Backtesting and execution are such key parts of algorithmic trading so choosing the wrong platform can have a huge impact on our trading.

There are loads of trading platforms available and a lot of considerations which need to be made when choosing one that suits our needs, so in this episode we’ll be discussing backtesting and execution platforms with Nitesh Khandelwal, department head at QuantInsti who also co-founded iRageCapital and iRage Global Advisory Services.

After our chat on algorithmic trading platforms we’ll also cover statistical arbitrage, high frequency trading and some interesting audience questions, so listen out for those.

Topics discussed

• The 3 key components to an algorithmic trading platform and the basic questions you need to answer before choosing a trading platform
• Why backtesting and execution platforms should be separate
• Choosing a programming language and why python has become a popular choice in trading
• The benefits and drawbacks of using python in trading
• Statistical Arbitrage, how it came about and the benefits of the approach
• The primary risks of statistical arbitrage, especially during times of market stress and how they can be reduced
• The most important factor in stat arb trading
• Common mistakes traders make when building statistical arbitrage models

Disclaimer:
Trading in the financial markets involves a substantial risk of loss and is not suitable for everyone. All content produced by Better System Trader is for informational or educational purposes only and does not constitute trading or investment advice. Past performance is not necessarily indicative of future results.

I’m sure we all want to create trading strategies that perform better and last for longer but there are a number of issues we need to look out for when developing robust trading strategies, some are well-known and some perhaps aren't.

In this episode we’ll be talking with Perry Kaufman about strategy development and more specifically some of the issues that can catch us out when creating trading strategies. Perry raises some interesting points about optimization that may not be well known plus he shares loads of tips to creating more robust strategies.

Perry writes extensively on markets and strategies, having published fourteen books and has just released a new book on building algorithmic trading strategies, which we'll be discussing in this episode.

He has worked and consulted to a number of successful CTA, investment and prop trading groups, creating systematic trading and hedging programs.

This is also his 2nd appearance on the podcast, appearing as a guest way back in Episode 10.

Topics discussed

• The most robust type of systems
• How your choice of optimization values could be misrepresenting your results and how to choose parameters that give a more accurate picture
• The mistakes traders make when analyzing optimization runs and tips to doing it properly
• How to really determine if a new trading rule is robust
• Reducing risk by using multiple parameters
• What the number of profitable runs in an optimization can tell you about the robustness of a strategy
• Why diversifying across strategies instead of across markets could be a better approach
• The challenges of building robust strategies using Genetic Algorithms and Neural Networks

Disclaimer:
Trading in the financial markets involves a substantial risk of loss and is not suitable for everyone. All content produced by Better System Trader is for informational or educational purposes only and does not constitute trading or investment advice. Past performance is not necessarily indicative of future results.