Forex trading for beginners Part 6: Consumer demand indicators

Consumer Demand Indicators

Consumer demand indicators are specific metrics that reflect consumers’ willingness to spend money on acquiring various goods.

Some of these indicators are crucial for foreign exchange markets, as high consumer demand stimulates production recovery in numerous industries and can serve as a foundation for economic growth.

Conversely, a decline or weakness in consumer demand signals and may cause an economic recession.

By monitoring these indicators, central banks can adjust interest rates or employ other financial policy tools that directly impact exchange rates.

Here, we will examine some of the most popular consumer demand indicators related to housing construction and the housing market, as well as retail trade indicators and the consumer sentiment index.

Housing Construction and Housing Market

Housing construction and housing market indicators as components of consumer demand can become highly significant for the foreign exchange market during transitional phases of economic cycles.

However, their volatility and dependence on numerous random factors, including weather conditions, generally make interpretation quite challenging.

For instance, by the summer of 1999, all consumer demand indicators in the United States were closely monitored by the foreign exchange market as the Federal Reserve (Fed) anticipated that further growth in consumer demand could lead to inflation, prompting potential interest rate hikes.

Additionally, American economic statistics manuals highlight that housing construction was the driving force that propelled the American economy out of every recession following the Second World War.

Housing construction and housing market statistics are tracked at all stages:

• Obtained Building Permits (Building Permits);
• Started Constructions (Housing Starts);
• Completed Constructions (Housing Completions);
• Sales of New and Existing One-Family Houses (New and Existing One-Family Home Sales);
• Construction Costs (Construction Expenditures).

In addition to general indicators, data is also released, categorized into four main regions: Northeast, West, Midwest, and South.

US data is released monthly, typically around the 15th business day of each month.

Retail

Retail Sales (RS) are one of the indicators of consumer spending.

Therefore, as an indicator of consumer demand and consumer confidence, RS 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, as consumer demand is its main driving force.

If consumers have more disposable income, then more goods will be produced and imported.

For example, we can refer to the composition of retail sales based on US statistics from 1992.

Retail is considered a converging indicator in business cycle dynamics.

Volatility in the business cycle is low, but seasonal dependence is highly pronounced, particularly in December and September.

Annual retail data generally shows growth on average, but there can be fluctuations from month to month within the same business cycle.

Information on individual components of retail sales, such as automobile sales, can also be valuable.

Sales of Trucks and Cars

Due to the increased internationalization of the automotive industry (American cars are assembled outside the USA, and Japanese and German vehicles are manufactured within the USA; out of 4,367,752 cars sold in the USA in 1991, 712,672 were foreign), and the influence of various variables, direct interpretation of this sector from the perspective of currency markets is not always straightforward.

However, as cyclical indicators, data on car sales (New Cars, NCAR), as well as sales of trucks and cars (Car and Truck Sales, C&TS), can serve as a useful guide for currency traders.

Sales figures for new cars, as well as separately for trucks and cars, typically appear as leading indicators but have behaved like coincident indices in the US in recent years.

They exhibit a pronounced seasonal cycle.

The average growth rate of passenger car sales during economic recovery is about 1.5% per month, and during expansion, approximately 2.0%. For trucks, the growth rate is around 0.9% during recovery and 0.3% during expansion.

During a recession, truck sales can even increase and typically surpass passenger car sales.

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:

• University of Michigan – Consumer Sentiment Index (University of Michigan’s Consumer Sentiment Index);
• Conference Board – Consumer Confidence Index;
• ABC News and Money Magazine – Opinion Poll.

The indicators are constructed based on various surveys that gauge the population’s opinions about current conditions and the near future (ranging from 6 to 12 months). These surveys assess how favorable conditions are for solving financial problems, acquiring durable goods, employment, etc. Indicators are derived from responses of the “better/worse” type in the following forms:

• 100 + (% better – % worse);
• better / (better + worse);
• better – worse (4-week average).

The period covered by the indices, and consequently the frequency of publication, ranges from one week to one month.

Business Cycle Indicators

As stated in an American textbook on currency trading, the primary piece of fundamental analysis advice given to novice currency traders is: “Keep an eye on interest rates.”

This is easier said than done, as central banks are reluctant to disclose their intentions and typically change their main interest rates as infrequently as possible.

The impact of rate changes on exchange rates can be long-term due to the economic system’s significant inertia.

To fully realize the effects of rate changes, sufficient time must pass for the central bank to assess the economy’s response to the new conditions.

However, the market does not only react to actual changes; traders also attempt to predict central bank actions to initiate buying or selling of currencies in advance, securing the most favorable rates. Consequently, a prevailing market sentiment may develop.

Anticipating changes in interest rates, the market may move currencies in a particular direction for extended periods.

Thus, a trader’s entire career is influenced by the rhythm of interest rate movements.

The effective strategy to avoid merely following the market crowd’s tail is to anticipate the waves by tracking economic cycles, as they are the primary determinants of leading central banks’ policies today.

All the economic indicators discussed exhibit cyclical behavior to some extent. Therefore, each can be used to analyze cycles.

However, there are specific indicators designed solely to clearly illustrate the cyclical dynamics of economic processes and reliably predict cycle turning points.

Here, we will examine two types of such indicators that are well-understood from the perspective of the foreign exchange markets.

Leading Economic Indicator

Considering that many economic indicators reflect economic cycles, each in its unique manner, it is logical to construct a composite indicator from several individual indicators.

Through generalization (averaging), this composite is more effective at predicting cycles than each indicator separately.

The Leading Economic Indicator (LEI) combines 11 indicators for this purpose:

• Average Length of the Working Week in the Manufacturing Sector.
• Average Weekly Number of National Unemployment Insurance Claims.
• New Production Orders for Consumer Goods and Materials (at 1982 Prices).
• Efficiency of Deliveries (the share of firms whose delivery deadlines are increasing).
• Contracts and Orders for Means of Production and Equipment (in 1982 Prices).
• Obtained Permits for Housing Construction.
• Backlog of Durable Goods Production Orders (Monthly Change, 1982 Prices).
• Change in Prices for Raw Materials and Materials.
• S&P 500 Stock Index (Monthly Average).
• Monetary Aggregate M2 in 1982 Dollars.
• Consumer Expectations Index (University of Michigan’s Consumer Expectations Index).

The value of the LEI index itself is calculated as a weighted average of these components:

LEI = w_i * I_i.

Various methods have been employed to determine the weights of the composite index.

However, recent consensus among statisticians suggests that using equal weights is as effective as more complex weighting schemes.

The LEI is founded on the premise that the primary motivating force in the economy is the expectation of future profits.

Anticipating rising profits, companies expand the production of goods and services, and invest in new plants and equipment.

Conversely, this activity declines when revenues are expected to decrease.

Therefore, the LEI is designed to encompass all major areas and indicators of business activity, including: employment, production and income, consumption, trade, investment, stocks, prices, money, and credit.

The American LEI index is published monthly, typically towards the end of each month.

Indices of Business Activity

Indicators based on the construction of diffusion indices have become extremely popular in recent years within economic statistics.

These indices, which inherently reflect the business optimism of market participants, are regularly published under the name PMI (Purchasing Managers’ Index) in the USA, England, and Germany by their respective business associations.

They are utilized to assess public opinion trends and to measure the dynamics of objective indicators.

In Japan, a similar TANKAN index has been adopted by the Central Bank of Japan as a tool for analyzing the dynamics of economic processes to inform monetary policy decisions.

Diffusion indices, unlike many other socio-economic indicators, are purely subjective measures.

They do not quantify output volume, order numbers, income, etc. Instead, they reflect how participants in economic processes perceive ongoing changes—whether they view them as positive or leading to deterioration.

Despite, or perhaps because of, their subjectivity, these indices possess exceptionally strong predictive capabilities.

They serve as leading indicators that are highly correlated with the primary parameters of economic cycles.

The diffusion index is based on survey results from a large number of participants.

Each participant responds to questions such as, “Have your business conditions improved in terms of new orders, prices, labor market, lead times, new export orders, etc.?”

and selects one of three options: “Yes”, “No”, or “No Change”.

The value of the diffusion index for a specific question is calculated as follows:

DI = (% Yes) + 0.5 * (% No Change);

After calculating diffusion indices for each question, they are averaged to obtain composite indices such as PMI or TANKAN.

These composite indices are highly effective in tracking the dynamics of the economic cycle as leading indicators.

For example, a decline in the index after a period of growth predicts a transition from expansion to recession, while an upward turn after a decline signals the beginning of recovery.

The strong correlation of diffusion indices with economic dynamics, as evidenced by long-term statistical data, enables their use in predicting future GDP values (at least a quarter ahead).

Today, such indices are published by nearly all G7 countries. For instance, in England, the PMI has been constructed since 1991.

The German PMI has been published since 1998 and includes surveys of 350 companies addressing the following five questions: output, new orders, employment, suppliers’ delivery times, and inventories 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 extensive coverage of business statistics, involving 34,000 participants, is provided by the American PMI index from the National Association of Purchasing Managers (NAPM), which has been maintained since 1931.

Notably, the staff providing these statistics numbered up to 300 people.

We will examine in detail the structure and characteristics of business optimism indices using the American Purchasing Managers’ Index (PMI) from the NAPM as an example.

The survey conducted by the American Association NAPM, which forms the basis of its PMI index, includes questions asking participants whether their business conditions 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 then-chairman of the Federal Reserve System, A. Greenspan.

For each item in the questionnaire, a diffusion index is calculated by adding the percentage of “higher” responses to half the percentage of “unchanged” responses.

These are then used to construct a weighted sum, resulting in the average PMI index. In 1994, the formula for PMI was as follows:

PMI = 0.30 * DI(New Orders) + 0.25 * DI(Production) + 0.20 * DI(Employment) + 0.15 * DI(Deliveries) + 0.10 * DI(Inventories)

Interpretation of the PMI Index: The primary characteristic of the PMI is its role as a leading business cycle indicator. There are several key levels of the indicator used for interpretation:

• Cyclic Maximum and Cyclic Minimum;
• 50% Level;
• 44% Level.

If, after a period of growth, the PMI begins to decline, it predicts a downward reversal of the business cycle. Conversely, if the PMI rises after reaching a minimum following a decline, it indicates a forthcoming recovery.

According to 40 years of US statistics, the PMI predicts the peaks of growth cycles an average of 7 months in advance and the troughs of growth cycles by 3 months.

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