Trump’s Tough Talk on NAFTA Raises Prospects of Pact’s Demise

The North American Free Trade Agreement, long disparaged by President Trump as bad for the United States, was edging closer toward collapse as negotiators gathered for a fourth round of contentious talks here this week.

In recent weeks, the Trump administration has sparred with American businesses that support NAFTA and has pushed for significant changes that negotiators from Mexico and Canada say are nonstarters. All the while, the President has continued threatening to withdraw the United States from the trade agreement, which he has maligned as the worst in history. Read more...

As India Crosses the Digital Divide, a New Era of Investment Opportunities Dawns

When can a country's bluechip stocks be a bargain if they're trading at historically high forward earnings valuations after posting world-beating returns over the last two decades? Right now, if they're Indian, and your investment horizon is at least five years or, better still, up to a decade.

The dollar-denominated MSCI India Index has returned just shy of 400% over the last 20 years, but Morgan Stanley still expects India's stock market capitalization to about triple over the next 10 years to $6.1 trillion. That's the baseline; in a bullish scenario, the potential upside quadruples to $8.5 trillion, driven by eye-watering earnings growth and multiple expansion in the country's consumer and financials sectors. Read more...

Good Advice vs. Effective Advice

One of the hardest parts about giving financial advice, or any advice for that matter, is the fact that good advice alone is not enough. Good advice is all around us and people simply choose to ignore it much of the time.

Telling a friend or family member who is overweight to eat better and workout periodically is good advice. But for most people, that good advice will not be effective. They already know what they should do. Read more...

When your robot learns from humans, who should train it?

Let's say you want to teach a robot to play basketball. How do you decide who should train it? Should you have it learn from an all-star, so that the robot mimics that player's particular style? Or should it learn from a blend of data from multiple players with varying play styles across myriad teams?

That question is top of mind for Suzanne Gildert, the co-founder and chief science officer of Vancouver-based robotics company Kindred. Since 2014, her company has been developing intelligent robots that can be taught by humans to perform automated tasks — for example, handling and sorting products in a warehouse. Read more...