loanshark

We looked at this briefly in earlier posts, but to recap it is expressed as:
S − I = Y − E = X − M
where:
S = Savings
I = Investment
Y = Income
E = Expenditure
X = Exports
M = Imports
This can actually be expanded by breaking down “savings” into public and private savings such that:
( Sp + Sg ) − I = X − M
where:
Sp = Private savings
Sg = Government savings
Here, government “dis-saving” reflects having a budget deficit. Thus, from this, we can see immediately that there is a possible link between a budget deficit and a trade deficit. If a country’s budget deficit continues to rise, this is reflected on the left-hand side of the equation by an increasingly negative value for Sg . Unless this is offset by a rise in private savings or a fall in investment, this will eventually mean that the left-hand side of the equation turns negative. Of necessity in this circumstance, the right-hand side of the equation must also be negative, which in turn means that the country has a trade deficit. Thus, a budget deficit can lead to a trade or a current account deficit. The link is not necessarily automatic. However, it should be assumed that widening budget deficits, if sustained over time, lead to widening trade and current account deficits. If we extend this, we see that at some stage widening current account deficits will become unsustainable, requiring a real exchange rate depreciation. Thus, widening budget deficits may eventually require real (and thus nominal) exchange rate depreciation.
Economists are not generally thought of as prone to high emotion. Yet, one has to say that the accounting identity is like a work of great art, hiding great intricacy and complexity behind the veneer of apparent simplicity. From this accounting identity, we can see how economies adjust to changes in fundamental conditions and therefore how exchange rates should adjust to those conditions. Again, this is probably best shown through an example.

So far in this blog, the focus has been on trying to create new exchange rate models based on capital flows to try to improve forecasting accuracy. As necessary as this is, it does not mean we abandon the traditional exchange rate models. Classical economic theory has provided the foundations for exchange rate analysis. The purpose of establishing a framework known as currency economics is to be able to combine the new with the exchange rate models and use both in a more targeted and focused way. Any major differences between this framework of currency economics and classical economics are more methodological than ideological. The traditional exchange rate models, focusing as they do on such factors as trade, productivity, prices, money supply and the current account balance, help provide the long-term exchange rate view. Capital flow-based models are considerably more helpful and accurate in terms of predicting short-term exchange rate moves.
However, these two types of exchange rate model should not necessarily be viewed as polar opposites. The very purpose of establishing a specific framework known as currency economics is to create an integrated approach to exchange rate analysis, which is capable of answering the riddles of short-, medium- and long-term exchange rate moves. The two sides do have some common ground, and it should be no surprise that this common ground is to be found in the balance of payments model — given that it focuses both on trade and capital flows. Within this, there are three specific analytical tools which should be of use to currency market practitioners in bridging the gap between short- and long-term exchange rate analysis:
The standard accounting identity for economic adjustment
The J-curve
The REER

When market conditions are perceived as stable according to the market indicators used by the index, they are of necessity optimum for investors to be in risk-seeking mode. Equally, when market conditions are unstable, this is synonymous with investor risk-aversion or avoidance. The focus for such an analytical tool has been the investor community. However, currency speculators and corporations can also use a risk appetite or instability indicator with which to trade or manage their currency risk.
Using the context of the 1997–1998 crisis period, the Instability Index seeks to measure risk appetite using leverage, credit spreads and cross-market (equity, fixed income and foreign exchange) options’ volatilities as its three benchmarks. The period of June 1997–September 1998 accelerated the focus in trying to measure risk appetite as first the Asian countries experienced currency crises one after another and then Russia devalued and defaulted in August 1998. Conceptually, everyone knew what it meant to be risk-averse, but measuring it was another matter, let alone trying to use that measurement to predict future phases of risk appetite. While investment banks needed analytical tools to track the overall risk appetite of clients across markets, particularly in times of stress, academics and policymakers also needed such a tool for the purpose of measuring just how orderly or disorderly market conditions were in order to help guide future policy responses. The Instability Index, which was formalized in 1999, is just such a guide and includes three main components:
De-leveraging — There are two parts to this. The first looks at the relationship in the currency market between the US dollar (as an equity-linked, higher yielding asset) and the likes of the Swiss franc (as a traditional safe-haven currency) and Japanese yen (as a low interest rate, funding currency). During times of market stress, the US dollar tends to lose ground against these as “leverage” or risk is cut. The second component looks at US and European bank equities as a measure of market “leverage”.
Credit spreads — In the US dollar credit markets, this tracks the spreads between BBB-rated industrial credits, emerging market Brady bonds and swaps to Treasuries, while it also tracks Euro swap spreads to Bunds. The overall reading gives a very good indicator of investor risk-tolerance.
Implied volatilities — Across the three asset classes of equities, debt and currencies, tracking three-month implied volatilities gives a good idea as to demand levels for option-related protection structures from investors. Option implied volatility tends to rise more sharply during asset market slumps than when asset prices are rising.
The advantage with the readings within this index is that they are relatively easily available and updated daily. Thus, using these three components to represent the degree of “stability” or “instability” in the market, we can have a daily indicator of risk appetite, which can in turn be used as a forecasting tool for currency markets.

Within such a cycle, there is obviously a substantial amount of intraday and intraweek volatility, reflecting swings in market sentiment. Traditionally, economists have either ignored such short- term periods or suggested they could not be predicted. While flow and technical analysis have done much to dispel such a view, recent work on the relationship between “risk appetite” and asset prices has made a real breakthrough in terms of being able to predict those short-term swings in sentiment and in turn how they affect currency and asset prices. Risk appetite or market sentiment are not easily definable concepts given that what these are focusing on is the investor’s willingness or otherwise to invest — which is not always based on logic! Despite such difficulties, the private sector has over the past few years been hard at work creating “risk appetite indicators” to measure overall conditions for risk tolerance across currency and asset markets. Within the investment banks, JP Morgan created its “LCPI Index” Bank of America has its “Global Hazard Indicator” and Salomon Smith Barney its “Instability Index”. For the purpose of an example, we will focus on the Instability Index. The index was originally created to track levels of risk appetite or conversely “instability” for fixed income investors. However, because it uses cross-market indicators for this purpose, we can also use it for managing and trading currency risk.
Risk appetite has become an increasingly important concept, not just because of the need to create more accurate models for forecasting short-term currency moves, but also because the last few years have shown a marked pick-up in cross-asset market volatility. Indeed, one can go as far as to suggest that as the globalization of capital flows has proceeded, so volatility has increased. Risk appetite is essentially a capital flow event and its relationship is directly proportional to the size of capital flows involved. For this very reason, just as capital flows across borders have grown exponentially, so the degree to which capital flows affect currency markets has grown proportionately. A crisis in one country is no longer isolated but is transmitted instantly around the global financial system. Investors who face losses in that one market may seek to take profit on other positions in order to offset those losses, thus creating a domino effect in hitherto unrelated markets.
Extreme bouts of cross-market volatility such as were seen in the wake of the ERM, Mexican and Russian currency crises prompted interest in creating risk appetite indicators which, if not predicting actual crises themselves, would at least be able to predict significant moves in terms of general investor risk tolerance. For this purpose, categories or levels of risk tolerance also had to be created. The three generally accepted categories within most such risk appetite models for this purpose are:
Risk-seeking
Risk-neutral
Risk-aversion
As the focus of the Instability Index is on market volatility and “instability” for the purpose of alerting investors to such bouts of unwanted volatility, these categories can be modified slightly for the purpose of focusing on such instability:
Stable
Neutral
Unstable

As with the supposed efficiency of markets, which does not actually work in practice, so there is the idea that supply and demand are completely independent of one another. If this were so, price trends could not exist because markets would instantly work to eliminate any supply or demand imbalances. The fact that this does not happen and that price trends do occur suggests that there are lags, sometimes substantial lags, before such imbalances can be eliminated. In addition, supply and demand are not completely objective concepts. Rather, at least in part, they reflect the views expressed by those market participants that make up that supply and demand. In other words, supply and demand are both cause and effect.
So much for the theory, what does this mean in practice? Actually, to a market practitioner, these ideas are relatively obvious. Currency interbank dealers know full well that particular flows will have more effect than others and thus will materially affect the supply/demand dynamics. Say a large multinational corporation transacts an end-of-quarter hedge in the Euro–dollar exchange rate. Granted, this is the most liquid currency pair in the world, but if the flow is large enough it may affect both current market pricing and future market thinking. Of course the term “future” means different things to different people. To the multinational, it means months at least if not years. To the interbank dealer transacting the flow in the market place it means minutes or hours at most. Currency markets are essentially flow-driven over short time frames, and therefore it is vital to understand the relationship between supply and demand dynamics.
Just as supply and demand are not independent of one another and are both cause and effect, so the relationship between “speculation” and economic fundamentals is also not just one-way. Economic theory requires that markets eliminate “speculative excess”, thus restoring equilibrium. However, we have already established that “equilibrium” is actually a moving target. If the “speculative excess” is the extent to which markets diverge from equilibrium, then that “speculative excess” is also a moving target. Finally, the presumption of economists is that economic fundamentals drive market pricing and thus to an extent speculative excess. Even if we accept this, it has also to be acknowledged that speculative excess can in turn affect economic fundamentals. This is best proven by example.