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Changing conditions

admin — Mon, 29 Mar 2010 13:50:20 +0000

Asset portfolio diversification theory depends on historic correlations being stable and reflecting some genuine underlying relationship. A high historic correlation on losses in two regions may have been because both regions depended to a large extent on a single, common industry. If that is no longer the case there is no reason to expect past correlations to be a good indicator of future correlations. This same argument can be put for equity holdings in VaR type analysis but a major difference is that the time frames involved in managing market risk are very different from those for credit risk.

First Order Price Risks

admin — Fri, 13 Nov 2009 14:33:40 +0000

Most basic valuation models assume that the change of the price of a financial instrument is directly proportional to the change in an underlying factor, in other words that a linear relationship exists. In many instances this is a first order approximation only and is equivalent to measuring the slope of the price graph against this factor. This ignores any effects due to curvature of the graph arising from higher order and secondary relationships:
Local currency interest rate instruments. Interest rate instruments include bonds, asset backed securities, short-term paper, forward rate agreements (FRAs) and interest rate swaps. The value of these instruments varies with the discount rate applied to their cashflows:
Risk-free rates and term spreads. The discount rates applied to risk-free government Treasury bonds and bills are based on yields-to-maturity taken from the yield curve. These yields are affected by the overall economic environment, inflationary expectations and monetary policy. Yields may change in equal amounts across all maturities or in a non-parallel way as shown by changes in term spreads. Term spreads are defined by the difference between yields on short- and long-duration risk-free instruments.
Credit and basis spreads. The discount rate applied to corporate and other non risk- free debt issues can be viewed as the yield on an equivalent risk-free instrument plus a credit spread. Credit spreads reflect the higher returns investors demand to compensate for the higher risks. In general, credit spreads tend to widen as an economy heads into recession and narrow during recovery. Individual issuer and issue credit spreads also vary depending on conditions at a single company.
Basis spreads are the spreads between benchmark rates such as those obtained from government securities and those from an interbank rate, such as LIBOR, against which floating rate debt instruments are priced.
The value of interest rate instruments is also affected by secondary factors such as the passage of time and the effects of embedded options such as those present in callable and putable bonds.
Foreign currency exposures. Exposures to foreign exchange risk may be direct, as in a US bank having an outright cash position in euros or being committed to deliver a quantity of foreign currency at some specified future date. They may also be indirect arising from positions held in other instruments priced in a foreign currency, such as bonds and equities. First order price changes are the result of changes in exchange rates. Other effects may arise because of changes in the discount rate used to value positions in foreign currency and convexity:
Spot rates. Spot rates are determined by supply and demand and by macroeconomic fundamentals. These are used to mark-to-market values of assets and liabilities concerned. Some currencies tend to move together when their economies are closely interlinked and affected by similar external factors.
Interest rate differentials. Forward rates are determined by spot rates and by the differential between foreign risk-free interest rates and those of the base currency.
Both spot and forward positions can be affected by central bank actions, by the use of managed exchange rate systems and from the imposition of capital controls.
Equity positions. Stock prices are determined by supply and demand which in turn are affected by changes in the macroeconomic and interest environment and perceptions of the intrinsic value of stocks:
Supply and demand. Stock prices in general are affected by overall demand for equities. This is, arguably, determined by changing expectations of future earnings prospects and by perceptions of the value of the discount rate, as “determined” by risk-free rates plus an equity risk premium to compensate investors for the higher risks taken. The discount rate may change as a result of changes in risk-free rates or from a widening or narrowing of the equity risk premium.
Intrinsic value. Individual stocks are affected by investor perceptions of intrinsic value. These are affected by changes in the equity market discount rate, by expectations of future earnings growth and by the perceived riskiness of returns at one company versus the equity market as a whole. This is captured by a stock-specific measure called beta. Beta affects the discount rate applied to individual stocks according to the capital asset pricing model (CAPM).
Corporate actions. Individual stock prices are also affected by corporate actions such as rights issues, special dividends, share buy-back programs, takeovers, mergers, dividend payouts and the exercise of rights and other dilutive issues.

MARKET OR TRADING RISK

admin — Fri, 02 Oct 2009 14:32:40 +0000

Every year a handful of banks make sufficiently large trading losses to make the non-business sections of the media take note. The surprising thing is not that some banks make large trading losses but how few very large losses are incurred, given the sheer volume of financial trading activities. Very few of the actual losses reported have been sufficiently large to threaten the solvency of the financial institutions concerned.
This state of affairs owes less to the skills of traders and more to the effectiveness and generally high standard of controls put in place to manage market risks. Most of the reported large losses have occurred as a result of fraud at banks where line management has not understood the nature of the risks being taken and failed to implement some of the most basic controls necessary. Single traders have been able to run up losses amounting to several hundred million dollars without anyone noticing. The traders concerned have, of course, taken the rap but the real finger of blame should be pointed in the direction of management.
Trading portfolio risks can be conveniently broken down into three parts: first order price risks, realization risks and model risks. These incorporate our more familiar definitions of interest rate risk, foreign exchange risk, counterparty risk and so on.

TECHNICAL ANALYSIS AND CURRENCY MARKET PRACTITIONERS

admin — Thu, 02 Jul 2009 10:47:55 +0000

The various techniques of technical analysis, which we have only brieﬂy touched on here, have been widely practiced by traders for a very long time — centuries rather than years. The ﬁrst futures market was created in Japan in the early 1800s and the Japanese candlestick charting theory is seen as having emerged on the back of this. The very fact that we can chart US Treasuries back to the American Civil War conﬁrms that the art of charting is also hardly a new phenomenon in the US either. While currency, equity and ﬁxed income traders have long followed technical signals, corporations and asset managers have on the whole been somewhat more reticent to do so, either because of scepticism as to the merits of technical analysis or a lack of knowledge of how it works — or both. The best advance of any type of analytical discipline is that it actually works in practice; that it is capable of predicting exchange rates in this case and therefore using it one can generate excess returns. As Osler shows in her piece “Support for resistance: technical analysis and intraday exchange rates”,3 empirical evidence demonstrates that technical analysis can help in exchange rate prediction over and above the results available by simply using a random walk theory. Simply put, there is something to this. Looking at a slightly longer time frame, can a corporate Treasurer or an investor use technical analysis as part of their currency risk decision? The answer in this case is also, yes they can. While the primary focus of technical analysis is short term, it is fully capable of predicting multi-month of even multi-year moves. As an example, at the end of 1999, when the dollar–rand exchange rate was trading at around 6, the CitiFX Technicals team put out a buy signal, based on a combination of Elliott Wave Theory and the “golden cross” between the 55- and 200-day moving averages, with a multi-year target of 9.4 The exchange rate hit 9.00 on September 27, 2001. Again, the sceptical may see this as coincidence. However the fact is that skilful application of technical analysis principles correctly forecasts a move in the exchange rate that no interpretation of the “fundamentals” would have provided. At the very least, technical analysis should be a consideration for all types of currency market practitioner. Short-term traders are likely to use it as their primary analytical tool ahead of fundamental analysis because it is better suited to predicting short-term exchange rate moves than the traditional fundamental exchange rate models. Corporations and asset managers can use it as a cross-check of their fundamental views and also in terms of timing their hedging activity. The fact that traders watch technical levels and that traders make up the majority of currency market participants automatically makes those levels important.
What we have attempted in these few posts is to look at the basic principles and schools of thought within technical analysis, along with how and why it works. Having looked at pricing patterns, it is also important to look at the structural dynamics that determine that price. That is to say, one can look at a chart of an exchange rate, but it is also important to know how that price has been created and under what circumstances. Indeed, the type of exchange rate regime can render virtually worthless for periods of time most types of analysis, distorting both the fundamental and the technical signals that might otherwise be read. Thus, in the series of posts we take a look at the types of exchange rate regime and how each type might impact the exchange rate itself.

SCHOOLS OF (TECHNICAL) THOUGHT 2

admin — Tue, 30 Jun 2009 20:46:34 +0000

The link between Fibonacci and ﬁnancial markets comes through another school of thought for technical analysis, Elliott Wave Theory, named after Ralph Nelson Elliott (1871–1948). Elliott ﬁrst made the connection between his Wave Theory and the Fibonacci sequence of numbers in his blog Nature’s Law — The Secret of the Universe (1946). Elliott Wave Theory suggests ﬁnancial markets move in ﬁve waves of progression followed by three waves of regression. As such a 5–3 wave move completes a wave cycle. The ﬁve “up” waves are labelled 1–5, while the three “down” waves are labelled a–c. Of necessity, waves 1, 3 and 5 are seen as impulsive waves while waves 2 and 4 are seen as corrective.
Remembering the Fibonacci sequence, it should be immediately obvious that 1, 3 and 5 are Fibonacci numbers. Furthermore, if we break each wave down into sub-waves, we notice two things, ﬁrstly that each sub-wave conforms to the 5–3 wave pattern and secondly that when we add up these sub-waves we come to 21 impulsive and 13 corrective waves, making 34 in total. Once again, 13, 21 and 34 are all Fibonacci sequence numbers.
Fibonacci sequence numbers are also used in other technical indicators, such as in moving averages — e.g. 5, 13 and 21 moving averages, 21, 34 and 55 or 31, 55 and 144. Within the ﬁnancial markets, the most widely used application of the Golden ratio is through the Fibonacci retracement, which relates to the fact that corrective waves have retraced the previous wave by 38.2%, 50% or 61.8%. Fibonacci fan lines provide key support or resistance corresponding to the Fibonacci retracement levels. Once such a Fibonacci fan line support or resistance has been broken, this tends to suggest the extension of a correction and thus a potential wave reversal. In sum, Fibonacci levels can provide crucial tops and bottoms in the market and are widely watched by both short- and medium-term currency market participants.
A ﬁnal school of thought is Gann Theory, created by W.D. Gann (1878–1955), which seeks to predict future prices using speciﬁc geometric angles. Gann angles or Gann lines can be created by graphing price against time. The basic Gann angle or line is created by assuming an increase in one unit for both price and time, resulting in a line which is at a 45◦ angle to both axes. Because of the price and time increases involved, this is called a 1 × 1 angle. Gann lines are drawn off major price tops and bottoms. If the price is above the 1 × 1 line, this signals a bullish trend and conversely if it breaks below the line this signals a bearish reversal. Including the
1 × 1 angle, Gann identiﬁed nine signiﬁcant angles or lines relating to price and time:
1 × 8 — 82.5 degrees
1 × 4 — 75 degrees
1 × 3 — 71.25 degrees
1 × 2 — 63.75 degrees
1 × 1 — 45 degrees
2 × 1 — 26.25 degrees
3 × 1 — 18.75 degrees
4 × 1 — 15 degrees
8 × 1 — 7.5 degrees
Each of the angles or lines can provide a support or resistance depending on the trend. Generally speaking, the 1 × 1 angle as reﬂected by a trend-line is not sustainable given the steepness of the angle involved. Prices cannot continue appreciating at a 45◦ angle forever. The 3 × 1 angle is generally viewed as more sustainable in terms of price trends over the long term.

SCHOOLS OF (TECHNICAL) THOUGHT 1

admin — Tue, 30 Jun 2009 10:43:51 +0000

Having gone through the basic building blocks of technical analysis and the technical indicators that are used, we will now look at the major technical schools of thought that have dominated the way technical analysts and traders look at price patterns. The ﬁrst one to focus on is the Fibonacci school of thought, named after Leonardo Fibonacci, an Italian mathematician born in 1170. Fibonacci discovered a series of numbers such that each number is the sum of the two previous numbers:
1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233 and so on . . . To some, these numbers may seem more or less random. In fact, they are actually far from random, containing important interrelationships, and they are found in a surprising number of real-life examples. Indeed, it is not too much of an exaggeration to suggest that these numbers represent the mathematical building blocks of life. For a start, note that any given number is roughly 1.618 times the previous one. Equally, any number is 0.618 times the following number. As it stands, this does not answer the question of how Fibonacci happened to found, albeit inadvertently, a type of technical analysis. For this, we have to look ﬁrst at Fibonacci’s so-called “rabbit problem”, which relates to his attempt to demonstrate the application of Hindu–Arabic numerals through the example of rabbits. The mathematical problem that Fibonacci posed is that if two rabbits were put in an isolated place, how many pairs of rabbits could be produced from that pair in a year if every month each pair produces a new pair, which itself from the second month also becomes reproductive? At the start of the ﬁrst month, there would only be the ﬁrst pair. By the start of the second month, there would be the original pair plus one new pair, resulting in two pairs of rabbits. However, during that second month, the original pair will again produce another pair while the second pair is maturing. Thus, at the start of the third month, there should be three pairs, which brings us back to the Fibonacci number series. In terms of a mathematical formula, this can be expressed as: X n +1 = X n + X n−1 where X n is the number of pairs of rabbits after n months.
This became known as the Fibonacci sequence, as coined by the French mathematician Edouard Lucas (1842–1891). As the Fibonacci sequence progresses, a clear relationship between the numbers becomes apparent, as reﬂected by the 0.618 and 1.618 ratios mentioned above. The very fact that there can be a consistent ratio between numbers is itself “statistically signiﬁcant”, conﬁrming that there is more in this than just a random series of numbers. Note also that if you take any number and divide it by the number two higher in the sequence the ratio comes to 0.382. Not coincidentally, 38.2% and 61.8% are major Fibonacci retracement levels within the Fibonacci school of technical analysis.
While we look to Fibonacci and Lucas as the founders of modern-day Fibonacci analysis, it appears that long before them the importance of this sequence of numbers and ratios was well known and appreciated. Indeed, these ratios appear to have been used in the construction of both the Great Pyramid of Giza in Egypt and the Parthenon in Greece. The 0.618 or 1.618 ratio, also known as the Golden ratio, is commonly viewed in mathematics as one of the building blocks of natural growth patterns — in geometry as in life. Even the human body can be shown to contain elements of the Golden ratio, measuring the distance from the feet to the navel and in turn from the navel to the top of the head as a ratio. The basic building blocks of human beings, the DNA double helix, also contains the Golden ratio.

Psychological Levels 2

admin — Mon, 29 Jun 2009 21:42:55 +0000

A layman might not be able to tell much apart from the fact that Euro–dollar has been in a downtrend. Sometimes, such basic observations, made either by a layman or by a practising technical analyst, are the most important ones. However, a “technician” should be armed with a skill set that at least allows for the possibility of a more complex and sophisticated analysis. Looking at the charts again, we can identify the following points accordingly:
Euro–dollar has traded within a long-term downward sloping trend-channel.
It has only broken that channel on a sustained basis to the downside up until July of 2001
when it broke through and held above channel resistance.
Before that, in December 2000, Euro–dollar brieﬂy managed to exceed that trend-channel resistance and made a major high of 0.9595. Major highs and lows usually reﬂect theultimate extension of a trend reversal. Thus, 0.9595 needs to be exceeded for the medium- term downward trend to be negated.
The fact that a shorter-term moving average has broken up through the longer-term counterpart would appear to validate the view that Euro–dollar trades higher in the short term, whether or not it actually manages to breach that level of 0.9595.
More speciﬁcally, however, the fact that the 55-day moving average has broken up through the 200-day moving average is potentially very signiﬁcant. Why? As we noted above, certain moving averages are seen as more equal than others. Notably, the break of a 200-day by a 55-day MA usually can potentially lead to impulsive moves and signal a short-term trend reversal. Here, the 55-day MA has broken up through the 200-day MA, which we call a “golden cross”, arguing for potentially dramatic gains. Conversely, if the 55-day MA were to break down through the 200-day MA, that would be termed a “death cross” and be correspondingly bearish as the name might suggest.
One could go on, but I hope from this that the reader gets a picture of charts being able to reﬂect substantial amounts of potentially important information, information that in the absence of major changes in fundamentals may be the primary reason for subsequent, future price action. Along with support, resistance and moving averages, there is another technical tool that is useful in determining short-term moves in exchange rates — the relative strength index (RSI). The aim of this indicator is to discover overbought or oversold levels, against which the index is measured. The time period for RSI is usually 14 days and overbought and oversold levels are usually taken as 70 and 30 for the index.
The two dotted lines indicate the 30 and 70 oversold and overbought levels for 14-day RSI. Hence, we can note from this that according to the charts the RSI reading is currently roughly in the middle of its range. Combining this with the underlying charts, we note that at the same time as the RSI reading is in the middle of its bands, Euro–dollar has broken to the upside of a trend channel and the 55-day moving average has broken up through the 200-day moving average. We can potentially conclude from this that the benign RSI indicator may suggest there is more upside to come. Note that the RSI reading usually exceeds its 70 or 30 overbought or oversold levels before the peak or trough in the spot exchange rate. RSI analysis can be particularly useful when comparing divergences between it and the spot price action. For instance, if a spot exchange rate is making new highs while the RSI reading has already peaked, it may suggest that the spot exchange rate is itself about to peak and subsequently head lower.
RSI is one type of technical indicator. More generally, technical indicators reﬂect a mathematical calculation that can be applied to either an exchange rate’s price or its volume. The result is of course a value, which is then used to try and predict future prices. By this deﬁnition, both RSI and moving averages are technical indicators. Another widely used technical indicator is the moving average convergence divergence (MACD) indicator. The MACD is usually calculated by subtracting a 26-day moving average of an exchange rate from its 12-day moving average. The result is an oscillator that reﬂects the convergence or divergence between these moving averages.
Here, we get a somewhat different picture than shown by the RSI comparison. While that appeared to suggest the Euro–dollar exchange rate may have been about to make further gains given the benign RSI reading relative to the move higher in price, this MACD comparison appears to be suggesting the opposite. For just at the time the Euro–dollar exchange rate ismaking gains, the MACD reading has clearly failed well ahead of its previous high and is heading lower. This suggests bearish divergence on MACD and a potentially bearish signal as well for the Euro–dollar exchange rate. MACD oscillates above and below a zero level. When it is above zero, it means the 12-day moving average is higher than the 26-day moving average, which is potentially bullish as it suggests that “current” expectations (as reﬂected by the 12-day moving average) are more bullish than those expectations made prior to the 12-day moving average. Equally, when the MACD falls below zero, it suggests a bearish divergence between the moving averages. In our example, the MACD reading is still above zero, but it is heading lower towards that level. Moving averages and MACD are examples of lagging technical indicators as they reﬂect previous price action and are particularly useful when an exchange rate trends over a long period of time. On the other hand, leading technical indicators give some indication of a price being overbought or oversold, thus RSI is an example of a leading indicator. Divergence occurs when the exchange rate trend does not agree with the trend of the technical indicator of that exchange rate.

Psychological Levels 1

admin — Mon, 29 Jun 2009 10:42:37 +0000

In addition to the types of support and resistance that are identiﬁed by previous price action and thus previous lows and highs, there are also other sorts that focus instead on psychological factors or instead on ﬂow dynamics speciﬁc to that particular exchange rate. In the ﬁrst, market participants frequently focus on round numbers — such as 0.9400 for the Euro–dollar exchange rate — hence such levels are termed psychological support or resistance. They are important not because they represent of necessity a previous low or high, but instead because they reﬂect the expectation of a future move if they are breached. In the second, there can exist within speciﬁc exchange rates support or resistance levels reﬂecting anticipated ﬂow dynamics. For instance, in the dollar–yen exchange rate, some Japanese exporters may prefer also to sell their receivables forward (selling dollars and buying yen) to achieve a round number. Thus, one anticipates this by adding the forward points. For instance, if the spot dollar–yen exchange rate is 120.45/55 and the three-month forward points are −73/−72.5, one might expect some exporter sales to occur at 120.73 (which would allow an outright level of 120.00 to be achieved). Consequently, one might see 120.73 as one type of resistance. Of course, the difﬁculty with this particular type of approach is that as the spot exchange rate and the interest rate differential move, so the forward resistance point moves.
A further complication within technical analysis is that there are various ways in which charts can be drawn. In the following section, we look at the three main types:
Line
Candlestick
Bar
The basic chart, which is a simple line chart, is as the title suggests formed from a single line. Of necessity that line must be formed by a series of highs, lows, open or closing levels. Thus, it is an approximation of the price action over a given time, reﬂecting
more the overall trend rather than the intraday price action. Yet, highs and lows can be just as important as that trend, hence the bar chart is also useful. Sometimes, for the same instrument, security or exchange rate, the line and bar charts can show quite different support and resistance levels. Yet, it can also be important when precisely those highs and lows occurred. For instance, the implication of price action on any given day may be quite different if the high in price action occurs at the start or at the end of a move. For this reason, analysis using a candlestick chart can be useful.
These are the three most basic types of chart. For all three, we can use a number of technical tools and schools of thought to try and develop predictive knowledge from past price patterns. Before we go on to some of the more complex tools, it is probably worth having another look at support and resistance, accompanied by another building block — the moving average. As the name suggests, this is the average of the exchange rate values over a set time period. Because that exchange rate is constantly moving, so is the average rate of necessity. Moving averages can be studied according to periods of any length, but the most widely used and thus most important are the 20-, 55- and 200-day and the 55- and 200-week moving averages. Thus armed with the initial building blocks of support, resistance and moving averages, let’s try to do some technical analysis.
Here, we have our Euro–dollar exchange rate with the following technical tools:
A trend-line
A trend-channel (two parallel trend-lines)
55-day moving average
200-day moving average