Did you know that the trading and investing system you are using today uses three sciences at once? Firstly, economics is the basis for the theory of supply and demand. Second, mathematics and statistics are tools for processing supply and demand information. Third, information and communication technologies are useful in transmitting the results of supply and demand data processing. to your screen

In this article, let us first get rid of the economic and technological aspects. Let’s focus on statistics. You must remember that technical indicators in trading use a combination of mathematical and statistical formulas. moving average For example, it is the quotient between the average price (average) and a period of time. It is called moving because its value changes with the change in the average value of the price during a given date.

In addition to moving averages There are still many statistical concepts used in trading and investing. One of them is linear regression. What is linear regression and how is it useful in trading and investing? Check out the following checks.

Definition of Linear Regression

Linear regression is a statistical method used to describe the relationship between a dependent variable and an independent variable. The concept of linear regression is widely used in finance, economics, investment or other research. that uses quantitative data analysis

Independent variables or independent variables are factors that may affect the change in the value of the dependent variable. A dependent variable is something whose value can be influenced by independent variables. Usually, these dependent variables are what become the main topic of research.

Simply put, the relationship between the dependent variable and the independent variable looks like this:

“How do dependent variables change? if the independent variable changes with beta”

type of regression

There are different types of regression in the world of statistics. However, there are two types of basic regression that you should understand first:

Figure 1: One Variable Linear Regression (Source: Mipa.ugm.ac.id)

The above equation is called linear regression because the independent variable has no order. (squared or power 3), so the graph shown is skewed. Linear regression may consist of a single independent variable or multiple independent variables.

Polynomial regression is a regression with independent variables in the form of powers. Typically, the graph displayed from the result of data processing using this regression takes the form of an arc. This graph can be skewed like a typical linear regression graph. If the pattern of the variable Y is changed to logarithmic (log) or natural logarithm (ln), as with linear regression. Polynomial regression can also consist of one or more independent variables at once.

In the two images above, there are a number of terms that you need to understand. First, beta zero is called a constant. Simply put, a constant is the value of Yi if the value of Xi is 0 in statistical terms. This value does not change the alias constant.

Second, the coefficient (beta 1) is the value of the change or influence on the variable Y if there is a change in variable X. For example, it can be seen that beta 1 equals 0.5. This indicates that a change of 1 unit in variable X changes the value of Y 0.5 in some fields of science This coefficient is also known as a gradient.

The last is the error variable. in the context of statistics Error is something outside the researcher’s control that can affect the Y value. Usually, this error is calculated using the standard deviation method.

Using linear regression in trading and investing

by page Investopedia, linear regression in investing and trading It is used to study the relationship between time and price in chart analysis. In this case, time acts as an independent variable. while price acts as a dependent variable. This interaction between price and time is called a trend.

If it relates to the concept of relationship between dependent variable and independent variable above. In this context, the purpose of linear regression in chart trading and investment analysis is to answer the question: “How do the prices of trading instruments and investments change if time changes by 1 unit (maybe days, hours, minutes or seconds).

Why is time used as an independent variable? Because at that moment, there are many things that can affect the price. be it the amount of incoming demand and supply, as well as something more fundamental in nature.

in fundamental analysis The use of linear regression in investing and trading is becoming more common, for example, to calculate the effect of a reference interest rate on a stock price. (independent variable) will cause the stock price to fall (dependent variable)

However, the decline in stock prices is influenced not only by interest rates. but also other factors such as the company’s income company business opportunities, etc. You can also combine other factors. These are independent variables.

How To Use Linear Regression To Make Profitable Trading

1. Understand the theory

The first way to use linear (or polynomial) regression to profit in trading is to understand the theory first. This theory is not the only theory of how to read the influence of independent variables on the above variables. but also economic theory So you know what factors you can include in the independent variables.

This is because each trading and investment tool has different influencing factors. Forex and stocks such as Although both are influenced by the benchmark interest rate and inflation. The share price is still affected by the company’s performance. while the exchange rate is not so.

2. Reading Research

The theory that you already understood above. You can use it for:

  • Process raw data directly and interpret your own research results.
  • Read other people’s research on the topic.

instead of using only one method It is better to use an understanding of the theory above for both simultaneously. The reasons are:

  • The topics discussed may be the same. For example, research findings on the effect of interest rates on stock prices in the United States may differ from research on the same topic in Indonesia.
  • The topic discussed may be the same, the same place, but the research time is different. It’s possible that you found research on the impact of interest rates on stock prices in Indonesia in 2000-2010, but not up-to-date. So you have to do it yourself.
  • The title, location, and year are the same. But the results differed between different researchers. This can happen due to different methods. Independent variables and dependent variables and the error value entered You have to infer for yourself what the overall outcome of the topic will be.

3. Using linear regression results in decision making

After understanding the theory Analyze yourself and read the research. You can now apply the results of your understanding to plan a trade and investment decisions

For example, the results of your analysis and the research you read prove that the impact of an increase in the Indonesian bank’s benchmark interest rate will lower stock prices on the Indonesian stock market. from this conclusion You can be prepared to sell the shares you own and switch to other investment tools that will benefit if interest rates rise.


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