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Automated Trading Edge Analysis with Quantpedia

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Each week Quantpedia’s team undertake significant research into strategies and global trends. The research is completed to help portfolio managers better execute their strategies. In their latest research, the specialists at Quantpedia look at Automated Trading Edge Analysis.

To find out if you have a profitable trading strategy you need to look at the results of the trading strategy itself. In their recent research paper, Quantpedia’s team discuss the best way to test a trading edge by examining what trading results it produces.

Quantpedia do this through backtesting the investment idea using historical data. To analyze risk and return characteristics of such a strategy or idea.

The Hurst Exponent can be used to measure long-term memory of the times series. Quantpedia applied the Hurst Exponent to find statistically significant trend / mean-reversion periods.

Used first to determine the size of a dam on the Nile River. And due to its ability to determine a long-term memory of a time series. It is also found today in many applications in finance and investing.

The methodology used by Quantpedia includes analyzing the days with the lowest and highest returns. The team look at days with the lowest and highest 21-day volatility. They also look at a host of other scenarios that can help better understand what strategy to use.

For a full overview of the research itself click here.

“In our research paper we focus on numerous statistical, empirical and other trading properties of the assets we all trade. We looked at several trading edge ideas and examined whether they work or not when applied to our chosen asset.” Daniela Hanicova, Quant Analyst at Quantpedia explained.

“All of the trading ideas presented by Quantpedia are not meant to be final investment strategies,” added Daniela. “The aim of our trading edge ideas are to inspire our clients and give them a place to start when building a more complex strategy of their choice.”

About Quantpedia

Quantpedia – the Encyclopaedia of Algorithmic & Quantitative Strategies

Quantpedia’s team consists of experienced members with a financial, mathematical, and business background combined with members with a strong IT and technical knowledge.

Quantpedia uses a great number of finance research resources from all over the world. This includes research portals, financial journals, universities, and conferences. The team sifts through these sources every day to search for new and interesting articles and papers.

Each article is evaluated based on the strategy’s implementability, backtest length period and overall soundness. Research papers with some type of risk characteristics (max. drawdown, volatility, etc.) are preferred.

Find out more about QuantPedia on Twitter. For the most important events affecting the industry, check QuantConferences regularly too.

#AlphaStrategy #QuantPedia #PortfolioManager #AssetManager #FamilyOffice #HedgeFund

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