Statistically Sound Indicators For Financial Market Prediction: Algorithms in C++ (Paperback)
暫譯: 金融市場預測的統計指標:C++中的演算法 (平裝本)
Masters, Timothy
- 出版商: Independently Published
- 出版日期: 2019-10-22
- 售價: $1,925
- 貴賓價: 9.5 折 $1,829
- 語言: 英文
- 頁數: 394
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1698339992
- ISBN-13: 9781698339993
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相關分類:
C++ 程式語言、Algorithms-data-structures
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商品描述
NEWS FLASH... This book was just awarded "Book of the Year" by The Technical Analyst
In my decades of professional experience as a statistical consultant in the field of financial market trading, the single most important lesson that I've learned about trading is this: the quality of the indicators is vastly more important than the quality of the trading algorithm or predictive model. If you are sloppy about your indicator computation, no high-tech model or algorithm is going to bail you out. Garbage in, garbage out still rules.
This book presents numerous traditional and modern indicators that have been shown to carry significant predictive information. But it will do far more than just that. In addition to a wealth of useful indicators, you will see the following issues discussed:
There are simple tests that let you measure the potential information-carrying capacity of an indicator. If your proposed indicator fails this information-capacity test, you should consider revising it. This book describes simple transformations that raise the information-carrying capacity of your indicators and make them more useful for algorithmic trading.
You will learn how to locate the regions in your indicator's domain where maximum predictive power occurs so that you can focus on these important values.
You will learn how to compute statistically sound probabilities to help you decide whether the performance of an indicator is legitimate or just the product of random good luck.
Most traditional indicators examine one market at a time. But you will learn how examining pairs of markets, or even large collections of markets simultaneously, can provide valuable indicators that quantify complex inter-market relationships.
Govinda Khalsa devised a powerful indicator called the Follow-Through Index which reveals how likely it is that an existing trend will continue. This indicator is extremely useful to trend-following traders, but due to its complexity it is not widely employed. This book presents its essential theory and implementation in C++.
Gary Anderson developed a detailed and profound theory of market behavior that he calls The JANUS Factor. This theory enables computation of several powerful indicators that tell us, among other things, when trading opportunities are most likely to be profitable and when we should stay out of the market. This book provides the fundamental theory behind The JANUS Factor along with extensive C++ code.
Whether you compute a few indicators and trade by watching their plots on a computer screen, or do simple automated algorithmic trading, or employ sophisticated predictive models, this book provides tools that help you take your trading to a higher, more profitable level.
商品描述(中文翻譯)
新聞快報... 本書剛剛被《The Technical Analyst》評選為「年度最佳書籍」。
在我作為金融市場交易領域的統計顧問的數十年專業經驗中,我學到的最重要的一課是:指標的質量遠比交易算法或預測模型的質量重要。如果你在指標計算上馬虎,沒有任何高科技模型或算法能救你。垃圾進,垃圾出仍然是規則。
本書介紹了許多傳統和現代指標,這些指標已被證明具有顯著的預測信息。但它的內容不僅限於此。除了豐富的有用指標外,您還將看到以下問題的討論:
有一些簡單的測試可以讓您衡量指標的潛在信息承載能力。如果您提出的指標未能通過這一信息承載能力測試,您應考慮對其進行修訂。本書描述了簡單的轉換方法,可以提高指標的信息承載能力,使其在算法交易中更有用。
您將學會如何定位指標領域中最大預測能力出現的區域,以便您可以專注於這些重要的值。
您將學會如何計算統計上合理的概率,以幫助您決定指標的表現是否真實,還是僅僅隨機運氣的產物。
大多數傳統指標一次只檢查一個市場。但您將學會如何同時檢查市場對,甚至是大型市場集合,這可以提供有價值的指標,量化複雜的市場間關係。
Govinda Khalsa 設計了一個強大的指標,稱為 Follow-Through Index,該指標揭示了現有趨勢持續的可能性。這個指標對於趨勢跟隨交易者非常有用,但由於其複雜性,並未被廣泛使用。本書介紹了其基本理論和在 C++ 中的實現。
Gary Anderson 開發了一個詳細而深刻的市場行為理論,稱為 The JANUS Factor。這一理論使得計算幾個強大的指標成為可能,這些指標告訴我們,除了其他事情外,何時交易機會最有可能獲利,以及何時應該退出市場。本書提供了 The JANUS Factor 背後的基本理論以及大量的 C++ 代碼。
無論您是計算幾個指標並通過觀察其在計算機屏幕上的圖形進行交易,還是進行簡單的自動化算法交易,或使用複雜的預測模型,本書都提供了幫助您將交易提升到更高、更有利潤水平的工具。