Tech stocks and Treasury yields Spread: 22% annual return in past 15yrs

[quantitativo]

Interest rates, influenced by Treasury bond yields, are crucial in determining the discount rates used in valuing stocks. When Treasury yields rise, the discount rate for future cash flows also rises, reducing the present value of these cash flows. Tech stocks, which often have high growth expectations and cash flows projected far into the future, are particularly sensitive to changes in discount rates.

With that premise, today I backtested the following idea:

Signal:

• We compute a spread between QQQ (QLD using 2x leverage) and TLT (UBT using 2x leverage) as the ratio between both prices;
  
  
• We then compute the 3-day RSI of the spread to track overbought and oversold signals;
  

Entry rules:

• When the 3-day RSI of the spread is below 10, we go long on QQQ;
• When the 3-day RSI of the spread is above 90, we go long on TLT;
  

Exit rules:

• When the 3-day RSI of the spread is above 60, we close QQQ trade;
• When the 3-day RSI of the spread is below 40, we close TLT trade.

Results

Equity curve

Monthly and annual returns

Summary of the backtest statistics

Summary of the backtest trades

Key points:

• The annual return achieved 22.1% in comparison to 18.4% QQQ in the same period;
  
  
• This annual return was lower than the QLD's (31.3%); however, the strategy was invested only 63% of the time. If it were invested the whole period, the return would have been 35.3% (the exposure-adjusted return);
  
  
• The strategy delivered a lower maximum drawdown (27%) in comparison to both QQQ and QLD;
  
  
• Although the average drawdown was worse (4.6% vs. 2.4% QQQ) and longer (24 days vs. 14 days QQQ), the strategy had almost half of the drawdowns (13/year vs. 23/year QQQ).
  

Although I like the logic of the idea, I didn't like these results.
Maybe the RSI of the spread, computed as stated, is not the best instrument to trade this relationship... anyway...

I created a full write-up with all the details here.

I'd love to hear what you guys think...

Cheers!

 

[vanzandt]

Interest rates, influenced by Treasury bond yields, are crucial in determining the discount rates used in valuing stocks. When Treasury yields rise, the discount rate for future cash flows also rises, reducing the present value of these cash flows. Tech stocks, which often have high growth expectations and cash flows projected far into the future, are particularly sensitive to changes in discount rates.

With that premise, today I backtested the following idea:

Signal:

• We compute a spread between QQQ (QLD using 2x leverage) and TLT (UBT using 2x leverage) as the ratio between both prices;
  
  
• We then compute the 3-day RSI of the spread to track overbought and oversold signals;
  

Entry rules:

• When the 3-day RSI of the spread is below 10, we go long on QQQ;
• When the 3-day RSI of the spread is above 90, we go long on TLT;
  

Exit rules:

• When the 3-day RSI of the spread is above 60, we close QQQ trade;
• When the 3-day RSI of the spread is below 40, we close TLT trade.

Results

Equity curve

Monthly and annual returns

Summary of the backtest statistics

Summary of the backtest trades

Key points:

• The annual return achieved 22.1% in comparison to 18.4% QQQ in the same period;
  
  
• This annual return was lower than the QLD's (31.3%); however, the strategy was invested only 63% of the time. If it were invested the whole period, the return would have been 35.3% (the exposure-adjusted return);
  
  
• The strategy delivered a lower maximum drawdown (27%) in comparison to both QQQ and QLD;
  
  
• Although the average drawdown was worse (4.6% vs. 2.4% QQQ) and longer (24 days vs. 14 days QQQ), the strategy had almost half of the drawdowns (13/year vs. 23/year QQQ).
  

Although I like the logic of the idea, I didn't like these results.
Maybe the RSI of the spread, computed as stated, is not the best instrument to trade this relationship... anyway...

I created a full write-up with all the details here.

I'd love to hear what you guys think...

Cheers!

No idea if the above means anything or not... but at least you never give up Quanto. I do like that.

 

[Actuarial_Fun]

Interesting. I'd be curious how it does in a bear market. This is pretty much vertical up for QQQ in this time period, so I would personally backtest from mid-90s to 2010 and see what those results look like. I understand you'd need to find a proxy for TLT, but I still think it's better to do this then not, given the bull market during this period.

 

[schizo]

Interest rates, influenced by Treasury bond yields, are crucial in determining the discount rates used in valuing stocks. When Treasury yields rise, the discount rate for future cash flows also rises, reducing the present value of these cash flows. Tech stocks, which often have high growth expectations and cash flows projected far into the future, are particularly sensitive to changes in discount rates.

With that premise, today I backtested the following idea:

Signal:

• We compute a spread between QQQ (QLD using 2x leverage) and TLT (UBT using 2x leverage) as the ratio between both prices;
  
  
• We then compute the 3-day RSI of the spread to track overbought and oversold signals;

Entry rules:

• When the 3-day RSI of the spread is below 10, we go long on QQQ;
• When the 3-day RSI of the spread is above 90, we go long on TLT;

Exit rules:

• When the 3-day RSI of the spread is above 60, we close QQQ trade;
• When the 3-day RSI of the spread is below 40, we close TLT trade.

Results

Equity curve

Monthly and annual returns

Summary of the backtest statistics

Summary of the backtest trades

Key points:

• The annual return achieved 22.1% in comparison to 18.4% QQQ in the same period;
  
  
• This annual return was lower than the QLD's (31.3%); however, the strategy was invested only 63% of the time. If it were invested the whole period, the return would have been 35.3% (the exposure-adjusted return);
  
  
• The strategy delivered a lower maximum drawdown (27%) in comparison to both QQQ and QLD;
  
  
• Although the average drawdown was worse (4.6% vs. 2.4% QQQ) and longer (24 days vs. 14 days QQQ), the strategy had almost half of the drawdowns (13/year vs. 23/year QQQ).

Although I like the logic of the idea, I didn't like these results.
Maybe the RSI of the spread, computed as stated, is not the best instrument to trade this relationship... anyway...

I created a full write-up with all the details here.

I'd love to hear what you guys think...

Cheers!

Interesting. Never thought there would be a correlation between Treasuries and Tech. Anyway, I would also like to see 2000-2002 and 2007-2008 bear markets in the mix.

 

[nitrene]

It's just CAPM quantized via DCF analysis.

The strategy would work even better if you differentiated long dated assets (lot of upfront investment with payoff much later) vs short dated assets (companies that don't need any more investment). Long dated assets were like HOOD, COIN, RIVN, RBLX, etc. vs short dated assets like all the big tech stocks. Long dated assets crashed hard where big tech didn't go down as much.

ARKK could represent long dated tech stocks vs. FNGS (or even SMH) for short dated tech stocks. I guess QQQ is already top heavy with short dated tech stocks as well.

 

[murray t turtle]

Interesting. I'd be curious how it does in a bear market. This is pretty much vertical up for QQQ in this time period, so I would personally backtest from mid-90s to 2010 and see what those results look like. I understand you'd need to find a proxy for TLT, but I still think it's better to do this then not, given the bull market during this period.

%%
MAYBE good in SPY -QQQ 2015 type markets=chop slop sideways trend;
if QQQ makes $7 on $100, 7% more or less-2015 i wouldnt want to trade QQQthen .
Of course we wouldnt know that in advance;
but QQQ had a negative JAN 2015, so likley a bear market, even though it made 7%+/ JAN-DEC 2015