U.S. President Donald Trump’s tax cut package is apparently yet to produce a substantial boost in business spending, as suggested by a recent survey result.
According to the National Association of Business Economics' (NABE) quarterly business conditions poll published on Monday, 84% of respondents indicated that corporate tax cuts did not lead them to change plans. That percentage is even bigger compared to the 81% in the survey published in October.
The $1.5 trillion cut tax package – which included a reduction of corporate tax rate to 21% from 35% - is the largest U.S. tax code overhaul in more than three decades. It was expected to free up more cash for companies to increase employment and/or expand capital spending. But that may not have fully translated into reality as yet, according to the survey.
The survey's gauge of capital spending fell in January to its lowest level since July 2017. Projections on capital spending for the next three months also dropped. There was a modest improvement in employment growth in the fourth quarter of 2018, compared to the third quarter. The measure for projected employment over the next three months declined to 25 in January, from 29 in October.
However, looking at the goods producing sector in isolation, the tax cut did seem to have an impact. Half of the respondents from that sector reported increased investments at their companies, while 20% claimed to have reallocated investments and employment to the U.S. from abroad.
Sergey Savastiouk, Ph.D. has a degree in Applied Mathematics from Moscow University and has extensive experience as an entrepreneur, investor, manager, and mathematician. His professional expertise is in applied mathematics, mathematical modeling, system and pattern analysis, and software and hardware system integration. He has served as the CEO of several hi-tech start-up companies and nonprofit organizations, which has given him proven capabilities in business strategy for high-tech start-up companies, market assessment, company formation, team building, product development, marketing, and sales. He has published numerous articles in journals and magazines on related fields. As a retail investor, he spent 15 years developing his proprietary trading and quantitative algorithms (now Tickeron’s A.I.), which brought him significant returns in trading the stock market. His current work and goal in founding Tickeron is to bring professional, sophisticated stock market analysis capabilities to retail investors via an easy-to-use interface.
SPY broke above its upper Bollinger Band on August 04, 2026. This could be a sign that the stock is set to drop as the stock moves back below the upper band and toward the middle band. You may want to consider selling the stock or exploring put options. The A.I.dvisor looked at 40 similar instances where the stock broke above the upper band. In of the 40 cases the stock fell afterwards. This puts the odds of success at .
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The Moving Average Convergence Divergence Histogram (MACD) for SPY turned negative on August 20, 2026. This could be a sign that the stock is set to turn lower in the coming weeks. Traders may want to sell the stock or buy put options. Tickeron's A.I.dvisor looked at 52 similar instances when the indicator turned negative. In of the 52 cases the stock turned lower in the days that followed. This puts the odds of success at .
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The Stochastic Oscillator demonstrated that the ticker has stayed in the oversold zone for 2 days, which means it's wise to expect a price bounce in the near future.
SPY moved above its 50-day moving average on July 31, 2026 date and that indicates a change from a downward trend to an upward trend.
The 10-day moving average for SPY crossed bullishly above the 50-day moving average on August 05, 2026. This indicates that the trend has shifted higher and could be considered a buy signal. In of 15 past instances when the 10-day crossed above the 50-day, the stock continued to move higher over the following month. The odds of a continued upward trend are .
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The average fundamental analysis ratings, where 1 is best and 100 is worst, are as follows
Category LargeBlend