At the same time, mortgage rates have hit seven-year highs, making things more expensive for any prospective home buyer. With this context in mind, today’s map comes from HowMuch.net, and it shows the salary needed to buy a home in the 50 largest U.S. metro areas.

The Least and Most Expensive Metro Areas

As a reference point, the median home in the United States costs about $257,600, according to the National Association of Realtors. With a 20% down payment and a 4.90% mortgage rate, and taking into account what’s needed to pay principal, interest, taxes, and insurance (PITI) on the home, it would mean a prospective buyer would need to have $61,453.51 in salary to afford such a purchase. However, based on your frame of reference, this national estimate may seem extremely low or quite high. That’s because the salary required to buy in different major cities in the U.S. can fall anywhere between $37,659 to $254,835.

The 10 Cheapest Metro Areas

Here are the cheapest metro areas in the U.S., based on data and calculations from HSH.com: After the dust settles, Pittsburgh ranks as the cheapest metro area in the U.S. to buy a home. According to these calculations, buying a median home in Pittsburgh – which includes the surrounding metro area – requires an annual income of less than $40,000 to buy. Just missing the list was Detroit, where a salary of $48,002.89 is needed.

The 10 Most Expensive Metro Areas

Now, here are the priciest markets in the country, also based on data from HSH.com: Topping the list of the most expensive metro areas are San Jose and San Francisco, which are both cities fueled by the economic boom in Silicon Valley. Meanwhile, two other major metro areas in California, Los Angeles and San Diego, are not far behind. New York City only ranks in sixth here, though it is worth noting that the NYC metro area extends well beyond the five boroughs. It includes Newark, Jersey City, and many nearby counties as well. As a final point, it’s worth mentioning that all cities here (with the exception of Denver) are in coastal states. Notes on Calculations Data on median home prices comes from the National Association of Realtors and is based on 2018 Q4 information, while national mortgage rate data is derived from weekly surveys by Freddie Mac and the Mortgage Bankers Association of America for 30-year fixed rate mortgages. Calculations include tax and homeowners insurance costs to determine the annual salary it takes to afford the base cost of owning a home (principal, interest, property tax and homeowner’s insurance, or PITI) in the nation’s 50 largest metropolitan areas. Standard 28% “front-end” debt ratios and a 20% down payments subtracted from the median-home-price data are used to arrive at these figures. on Last year, stock and bond returns tumbled after the Federal Reserve hiked interest rates at the fastest speed in 40 years. It was the first time in decades that both asset classes posted negative annual investment returns in tandem. Over four decades, this has happened 2.4% of the time across any 12-month rolling period. To look at how various stock and bond asset allocations have performed over history—and their broader correlations—the above graphic charts their best, worst, and average returns, using data from Vanguard.

How Has Asset Allocation Impacted Returns?

Based on data between 1926 and 2019, the table below looks at the spectrum of market returns of different asset allocations:
We can see that a portfolio made entirely of stocks returned 10.3% on average, the highest across all asset allocations. Of course, this came with wider return variance, hitting an annual low of -43% and a high of 54%. A traditional 60/40 portfolio—which has lost its luster in recent years as low interest rates have led to lower bond returns—saw an average historical return of 8.8%. As interest rates have climbed in recent years, this may widen its appeal once again as bond returns may rise. Meanwhile, a 100% bond portfolio averaged 5.3% in annual returns over the period. Bonds typically serve as a hedge against portfolio losses thanks to their typically negative historical correlation to stocks.

A Closer Look at Historical Correlations

To understand how 2022 was an outlier in terms of asset correlations we can look at the graphic below:

The last time stocks and bonds moved together in a negative direction was in 1969. At the time, inflation was accelerating and the Fed was hiking interest rates to cool rising costs. In fact, historically, when inflation surges, stocks and bonds have often moved in similar directions. Underscoring this divergence is real interest rate volatility. When real interest rates are a driving force in the market, as we have seen in the last year, it hurts both stock and bond returns. This is because higher interest rates can reduce the future cash flows of these investments. Adding another layer is the level of risk appetite among investors. When the economic outlook is uncertain and interest rate volatility is high, investors are more likely to take risk off their portfolios and demand higher returns for taking on higher risk. This can push down equity and bond prices. On the other hand, if the economic outlook is positive, investors may be willing to take on more risk, in turn potentially boosting equity prices.

Current Investment Returns in Context

Today, financial markets are seeing sharp swings as the ripple effects of higher interest rates are sinking in. For investors, historical data provides insight on long-term asset allocation trends. Over the last century, cycles of high interest rates have come and gone. Both equity and bond investment returns have been resilient for investors who stay the course.

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