“Diversification is the Only Free Lunch”
I’m sure everyone has heard this old adage at some point in their trading career. Most people probably shrug it off and go back to watching The Big Short and dreaming of putting on that one career-making trade. Or maybe they’re still trying to figure out how to pick every single top and bottom on one instrument, thinking all they need is that one perfect strategy. The idea of concentrated bets and being right is just so sexy. Compare this to trading a basket of strategies across styles, time frames, and asset classes. Hopefully the thought alone hasn’t bored you to sleep. Because what I hope to prove with this post is that diversification can combine multiple small edges into a portfolio with both reduced risk AND increased reward . This was a true turning point in how I thought about trading, and hopefully it will be for you too.
Continue reading “Position Sizing for Practitioners [Part 3: A Portfolio Approach]”
Autumn is my favorite time of year. Football (and more importantly as a Bills fan, fantasy football) is back, everything tastes like pumpkin, and I don’t get sweaty walking around outside. It’s also the start of the cryptocurrency bull season! Or is it? Let’s find out.
Continue reading “Bitcoin Seasonality: Fooled by Randomness”
Jupyter Notebook for this post can be found here
Traders love their performance metrics. Anyone who’s used their platform’s backtesting features has probably come across a few dozen of them, and everyone’s got their favorite. Anybody who’s anybody in the finance world has one named after them: Sharpe, Sortino, Calmar, Treynor, Gartman, etc. (OK, maybe not the last one). But which ones are the most important? There should be some kind of objective answer to this, right? If you look for the answer to this question on Google, you’ll be quickly overwhelmed. Most people want to give you 5+ different metrics you should be focusing on, all at once. But they can’t all be equally important; what we really want is a fitness function, or one statistic that can be optimized to compare all strategies against one another.
Continue reading “Trading Metrics that Actually Matter”
The Problem with Optimal f
What does “optimal” mean, anyway? In the first part of this series, we discovered that the staked fraction of capital that yields the greatest compounded returns also yields a less-than-optimal level of drawdown. To realize the greatest return on capital, an investor in SPY since its inception should have used over 3x leverage to buy in. This would have yielded the greatest compounded rate of return, but would have induced a 97% (!!!) max drawdown along the way. Since a 20% retracement from peak equity causes most investors to start tossing in their sleep, this approach doesn’t seem very realistic. This post will help traders maximize their gains while still getting their beauty rest!
Continue reading “Position Sizing for Practitioners [Part 2: Dealing with Drawdown]”
Albert Einstein once proclaimed that “compound interest is the eighth wonder of the world” (allegedly, at least; people attribute all kinds of sayings to that guy). Let’s just assume that he did. This is the single most important reason why people participate in the markets. The magic of compounding interest turns time into an exponential money multiplier, and the greater the rate the more dramatic the results. This is the single most important concept that traders need to understand.
Continue reading “Position Sizing for Practitioners [Part 1: Beyond Kelly]”
Outside of price action, two of the most popular market characteristics analyzed are volume and volatility. Volatility is often used to determine market regime, while the traditional use for volume is to confirm price movement. This post will investigate the relationship between these two characteristics, and whether using both of them may be redundant.
Continue reading “Volume and Volatility: A Tale of Two Vols”
The events of the past month, most notably the implosion of XIV, has focused public interest on volatility as an asset class. They’ve also illustrated that short vol as a strategy might be a little more risky than advertised (gasp!).
Continue reading “Excess VIX: A Predictive Volatility Model”