Forex trading for beginners Part 7: Market psychology, Types of charts, Trend Analysis
Forex trading for beginners Part 5: Exchange rate, Manufacturing indicators
Consumer demand indicators
There are special indicators that characterize the willingness of consumers to spend money on the acquisition of various goods. Some of these indicators are important for foreign exchange markets, as high consumer demand stimulates the recovery of production in many industries and can serve as the basis for economic growth. On the contrary, the weakness of consumer demand or its decline is a signal and may be the cause of a recession in the economy. Focusing on these indicators, central banks can change interest rates or use other levers of financial policy that directly affect exchange rates. We will look here at some of the most popular consumer demand indicators related to housing construction and the housing market, with indicators of retail trade, as well as an index of consumer sentiment.
Housing construction and housing market
Indicators of housing construction and the housing market as components of consumer demand can become of great importance for the foreign exchange market during transitional periods of economic cycles. Still, on average, their volatility and dependence on many random factors, up to the weather, make interpretation quite difficult. But by the summer of 1999, for example, all indicators of consumer demand in the United States were considered by the foreign exchange market most attentively since the FED saw further growth in consumer demand as a source of inflation in the fight against which it was ready to raise interest rates. In addition, American manuals on economic statistics emphasize that housing construction was the driving force that lifted the American economy out of all the recessions after the Second World War.
Housing construction and market statistics are tracked at all its stages:
– Obtained building permits (Building Permits);
– started constructions (Housing Starts);
– completed constructions (Housing Completions);
– sales of new and sales of existing one-family houses ( New and Existing one-family Home Sales);
– construction costs (Construction Expenditures).
In addition to general indicators, data is also released, grouped into four main regions: northeast, west, midwest, and south.
US data is released monthly, around the 15th business day of the month.
Retail
Retail sales (RS) – one of the indicators of consumer spending; therefore, as an indicator of consumer demand and consumer confidence, it can serve as a benchmark for the foreign exchange market at turning points in the business cycle. Such indicators are especially important for tracking the US economy since consumer demand is its main driving force. If the consumer has more disposable income, then more goods will be produced as well as imported.
As an illustration, we can cite the composition of retail sales according to US statistics for 1992.
In business cycle dynamics, retail is a converging indicator. Volatility in the business cycle is low, but seasonal dependence is strongly pronounced. So, the special months in each year are December and September. Annual retail data is always growing on average, but there can be ups and downs from month to month within the same business cycle. Information on individual components of retail sales, such as automobile sales, can also be useful.
Sales of trucks and cars
Due to the increased internationalization of the industry (American cars are assembled outside the USA, and Japanese and German vehicles are manufactured in the USA, out of 4,367,752 cars sold in the USA in 1991, 712,672 were foreign), and also due to the influence of various variables, direct interpretation of this sector from the point of view of currency markets is not always simple. Still, as cyclical indicators, data on car sales (New Cars, NCAR ), as well as separately on sales of trucks and cars ( Car and Truck Sales, C&TS ), can be a useful guide for the currency trader.
Sales figures for new cars, and separately for trucks and cars, usually look like leading indicators but have behaved like coincident indices in the US in recent years; they have a pronounced seasonal cycle. The average growth rate of sales of passenger cars in recovery is about 1.5% per month, in expansive about U.2/o; of trucks – in recovery 0.9%, in expansion 0 3%. In a recession, sales of trucks can even grow and always become larger than sales of passenger cars.
Consumer sentiment indices
In the United States, three statistical data providers offer indicators that measure the willingness and confidence of the population to spend money on various goods in the near future:
1. University of Michigan – consumer sentiment index (University of Michigan’s Consumer Sentiment Index);
2. Conference Board – Consumer Confidence Index ;
3. ABC News and Money magazine – opinion poll.
The indicators are built on the basis of various surveys of the opinions of the population about the conditions of today and the near future (from 6 to 12 months) – how favorable they are for solving financial problems, acquiring durable items, employment, etc. From the received answers of the “better/worse” type, indicators are built in the form:
1) 100 + % better – % worse;
2. better / (better + worse);
3. better – worse (4-week average).
The period covered by the indices (and, accordingly, the frequency of publication) is from a week to a month.
Business cycle indicators
As stated in an American textbook on currency dealing, the first piece of fundamental analysis advice given to a novice currency trader is: “Keep an eye on interest rates.” This is easier said than done, as central banks are in no hurry to reveal their intentions and, indeed, tend to change their main interest rates as little as possible. The impact of changes in rates on exchange rates can be very long-term since the economic system has a large inertia, and to get the full effect of changes in rates, sufficient time must pass, during which the central bank evaluates the economy’s response to new conditions.
But the market is not only reacting to the changes that have taken place; traders try to predict the actions of central banks in order to start buying or selling currencies in advance, while it can still be done at the most favorable rate. As a result, a prevailing opinion may form in the market. Then, in anticipation of a change in interest rates, the market will move the currency in a certain direction for a very long time. So, it turns out that the whole life of a trader is subject to the rhythm of movements in interest rates. The right way not to follow the tail of the market crowd but to anticipate the waves is to pursue economic cycles since they are the ones that determine the policies of leading central banks today.
All the economic indicators we have considered demonstrate cyclical behavior in one way or another. Therefore, each can be (and is) used to analyze cycles. Still, there are indicators designed for the sole purpose of most clearly showing the cyclical dynamics of economic processes and reliably predicting turning points of cycles. We will consider here two types of such indicators, well understood from the point of view of the foreign exchange markets.
Leading economic indicator
In view of the fact that many economic indicators show economic cycles, but each in its way, it is natural to try to construct one from several indicators, which, thanks to generalization (averaging), will be better at predicting cycles than each separately. The composite leading indicator (Leading Economic Indicator, LEI) combines 11 indicators for this purpose:
- 1. The average length of the working week in the manufacturing sector.
- 2. Average weekly number of National Unemployment Insurance claims.
- 3. New production orders for consumer goods and materials (at 1982 prices).
- 4. Efficiency of deliveries (the share of firms whose delivery deadlines are increasing).
- 5. Contracts and orders for means of production and equipment (in 1982 prices).
- 6. Obtained permits for housing construction.
- 7. Backlog of durable goods production orders (monthly change, 1982 prices).
- 8. Change in prices for raw materials and materials.
- 9. S&P500 stock index (monthly average).
- 10. Monetary aggregate M2 in 1982 dollars
- 11. Consumer Expectations Index (University of Michigan’s Consumer Expectations Index).
The value of the LEI index itself is built from these components as a weighted average,
LEI = wi *Ii.
They tried to choose the weights of a composite index in different ways, but recently, statisticians have come to the conclusion that in the simplest case, with the same weights, the indicator works no worse than in more complex options.
This index is based on the idea that the main motivating force in the economy is the expectation of future profits. In anticipation of rising profits, companies are expanding the production of goods and services, investing in new plants and equipment; accordingly, this activity declines when revenues are foreseen. Therefore, the index is designed in such a way that it covers all the main areas and indicators of business activity: employment, production and income, consumption, trade, investment, stocks, prices, money, and credit.
The American LEI index is published monthly, towards the end of the month.
Indices of business activity
Extremely popular in recent years in economic statistics are indicators based on the method of constructing the so-called diffusion indices. Indexes of this kind, which by their nature are indicators of the business optimism of business participants, are regularly published (under the name PMI) in the USA, England, and Germany, where the relevant business associations create them; they are used both to assess the direction of public opinion and to measure the dynamics of objective indicators. In Japan, a similar TANKAN index has been adopted by the Central Bank of Japan itself as a tool for analyzing the dynamics of economic processes for making decisions in the field of monetary policy.
Diffusion indices, unlike many other indicators of socio-economic statistics, are purely subjective indicators. They do not measure the volume of output, the number of orders, income, etc. Still, they are only a reflection of how participants in economic processes perceive the changes taking place – whether they are for the better (in their opinion) or they lead to deterioration. Despite such subjectivity, or rather precisely because of it, these indices have extremely strong predictive properties; they are leading indicators that are highly correlated with the main parameters of economic cycles.
The diffusion index is based on the results of a survey of a large number of participants, each of which answers a question like “Have your business conditions improved in terms of new orders, prices, labor market, lead times, new export orders, etc. “; at the same time, he chooses one of three answer options: “yes”, “no”, “no change”. The diffusion index value is calculated for a specific question as the sum.
DI = (% of those who answered “yes”) + 0.5 *(% of those who answered “no change”);
having calculated such diffusion indices for each question, they are then averaged, obtaining composite average indices such as PMI or TANKAN. They are very effective in tracking the dynamics of the economic cycle, being leading indicators: the beginning of the fall of the index after a period of growth predicts the transition of the business cycle from expansion to recession, and an upward turn after the fall predicts the beginning of recovery. The close correlation of diffusion indices with economic dynamics, estimated from long-term statistical data, makes it possible to use them even to predict future GDP values (at least a quarter ahead).
Such indices are published today by almost all G7 countries; for example, in England, they have been built since 1991. The German PMI has been published since 1998 and includes a survey of 350 companies on the following five questions: output, new orders, employment, supplier’s delivery times, stocks of goods purchases). Since 1999, there has also been a consolidated PMI for the Euro-region, covering 11 states with a single euro currency (EU PMI). The most powerful coverage of business statistics (34,000 participants) is provided by the American PMI index of the National Association of Purchasing Managers (NAPM), which has been maintained since 1931; only the staff providing statistics was up to 300 people.
We will consider in detail the structure and properties of business optimism indices using the American Purchasing Managers’ Index (PMI), NAPM as an example. The review of the American Association NAPN, which is the basis of its PMI index, includes questions that the survey participant is asked to answer – whether the conditions of his business have changed over the past month for the better (“higher”), for the worse (“lower”), or remained unchanged (“unchanged”) in relation to the following factors:
- – employment (employment),
- – prices (commodity prices),
- – delivery time (vendor deliveries),
- – production (production),
- – stocks (inventories),
- – new customer orders (new orders from customers),
- – new export and import orders (new export and import orders),
- – accumulated unfulfilled orders (order backlogs; this item was introduced in 1993 at the suggestion of the current chairman of the Federal Reserve System, A. Greenspan).
For each item in the questionnaire, a diffusion index is determined (the percentage of “higher” responses plus half the percentage of “unchanged” responses), and then a weighted sum is constructed from them, which is an average PMI index; in 1994, the formula for PMI was as follows:
PMI = 0.30 % DI(new orders) + 0.25 % DI(production) +
0.20 х DI(employment) + + 0.15 х DI(deliveries) + 0.10 х DI(inventories)
Interpretation of the PMI index. The main property of PMI is a leading business cycle indicator. There are a number of main levels of the indicator for interpretation:
– cyclic maximum and cyclic minimum;
– 50% – level;
– 44% – level.
If, after a period of growth, the PMI turns down, then this predicts a downward reversal of the business cycle. On the contrary, if after the fall of PMI, having reached a minimum, it turns up, then this is a sign of a future recovery. According to 40 years of US statistics, PMI predicts the highs of growth cycles in an average of 7 months and the lows of growth cycles in 3 months.
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