Most traders today use technical analysis to trade. This refers to techniques based on price and other objective data that result from market action. The technician’s credo is “Everything is in the market price.”
           The factors examined in fundamental analysis, such as a country’s income, gross national product, and interest rates certainly drive currency prices in the long run. The problem for the currency trader is, as Keynes said, “In the long
run we are all dead.” The FOREX markets are highly leveraged; this is one of their main attractions. You can be correct about a currency pair in the long run, but the leverage may cause a price movement more than ample in degree to take
you out of the market before you can profit from being correct about the fundamentals. It is discouraging to be correct in your determination of long-term trend direction—for example, “Interest rates will drive the U.S. dollar lower
against the euro”—but lose money because volatility and leverage cause so many short-term fluctuations that you are never able to board the long-term trend successfully.
         No one denies that fundamentals such as money supply, labor statistics, political events, and many others drive the currency markets. The problem and why most traders use technical analysis—is how to interpret them, especially in the short term.
          Most fundamental information is quantitative but much is not. For example, how does a trader convert an unemployment statistic to a price value?
To further complicate matters, there are hundreds of fundamentals that impact prices, and the matrix of possibilities is astronomical. And some fundamentals, such as geopolitical events, are not even quantifiable.
The prices in Figure 1 —tracked hourly for 30 days on EUR/USD— were ultimately driven by a wide range of fundamentals. But how does the trader discern them in advance?
Technical analysis allows you to zoom in as close to the markets as you want. In fact, an advantage of technical analysis is the ability to visualize the markets at multiple price levels simultaneously.  There is no perfect world, of course. Fundamentalists will counter that the prices you use to do technical analysis are already history by the time you do your calculations, and they have no rational effect on the future prices. But a simple example will show this concept to be incorrect, at least in theory. It is true that after I enter my order to buy or sell, I have had all the impact on prices that I will have until I enter the opposite order to exit the market. Yet every trader has a propensity to exit the market, once entered, on variable factors of price and time. At what price will I take a profit? At what price will I take a loss? How long am I willing to stay in a trade? These propensities vary from trader to trader, but the aggregate of all propensities

creates a push and pull on the market that should, again in theory, be measurable. All traders have access to market prices; the same cannot be said of fundamentals. There are literally millions of fundamental factors in any given cur-
rency, and the relationships among them are in the billions. Someone will almost certainly know a piece of fundamental information before you do. And how do you translate a fundamental like gross domestic product (GDP) to a specific market value or even a specific entry price? To add gasoline to the fire, remember that these relationships are almost certainly nonlinear and are changing rapidly all the time.
Fundamental traders conclude that prices have no memory and that only raw fundamental information drives the markets. The following is only a partial list of potential fundamentals for the U.S. dollar (USD). Other countries
will have similar lists. Now, don’t you really want to be a technical trader!
Trading Techniques
TABLE 1.1 The Technical Market Paradigm
The theory of technical analysis states that all information relevant to the market is
contained in the price data. Even volume and open interest statistics (not available to
FOREX traders unless artificially synthesized from price data) are secondary to price
• Bridge/Commodity Research Bureau (CRB) indexes.
• BTM-UBSW Chain-Store Sales Index.
• Building permits.
• Business inventories.
• Capacity utilization.
• Capital flows, per Treasury International Capital System (TIC).
• Confederation of British Industry (CBI) report.
• Challenger, Gray, and Christmas layoff announcements.
• Chicago Purchasing Managers Index (PMI).
• Chicago Purchasing Managers Survey.
• Chartered Institute of Purchasing and Supply (CIPS) report.
• Composite Index of Leading Economic Indicators.
• Consumer confidence.
• Consumer installment credit.
• Consumer price index (CPI).
• Consumer sentiment.
• Consumer spending.
• Corporate profits.
• Current account (balance of payments).
• Durable goods orders.
• Employment cost index.
• Employment report.
• Employment situation.
• Existing home sales.
• Export prices.
• Factory orders.
• Federal budget.
• Federal government finances.
• Federal Reserve Policy disclosures.
• Financial account balance.
• Federal Open Market Committee (FOMC) minutes and
• Foreign trade.
• GDP.
• GDP advance.
• GDP deflator.
• GDP final.
• GDP provisional (revised).
• GNP indicators.
• Goldman Sachs Commodity Index.
• Goldman Sachs Retail Index for Same-Store Sales.
• Help-wanted index.
• House prices.
• Housing starts.
• Humphrey-Hawkins testimony.
• German IFO index.
• Import prices.
• Industrial production.
• Industrial Production and Capacity Utilization report from Federal
Reserve Board.
• Initial claims.
• International trade.
• Institute for Supply Management (ISM) Manufacturing Index.
ISM Nonmanufacturing Survey.
•  ISM Services Index.
•  Jobless claims.
•  Kansas City Federal Reserve Bank manufacturing survey.
•  Lynch, Jones & Ryan (LJR) Redbook report.
• Manufacturers’ shipments, inventories, and orders.
• Manufacturing and trade inventories.
• Michigan Consumer Sentiment Index (MCSI).
• Monetary base.
• Money supply figures (M1, M2, M3) released monthly by Federal
• Reserve Economic Data (FRED).
• Mortgage Bankers Association weekly survey.
• National Association of Purchasing Managers (NAPM) index.
• National Association of Home Builders (NAHB) survey.
• New home sales.
• Nonfarm payrolls.
• New York’s Empire State Index.
• Orders, sectoral production, and inventories.
• Payroll employment.
• Personal consumption expenditures.
• Personal income.
• Philadelphia Fed index.
• Philadelphia Federal Reserve Bank Business Outlook Survey.
• Prices, wages, and productivity.
• Producer price index (PPI).
• Productivity.
• Purchasing Managers Index (PMI).
• Real earnings (real average weekly earnings).
• Real GDP.
• Redbook Index.
• Residential construction spending.
• Retail sales.
• Richmond Federal Reserve Bank Survey.
• Trade balance.
• Tankan report
• Unemployment insurance claims.
• Unemployment rate.
• Unit auto and Ttuck sales.
• Unit labor cost.
• U.S. Treasury Borrowing Schedule.
• Wholesale inventories.
Econometric Analysis
Econometric analysis attempts to convert fundamental data into pricing forecasts, most typically long-term forecasts. Because of the high leverage in FOREX, long-term forecasts may not be of value to many traders.
Econometric analysis typically yields complex mathematical/statistical models. Because of the complexity they are computer-based simulations.
The EXPO econometric software ( attempts shorter-term price forecasts, incorporating the following factors:
• Data Transformations: Box-Cox Transformations, Differencing, Logit, Seasonal Adjustment, and Periodicity Conversion.
• Statistical Analysis: Autocorrelation and Partial Autocorrelation Analysis, Q-statistics, Restricted Histogram, Correlation, and Variance/Covariance Matrix.
• Econometric Tests: Additional variables, superfluous variables, Dickey-Fuller Unit Root, Engle-Granger Cointegration, Granger Causality, Multicollinearity, Normality, LM Serial Correlation, GARCH and White Heteroskedasticity, Chow, and Ramsey.
• Model Estimation and Forecasting: OLS, GARCH, ARIMA, Ridge, rolling/moving regression, instrumental variables, and auto-regressive errors.
• Random Number Generation: Using Binomial, Chi-square, Exponential, F, Student-t, Normal, Lognormal, and Poisson Distri-butions.
• Frequency Analysis: Convolution, Discrete Fourier Transform, Fast Fourier Transform, Inverse Fourier Transforms, impulse  filters, power spectral density, trigonometric functions generator,

digital filter functions.
• Polynomial Analysis: Cubic spline interpolation, polynomial esti-
mation, and statistics.
• Statistics: Summary statistics, rolling correlation and statistics;
Student-t, F, ANOVA, and Chi-square tests.
• Mathematical Functions: An extensive set of advanced functions
for matrix math and calculus are provided in EXPO’s “Analyze”
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