Stochastics Back U.S. Bond Rally, RBS Says: Technical Analysis

Treasury 30-year bond momentum “is turning bullish” and the debt may be poised to pare the worst losses since 2009, according to Royal Bank of Scotland Group Plc, citing technical analysis.

Weekly slow stochastics, a measure used to predict a security’s movement based on how close its price is to its highest or lowest levels, are signaling stronger sentiment for the long bond after indicating weakness since May, according to William O’Donnell and John Briggs, interest-rate strategists in Stamford, Connecticut, at the bank’s RBS Securities unit.

“The price momentum of the selloff has been losing thrust in recent weeks as the market has become oversold,” said O’Donnell, head U.S. government-bond strategist at RBS, one of 21 primary dealers that trade with the Federal Reserve. “We may be looking at the end of bearishness and a phase of lower rates.”

Yields on 30-year bonds fell two basis points, or 0.02 percentage point, to 3.69 percent in New York, according to Bloomberg Bond Trader prices. The yield on the benchmark 10-year note traded at 2.75 percent.

Thirty-year debt has lost 12.5 percent this year, the worst since a 26 percent drop in 2009, according to Bank of America Merrill Lynch indexes. Benchmark 10-year notes have lost 6.8 percent, the most since a 9.7 percent drop in 2009.

A close below 2.74 percent on the 10-year yield would signal a breakout of a bearish trend that may send the benchmark yield to as low as 2.43 percent, O’Donnell said.

Debate about when Fed policy makers will taper $85 billion in monthly bond buying has roiled financial markets around the world during the past three months and sparked a selloff in fixed-income assets.

In technical analysis, investors and analysts study charts of trading patterns to forecast changes in a security, commodity, currency or index.

To contact the reporter on this story: Cordell Eddings in New York at ceddings@bloomberg.net

To contact the editor responsible for this story: Dave Liedtka at dliedtka@bloomberg.net

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