Understanding market forecasts
Market forecasts help investors prepare for changes in prices and economic conditions. Learn which signals to watch and how they can inform investment decisions.
What goes into a market forecast
Market forecasting draws on economics, psychology, and data science to explain price movements. Understanding what drives those movements can help investors spot emerging trends and decide how to respond.
Forecasters study liquidity, market sentiment, and economic conditions to estimate possible outcomes. A model that fits past prices may fail on new data, and a forecast does not guarantee a profitable investment.
Economic indicators
Interest rates, inflation, and GDP growth all influence global markets. Central bank policies, particularly those of the Federal Reserve, affect how much liquidity is available.
- Interest rates set the cost of capital and influence willingness to invest.
- Inflation reduces the purchasing power of money. Its effect on asset prices depends on market conditions and expectations.
- GDP measures the value of final goods and services produced within an economy; it is not a direct measure of productivity.
Technical analysis and sentiment
Economic analysis helps explain why markets move; technical analysis helps forecasters assess timing. Sentiment reflects the collective mood of market participants. Excessive optimism or pessimism can create opportunities for investors who take the opposing view.
Short- and medium-term forecasts draw on support and resistance levels, momentum oscillators, and volume profiles. Our techniques page explains approaches to forecasting.
Forecasting different asset classes
Equities
Equity forecasts use earnings yields, sector rotation, and equity risk premiums to find gaps between stock valuations and growth potential.
Fixed income
Bond forecasters study yield curves and credit spreads for signals about the bond market and the wider economy.
Commodities
Forecasts for gold, oil, and agricultural products account for supply chains and geopolitical stability, as well as currency movements, particularly in the US dollar.
Planning for market shocks
Black swan events are unpredictable shocks with large consequences. A financial forecasting model can include stress tests for extreme outcomes, even when it cannot predict the events themselves precisely.
Stress tests explore how a portfolio could respond to specified shocks. They cannot cover every possible event or establish the maximum loss an investor could face.
Alternative data sources
Forecasters also use alternative data to supplement traditional market records:
- Satellite imagery helps monitor retail parking lots or oil tankers.
- Natural language processing (NLP) tracks consumer trends through social media sentiment in real time.
- Credit card transaction data can reveal spending changes before official reports.
Our forecasting guide covers data collection and tools for working with these sources.
Market sentiment
Market sentiment is one input to a forecast. Compare it with prices, trading volume, and economic data before drawing conclusions.