Better System Trader

Alan Clement, an experienced trader and expert in market regimes, discusses the impact of market conditions on trading strategies. He explores different approaches to incorporating market regimes, including building specific strategies or adding regime filters. Topics covered include market breadth analysis, intermarket measures, and simple indicators for beginners. The importance of patience in trading is emphasized. Join the conversation and visit the show notes for more resources.

The performance profile of Mean Reversion is extremely desirable to a lot of traders. Mean reversion trading strategies can produce high win rates and a smooth equity curve, however there are risks, which can result in giving back a large portion of profits, or of your trading account, some times in a very short period of time. So what can you do to build mean reversion strategies that produce consistent profits while managing risk effectively? Todays guest, PJ Sutherland, is here to share the knowledge he has gained from years of research and trading mean reversion strategies, and as you’re going to hear, he has some really interesting insights to share with us. PJ has extensive experience in the development and deployment of quantified trading systems and has been active in the market for the past decade. He is the founder and director of Alpha Investment Advisors, providing research to hedge funds and prop trading firms, and the founder of the website Quantlab for private traders. In our chat today, you will learn: The key drivers of short-term returns in mean reversion trading The impact of market environments on mean reversion strategies and how to detect and adjust strategies to varying market conditions Should you 'Catch a falling knife' or wait for confirmation? How to determine which entry technique is best for you Building a portfolio of strategies using parameter ranges across the mean reversion curve Simple but powerful techniques to managing risk in mean reversion strategies   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.

There are a number of different aspects to trading that we really need to get a handle on to increase our odds of success. Some aspects we often put a lot of thought and analysis into, and others we may not consider so carefully or at all, which could be impacting our trading results without us even realizing. Todays guest, Dr Howard Bandy, is here to discuss the foundations of trading, and some of these aspects we really need to consider, whether we’re just starting out or a more experienced trader. Howard has over 50 years experience in the research and application of modelling and simulation of financial systems. He has previously worked as a senior research analyst for a CTA firm, is a consultant to trading companies and individuals, as well as being an international speaker and publishing a number of books on quantitative trading systems. In our chat today, you will learn: How to systematically choose the right markets to fit you risk profile, trading style and objectives The 3 characteristics a market must have to be tradable The difference between Impulse signals vs State signals and how they can be used to manage trades and monitor trade health The four parameters you need to understand to define your own risk tolerance Choosing the best objective function to evaluate trading strategy performance   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.

Why is it that some traders can create trading strategies that perform well in real-time trading while other strategies fall apart? How do some traders keep their trading strategies fresh and adaptive to market conditions while other strategies just stop working altogether? Robert Pardo, president of Pardo Capital, author of the book ‘The Evaluation and Optimization of Trading Strategies’ and creator of the ‘Walk Forward Analysis’ approach, is here to chat about creating and optimizing strategies that are robust and continue to work in the future. In our chat today, you will learn: Common mistakes traders make that can cause strategies to fail in real-time trading The dangers of traditional optimization techniques and how they can be reduced and even overcome How to determine if a strategy really is robust, while keeping it fresh and adapting to 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.

Who wants a steadily rising equity curve with little or no drawdown? I'm sure most traders do, but unfortunately it doesn’t usually end up that way. Drawdown is a big part of trading and can be one of the the biggest challenges traders face, so what techniques can we use to potentially help reduce drawdowns? Our guest for this episode, Scott Phillips, is going to share techniques he uses to manage drawdowns in his own trading. In our chat you will learn: How to quickly test a trading idea to determine if it’s worth more investigation Why it’s so important to understand market types, the impacts it could be having on your trading results and how you can leverage this knowledge to create strategies with enhanced performance How to improve your trading results through better trade management and multiple exits.   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.

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.

Whether you’re a retail trader with a small account or a fund manager with millions or billions under management, something that we all need to consider carefully as traders is how or where we’re going to use the money in our trading accounts. 'Capital allocation' sounds boring but it can have such a huge impact on our trading results. Unfortunately, it can sometimes be overlooked for other aspects of trading like entries and exits, leaving traders with an inefficient use of their capital and can result in lower returns and poor performance. Can we use our trading capital more efficiently to achieve higher returns? And if we can, then how? Todays guest, Michael Melissinos, started out as a junior analyst at Bear Stearns and is now running his own systematic trend-following fund Melissinos Trading. Mike is a competitive guy, always looking for ways to improve his trading performance and in today’s episode he's going to share with us some practical ideas and research, including: The 3 most important things that influence trading performance Why what you trade is more important than entries and exits Ideas to improve trading results through dynamic capital allocation How to use indicator scores to measure trend strength And much more.   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.

Today’s guest is a trader that has been requested quite a few times actually, I’ve had a lot of requests to have this person as a guest on the show, and the guest is Adam Grimes. Adam has two decades of experience in the industry as a trader, analyst and system developer and is currently Chief Investment Officer of Waverly Advisors. He’s previously held positions at Level Partners, MBF Asset Management and SMB Capital and is the author of ‘The Art & Science of Technical Analysis: Market Structure, Price Action & Trading Strategies’. For those of you that know Adam and his work, his approach to trading is a mix of quant and discretion, and I think even if you’re a purely systematic or quant based trader it’s interesting to hear other people’s approaches and points of view. So we start off the chat by discussing his approach of mixing quant and discretionary models, and then we move onto behavioral factors in the market and why approaches that look at the market as purely rational fail. We then end the chat discussing Keltner channels and their applications to trading, so there’s quite a variation in topics here but I’m sure you’ll find it interesting. Topics discussed Mixing discretionary decisions with a quantitative framework Why behavioral factors in the markets are so important and why approaches that look at the market as purely rational fail The application of Keltner Channels in trading   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.

When I was preparing for the previous podcast episode on system trading through the Brexit, I had to review some of the past podcast episodes so that I could include some background content for the guests, and as I was going through some of those past episodes I realized that there was so much great information in them that I had already forgotten about. I even found some concepts or ideas that didn’t really catch my interest because it wasn't appropriate to my trading at the time but it’s now more relevant to me personally, so I thought it might be time to do another review of some of the past episodes as a reminder and to perhaps gain or reinforce past insights. Last year, we did a podcast episode where we reviewed episodes 1- 20. That was episode 30 if you’d like to go back and hear that. In this episode we'll review lessons and highlights from episodes 21-40. Some of the topics we’ll be discussing are: How to never run out of trading ideas, The importance of creativity and a simple technique to increasing our creativity, How to manage data mining and avoid overfitting, A number of approaches to building robust trading strategies, How to bet bigger with a smaller overall risk, Plus much more!   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.