Non-farm Payrolls Suspense: Between 70,000 and 225,000, which number is most likely to shake the market?

Forexlive analyst Eamonn has released the estimated range for today's US non-farm payroll report. These ranges are crucial for market reactions, as unexpected effects occur when actual data deviates from expectations. Another important factor influencing market reactions is the distribution of forecast values. In fact, while we may have an estimated range, most forecasts may be concentrated at the upper limit of the range. Therefore, even if the data falls within the estimated range but at the lower end of the range, unexpected effects can still occur. Forecast Distribution Non-farm Employment The estimated range is 70,000 to 225,000 Most concentrated between 165,000 and 185,000 Unemployment Rate 4.2% (7%) 4.1% (83%) 4.0% (10%) Average Hourly Earnings Annual Rate 3.9% (3%) 3.8% (27%) 3.7% (52%) 3.6% (18%) Average Hourly Earnings Monthly Rate 0.4% (10%) 0.3% (64%) 0.2% (26%) Average Weekly Hours 34.3 (77%) 34.2 (20%) 34.1 (3%) Why is it important to understand these expected ranges? Data results that exceed the market's expected lows and highs often have a more significant impact on the market for the following reasons: Surprise factor: Markets typically price based on forecasts and past trends. When data significantly deviates from these expectations, a surprise effect occurs. This leads investors and traders to quickly reassess assets based on new information, triggering significant price fluctuations. Psychological impact: Investors and traders are influenced by psychological factors. Extreme data points can trigger strong emotional reactions, leading to market overreactions. This amplifies market volatility, especially in the short term. Risk reassessment: Unexpected data leads to a reassessment of risks. If data is significantly lower or higher than expected, it changes the perceived risk of certain investments. For example, better-than-expected economic data may reduce the perceived risk of investing in stocks, leading to a market rally. Triggering automated trading: In today's markets, most trades are executed by algorithms. These automated systems often have preset conditions or thresholds, and when unexpected data triggers these conditions, it can lead to large-scale buying or selling activities. Impact on monetary and fiscal policy: Data significantly deviating from expectations affects central banks and government policies. For example, in today's upcoming non-farm payroll report, a weaker employment report will increase speculation of more and potentially larger Federal Open Market Committee (FOMC) rate cuts. A stronger report will reduce such expectations. Liquidity and market depth: In some cases, extreme data points can impact market liquidity. If data is surprising enough, it may cause a temporary imbalance between buyers and sellers until a new equilibrium is found, leading to significant market fluctuations. Chain reactions and correlations: Financial markets are interconnected. As unexpected data leads to significant fluctuations in one market or asset class, it may trigger correlated fluctuations in other markets, amplifying the overall market impact