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Quantitative Trading

June 11, 2020

June 11, 2020

Quantitative TradingOleg Tkachenko

How to use quantitative trading strategies

Classic trading uses fundamental and technical analysis. Quantitative trading strategies are a radically different approach that has much in common with algorithmic trading and neural networks, some of them have direct correlation to high-frequency trading. Quant trading strategies rely on mathematical modeling using software algorithms and statistical methods. In other words, quant-based trading strategies are automated systems written in classical programming languages ​​(C ++, Python, etc.) using computer programming software such as EViews or MATLAB. Are they accessible for private traders? This is a rhetorical question. But you need to know about their existence if only because quant based trading strategies are used by market makers (hedge funds or investment banks).

Quant-based trading strategies as an alternative to technical and

fundamental analysis

Which strategies are more profitable: ones based on technical or fundamental analysis? Manual strategies or ones that use trading advisors? The example of the world’s leading investment funds shows that neither fundamental nor technical analysis meets expectations. However, there is another trading method - quantitative strategies. In this review, I will try to outline the essence of this method and show the main differences from the usual trading strategies based on fundamental and technical indicators.

Note. Quantitative trading is built on mathematical methods and statistical analysis using programming. Therefore, the purpose of this review is to only inform of the existence of such a method. If you have knowledge of higher mathematics and programming languages ​​(we are not talking about MQL), try to dig deeper and be sure to share your experience in the comments!

Quantitative trading strategy for a private investor: what it is and

how to model it

The trader’s job is to determine the direction of the trend and possible reversal points. It does not matter what tools, strategies or type of analysis are used for this, as long as it does the trick. You only need to find reversal points, determine the strength of the trend and enter the market at its beginning.

  • In fundamental analysis, the trader tries to predict the direction of movement after the news or based on wave-like movement of the global economy. The strategy is based on the fact that the market will somehow respond to information, stimulating the growth of demand or supply.

  • In technical analysis, fundamental factors are excluded. The trader analyzes the history and finds patterns. Force majeure and other fundamental factors are automatically taken into account in the general trend.

But there is another trading method that does not involve either technical or fundamental analysis. For it, predicting the direction of the trend is a secondary issue, and the releases of the Central Banks are irrelevant. Currency quotes here are just a set of basic input market data on which the network machine algorithm is built. This method is called quantitative trading strategy or quant based trading strategy.

The point of quants trading strategies is not to predict the direction of the trend, but to find the optimal strategy and the best set of trading tools by selecting a mathematical set of parameters that will ultimately allow you to get a stable profit.

![LiteForex: Quant trading and Quantitative Trading Strategies][1]

A bit of history of Quant trading

Despite seeming somewhat pointless, algorithmic trading and quantitative strategies have been known for more than half a century and actively used by investment hedge funds.

One of the first companies to apply quant based trading strategies was the George Soros Foundation. Soros was able to prove in practice that fundamental and technical analysis are inferior in comparison with the strength of capital. By having access to insider information and artificially shaping people’s opinion with the help of the media, he changed the direction of the trend at his discretion with large volumes, bringing down the policies of the Central Banks. This is why his fund was one of the first to give up assessing the monetary policy of the Central Bank and searching for technical patterns in favor of mathematical modeling and programming.

In 1973, Fischer Black and Myron Scholes first published the option pricing model formula. The key point in determining the value of the option was the expected volatility of the underlying asset, the level of which can be calculated mathematically. Without going into details, the formula includes the cumulative distribution function of the standard normal distribution, the risk-free interest rate (we see something similar in the [Sharpe ratio][2]), spot and strike prices, and volatility. To characterize the sensitivity of the option price to changes in certain values, coefficients called greeks (based on the letters of the Greek alphabet) are used.

In 1997, the Black-Scholes model won the Nobel Prize in economics, radically changing the approach to developing trading strategies. The yield of 75-80% of transactions based on mathematical analysis has become a proof of the effectiveness of this technique and was adopted by market makers and investment banks. Today’s real examples of using quantitative trading models are:

  • Two Sigma Investments - the fund was founded in 2001. Its trading strategies are based on methods using artificial intelligence, machine learning (an analogue of neural networks), and distributed computing.

  • DE Shaw&Co - the fund was founded in 1988. The company is known for its development of sophisticated modeling systems and programs that track market anomalies.

  • Renaissance Technologies LLC - the company was founded in 1982. It specializes in trading in quantitative models developed on the basis of mathematical and statistical analysis.

There is practically no human involvement in their trading methods.

There is practically no human involvement in their trading methods.

What is quantitative trading and how it works?

Quantitative trading is based on the principle “the more the better”. The mathematical apparatus allows you to sort through many strategies for all trading assets, choosing the optimal result of the risk/profit ratio. In general terms, the algorithm uses the analysis of a certain time section, where the values ​​of price quotes are fixed (for example, closing price). The data obtained are interpreted as follows:

  • As a function. The job of the programmer writing the model code is to find this very function (to build an equation) that would describe the distribution of quotes in a time series.

  • As a time series that is analyzed by statistical methods. The accuracy of forecasting by statistical regularity is tested on other time intervals (forward testing).

The quantitative trader can get some extreme points from the function and time series that describe the price movement chart. By adding an additional mathematical apparatus (approximation, entropy), you can calculate the areas of trend slowdown, flat, or calculate the predicted stop order points. And only later a quantitative trader may try the strategy in real time, applying the risk management required.

Another method of econometric analysis on which quantitative trading strategy is based is to break the time section into separate clusters (areas where you can see a clear price movement according to a certain pattern). For example, a section 10 years long, is divided into segments of different lengths (1 day, 1 week - they do not have to be the same), on which the pattern is visible. Moreover, the sections can intersect and overlap each other - a neural network with algorithmic program code finds all these sets of patterns. The current market conditions are compared with similar patterns of price behavior in the past, based on which a further forecast is made.

Mandatory conditions for using the quantitative trading strategy:

  • High liquidity. Only highly liquid instruments are selected for quantitative trading strategies, therefore this method is more common on [stock markets][3] than on Forex.

  • Diversification. Quant trading strategies involves launching mathematical algorithms for a large number of instruments. It will not work on one currency pair. In this case, the correlation coefficient between instruments should be as low as possible.

  • Quantitative analysis works for the largest possible number of algorithms (three variants of such algorithms - function search, distribution of number series and template trading - are described above).

The model of quantitative strategies has something in common with the algorithmic advisor trading. The formula of moving averages attempts to search for patterns of price movement. And over time, technical analysis enthusiasts added a series of coefficients to the formula, which became EMA, LMA, etc. However, the problem remained the same - there are no ideal tools that would bring 100% income.

Still, forex quantitative trading is not the Grail, but just another trading method. There are companies involved in the development of such algorithms and selling the product to individual traders. In my opinion, given the complexity of the product, the need for software support and the cost, the idea of ​​using quantitative trading systems in private trading seems unreasonable.

Conclusion

Quant trading strategies are another attempt to get closer to the Grail using the methods of mathematical and statistical analysis and programming. There are a lot of quant traders convinced that this model works in financial markets much better than technical and fundamental analysis. But I did not find open information about the profitability of such strategies.

Quant based trading strategies should only be used for stock market instruments. Therefore, quantitative trading strategies are used either for trading securities ([stocks of corporations][4]), or [stock indices][5].

It’s useful to know about such methods, if only because they may be the future of automated trading. If you have experience in using quant trading strategies, be sure to share it in the comments!

P.S. Did you like my article? Share it in social networks: it will be the best “thank you” :)

Ask me questions and comment below. I’ll be glad to answer your questions and give necessary explanations.

Useful links:

  • I recommend trying to trade with a reliable broker [here][6]. The system allows you to trade by yourself or copy successful traders from all across the globe.
  • Use my promo-code BLOG for getting deposit bonus 50% on LiteForex platform. Just enter this code in the appropriate field while [depositing][7] your trading account.
  • Telegram channel with high-quality analytics, Forex reviews, training articles, and other useful things for traders

![Quantitative Trading][8]

The content of this article reflects the author’s opinion and does not necessarily reflect the official position of LiteForex. The material published on this page is provided for informational purposes only and should not be considered as the provision of investment advice for the purposes of Directive 2004/39/EC.

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  2. www.liteforex.com/blog/for-beginners/sharpe-ratio-trading-strategy-evaluation/
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