Crypto Trader's Edge Course: https://www.algoadvantage.io/academy/crypto-traders-edge/

Most crypto traders are still thinking like coin pickers when they should be thinking like portfolio architects. High-performance systematic crypto trading is not about chasing narratives — it is about robust portfolio construction, trend following, mean reversion, risk management, alpha stacking, diversification, and building strategies that can survive extreme volatility.

This pod with David Bush breaks down how to build a smarter algorithmic crypto trading portfolio using proven trading logic, better R&D, and an all-weather mindset. If you want to trade crypto like a serious systematic trader — not a gambler — this is worth your time.

#CryptoTrading #AlgorithmicTrading #SystematicTrading #QuantTrading #CryptoPortfolio #PortfolioConstruction #RiskManagement #TrendFollowing #MeanReversion #TradingStrategy #Backtesting #RobustTrading #QuantResearch #Alpha #CryptoMarkets

This interview with Michael Wallace (who was inspired by Larry Williams & Ralph Vince) brings a few things to mind. First is the absolute centrality of the role of position sizing in trading, second is the nature of ‘probabilities’ in trading. They are highly related obviously. Sizing is not an afterthought; it can change everything. Presuming an ‘average win rate’ is going to apply to your next 10 trades is not a wise way to proceed either. You want to be more ‘statistically minded’ than that – just toss a coin 10 times, and do that 10 times, the number of heads you get in each group of 10 is going to vary wildly no doubt. Toss it 10,000 times and ‘averages will tend to show up, this is the law of large numbers, but accounts can blow up a long time before averages play out. Because... sequencing risk.

SEE MY FULL WRITE UP ON POSITION SIZING: https://www.algoadvantage.io/podcast/048-michael-wallace

Courses, community & more: https://www.algoadvantage.io

Courses, community & more: https://www.algoadvantage.io

This is part II, part I is Episode 46.

I know we all want “quick, actionable take-aways”, but the reality is that foundational principles of strategy development process is at the core of successful trading, and you more than likely do not have half of this in place like you should.

So, while this is ‘foundational’, and can only be covered briefly, don’t skimp on reviewing this stuff. It’s only in the Algo Collective that we’ll be able to take the time to deep-dive how to set this all up in a highly practical way.

Believe me, once you have a pipeline for strategy development, you’re done! You churn out strategies that are more robust, quickly drop bad ideas and refine your portfolio quickly. You can focus on risk management, other research and constant review, while your trading takes place automatically in the background.

At least, that’s my approach.

Detailed write up on how institutions trade differently: https://www.algoadvantage.io/podcast/046-tom-starke/Part 2: coming soon!Dr Tom Starke trades significant institutional capital as a quant trader for a private fund. In Part 1, we cover the common pitfalls of 'retail' or newer traders. Tom makes the case that institutions 'think differently', applying an extra dimension to their thinking, as compared to retail traders. A significant result of this is the critical role a systematic R&D process plays in strategy development.

The development pipeline is a 'research first', 'hypothesis testing' laboratory, designed to invalidate bad ideas quickly, and push viable ideas through a strict robustness testing framework to ensure out-of-sample results. Applying a scientific approach (which is just good data science), means letting the data speak, rather than squeezing it for the answers we want! The result is a process designed to minimize overfitting and produce the highest risk-adjusted returns for the pre-defined objectives.

Courses, Community & More: https://algoadvantage.ioContents:0:00 Introduction to Systematic Trading and Research6:47 Tom Stark’s Journey: From Physics to Trading13:16 The Scientific Approach: Pros and Cons in Trading19:30 Avoiding Analysis Paralysis in Quant Trading26:02 The Transition: Retail vs Institutional Trading32:28 The Motivation Behind Teaching and Mentoring Traders38:04 Mindset Shifts: From Retail to Institutional Thinking44:34 Risk Management: How Institutions Approach Risk51:08 Defining Trading Objectives: A Key Starting Point57:06 Portfolio Construction: Balancing Risk and Return1:03:10 Diversification: The Key to Long-Term Success1:09:30 Position Sizing: Crucial for Strategy Success1:15:00 Machine Learning’s Role in Systematic Trading1:21:10 Python: The Essential Tool for Quantitative Research1:27:00 Back-testing and Strategy Evaluation: Avoiding Overfitting

Detailed write-up on all of the concepts discussed here: https://www.algoadvantage.io/podcast/045-rob-hanna

Rob Hanna has been trading since the mid 90's and has slowly progressed from discretionary swing trading to a systematic, research driven approach, while still carrying some of those qualitative features into his quant trading. He trades a diversified set of strategies in equities and ETFs, with a focus on the shorter term (and particularly mean-reversion) models. Of particular interest to me was his VIX trading strategies due to their usefulness as a hedge in times of crises, and because they employ more than just price data (they look to the VIX futures curve - whether in backwardation or contango as a critical filter to his models).

Trading volatility (through the futures, options or ETFs) can be extremely risky, but given the strong edges that are present in trading a consistent down-trending market, it's always of interest to me how traders find a way to profit while minimizing the risks inherent in these models. Rob has been trading the VIX long enough to share some invaluable insights. Enjoy!

The only reliable source for trading COURSES, COMMUNITY & more: https://algoadvantage.io

I think Nick Radge’s edge is actually an architecture: robust, simple, momentum-driven systems stitched together into a portfolio that survives, adapts, and compounds. Across nearly four decades, he’s traded through crashes, chop, and melt-ups; shifted from futures to equities for business reasons; and kept his build-process stubbornly logic-first and comfortingly boring—by design.

The pro vs amateur divide, per Nick: pros ride the drawdowns and are present for the next outlier. They profit from human bias—fear, greed, crowding—by refusing to trust their own emotions and by outsourcing discretion to rules they can defend under pressure. Write the plan. Build the engines. Diversify the return streams. Rebuke complexity. Then let compounding do its weird, beautiful work.

COURSES, COMMUNITY & MORE OVER ON THE WEBSITE:

https://www.algoadvantage.io

Can caveman-simple trading rules still work in today’s markets? Brent Penfold says yes. In this interview, he reveals why old strategy rules remain powerful, why portfolio-level thinking is the real edge, and how diversification and discipline create timeless success.Brent talks about trading patterns in a range of 30 futures markets, deploying 20 strategies diversified across mean reversion and trend following principles. I write an article inspired by each podcast which are full of my insights and practical tips. Check them out on the website: https://www.thealgorithmicadvantage.comLinks for Quant Strats conference in London on the 14th-15th October 2025:

https://www.alphaevents.com/events-quantstratsuk

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Round II of a systematic trading masterclass with Laurens Bensdorp: architect non-correlated, purpose-built portfolios—mix trend following, mean reversion, and long-volatility hedges to drive smoother, higher risk-adjusted returns.

We unpack the “paradox of diversification” (Parrondo’s paradox) to turn “ugly” equity curves into compounding machines, and when (not) to switch systems off to avoid recency bias and overfitting.

Plus: robust portfolio construction, capital allocation, and highlights from Laurens’ latest book, Trading Retirement Accounts.

Combining losing investments into a winner:

https://blog.ephorie.de/parrondos-paradox-in-finance-combine-two-losing-investments-into-a-winner

"The Paradox of Diversification" paper:

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1567126

More on our site: https://www.thealgorithmicadvantage.com

#Quant #SystematicTrading #AlgorithmicTrading #PortfolioConstruction #Diversification #RiskManagement #TrendFollowing #MeanReversion #Volatility #Hedging #Backtesting #Robustness

Dive into the deep experience of quantitative trading with Cesar Alvarez (trader first, martial artist second), a veteran trader known for his mastery in mean reversion, breakouts, momentum, ETF and volatility strategies. Discover his innovative methods building a dynamic portfolio, retiring strategies, parameter sensitivity tests, strategy robustness checks, and the art of balancing risk and return to ensure long-term trading success. Cesar’s insights highlight essential strategies for thriving in volatile markets, fine-tuning strategy components, and avoiding the trap of overfitting. Perfect for systematic traders looking for practical edges!

#QuantTrading #MeanReversion #AlgorithmicTrading #ETFStrategies #QuantTrading

Contents:

0:00 Cesar's Journey: Discretionary to Quant Trading

3:59 Inside Connors Research: Mean Reversion Insights

5:48 Cesar's Current Quant Trading Portfolio

8:35 Tactical ETF Strategies & Retirement Focus

14:34 Designing Quant Strategies: Goals & Principles

17:07 Robustness Testing & Avoiding Overfitting

22:49 Knowing When to Retire a Trading Strategy

29:53 Amibroker vs RealTest: Tools for Systematic Traders

34:03 Cesar’s Featured Quant Trading Strategies

37:03 Short Selling & Mean Reversion in Bear Markets

41:12 Breakout & Momentum Strategies for Stocks

43:53 Navigating Volatility: Trading VIX & SVIX ETFs

50:50 Secrets to Effective Mean Reversion TradingWhat could it be?

A Smart Portfolio of Trend Following, Mean Reversion & Hedging Strategies

Unlock insane returns with quant crypto trading! Discover how Pavel from Robuxio builds robust portfolios combining mean reversion, momentum, and hedging strategies—even with limited historical data. Learn essential techniques for managing crypto volatility, optimizing execution, and leveraging diversified strategies. Curious? Dive into the show!

#QuantTrading #CryptoTrading #Momentum #MeanReversion #Hedging #AlgorithmicTrading #CryptoStrategies