FAQ's about the Market Libraries and volatility
|Where does The Currency Library data come from?
||Currency rates are supplied by DTN Market Access vs. Tullet
Tokyo and Barclays.
They are interbank rates.
|What is volatility, anyway?
||Well, at least to some degree, it depends
upon whom you ask
As a terse, general definition it would be hard to improve upon
the following, from a paper recently published in the derivatives journal, Futures and
And for a more closely specified definition from a particularly authoritative source:
However general or closely specified the definition may be, the never-ending search for better tools to reduce risk and enhance reward - combined with faster, more powerful and cheaper computer-based analysis - have brought the study of volatility to the forefront of financial study and practice in recent years, where it is likely to remain. The contents of the Market Libraries place powerful tools for state-of-the-art volatility analysis in the hands of any financial practitioner with access to the Internet.
types of Volatility calculations will I find in the Market Libraries?
||The Market Libraries include charts
different methods of calculating price and rate volatility:
|Why do the Market Libraries offer charts with differing time-frames?||The Market Library offers several different
time-frames or "x-axis windows", designed to meet the requirements of different
categories of financial professionals. Corporate strategic planners, for instance, often
require the perspective of 5-year and 3-year time-frames, while dealers and traders may
need the detailed focus of 1-month charts.
|How can Dealers use theFinancials.com Volatility Charts?||There are many specialties in the spot
and forward dealing world - not only in terms of specific instruments or commodities, but
in terms of trading and risk-management horizons, multi-currency portfolio risk and
style-of-trading as well. State-of-the-art volatility analyses tailored to meet individual
requirements can make an important contribution to the successful dealing desk.
can corporate financial managers make of theFinancials.com Volatility Charts?
||Corporate financial managers often have
responsibility for more than one category of exchange rate risk management, ranging from
"macro", long range strategic protection, to monthly cash flow series and
one-off capital projects. theFinancials.com
Volatility Charts chosen to reflect specific situations can be a big help in
making effective boardroom presentations, as well as in developing, implementing and
monitoring risk management strategies.
|What use can investors make of theFinancials.com Volatility Charts?||Exchange rate and price risk accompanies a very wide
range of investment choices in the international debt and equity markets. Often, with
hindsight, exchange rate and price movements turn out to be as important to net results as
the "domestic-context" price or rate behavior of the underlying instrument
itself. Having the right charts to monitor and evaluate foreign-exchange rate and
commodity price risk for individual and portfolio situations can be a big help in the
search for superior results.
Market Library Charts available for other instruments or in other formats?
||When we invite our clients to think of
the Market Libraries as an in-house resource, we arent kidding. Only a small
percentage of our chart resources are on display at any given time.
Example: You need a combination of Italian Lira-based GARCH charts vs. several other currencies and in varying time-frames, all packaged in a very specific way. No problem.
|How does theFinancials.com calculate Historical Volatility (VolSD)?||Actually, any method of
calculating the volatility of a time series which relies on past values could be
classified as a measure of "historical" volatility. However, in the financial
markets, and the financial option markets in particular, "Historical Volatility"
is generally taken to mean the measure of volatility specified by Professors Fischer Black
and Myron Scholes, in describing the required inputs to the seminal Black-Scholes Model
for European-style Options, (1973). This measure centers upon a standard deviation
calculation applied to a historical time series of prices or rates, hence the time series
label VolSD used in Market Library Charts.
In one sentence, this measure could be defined as
|How does theFinancials.com calculate Exponentially Weighted Moving Average volatility (VolEWMA)?||The
Exponentially Weighted Moving Average (EWMA)
approach to characterizing volatility is an example of exponential smoothing.
Exponential Smoothing (ES) techniques employ one or more exponential smoothing parameters
to give more weight to recent observations and less weight to older observations, in an
attempt to respond "dynamically" to the changing value of the time series. The
smoothing process is exponential because the weights employed are not arithmetic, but,
instead lie along an exponential curve.
EWMA is an example of the simplest form of the exponential smoothing method, or Single Exponential Smoothing (SES), which, logically enough, employs a single smoothing parameter. Several assumptions must be made about the nature of the data making up the underlying time series, in order for an SES technique like EWMA to be an appropriate analytic tool:
|How does the theFinancials.com EWMA measure of volatility differ
J.P. Morgan RiskMetrics© approach used in VaR calculations?
|The J.P. Morgan RiskMetrics© approach to estimating
and forecasting volatility uses an exponentially weighted moving average model (EWMA)
which is virtually identical to the method used for theFinancials.com EWMA Volatility
Both models require that a "decay factor" be specified, in order to determine the rate at which the weighting of past observations diminishes. In order that Market Library EWMA Charts provide closely-comparable output to RiskMetrics volatility estimation, our model uses the same decay factor as RiskMetrics EWMA, i.e. 0.94.
Likewise, in choosing between yesterday's and today's price movement to reflect "market change", both the VaR and theFinancials.com versions utilize "todays market change" for this purpose.
|What is GARCH volatility?||GARCH stands for Generalized Autoregressive
Conditional Heteroskedasticity - and thats a mouthful for anyone. GARCH
models are comparative youngsters on the econometric modeling scene, having being first
specified by R.F. Engle in 1982 and T. Bollerslev in 1986. In a relatively short period of
time, they have become popular in many areas of econometrics, including dealing, trading,
hedging and investing in and with financial instruments, in large part because they are
specifically designed to model and forecast changes in variance, or volatility per se.
One reason many sophisticated practitioners prefer GARCH volatility estimation and forecasting techniques over other approaches relates to the fact that GARCH model specification "makes sense" in terms of the real-world context within which professionals actually operate. Broadly speaking, A GARCH(1,1) model incorporates the assumption that todays volatility depends upon three factors:
This specification parallels, in an informal sense, an environment wherein a dealer or trader typically tries to assess todays volatility in the context of
Furthermore, the GARCH specification incorporates and handles well the frequently-observed financial time series behavior called "volatility clustering." Volatility clustering describes the situation wherein large volatility movements are more likely to be succeeded by further large volatility movements of either sign than by small movements.
Another aspect of financial price and rate behavior that GARCH handles particularly well relates to the speed with which it "re-adjusts" in the aftermath of event-induced "shocks" to the time series in question. This can be observed time after time in Market Library chart formats which display the varying responses of three different measures of volatility to the same underlying event.
Does the GARCH specification do a "perfect" job of estimating and forecasting volatility? Of course not. Interestingly enough, even the academic underpinnings of the GARCH specification do not support the expectation of superior "point forecasts" for the underlying series. However, for gaining a sophisticated grasp of how volatility has behaved in the past, especially the recent past, it pretty much represents state-of-the-art for most practitioners.
|Which measure of Historical Volatility is best?||Forget the temptation to define the "best"
measure of volatility as being the one that always leads to successful market decisions is
best, cause there aint no such animal...on the other hand, some general
conclusions regarding the comparative advantages and disadvantages of the three volatility
methodologies employed in the Market Libraries can be drawn.
Before attempting to discuss the comparative advantages and disadvantages embodied in different approaches to analyzing the volatility of exchange rates - or any other financial price or rate series - it is important to distinguish between several different yet related objectives of such analysis. These objectives are:
1) "Classic" Historical Volatility (VolSD).
2) Exponentially Weighted Moving Average volatility (VolEWMA).
The use of exponential smoothing in both the theFinancials.com and RiskMetrics EWMA calculation represents an attempt to deal with the weaknesses inherent in the "classic" Historical Volatility calculation. This is not to say, however, that exponential smoothing results in a "perfect" depiction of volatility as it changes over time.
3) GARCH volatility (VolGARCH)
In summary, then, assuming that the computational intensity involved in cranking out GARCH values is not a problem, the GARCH methodology should provide
|Isnt Implied Volatility better than Historical Volatility?||Most currency and commodity option dealing
desks rely very heavily upon the volatility implied by the actual trading levels of
currency and commodity option premiums for the pricing, risk management and pursuit of
profit in their currency option books.
There are, however, there are, however, several major conceptual and practical problems with this approach:
Conclusion: While the case for forecasting underlying exchange rate and price behavior from the volatilities implied by market transactions in derivative instruments has its exponents, most spot and forward practitioners will most likely continue to rely primarily upon one or more directly-modeled approaches for the foreseeable future, perhaps with one eye on option-based analysis when and where it is available.
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