The business strategy of purchasing teams and organizations must closely monitor real time commodity price forecasts and trends. It enables companies to foresee pricing-related risks, and plan, and manage suppliers proactively while avoiding supply chain interruption brought on by price volatility.
Category managers have a crucial role in budget planning, and the structure of the organization, the financial and procurement teams may also play apart. Based on industry and price projection insights for the upcoming six, twelve, and eighteen months, forecasting solutions enable buyers of commodities, natural resources, and services to make confident planning decisions.
The ability to prioritize categories and concentrate on the most volatile ones is a key advantage of price tracking and forecasting in various categories within a manager's product portfolio. This includes looking at price hedges as a risk mitigation approach.
AI-Based Forecasting - Live Commodity Prices
Forecasting models based on AI/ML can offer more precise projections over a wider range of regions and exchanges for longer periods. Additionally, these algorithms are capable of sifting through vast volumes of previous data to uncover hidden patterns that aid businesses in making wiser and more profitable business decisions. The following are some advantages of AI-based commodities forecasting :
- The ability to handle extreme price fluctuation.
- The ability to combine many predictors from different sources.
- Accurate forecasting across several time horizons
- Model errors in reading, or the ability to recognize a variable's importance.
Factors influencing the product Price Sensitivity
Supply and demand are important factors. Prices for oil, natural gas, and electricity are frequently more erratic than those for other commodities. The fact that several users have few options for switching to alternate fuels when the cost of natural gas , for instance, changes is one reason for the unpredictability of energy costs. Residential customers often cannot quickly alter their heating systems, and it might not be financially advantageous in the long run.
Customers can quickly replace food items when the relative costs of foodstuffs change, but they are limited in their ability to accomplish this when it comes to heating their homes.
How does Commodity Price Forecasting work?
PriceVision examines previous price changes and levels to make price predictions using specific techniques. Although this has been compared to driving a car while only looking in the rearview mirror, the wide acceptance of traders gives it credibility. By tracking prices (often futures) and searching for recurring patterns, traders forecast when price movements will alter and how both high and low prices will move.
Commodity markets are examined using both technical and fundamental research. Foundations, or supply/demand factors, typically provide the market with its underpinnings. Price vision is used to predict the timing and size of price changes as well as to show the general price trend. Fundamentals are the most powerful force of the two. While a market's reaction to technical indicators can have a significant impact because so many financial markets pay attention to them.
To investigate lines and patterns, a variety of techniques are employed. They can change depending on the person, the type of evaluation, and the current style. Because so many individuals use those popular strategies to invest money, the most popular techniques frequently turn into the ones that are most correct. So, they might end up being a self-fulfilling prophecy. The most popular methods are:
- High/low/close or bar charts
- Dynamic averages
- pattern lines
- Axes of resistance and support
- Overlapping tops and bottoms
- Forming a head and shoulders
- Trading activity
- Open curiosity
How PriceVision Helps in Demand Prediction
In order to help shops be more competitive, PriceVision helps forecast the future need for every item and obtains real-time information. Producing daily, weekly, or monthly pricing estimates, enables wise and lucrative business decisions.
- Charts technical analysis can be used to support your analysis.
- Avoid losses and lost opportunities to save money.
- predicting pricing across all regions
- Using simple data drivers
- ML-based prediction of commodities prices
- more extensive time frames for commodity forecasting
Potential Use of Artificial Intelligence in Commodities Management
One thing is certain: AI would play a key role in commodities intelligence in the future. With increased volatility and unpredictability affecting commodities and more information sources are accessible to support decisions. Numerous businesses are already providing AI solutions for commodity management as a result. Since we belong to them, we should know.
We do, however, also understand that chasing the latest tech may not be the best course of action — acceptability, flexibility, and ROI all have an impact — and as a result, traditional approaches to commodities forecast management continue to provide a sizable amount of value.
Commodity managers can gain the knowledge they need from AI to improve their decisions and estimate the prices of future commodities .
Due to supply chain disruptions brought on by the coronavirus epidemic, prices have recently experienced unprecedented volatility, testing the basic foundations of the discipline for commodity price forecasting. As a result, the PriceVision team keeps collaborating with our clients to deliver real-time price tracking and monitoring across regions based on macro trends like global pandemic developments, border closures, labor market slowdowns, and legislative changes, rules, and regulations.
To discuss your commodity price forecasting and tracking needs or to gain a better understanding of the procurement services offered by PriceVision visit us at https://pricevision.ai/