What is Tortoisedge?
Last updated
Last updated
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What is Tortoisedge?
Quantitative trading and an investment algorithm that generates better returns or risk-adjusted performance compared to simply holding the asset over a specific time period.
Quantitative Strategy
An algorithm is a set of rules or procedures designed to execute specific tasks. In the context of financial markets, a quantitative trading algorithm involves mathematical models and statistical analysis to make investment decisions. The algorithm could use various factors, such as technical indicators, fundamental data, or machine learning techniques to guide its trading decisions.
Comparison with Benchmark
The algorithm’s performance is compared against a benchmark representing the performance of the asset class being traded. This benchmark could be an index, such as the S&P 500 for stocks or BTC for crypto assets. Outperformance means that the algorithm has generated better returns or managed risks more effectively than the benchmark.
Risk Management
Outperformance is not solely about generating higher returns; it also involves managing risks effectively. Tortoisedge has built in risk management mechanisms to control downside risks and avoid significant losses.
Back testing
Before deploying the Tortoisedge algorithm in live markets, our team has back tested it using historical data to assess how it would have performed in the past. *The back testing results are dependent on the set Sensitivity, Source and Session.
Continuous Monitoring and Adaptation
Financial markets are dynamic, and what works today may not work tomorrow. Tortoisedge algorithms are adaptive and continuously monitored and refined to account for changing market conditions.
Consideration of Costs
Trading costs such as transaction costs, slippage, and other trading expenses should be considered.
It’s important to note that algorithmic trading involves risks, and past performance is not always indicative of future results.
Unexpected market events or changes in market dynamics can impact the performance of algorithms.
