New academic paper related to #12 – Pairs Trading with Stocks

"In this study, we show that pairs trading, assuming the mean-reverting spread process, satis es the de nition of statistical arbitrage. However, we also show that a time independent error in trader's guess or forecast of the long-term mean level causes the failure of the statistical arbitrage de nition. In other words, a perfect statistical arbitrage with the probability of loss decaying to zero is not available whenever there is uncertainty in the model parameters. The good news is that the probability of loss can be bounded as a function of the estimation error and given suciently good estimates, the trader can still implement pairs trading knowing the potential probability of loss involved.

Second, we derive optimal thresholds for starting the pairs trading, which can be used by the trader to select the best pairs of stocks for trade. In our framework, out of hundreds of possible pairs of assets, the trader can identify the pairs with highest probability of successful execution for a given investment horizon."


Are you looking for more strategies to read about? Sign up for our newsletter or visit our Blog or Screener.

Do you want to learn more about Quantpedia Premium service? Check how Quantpedia works, our mission and Premium pricing offer.

Do you want to learn more about Quantpedia Pro service? Check its description, watch videos, review reporting capabilities and visit our pricing offer.

Are you looking for historical data or backtesting platforms? Check our list of Algo Trading Discounts.

Would you like free access to our services? Then, open an account with Lightspeed and enjoy one year of Quantpedia Premium at no cost.


Or follow us on:

Facebook Group, Facebook Page, Twitter, Linkedin, Medium or Youtube

Share onRefer to a friend
Subscription Form

Subscribe for Newsletter

 Be first to know, when we publish new content
logo
The Encyclopedia of Quantitative Trading Strategies

Log in

SUBSCRIBE TO NEWSLETTER AND GET:
- bi-weekly research insights -
- tips on new trading strategies -
- notifications about offers & promos -
Subscribe
QuantPedia
Privacy Overview

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.