April 2022
Intermediate to advanced
368 pages
6h 20m
Japanese
Content preview from Pythonからはじめるアルゴリズムトレード ―自動売買の基礎と機械学習の本格導入に向けたPythonプログラミング
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4章ベクトル化バックテストの習得
ばかげたことに過去を見て未来が予測できると考えているのだ†1。
—The Economist
[†1] 「Does the Past Predict the Future?」The Economist、2009年9月23日（https://www.economist.com/free-exchange/2009/09/23/does-the-past-predict-the-future）
一般的に、アルゴリズムトレードのプログラムのアイディアや仮説を練ることは、準備段階ではより創造的で、時には楽しい部分でもあります。そして、それらを徹底的に検証することは、一般的に、より技術的で時間のかかる部分です。本章では、さまざまなアルゴリズムトレード戦略のベクトル化バックテストについて説明します。以下の種類の戦略をカバーしています（「1.5 トレード戦略」も参照してください）。
- 単純移動平均（SMA）を使った戦略
- 売買シグナルの生成にSMAを利用するという基本的な考え方は、既に数十年前から存在しています。SMAは、いわゆる株価のテクニカル分析の主要なツールです。例えば、短い時間軸で定義されたSMA（例えば42日）が、長い時間軸で定義されたSMA（例えば252日）とクロスした場合にシグナルが発生します。
- モメンタム戦略
- モメンタム戦略とは、直近のパフォーマンスがある程度の期間継続するという仮説に基づいた戦略です。例えば、下降トレンドにある銘柄は、その傾向が長く続くと想定されるため、そのような銘柄は空売りされます。
- 平均回帰戦略
- 株価やその他の金融商品の価格が、ある平均レベルやトレンドレベルから大きく逸脱した場合、それらのレベルに戻る傾向があるというのが、平均回帰戦略の背景にはあります。 ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.