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You're reading from  Getting Started with Forex Trading Using Python

Product typeBook
Published inMar 2023
PublisherPackt
ISBN-139781804616857
Edition1st Edition
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Alex Krishtop
Alex Krishtop
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Alex Krishtop

Alexey Krishtop is a quantitative trader and researcher with 20 years of experience in developing automated trading solutions. He is currently the head of trading and research at Edgesense Technologies and CTO at ForexVox Ltd. He develops market models and trading algorithms for FX, commodities, and crypto. He was one of the first traders who started using Python as the ultimate environment for quantitative trading and suggested a few approaches to developing trading apps that, today, have become standard among many quant traders. He has worked as a director of education with the Algorithmic Traders Association, where he developed an exhaustive course in systematic and algo trading, which covers the worlds of both quantitative models and discretionary approaches.
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Statistical arbitrage

As we saw in the previous section, arbitrage is based on the idea of mispricing: a situation in which an asset is priced incorrectly. But to say whether something is priced incorrectly or correctly, we need a reference that is known to be priced correctly, don’t we?

In classical arbitrage, such a reference is the asset price itself, and we take advantage of mispricing across different trading venues trading the same asset. Statistical arbitrage (stat arb) uses the concept of fair value to determine whether the asset is mispriced. In simple terms, with classical arbitrage, we compare the price of the asset versus another price of the asset that exists at the same moment in time. With stat arb, we compare the price of the asset to a theoretical fair value to which we expect the price to revert in the future.

In a certain sense, stat arb is a modification or extension of the concept of mean reversion. Indeed, a successful mean reversion strategy is based...

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Getting Started with Forex Trading Using Python
Published in: Mar 2023Publisher: PacktISBN-13: 9781804616857

Author (1)

author image
Alex Krishtop

Alexey Krishtop is a quantitative trader and researcher with 20 years of experience in developing automated trading solutions. He is currently the head of trading and research at Edgesense Technologies and CTO at ForexVox Ltd. He develops market models and trading algorithms for FX, commodities, and crypto. He was one of the first traders who started using Python as the ultimate environment for quantitative trading and suggested a few approaches to developing trading apps that, today, have become standard among many quant traders. He has worked as a director of education with the Algorithmic Traders Association, where he developed an exhaustive course in systematic and algo trading, which covers the worlds of both quantitative models and discretionary approaches.
Read more about Alex Krishtop