Walk-Forward Analysis Demonstration with backtrader

DISCLAIMER: Any losses incurred based on the content of this post are the responsibility of the trader, not me. I, the author, neither take responsibility for the conduct of others nor offer any guarantees. None of this should be considered as financial advice; the content of this article is only for educational/entertainment purposes.

Finally I can apply a walk-forward analysis!

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Getting Started with backtrader

A few weeks ago, I ranted about the R backtesting package quantstrat and its related packages. Specifically, I disliked that I would not be able to do a particular type of walk-forward analysis with quantstrat, or at least was not able to figure out how to do so. In general, I disliked how usable quantstrat seemed to be. The package’s interface seems flexible in some areas, inflexible in others, due to a strange architecture that I eventually was not willing to put up with anymore.

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Who Survives Riddler Nation?

Introduction

Last week, I published an article on learning to fight in the Battle for Riddler Nation. Here’s a refresher of the rules:

In a distant, war-torn land, there are 10 castles. There are two warlords: you and your archenemy. Each castle has its own strategic value for a would-be conqueror. Specifically, the castles are worth 1, 2, 3, …, 9, and 10 victory points. You and your enemy each have 100 soldiers to distribute, any way you like, to fight at any of the 10 castles. Whoever sends more soldiers to a given castle conquers that castle and wins its victory points. If you each send the same number of troops, you split the points. You don’t know what distribution of forces your enemy has chosen until the battles begin. Whoever wins the most points wins the war.

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Winning the Battle for Riddler Nation; An Agent-Based Modelling Approach to the Solution

Introduction

Oliver Roeder runs a column on FiveThirtyEight called “The Riddler,” where he proposes logical and mathematical puzzles for readers to solve. On February 3rd of this year, he posted in Riddler Classic the problem, “Can You Rule Riddler Nation?” Here is the description:

In a distant, war-torn land, there are 10 castles. There are two warlords: you and your archenemy. Each castle has its own strategic value for a would-be conqueror. Specifically, the castles are worth 1, 2, 3, …, 9, and 10 victory points. You and your enemy each have 100 soldiers to distribute, any way you like, to fight at any of the 10 castles. Whoever sends more soldiers to a given castle conquers that castle and wins its victory points. If you each send the same number of troops, you split the points. You don’t know what distribution of forces your enemy has chosen until the battles begin. Whoever wins the most points wins the war.

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The End of the Honeymoon: Falling Out of Love with quantstrat

Introduction

I spent good chunks of Friday, Saturday, and Sunday attempting to write another blog post on using R and the quantstrat package for backtesting, and all I have to show for my work is frustration. So I’ve started to fall out of love with quantstrat and am thinking of exploring Python backtesting libraries from now on.

Here’s my story…

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Three Reasons Why Investigating Trump is Not About Being a “Sore Loser”

When I say that I want the investigations of the Trump campaign’s ties to Russia strengthened, I hear the infuriating criticism that I’m just a sore loser, that I’m not over the 2016 election, that I’m just upset that Hillary Clinton lost. Sure, I wanted Hillary Clinton to win. I really wanted Hillary Clinton to win, and I really don’t like Donald Trump. But this line of reasoning fails spectacularly to appreciate why I want Donald Trump’s campaign investigated.

Here’s a list of reasons why the “sore loser” argument is wrong.

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Order Type and Parameter Optimization in quantstrat

DISCLAIMER: Any losses incurred based on the content of this post are the responsibility of the trader, not the author. The author takes no responsibility for the conduct of others nor offers any guarantees.

Introduction

You may have noticed I’ve been writing a lot about quantstrat, an R package for developing and backtesting trading strategies. The package strikes me as being so flexible, there’s still more to write about. So far I’ve introduced the package here and here, then recently discussed the important of accounting for transaction costs (and how to do so).

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