{"id":252,"date":"2020-08-31T08:56:49","date_gmt":"2020-08-31T07:56:49","guid":{"rendered":"https:\/\/www.scichart.comblog\/algorithmic-trading-with-scichart\/"},"modified":"2023-11-09T15:35:01","modified_gmt":"2023-11-09T15:35:01","slug":"algorithmic-trading-with-scichart","status":"publish","type":"blog_scichart","link":"https:\/\/www.scichart.com\/blog\/algorithmic-trading-with-scichart\/","title":{"rendered":"Algorithmic Trading with SciChart"},"content":{"rendered":"\r\n

Trading, investing is a little bit of a passion of mine. In my career, I’ve worked in Tier-1 Investment banks<\/a>, trading firms and been involved in one way or another with financial markets for over 10 years. My company, SciChart<\/a>, has to balance and hedge incomes in Euros and Dollars. I post over on my Twitter<\/a> about trading, as well as SciChart and business & entrepeneur tips I’ve learned over the years.<\/p>\r\n\r\n\r\n\r\n

Also, I’m a software engineer and big proponent of High Performance WPF Charts<\/a> as you know! So, I thought to myself ‘what if I combine these two skills in a project’<\/em>? Enter: Algorithmic Trading with SciChart<\/strong>.<\/p>\r\n\r\n\r\n\r\n

The Problem<\/h2>\r\n\r\n\r\n\r\n

The cryptocurrency market (Bitcoin, Ethereum etc…) is extremely volatile. It’s notoriously difficult to trade. We’re talking about a market where an asset increased 20x in a single year (January 2016 – December 2017) and then decreased by 70% in the following year. How is such a market tradeable?<\/p>\r\n\r\n\r\n\r\n

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Bitcoin USD increased from $800 in January 2017 to $20,000 by the end of the year, a more than 20x increase in a single year<\/figcaption>\r\n<\/figure>\r\n\r\n\r\n\r\n

It turns out, it is.<\/p>\r\n\r\n\r\n\r\n

With simple rules, signal processing and statistical analysis, I created a trading algorithm which yielded 200% returns year-on-year, or 600% in a specific two-year period.<\/strong><\/p>\r\n\r\n\r\n\r\n

The Algorithm<\/h2>\r\n\r\n\r\n\r\n

Divulging exact specifics of my trading algorithm would be giving away valuable information, but I can tell you that it used a combination of the following.<\/p>\r\n\r\n\r\n\r\n

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  • Moving averages<\/li>\r\n
  • Indicators such as Relative Strength Index (RSI)<\/li>\r\n
  • Volume analysis<\/li>\r\n
  • Trend Analysis<\/li>\r\n
  • Support & Resistance analysis<\/li>\r\n
  • Multi-timeframe analysis<\/li>\r\n<\/ul>\r\n\r\n\r\n\r\n

    In other words, there’s no crazy magic behind this algorithm, it doesn’t use AI (artificial intelligence) or Machine learning. It doesn’t divulge sentiment from twitter posts or anything like that. Just good old-fashioned trading techniques automated into a bot which isn’t subject to human emotion or hesitency.<\/p>\r\n\r\n\r\n\r\n

    Trading Results<\/h2>\r\n\r\n\r\n\r\n

    So how well does this trading algorithm perform? In simulated backtests, it averages 200% year on year with historical data on the BTC\/USD pair on Binance, or up to 600% for a two-year period. Pretty incredible!<\/p>\r\n\r\n\r\n\r\n

    You can watch a webinar below<\/a> talking about the trading algorithm and implementation with SciChart, or read on to find more details below.<\/p>\r\n\r\n\r\n\r\n