{"id":253,"date":"2023-07-18T08:25:34","date_gmt":"2023-07-18T12:25:34","guid":{"rendered":"https:\/\/www.tiingo.com\/blog\/?p=253"},"modified":"2023-07-18T08:25:36","modified_gmt":"2023-07-18T12:25:36","slug":"backtesting-stocks","status":"publish","type":"post","link":"https:\/\/www.tiingo.com\/blog\/backtesting-stocks\/","title":{"rendered":"Simulate Your Investment Strategy by Backtesting Stocks"},"content":{"rendered":"
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\"Backtesting<\/figure>\n<\/div>\n\n\n

<\/a>Want to test a trading strategy before committing any of your or a client’s investment capital? Backtesting stocks and trading strategies is a smart move.<\/p>\n\n\n\n

Backtesting stocks is a method of simulating an investment strategy without risking any money. You\u2019re only performing paper trades without risking any capital. Historical data is the only way to backtest stocks and trading strategies.<\/p>\n\n\n\n

Investment professionals that use backtesting and simulations that rely on adjusting strategies and variables based on historical data could increase their confidence when it comes to live trading.<\/p>\n\n\n\n

In this article, we explain backtesting stocks, why investors, brokers, and analysts use this approach, the pros and cons, and the best practices for backtesting. <\/em><\/p>\n\n\n\n

What Is Stock Backtesting?<\/h2>\n\n\n\n

Any investment strategy carries an element of risk. Traders, investors, and analysts working for brokers want to know an investment strategy has the potential to work in theory before putting it into practice. Otherwise, you increase the risk of losing your money, client funds, or both. Hence the value of backtesting stocks, instead of diving into a live investment strategy without validating your approach.<\/p>\n\n\n\n

Everyone knows that what goes up must, at some point, come down, and the usual investment disclaimer is that past performance doesn\u2019t guarantee future profits.<\/p>\n\n\n\n

However, smart investors look for ways to minimize risk and maximize gains. Backtesting stocks and trading strategies is one approach to reducing downside risks. In theory, if a strategy can be quantified and tested on historical data and \u2014 crucially \u2014 works, then it should give you more confidence to put it into practice.<\/p>\n\n\n\n

The idea is that a backtesting strategy that performed well in the past should perform well in the future. In most cases, the ultimate measure of success is, \u201cDid my trading strategy yield a profit from financial markets?\u201d If yes, then it could be viable for live trading. If not, then it\u2019s time to rethink and tweak your trading system.<\/p>\n\n\n\n

Although, it helps to backtest using a timescale when market conditions were comparable to the present to make it realistic. This means finding a time period with similar levels of volatility, whether bull or bear, depending on the different markets you want to invest in. <\/p>\n\n\n\n

If your tests prove successful, then you can test your theories further with different time periods, timeframes, datasets, and out-of-sample data.  <\/p>\n\n\n\n

Backtesting doesn\u2019t only apply to stocks and shares. Investors and analysts can use this for anything from derivatives, commodities, currencies, forex trading<\/a>, crypto (although historical data is more limited as Bitcoin only launched in 2008), exchange-traded funds (ETFs), futures markets, and numerous other asset classes.<\/p>\n\n\n\n

Why Do Investors Use Backtesting Stock Strategies?\u00a0<\/h2>\n\n\n
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\"Employees<\/figure>\n<\/div>\n\n\n

<\/a>Investors deal in numbers and data \u2014 hence the value of understanding technical indicators<\/a>. Almost everything can be quantified except for useful elements of qualitative data when investors are applying fundamental analysis<\/a> methodologies.\u00a0<\/p>\n\n\n\n

Trading strategies can be quantified too, provided you\u2019ve got one that can be coded into a trading platform (e.g., using a programming language such as Python), an online simulator, or defined using backtesting tools and software settings and parameters. <\/p>\n\n\n\n

That\u2019s what backtesting stocks is all about: testing a quantifiable investment strategy or theory using historical market and price movement data over a fixed time period. As no investment strategy is risk-free, this acts as a smart approach to risk management. Once you\u2019ve evaluated trading ideas with historical data, you can implement forward testing before putting your theory into practice. <\/p>\n\n\n\n

Backtesting is used to safeguard investor funds before implementing actual trades that risk real capital. Investors that spend time drawing up trading strategies for a backtesting scenario can then implement the same strategy during live trading, perhaps manually on a small scale at first before investing more and perhaps using algorithmic trades to execute the strategy faster, provided it yields a profit.<\/p>\n\n\n\n

Investors or analysts backtesting any strategy need to be clear on the stocks, commodities, or other investment vehicles they include in any test.<\/p>\n\n\n\n

A backtesting strategy could be as simple as using candlestick charts, Bollinger bands, or a simple moving averages crossover over a fixed timescale to compare a basket of stocks in a particular sector. Or it could be more complicated, such as using algorithmic trading<\/a> to plot a seven-figure investment strategy spread across hundreds of funds, stock markets, and ETFs.<\/p>\n\n\n\n

Pros and Cons of Backtesting Trading Strategies<\/h2>\n\n\n\n

Here are the pros and cons of backtesting stocks that every trader and investor needs to think about before going ahead with a simulated approach. <\/p>\n\n\n\n

Advantages of Backtesting Stocks<\/h3>\n\n\n\n