I wrote an article on how to automate the process of updating quotes, updating multiple trading strategies and e-mailing next day signals form the cloud to our own e-mail boxes. This time I am using QuantShare as the trading software and an Amazon EC2 micro instance as the host cloud. You can read the article …
strategy development
Amibroker – From Backtest to Trading – Going Live
Going Into Production So you have a system in Amibroker that you backtested and you are happy with. You now want to go “into production”.How do you get your signals? How do you keep track of open orders, position sizes, ranking rules, etc. It’s not as easy as it may seem. Explore or Scan? If …
Uncover Hidden Market Relationships Using Fuzzy Logic
In the previous posts (pt1, pt.2, pt.3) we talked a bit about how to take various indicators and fuzzify them. Now I will show how we can quickly test for relationships in indicators.So the question is: Can we only use RSI(3) and RSI(14) (short term and medium term Relative Strength Index) to trade the S&P500?So …
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Fuzzy Logic Optimization -The “WOO-FOO-SMASH-EFIS-MEE-COPT” model
Fuzzy Logic pt.3: Auto-generate model parameters I often tire of reading these complicated academic papers that are filled with impossible jargon only to make my life harder. I have found that often times the difficult terminology only hides the simple concepts that lie behind. So here I will use a difficult term myself, just to sound smarter …
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The case for Fuzzy Logic in Trading – Pt. 2: Amibroker
Backtesting Fuzzy Logic in Amibroker In pt.1 we backtested a “fuzzified” trading strategy in Matlab (read part 1): Buy when RSI(3) is Low and it’s before Expiration week. Although it was easy to develop this fuzzy model in Matlab, due to the intuitive GUI, it is difficult to get meaningful backtest results, visual signals, statistics …
Read moreThe case for Fuzzy Logic in Trading – Pt. 2: Amibroker