Quantitative trading is simply put as buying and selling of financial securities using mathematic models, statistics and algorithms. While it looks complex, it has an’ unequivocally simple’ approach to it- how you set up your first quantitative trading strategy! In this article, I will take you through baby steps that can help you develop one.
1. Starting off with Quantitative Trading
To make a strategy, it is important to first understand the rudiments of quantitative trading. This includes:
Taking Decisions based on Data: This would mean real and past information.
Mathematical frameworks: This encompasses all algorithms or calculations used to determine when to purchase or sell.
Backtesting: Testing a model or strategy against prior years worth of data.
Automating: Another form of trading without legit inputing by the human hand.
2. Come up with a Market and Investment Class
There are quite several asset classes that quantitative trading can be employed, among them are:
Stocks
Forex
Commodities
Cryptocurrencies
Commence by coming up with a market that you are well acquainted with, for example, if you have knowledge equities area are able to deal with stocks.
3.Formulate a Trading Idea
Every strategy begins with an idea: a ‘what if’ scenario. For example: Average price- the price always tends back to its mean, or a momentum, where an asset willcontinue to head in the same direction.
If you were to come up with a hypothesis, it can be stated that stocks who experience a drop in price should be able to recover within the span of a week.
4. Data Collection and Analysis
The heart and soul of quantitative trading rests in data. In order to fully grasp such a concept, it is important to know what data is needed for:
Historical Data: Necessary for the purpose of backtesting your strategies and frameworks.
Live Data: Needed to carry out day to day trades.
Some of the platforms providing such financial data are Quandl and Yahoo Finance. When collecting data from these platforms, it is crucial to ensure its accuracy and its relation to the market selected.
5.Strategy Formulation
Keep it basic. Formulate the following three aspects:
Entry Criteria: What events would trigger a buying or selling of a stock?
Exit Criteria: What events compel one to close the position?
Position Sizing: What would be the amount of money the trader puts per trade?
Risk Management: What risk strategies will help to cut losses?
Consider an example where a mean reversion strategy is implemented, the criteria would be as follows:
Entry: Purchase when the price is 5% less than the 20 day average this is measured over a span of 20 days.
Exit: Sell the stock when its price reaches back at the average.
Position Sizing: An investment of 2% of the portfolio would be done for a position.
6. Back Test Your Strategy
Back testing is the measuring instrument used in determining how the strategy would have performed in previous years. Historical data works as a best substitute, allowing for one to conduct ‘virtual’ trades. Points of interest on such an analysis include;
Win Rate: The total number of trades that turned out to be profitable in percent form.
Profit Factor: The total number of successful trading activities to over all losses ratio.
Drawdown: Percent of loss facing capital hardware across the simulated trading period.
For backtesting purposes, you may use tools such as QuantConnect, Backtrader, or even Excel.
7. Optimize Strategy – Don’t Over Fit The Models
Another goal of an optimization is to adjust its parameters with the objective to increase performance. The main red flag to look for would be overfitting the strategy to the historical data, that is, the strategy will perform well in back-testing yet when running on real markets it will fail. Attempt out-of-sample testing as a means of testing.
8. Execute the Strategy
Once the validation is done, use a broker or a specific trading platform to roll out your strategy. A few of these platforms are as follows:
MetaTrader – Used mostly for trading foreign exchange and stocks,
API of Interactive Brokers -This is used exclusively for stocks Trading,
Crypto Exchanges like Binance or Coinbase – for trading in cryptocurrencies.
Real-time execution of the strategy can be done by trade automation software such as NinjaTrader or TradeStation.
9. Track and Alter
Markets are not static but dynamic, therefore it is essential that your strategies are being tracked on a regular basis to see if they are performing to expectations. Parameters can be altered or the logic changed according to the current market trends.
10. Ensure Risk Management
To safeguard your capital, risk management is key, these include some of the best such as:
Stop-Loss Orders – A position will automatically be closed when a certain estimate or predefined amount of losses are reached.
Diversification – Capital will be allocated in more than one asset.
Risk-Reward Ratio – The risks taken should not exceed the rewards received.
Challenges to Anticipate
It is important to understand that accuracy is very much needed in trading. There can worst be a lot of data quality issues, such as missing or inaccurate data obtained during trades.
Moreover, be prepared for technical issues such as glitches in your code or the trading platform itself.
Finally, keep in mind that a degree of emotional willpower is needed – even if the trading is automated, it’s important to still follow your rules.
Conclusion
There are steps involved in setting up a new quantitative trading strategy for the first time you set a new one and they involve hypothesis formation, analysis, backtesting, and execution. Try first with an uncomplicated, well-articulated concept and after that over and over augment it with your growth.
As with everything else, it will take time, effort and practice, but in time you will come to appreciate how effective quantitative trading can be in improving your trading results.
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