What Is a Market Average?

The average market forecast is a kind of market forecast. It uses the theory of fluctuation equilibrium and the concept of averages to find a research statistical method that can reflect and express the overall market situation.

Market average forecast

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The average market forecast is a kind of market forecast. It uses the theory of fluctuation equilibrium and the concept of averages to find a research statistical method that can reflect and express the overall market situation.

Chinese name

Market average forecast

Types of

Average forecast

Category

professional phrases

Object

market

Market average forecast

Use scientific methods to investigate and study the factors affecting market supply and demand changes, analyze and foresee their development trends, grasp the laws of market supply and demand changes, and provide a reliable basis for business decisions, that is, market forecasts.

Market forecasts have a long history. According to the "Historical Records" of our country, after the 6th century to the 5th century BC, after Fan Fuguo defeated Wu Fuguo, he abandoned his business and business, and in 19 years, he won three golds and became a rich man in the world. His achievements in shopping malls depend on his understanding of market predictions. . For example, "If you have insufficient surplus, you will know that you are expensive, that is expensive, that which is expensive, and that which is low, which is expensive." This is how he predicts the price changes of commodities based on the supply and demand of commodities in the market.

Strictly speaking, market forecasts start in the second half of the 19th century. On the one hand, the market changes in the capitalist economy are extremely complicated. As long as it can obtain profits and reduce operating risks, it is necessary to grasp the changing laws of the business cycle. On the other hand, mathematical economics has gradually deepened the relationship between phenomena and quantities. The accumulation of data is also increasingly abundant, and the statistical methods applicable to dealing with economic issues, including market forecasts, are gradually being improved. Milestones in academia regarding market predictions have been counted by Austrian economist and statistician Spallat Neiman. He used index analysis to study the production of gold, silver, coal, iron, coffee, and cotton, issues related to railways, shipping, telecommunications, and international trade, as well as import and export value data from 1866 to 1873.

Forecasting serves decision-making in order to improve the scientific level of management and reduce the blindness of decision-making. We need to use forecasting to grasp the relevant dynamics of economic development or future market changes, reduce future uncertainty, and reduce risks that may be encountered in decision-making. Make the decision-making goals smoothly achieved.

Market forecasting, as an important part of modern business management activities and a complete modern management science, has the following basic characteristics:

(1) Systematic

(2) Scientific

(3) Application

The prophets of the future are not only longed for by humans, so predictions have been made for a long time, including the myth of "500 years before and 500 years later," so the prediction is that a disgraceful predecessor called "divination."

Of course, if a company can achieve a certain degree of prophecy, the benefits to the company's operation are of course self-evident. Of course, it is impossible to achieve complete prophecies. Otherwise, everyone is a millionaire and every business must flourish.

Although enterprises are not sure about the future, the progress of human understanding and thinking has made people discover the importance of "law". The ancients have long said that "distinguish and follow the way". "Tao" is the law. With historical experience, Accumulation and technological progress have greatly enhanced the ability of humans to understand nature. As an enterprise, discovering, recognizing, and using "laws" (including market, customer, technology, and enterprise development) will surely increase your chances of operation.

(I) Basic principles of prediction

In the simplest and most understandable way: it s a pattern like this

Known unknown, past, present future

Law, trend, logic, experience, and substance are the ability and means to analyze problems.

(B) Four Principles of Forecasting

Forecasting itself must rely on methods such as mathematics and statistics, as well as advanced methods. Let s not talk about technology and methods first. For the managers of an enterprise, what may be the first concern is how to form an effective way of thinking? The following principles may be instructive:

1. Relevant principles: It is based on the thinking of "classification", and pays attention to the correlation between things (categories). When you know (or assume) that something changes, you can infer the change trend of another thing. The most typical correlations are positive and negative correlations. In terms of ideas, they are not entirely data correlations, but more "qualitative". (1) Positive correlation is the "promotion" between things, for example, the average income of residents and the "air-conditioning ownership of 100 households"; some companies realize that "only children are valued" to infer the market for toys, education-related products and services; The regional government repeatedly asked the enterprise a question: "what opportunities does the improvement of people's material and cultural living standards bring?" This is actually the biggest opportunity facing unknown markets at present! The "home appliance industry", "kitchen revolution", and "healthcare products" that have been developed in this region should be the result of full understanding and detailed implementation. This also reflects the company's sense of opportunity. Another example is the current population census. Some experts suggested that the information is the "treasure" of the enterprise. It depends on how you know it. There is a large furniture company. One of the biggest opportunities to start is "the third wave of fertility in China. People are now at the height of starting a family. " (2) Negative correlation refers to the "restriction" between things, and the development of one thing leads to the restriction of another. Especially "alternatives." For example, the introduction of resource policies and environmental protection policies will inevitably lead to the emergence of "one-time resources" alternatives, such as the PVC plastic steel developed by "wood-generation steel"; The opportunity is the same.

2. Principle of inertia. The development of anything has certain inertia, that is, to maintain the original trend and state under certain conditions and conditions, which is also the theoretical basis of most traditional forecasting methods. Such as "linear regression", "trend extrapolation" and so on.

3. Analogy principle. This principle is also based on the thinking of "classification" and pays attention to the relationship between things. (1) Seeing big from small-inferring the general trend of things from a certain phenomenon: for example, now that someone is starting to buy a private car, what do you foresee? The use of this idea should prevent the substitution of dots and partiality. (2) From the surface to the surface-to push the essence from the surface phenomenon: for example, "Unified Food" was built in Kunshan, what should Wuxi "Zhongcui Noodles" be aware of? "Hai Lier" washing powder went to Southern Jiangsu for promotion, "Jia Jia washing powder" realized that it might be to grab the market. Another simplest example: the emergence of disposable liquid lighters, there are really examples of match factories not aware of the threat. (3) From here and beyond-the introduction of foreign advanced management and technology can also be explained by this idea. You remember a word: Sichuan people may not have thought of what they did in Shanghai. Things that have been eliminated in developed regions may have markets in backward regions. (4) From the past to the present-Mao Zedong said: I am not Li Zicheng. It can be seen that historical things are extremely instructive for future development. In other words: 10 years ago, who would dare to think that his home had air-conditioning, computers, and telephones? So standing now, we ask: Can you think about how you will own your car in 10 years? This reasoning is quite enlightening for businesses. Can you summarize the development law of Chinese home televisions? Maybe you can find business opportunities from it! (5) From far to near-such as foreign products, technologies, management models, marketing experience, and methods. Because it may be more advanced, it represents an advanced direction, which may be "the way to go tomorrow". (6) Bottom-up-from the typical local inference, a moderate-sized township requires 3 harvesters. This county has 50 similar towns. It can be estimated that the possible market capacity of this county's harvester is 150. station. (7) from top to bottom-subdivide from the global to understand and infer a certain part. For example, we want to know the capacity of a women s bicycle market in a city of 400,000 people, with 400,000 people200,000 women (removing under 12 and over 50 years old) and 100,000to investigate the rate of women s bicycles per 1,000 (Assuming 60%)-possible market capacity is 60,000. It is helpful to get a rough idea of a market.

4. The principle of probability inference. We cannot fully grasp the future, but based on experience and history, many times we can roughly estimate the approximate probability that an event will occur, and take corresponding measures based on this possibility. Poker, chess games, and corporate game-type decisions all use this principle unconsciously. Sometimes we can use scientific methods such as sampling design and surveys to determine the possibility of a certain situation.

To do a good job of forecasting, we must grasp the four basic elements of forecasting:

1. Information. Information is the representation and reflection of the characteristics and changes of objective things. It exists in various carriers and is the main work object, work basis and result reflection of prediction.

2. Method. Methods refer to various methods used in the qualitative and quantitative analysis in the process of prediction. The prediction methods can be divided into different categories according to different criteria. According to the attributes of prediction results, it can be divided into qualitative prediction and quantitative prediction. According to the length of the prediction, it can be divided into long-term prediction, medium-term prediction and short-term prediction. According to the method itself, it can be divided into many categories. The most basic are model prediction and non-model prediction.

3. Analysis. Analysis is a thinking research activity based on related theories. After the prediction conclusion is obtained according to the prediction method, two aspects of analysis must be performed: one is to theoretically analyze whether the prediction result meets the conditions of economic theory and statistical analysis; the other is to accurately analyze the prediction error in practice And evaluate the reliability of prediction results.

4. Judgment. It is necessary to judge whether the forecast result is adopted or not, or to modify the forecast result based on relevant economic and market dynamics. At the same time, the choice of information materials and forecast methods also needs to be judged. Judgment is an important factor in prediction technology.

Forecasting should follow certain procedures and steps to order work, coordinate planning and collaboration. The process of market forecasting roughly includes the following steps:

1.Determine the prediction target

Defining the purpose is the first step in carrying out market forecasting work. Because the purpose of the forecast is different, the content and project of the forecast, the required data and the methods used will be different. Clarifying forecasting goals is to formulate forecasting projects, formulate forecasting work plans, prepare budgets, allocate forces, and organize implementation to ensure that market forecasting work is carried out in a planned and rhythmic manner according to problems in business activities.

2. Collect information

Adequate information is required to make market forecasts. With sufficient data, a reliable basis for analysis and judgment can be provided for market forecasting. Under the guidance of the market forecasting plan, investigating and collecting relevant information about forecasting is an important part of market forecasting and the basic work of forecasting.

3.Select a prediction method

According to the prediction target and the applicable conditions and performance of various prediction methods, a suitable prediction method is selected. Sometimes multiple prediction methods can be used to predict the same target. Whether the prediction method is selected properly will directly affect the accuracy and reliability of the prediction. The core of applying the prediction method is to establish a model that describes and summarizes the characteristics and changes of the research object, and calculate or process according to the model to obtain the prediction result.

4.Predictive analysis and correction

Analytical judgment is a comprehensive analysis of the data collected by the survey, and through judgment and reasoning, the perceptual knowledge is promoted to become a rational one. On the basis of analysis and judgment, the original forecast results are usually evaluated and revised based on the latest information.

5. Write a forecast report

The forecast report should summarize the main activities of the forecast research process, including the forecast goals, forecast objects and related factors, analysis conclusions, main data and data, the choice of forecast methods and the establishment of models, and the assessment, analysis and correction of forecast conclusions, etc. .

The contents of market forecasts are very extensive and rich, from the macro to the micro, they are interconnected and complementary. Specifically, it mainly includes the following:

1. Forecast market capacity and changes. Market commodity capacity refers to the total demand for a certain currency to pay. The forecast of market capacity and its changes can be divided into market forecasts of production materials and market forecasts of consumer materials. The production capacity market forecast is based on a study of the development direction and development focus of the national economy, a comprehensive analysis of the adjustment of industrial production technology and product structure during the forecast period, and a forecast of the demand structure, quantity, and trend of industrial products. The focus of the consumer data market capacity forecast has the following three aspects:

(1) Forecast of consumer purchasing power. To predict consumer purchasing power, two predictions must be made: first, the number of people and their changes. The number of people and their development speed largely determine the level of consumer spending. Second, the forecast of consumer money income and expenditure.

(2) Prediction of purchasing power. The level of consumer income determines the consumption structure, that is, the ratio of commodity consumption expenditure to non-commodity consumption expenditure in consumers' living consumption expenditure. Consumption structure law is that the higher the income level, non-commodity consumption expenditures will increase, such as entertainment, recreational and labor expenses. Expenditure on food expenses will be greatly reduced. In addition, the influence of consumer psychology on purchasing power must be fully considered.

(3) Forecast changes in commodity demand and its development trends. According to the total purchasing power of consumers and the investment direction of purchasing power, predict the quantity, color, variety, specifications, quality, etc. of various commodity needs.

2. Predict changes in market prices. The price of input products and the sales price of products in an enterprise are directly related to the profitability of the enterprise. In the prediction of commodity prices, it is necessary to fully study the changes in labor productivity, production costs, profits, the development trend of market supply and demand, changes in currency value and currency circulation, and the impact of national economic policies on commodity prices.

3. Predict production development and its changing trend. The prediction of production development and its changing trend is the prediction of the supply of commodities in the market and its changing trend.

There are many ways to predict the market, including the following:

First, the time series prediction method

In market forecasting, we often encounter a series of time-varying economic index values, such as the annual (quarterly) sales volume of a company's product, the consumer's annual income, and the purchasing power growth statistics, etc. Group data is called time series. Time series prediction

Second, regression prediction method

1. The meaning of "regression". Regression is used to analyze and study the dependency relationship between one variable (dependent variable) and one or several other variables (independent variables). The purpose is to estimate or predict the dependent on a set of known independent variable data values. The population mean. In economic forecasting, people take the forecasting object (economic indicator) as the dependent variable, and those influencing factors that are closely related to the forecasting object as independent variables. Based on the historical and current statistics of the two, a regression model is established and used for prediction after statistical testing. Regression prediction has a one-variable regression prediction of one independent variable and a multiple regression prediction of multiple independent variables. Here, only one-variable linear regression prediction method is discussed here.

2. Basic conditions of regression analysis. When applying a set of known independent data to estimate and predict the value of a dependent variable, these two variables need to meet the following two conditions:

First, statistical correlation. Statistical correlation is an uncertain functional relationship, that is, a functional relationship in which the value of the dependent variable (predictive variable) is significantly related to the value of one or more independent variables, but cannot be precise and cannot be uniquely determined. All of the variables are Is a random variable. Such correlations are abundant in economic phenomena. For example, the relationship between the yield per mu of grain y and the amount of fertilizer x is obviously related but there is no strict functional relationship. The yield per mu is not only related to the amount of fertilizer applied, but also to various factors such as soil, rainfall, and temperature. There is randomness in the yield y.

Second, causality. If one or several independent variables x change, it affects another variable y according to a certain rule, and the change of y cannot affect x, that is, the change of x is the cause of the change of y, but not the opposite. Causality, a model that reflects causality is called a regression model.