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A Clocked Flip-Flop, N-Bit Register and Computer Memory. Sequential Logic and Semiconductor memory. Since December, bitcoins can not only be traded at more or less dubious exchanges, but also as futures at the CME and CBOE. And already several trading systems popped up for bitcoin and other cryptocurrencies. None of them can claim big success, with one exception. There is a strategy that easily surpasses all other bitcoin systems and probably also all known historical trading systems. In the light of the extreme success of that particular bitcoin strategy, do we really need any other trading system for cryptos?
In this article we’ll look into a real options trading strategy, like the strategies that we code for clients. This one however is based on a system from a trading book. The system that we’ll examine here is indeed able to produce profits. But it is also obvious that its author has never backtested it. They need not attempt to predict future prices.
They know the future prices already. Or rather, they know the prices that lie in the future for other, slower market participants. Recently we got some contracts for simulating HFT systems in order to determine their potential profit and maximum latency. This article is about testing HFT systems the hacker’s way. Especially into combining different option types for getting user-tailored profit and risk curves. Just a quick post in the light of a very recent event. Scripts and programs based on historical price data suddenly didn’t work anymore.
This article is the first one of a mini-series about earning money with algorithmic options trading. I’ll try to explain all steps in detail. Most trading systems are of the get-rich-quick type. They require regular supervision and adaption to market conditions, and still have a limited lifetime. Their expiration is often accompanied by large losses.