Better System Trader

Most trading strategies have an optimal type of market condition where they work at their absolute best, so having an understanding of market conditions and being able to detect and adapt to them can really have a huge impact on trading performance. But how can we measure market regimes properly? What techniques can we use to find that delicate balance between stability and reactivity so that it improves performance rather than reduces it? Our guest for this episode, Alan Clement, has completed considerable research into market regimes and is going to share his knowledge with us today! Alan is a Certified Financial Technician, full time independent trader, quantitative trading systems designer and private investment consultant. In our chat today, you will learn: Market regimes – what they are and how they can impact the performance of your trading strategies The different types of Market Regimes and key aspects to consider when defining them Indicators, market breadth and intermarket measures – which ones ar

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 wi

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

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 Bette

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 purp

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

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 p

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 tha

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

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 increasin

The results of the Brexit decision took a lot of people by surprise and the markets reacted accordingly. What was interesting about this market event is that we all knew the date and time period when the Brexit votes would start rolling in, so we had a rough idea when we might see some type of market reaction, if the market reacted at all. As systematic traders, what should we do in this type of situation: Should we continue trading as usual, following our systems? Should we override our systems to reduce exposure, or perhaps temporarily stop trading altogether? Are there any other approaches that we should consider? How do we go about deciding what to do? In this episode we’re asking 13 system traders and past guests of the podcast (actually it's 12 past guests and one future guest) about their approach to trading around the Brexit vote. I’ll be asking them what their trading plan was going into the Brexit decision and you might be surprised with some of their answers. I’ll also be asking them what factors

Traders are always looking for an edge and today's guest shares a simple approach he calls an 'unfair trading advantage', that can have a dramatic impact on trading strategy performance. The guest on this episode has been on the show before, to discuss breakout trading strategies back in Episode 43. In that episde we discussed the steps to building breakout strategies and we even released a breakout strategy toolkit, included an ebook, cheatsheet and EasyLanguage code for 2 breakout trading strategies. In this episode, our guest Tomas Nesnidal will be sharing a different trading approach, and it’s something he likes to call ‘an unfair trading advantage’. He’s going to explain to us what it is and why he calls it an 'unfair advantage.' It's something that a lot of traders have probably heard about but perhaps are not aware of how to use it properly or even the positive impact it can have on trading results. Tomas will explain it in this chat so take a listen! Topics discussed An 'unfair trading advantage' a

Today we’re covering a topic which can really be a concern for traders of all levels, from beginner to pro, and that is the topic of strategy evaluation. Have you ever found that real-life performance does not match expected results? Or perhaps you have a strategy that is stuck in a drawdown and wondering if it’s actually broken? I’m sure we’ve all heard of data mining bias, over-optimization and curve fitting and the impacts this can have on our trading accounts. We may be even using techniques such as Out Of Sample testing, Walk Forward Analysis, Monte Carlo analysis and a number of other measures to identify or reduce the impact of these issues, but do these approaches actually work? Are there limitations or dangers with these techniques? Are there better ways? In this episode we talk to someone who evaluates trading systems for a living, plus his research into system evaluation techniques has won awards. The guest is Dave Walton. Dave was the winner of the Wagner award in 2014 for a paper titled ‘Know y

Nelson Freeburg was the editor of Formula Research, a newsletter that developed systematic timing models for the stock, bond, and commodity markets. He was also a research consultant working with institutional money managers to design proprietary timing models. Nelson had been an active trader since 1980 and occasionally spoke about his work to audiences around the world. In this episode, Linda Raschke shares memories of Nelson, his approach to model development and what we can learn by studying his work. Topics discussed Timing models and the components Nelson used in his models Russell growth vs Russell value model Out of sample testing and sample size Why Nelson focused so much on reducing drawdown Nelsons biggest strengths in modelling and what we can learn from his approach Voting systems The benefits of overlaying 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

Markets are constantly changing. Trading edges come and go. In an industry with such a low survival rate, where some areas are changing at an ever increasing rate, what does it actually take to not only survive, but thrive, over an extended period of time? The guest on this episode, Linda Raschke, has been trading for over 35 years. She traded for several hedge funds before starting her own, ranking 17th out of 4500 hedge funds by Barclays Hedge for 'Best 5 year performance'. She's experienced a large number of changes in the industry, some of them have been huge, but she’s managed to adapt and continues trading even today. Linda stand out from the crowd for three factors: Performance, Longevity and Consistency, so what does it actually take? What has she learnt over the years and what can we do to improve our own chances of performance, longevity and consistency? In our chat with Linda we discuss some of the changes she’s experienced over the years and the impacts this has had on trading. We also hear about

Trading can be tough, markets are noisy and finding signals in the market noise can be challenging. Also, applying indicators to trading strategies can introduce lag, however a lot of traders don’t even realize the lag their indicators are introducing or the impact it can have on trading. In fact, the guest in our chat today, John Ehlers said “One of the biggest enemies of traders is lag”. So, what's the solution? John Ehlers is well known in the commodity futures arena as the Creator of MESA, having pioneered the MESA method of cycle analysis in the late 1970's and becoming the founder of MESA Software. He is author of four books including Rocket Science for Traders, Cycle Analytics for Traders, Cybernetic Analysis for Stocks and Futures and MESA and Trading Market Cycles. He has also been a contributing editor of Stocks & Commodities, winning a number of awards for his work. In our chat with John we discuss the issue of indicator lag, the impact it can have on trading and some solutions. We also talk ab

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,

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 m

Andrea Unger is the only trader to ever win the World Cup Championship of Futures Trading ®* titles 3 years in a row, with returns of 672% in 2008 (futures division), 115% in 2009 (futures division) and 240% in 2010 (futures & forex division). This is his 2nd appearance on the podcast, he was also a guest on Episode 16. In this episode Andrea discusses his approach to trade entries, how the traditional approach to entries can limit our ability to read the market and how he's modified the standard approach to identify entry opportunities. Topics discussed The typical approach to entries and how Andrea uses a modified approach to identify and test his entries Why starting an entry with a setup can limit your ability to read the markets The grouping of setups and how the style of trigger you use can determine the most appropriate setup The best timeframes for indicators and the impact lower timeframes can have on indicators Combining intraday and daily timeframes for better entries How Daily Factor can be u

Back in Episode 32 we had a chat with Laurent Bernut, a systematic short seller who spent years working in the Hedge Fund world specializing in short selling strategies. He shared loads of knowledge with us in that episode but we actually had a lot more to talk about. We ran out of time back then so in this episode we’re going to continue with the chat, covering a bit more on short selling, including common problems and mistakes traders make when short selling, the 5 psychological stages of a bear market, how these stages manifest in market behavior and where we are now. We also chat about his Convex position sizing model, visualizing your trading edge and how to tilt it more in your favor PLUS he shares with us a special trick to switch our minds from a flight or fight mode back into a state of flow. We also have some great questions submitted by podcast listeners so listen out for those. Topics discussed Common problems traders face when short selling When to never short a stock The 5 psychological stages