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How can traders make better decisions to improve their trading results?   In this episode, Matt Zimberg from Optimus Futures joins me to discuss decision making, what traders do wrong and how to be a more successful trader (and person) by making better trading decisions.   Here are some of the topics we discuss: The importance of decision-making in trading, Common mistakes traders make, How traders underestimate “the game of trading”, Filtering out bad trading information and training your brain to make good decisions, The importance of learning about things outside the market, The 3 main goals of successful traders, Fear and euphoria, Contrarian trading, people who shouldn’t trade, and much more.

Are you looking for unique ways to use “Big Picture” analysis to guide your trading decisions? In this episode, Brent Penfold from indextrader.com.au joins me to share some interesting (and effective) techniques he uses to determine the big picture to guide trading and investing decisions, including:   Why the big picture is so important in trading, How technical analysis can fool traders, What are fractals and why they matter, Validating market reactions to specific levels, The Market Ladder that projects support and resistance levels, Using fractals to see the big picture and the simplest fractal pattern there is, Pivot points over multiple timeframes and market expectations around pivots, Examples of market reactions to pivot points, Is it safe to get back into the market? Fractals and pivot points on non-index markets, Dynamic pivot points vs static pivot points, Robustness in old trading ideas, And much more!

Which is better for trading strategies - Indicators or Price Action? In this episode, Scott Welsh from scottwelshstrategies.com joins me to answer this eternal question. Here are some of the topics we discuss: Strange things that have impacted the markets this year, The value of reviewing simple strategies, Expectations traders have of trading strategies, Choosing the right trading style for a market, How to determine which markets trend the most, Old trading strategies that continue to do very well, How to manufacture “lucky” trading, Tracking dozens of old strategies, Identify strategy failure, The recent performance simple trading strategies, Plus much more!    

3 amazing guests join us to discuss trading insights of the past year and how to prepare for a HUGE trading year ahead, including: Getting better as a strategy builder, Challenges building short index strategies, Switching between old and new strategies, Timeframes for short-term trading strategies, Scaling out in volatile sideways markets, When the next bear market will begin and the transition from Bull to Bear, Trend following over the last few months, "V" price movements in the markets, Stop & Reverse and small stops in crazy markets, Plus doing more of what works, old strategies that do well, algorithmic short selling and much more.

Adrian Reid from Enlightened Stock Trading joins us to discuss systematic crypto trading, including: Why traders should consider the crypto markets right now, The mistakes most traders make with crypto, Choosing the best exchanges, data and software for crypto trading, Why buy and old is a bad approach to crypto and what you should do instead, The types of strategies that work in the crypto markets right now, The 3 types of risk in the crypto space (and how to reduce them), How to overcome limitations in crypto data, plus Regime filters, optimization, stop losses, backtesting, robustness, auto trading, price behaviour and much more.

David Stendahl from SignalTradingGroup joins us to discuss techniques traders can use to achieve more stable results, including: Why it's good to understand a systems logic and will simple systems continue to work, How to apply adaptive logic to simple systems, Mistakes traders make using seasonals, How "seasonal depth" can identify when a market is likely to make a big move, Using environmental overlays to adjust position sizing, Using VIX to switch strategies on/off, Plus, we discuss which is better: diversification of systems or markets?

Lawrence Chan from DayTradingBias joins us to discuss market bias and how to leverage structural bias to increase strategy performance, including: "Atomic strategies" and knowing when to NOT trade, The most toxic period to backtest a strategy, Why market behaviours are becoming so predictable, How some trading platforms are taking traders down the wrong path, Exploring biases caused by recurring events, Why traders should think in concepts first, Plus, leverage and volatility breakouts, chart patterns, simple tools, knowing the behaviours of market participants, human psyche, market internals and much more.

Jason Shapiro from Crowded Market Report discusses a contrarian approach to trading profits, including: Why contrarian trading makes sense, How to identify crowded trades and why price is not a good contrarian signal, What the markets really are and why traders don’t understand it, Risk management for contrarian trades, Why traders shouldn't care about being right or wrong, Plus, COT report, hedgers and speculators, fading the “experts”, trading through news events and much more.

Larry Tentarelli from Blue Chip Daily joins us to discuss techniques to buying pullbacks and avoiding bear markets, including: Determining the trend with price action and why price action is better than indicators, Using volatility and range expansion as warning signs, Impact of the index on individual stocks, Managing trades when markets are breaking down, Reliability of moving average crosses, Clues that indicate a pullback may be turning into a bear market, Using market internals to identify potential turning points, Plus, systematic rules vs discretionary trading, trading in a bear market, controlling the urge to overtrade, scaling-out of positions, sector rotation and selection, what to watch for in the markets right now, and much more.  

Kris Longmore from RobotWealth joins us to discuss 4 key areas part-time traders need to take seriously to be successful, including: Why it’s important to understanding market participants and why they're trading, 3 common things traders do that almost guarantee they will blow up, Setting realistic expectations for retail traders, The "edge pyramid" and where retail traders should target, The “backtest cycle of doom”, why backtesting is not research, and a better approach to finding a trading edge, plus Risk premia harvesting, turn of the month edges, universe selection, VIX trading edges, FX seasonality, portfolio Zen, risk allocation, crypto trading, machine learning and much more!

Martyn Tinsley from TradeLikeAMachine joins us to discuss market noise, and how to leverage noise to improve trading strategies, including: Why it's important to understand market noise, The impact of market noise on trading strategies, Using noise to filter assets and timeframes, Example of impact of market noise on Mean Reversion strategies, The best strategies to trade in noisy markets, The difference between noise and volatility, Harmonic price patterns, instantaneous noise filtering, trading currency pairs, signal lag in noise indicators, repeatable patterns vs indicators and much more!

Brian Blandin from Markets Science joins us to discuss how to find and trade statistical edges in the crypto markets, including: The things traders need to be aware of before trading crypto, Common factors and repeatable patterns that move the crypto markets, Software, programming language and exchange selection, How to screen cryptocurrencies to find those worth trading, Safety of funds at unregulated brokers, Crypto market correlation to stocks and index futures, Moving from discretionary to systematic crypto trading, volatility, slippage, liquidity and much more!  

Curtis White from Beyond Backtesting joins us to discuss 3 ways traders can build better trading models, including: The problem with trading models and why traders struggle to incorporate predictive factors into models, What drives the markets and using market cognition for better trading ideas, Identifying and trading different markets and datasets, Using statistical creativity in the strategy validation process, Problems with Walk Forward Optimization and the 'proven winner' solution, Testing with different bar types, the negative impacts of being too risk averse, and much more!

Kyle Schultz from Algorithmic Futures joins us to discuss how to leverage volatility in your trading strategies to improve risk/reward and outperform the market, including: Why volatility is a key component in trading strategies, 3 main ways to apply volatility in trading strategies,\ Types of volatility filters and when to use them in the strategy development process, Using VIX term structure as a regime filter, Adapting strategies to different volatility regimes, Mean reversion vs momentum in different volatility regimes, And much more!

Jeff Swanson from EasyLanguageMastery discusses how to avoid curve fitting your trading strategies using the "independent testing" technique, including: The things traders do that cause curvefitting, Is curvefitting a trading strategy really that bad? Independent testing and why you should use it when developing trading strategies, How to do independent testing of filters and using optimization to judge filter consistency, Testing combinations of filters and why you should look to remove Plus, types of filters to test, where to get trading ideas, how long to test a trading idea, when to switch strategies off, combining filters, tweaking a strategy and much more!

Algorithmic trader Cesar Alvarez from Alvarez Quant Trading joins us to discuss low effort trading strategies, including: An explanation of rotational trading and the benefits/challenges of using rotational strategies, Why rotational trading is a fantastic way to diversify time (and also get to “trade lazy”), How often to rebalance and the impacts of the day you choose to rebalance, Ranking methods and some of the most effective ways to find the best candidates, How to reduce the churn in rotational trading with one small but powerful exit tweak, Plus, universe selection, risk management, rebalancing, short trades, mean reversion, stock splits, audience questions and much more!

Trend following trader David Lundgren joins us to discuss how to improve trend following performance, including: The problem with momentum (and why momentum “doesn’t work”), Why momentum isn't working today, Mixing momentum with trend following for better performance, The 4 conditions that must happen for a trend to occur, Modeling regime drivers and digging deeper to understand true market health, What to do when trading strategies are struggling, And much more.

Trader, author and performance coach Dr Brett Steenbarger discusses how traders can get an edge by applying innovation to their trading, including: The 2 levels of improvements traders can make, Why traders resist innovation and how to address hesitation to change, How to innovate by looking at what we do well, Why NOT trading can be an innovation for traders, Impacts of lifestyle and mindset on innovation, Why you should “limit your search” when looking for edges, The 2 qualities most shared amongst successful traders Plus, odds and backtesting market patterns, skill vs luck, testing in relevant market regimes, what successful traders focus on and much more!

Quant trader Ernie Chan from PredictNow.ai joins us to discuss how to predict the profitability of trades using machine learning, including: Unconditional probability and the problem with win% in backtest reports, Why “conditional probability” is much more useful for a trader and how to apply conditional probabilities to capital allocation, Why you should use Machine Learning for risk management and capital allocation only (and not for building trading strategies), Why feature selection and feature importance ranking are so valuable, Plus, the best ML techniques for prediction, how simple should trading strategies be, insights from cluster-based feature selection, do these techniques really work, ML as a crystal ball and much more!

Richard Metzger from Quantsys.net joins us to discuss how to combine algos using state-based market design techniques for more consistent trading performance, including: Why it's important to be sceptical of your algos, The main causes of poor algo performance and how state-based market design can address these issues, How to define market states into "buckets" and why you should keep them simple, Combining state-based algos to create a system, plus Adjusting inputs for market states, combining strategies in Tradestation, market states vs regime filters, and much more!