Building robust trading strategies that can detect and adapt to market conditions can be a real challenge, and failure to do so can often result in poor trading performance and drawdowns.

How can we build more robust trading strategies that adapt to market conditions as they change?

Our guest for this episode, John Ehlers, who has a guest on episode 48, joins us to share some common problems traders face when building trading strategies along with tips on how to overcome them.

In our chat you will learn:

• Tips and techniques to detecting and adapting to market conditions
• Common problems traders face with indicators and how to fix them
• The 4 requirements to building a robust trading strategy
• How the conventional wisdom of using indicators causes late signals and how to use them to anticipate instead
• A simple technique to determine if your indicators are working properly for the market conditions

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.

Trading algorithmically based on sentiment data is a relatively new field compared to more established approaches. With the explosion of social media and computing power, the analysis of sentiment data has also increased, with some hedge funds committing considerable resources to researching the applications of sentiment data in trading.

However, there is also some skepticism of the value of analyzing social media for trading, so what is sentiment trading all about? Can sentiment actually be used in trading models and how?

Our guest for this episode, Richard Peterson, has been analyzing sentiment for over 20 years. He started what was probably the world’s first fund specializing in sentiment trading, and now runs a company called MarketPsych, specializing in the collection and analysis of sentiment data.

In our chat you will learn:

• Why sentiment is so important and how it can give traders an edge
• The challenges of using sentiment data in trading models
• The best and worst markets for sentiment analysis as a predictor
• Applications of sentiment analysis in quant models and the future of sentiment analysis

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.