Trading Order Out of Chaos
This is the third article in the series on trading the Bullish and Bearish Engulfing candle stick patterns. Following on from Part I and Part II, we will look at trading the short signals for AUDUSD, EURUSD, GBPUSD, USDJPY, and USDCAD. Let’s recap the results for the long side:
- We used hourly rolling bars to identify the appropriate four-hourly patterns
- Trading in the direction of the breakout was profitable
- There was a sweet-spot for holding the trade for roughly 12 hours
- After usi… Read more
EURUSD tick data for the period 10th January 2016 to 15th January 2016. Zip file contains CSV files for each day. The format of the CSV files are: Local Time, Server Time, Server Time Milliseconds, Bid, Ask. The time resolution is in seconds. This means that there can be multiple quotes per second.
Taking Control of Your Trading Numbers – that means actually being able to replicate the results that others produce. It’s the only way to be sure that you know what’s going on. Well, many people got back after last week’s article asking about the details of the calculations as well as about some of the more technical jargon:
- What do I mean by asset?
- What’s an asset bias?
- What does it mean to risk-adjust returns?
- How can I go about calculating the charts in the article?
- How … Read more
EURUSD tick data for the period 14th February 2016 to 19th February 2016. Zip file contains CSV files for each day. The format of the CSV files are: Local Time, Server Time, Server Time Milliseconds, Bid, Ask. The time resolution is in seconds. This means that there can be multiple quotes per second.
EURUSD tick data for the period 27th March 2016 to 1st April 2016. Zip file contains CSV files for each day. The format of the CSV files are: Local Time, Server Time, Server Time Milliseconds, Bid, Ask. The time resolution is in seconds. This means that there can be multiple quotes per second.
Intro
Backtesting is every systematic trader’s basic tool. And Python is becoming the lingua franca of programming. So putting Python into Backtesting to get fast results should be possible!
Yes and no!
In this article, we’ll cover how to really improve your Python backtesting and boost your speeds by several orders of magnitude!
Most people are familiar with the term ORB (open range breakout). It was popularized by Toby Crabel’s book “Day Trading with Short Term Price Patterns and Opening Range Breakout”, as well as the The Logical Trader: Applying a Method to the Madness (Wiley Trading) by Mark Fisher. ORB uses the price range set at the start of a trading period to determine the future price moves, using a breakout-style approach. In this article we’re going to apply this principle to the FX market using a who… Read moreHow to Trade the Start of the Year: Guide to Stress-Free Positioning
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