Our model readings from last week held steady as mid and small-cap areas gained some steam from low levels.
This Week on Wall Street - Week of April 24th
Our model readings from last week held steady as mid and small-cap areas gained some steam from low levels. Foreign Developed is still showing relative strength while growth widened its gap over value.
We are still in a choppy trading zone as traders look to 4,180 as strong resistance. As we enter the thick of earnings season, volatility will remain elevated. It is a lighter week on the economic front outside of the GDP number on Thursday. Fed members are in their blackout period for the week.
Among sectors, we are seeing strength out of Cyclicals, Technology, and Communications while Energy and Health Care are at the bottom of the pile. Picking names with relative strength within sectors has remained the dominant and most effective strategy.
What is Newton?
r Newton model attempts to determine the highest probability of future price direction by using advanced algorithmic and high-order mathematical techniques on the current market environment to identify trends in underlying security prices. The Newton model scores securities over multiple time periods on a scale of 0-20 with 0 being the worst and 20 being the best possible score. Trend & level both matter.
Economic Releases This Week
Monday: None Scheduled
Tuesday: S&P Case-Shiller Home Price Index,
Wednesday: Fed Beige Book, New York Fed President Williams Speaks
Thursday: Initial & Continuing Jobless Claims, Q1 2023 GDP, Pending Home Sales
Friday: Employment Cost Index, PCE Index, Personal Spending
Technical trading models are mathematically driven based upon historical data and trends of domestic and foreign market trading activity, including various industry and sector trading statistics within such markets. Technical trading models, through mathematical algorithms, attempt to identify when markets are likely to increase or decrease and identify appropriate entry and exit points. The primary risk of technical trading models is that historical trends and past performance cannot predict future trends and there is no assurance that the mathematical algorithms employed are designed properly, updated with new data, and can accurately predict future market, industry and sector performance.