Blog @ AlgoTrading101

AlgoTrading101 is an Investopedia-featured algorithmic trading course that doesn’t suck (too much)

3 Types of Algorithmic Trading Risks

Broadly speaking, there are 3 main types of risks in algorithmic trading: Research, Market and Operational risk. Research Risk Research risk relates to risk of inaccuracies during the testing phase. Eg. Does the market inefficiency exist for a fundamental reason? Did you use proper testing...

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Making Profits Doesn’t Mean You Made a Good Trade

Making profits doesn’t mean you made the right trade. Making losses doesn’t mean you made the wrong trade. Let’s illustrate with a dice game. If you roll 1, 2, 3, 4 or 5, you win $50. If you roll a 6, you lose $10. You chose to play this game. You rolled a 6 and lost $10. Does that mean you...

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Market Alpha Is Not In Price Alone – How To Trade Using Data

When we develop trading strategies using data, we don’t use price data alone. We don’t add layers and layers of technical indicators that are all based on prices, and hope some mathematical formulas will output some sort of magical market alpha. We find market inefficiencies (i.e. sources of...

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Clean Data, Biased Output – Backtesting vs Live Trading Results

Our backtest results and live trading performance may differ greatly (and usually in a bad way). Our backtests may tell us that there is easy money on the table, but sometimes, they are lying. There are times where our data are clean, but they do not tell us the full story. We need to dig...

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Retail vs Institutional Traders – How can Individual Traders Beat the Hedge Funds?

Short answer: It is difficult but definitely not impossible to outperform hedge funds and asset management firms over the long run. Long answer: There isn’t a direct answer to this. Hedge funds and big trading firms have billions in capital, teams of experienced and highly qualified portfolio...

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How to Learn Algorithmic Trading: 6 Key Components for You to Google

The ancient city of Carthage stood against the Roman Empire for over a hundred years. “Victorious warriors win first and then go to war, while defeated warriors go to war first and then seek to win.” – Sun Tze. Finance, Mathematics and Programming. That is what I used to tell my...

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Optimizing Your Trading Strategy to 2 million in Profits! - What is Curve Fitting (Overfitting)

Ok, yes, I understand that many of you experienced traders feel that curve fitting (aka overfitting aka data fitting) is such a rudimentary (and over-blogged) topic. However, understanding this concept is extremely important for designing and testing effective trading strategies. Thus, for those...

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Dynamic Trading Systems: Fixed Strategies Can’t Adapt!

“We need our trading strategies to adapt to the market to maintain their effectiveness!” What does that statement mean and how do we achieve it? For our trading strategies to adapt to the markets, they need to have adaptive components. Defining Adaptive Components Adaptive Component: A...

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Trading Edge: 4 Types of Market Alpha/Inefficiencies

Generating trading ideas can be a frustrating process, especially if there isn’t a structured framework for it. To assist us with our ideas generation process, we break down algorithmic trading ideas into 4 main categories. These 4 categories are essentially different types of market...

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Market Prudence - Reason For The Trade

Approach to Designing Amazing Strategies “Add an SMA(30)! No, add an EMA(18)! Actually, maybe it’s time to optimise it to find the best parameter value. Ok, we’ll stick to EMA(15). Throw in 3 date and time filters, 3 optimised price indicators and 3 volume indicators (that are essentially saying...

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