury futures and short Eurodollar futures -- thus creating a spread. For more details see here.

As of yesterday, the 3M TED spreads (for US, UK and Euro) have widened while the 6M TED spreads have reduced thee difference. In the short term, the market continues to price a worsening credit environment; while over the 6M period -- these spreads have declined, because the underlying trades are assumed to be liquid, well executed and easy to offload. In essence, the system is assumed to be working.

So, what to do if you believe that there is an extended stretch of trouble that the market is not pricing? i.e., Systemic crises is likely to worsen. You are then betting on the spreads to widen. Note that, TED = 3M Eurodollar - 3M Treasury. This can happen by Treasury yields falling, EuroDollar futures implied rates rising or both yields moving in opposite direction. Being pessimistic is equivalent to being long TED spreads, which equivalent to buying Treasury futures and short-selling Eurodollar futures.

If you are feeling optimistic about the economy at large, sell Treasury futures and buy Eurodollar futures...

As an aside, I read about Christian Siva-Jothy's monster trades post the first plane attack on 911, predictably he bet on yields on Eurodollars falling (and went long Eurodollar notes). I am not sure what the TED spreads did in those hours of 911... Any guesses?

Lessons from Leamer: Part 2

Continuing from previous post.

1. Housing shows up in the GDP accounting via employment generation. Price appreciation of houses is not part of GDP; and more importantly, increased land prices today if booked as an asset, a liability has to be entered. Where? Liabilities for future buyers. This is transfer of wealth from future generations to present generations!
2. The stickiness of housing prices downwards means, most importantly, price cycles follow sales volume cycle. Also, the volatility of the housing volumes is much higher than the price.
3. Sellers develop their expectations of prices from a backward perspective (“what did I pay for it compared to the offer price?”). Buyers have forward looking price expectations (“what will I get for the house 5 years from now”). So, sales only happen when there is a high bid price by sellers.
4. In a housing boom, the fastest appreciation happens for small houses with low-income zip codes (and smaller square footage = condos and small homes). Predictably, during a bust – they get hit the most.
5. To avoid business cycle fluctuations – one must avoid housing cycle fluctuations and job-losses in consumer durables.
6. Monetary policy that acknowledges the two factors – must face up to the fact that if real interest rates fall temporarily, then for equilibrium level of housing stock will return to “normal”, only if production and sales fall and allow a return to the mean. In contrast, if real interest rates fall permanently, then equilibrium levels of housing stock will rise.
7. Monetary policy that accounts for housing investment is a difficult inter-temporal resource allocation issue.
8. Today, one observes the presence of weak housing starts (new houses being built) and increased inflation – resulting in a conflict for what the “right” policy prescription ought to be.
9. In case of policy choices to be made between housing starts and inflation – there is no real conflict.
10. The best predictor for Fed Funds rate is the 10-year Treasury bond yields.
11. Its the Housing Cycle!
    

Lessons from Leamer (Part 1)

Professor Edward Leamer has written a very interesting paper; and was presented at the Jackson Hole conference. I have been going through it in detail -- and I must admit it is a remarkable piece of analytical detective work. Following two posts are dedicated to his work. Although the original is nearly 70+ pages -- it is written in a very reader friendly style. So, worth the effort. For the rest, here is a quick summary. Caveat Lector!

1. Conclusions can be drawn of effects of policy X, if there are control and treatment groups. In macroeconomics, we only have non-experimental data. So, we rely on “story-telling”.
2. Monetary policy affects economy via housing-related decisions. Tempering business cycles means figuring out how housing-related choices are affected.
3. Inflation is a “daily” phenomenon, while housing is reinforced by a “wave”.
4. Monetary policy at different stages of the housing cycle – can exacerbate or diminish the extent of hurt that happens when a boom declines.
5. Housing booms are very susceptible to interest rate changes at the end of the boom, rather than in the early and middle stages.
6. Historically, the US economy has been growing at 3% over the past 30 years – despite all kinds of real, monetary and technological shocks. Monetary and fiscal policy must restrict itself to smoothening out the cycles (the amplitude and the frequency).
7. Contributions to long run growth are led by, in order of importance from a 2005 perspective, Consumer services, Non Durable Consumer Spending, Durable Consumer Spending, Equipment, State and Local Expenditure, Defense expenditure, Residences etc., i.e., Residences do not contribute substantively in long term growth.
8. For business-cycle fluctuations, Residences are very important. Typically, Residences contribute to the weakness in GDP growth before the “recession” starts and contribute above normal before the “recession” ends. This is in contrast to equipment and software sales. i.e., Residential spending is a pro-cyclical predictor of GDP growth. Equipment sales just mirrors GDP growth rate.
9. To address decline in GDP growth, one must address the “consumer” side of the equation and not the business side. So, Monetary policy must explicitly take into account Residential and Durables levels and volatilities.
10. There have been 10 U.S. recessions. Only two were driven by “production” side (i.e., by lack of demand on the business side) – post-Korean war and 2000/01 internet bubble collapse. Rest of the recessions have been caused by lack of consumer demand.
11. Housing prices are sticky downwards – i.e., prices don’t fall all that much. So, the natural way the market clears is by massive reduction in demand. This reduction is demand affects GDP/employment.