Algo Trading and Market Volatility

Tomer Solel is a Financial Analyst  at I Know First. He graduated from Cal Poly Pomona with a bachelor’s degree in applied mathematics.

Algo Trading and Market Volatility

Summary:

  • There are a lot of different factors that can make a market volatile.
  • Algorithmic trading could reduce volatility in stock markets.
  • Performance maximization during volatile periods is key for traders.
  • Mass psychology leads to chaos in the stock market.
  • I Know First uses an advanced predictive algorithm which is able to predict chaos.

Algo Trading

Introduction

Stock markets are rather unpredictable. Sometimes there are stable periods, but other times the markets get chaotic, and stocks become volatile. Trading stocks in a volatile market can be risky, but there are some tips that can help us. Algorithmic trading is becoming so advanced that it is now able to make predictions even when the markets get volatile, using high-frequency computers. Technological developments have allowed investors to turn to such a form of trading. The key risk for an individual in today’s market is volatility. The CBOE’s volatility index, (INDEXCBOE: VIX), is Wall Street’s fear index. Spikes in the VIX mirror heightened market volatility. On January 13, 2016, I Know First published an article talking about the complexity of the stock market. Volatility is a big reason that the stock markets are as complex as they are.  Overall, algorithmic trading has a big impact in volatile markets.

Algo Trading

(Source: javacodegeeks.com)

Algorithmic Trading In Volatile Markets

Algorithmic trading contributes to the stock price decline when there is a large drop in the market. It also plays a large role in terms of price discovery and liquidity. Until recently, most algorithmic trading studies focused on the short term, going anywhere from milliseconds to minutes. However, long-term investors have different concerns than short-term investors. Algorithmic trading has implications in the long term. Algorithmic trading could reduce volatility by mitigating market frictions, being able to quickly respond to future markets and adjust their position in the spot market.

Algo Trading

(Source: marketsmedia.com)

The Negative Effect of Volatility On Trading Costs

Choosing the right algorithm can minimize trading costs in volatile markets. The market crisis of 2008 shows us a great example of that. That year, the VIX climbed from 30 to 70 from March to October. Performance maximization during extreme volatility scenarios emphasizes the valuable role a trader can play in managing his/her investments. Volatility has a triple negative effect on trading costs. Therefore, a rising volatility increases trading costs. Algorithms can perform well in both low and high volatility periods. Opportunistic algorithms are not bound by any rate or schedule. Because of that, they have a leeway to adjust their aggressiveness based on real-time market conditions. Since they make use of liquidity opportunities, it helps them in minimizing the dispersion of cost. According to financial times, the growing use of new types of computer models that react to the latest moves in prices is exacerbating the historically high levels of volatility in equity markets. Aggressive, up to date algorithms have replaced long-term evaluations going back 10 years or more. Sudden recent moves in prices can, therefore, prompt algorithmic traders to quickly enter or exit the market. Many traders are now seeking out liquidity at all costs, finding a particular price, filling an order, and quickly moving onto the next price level. Traders have the power to control and reduce costs by using the right algorithms.

Algo Trading

(Source: marketsmedia.com)

Chaos and Randomness in Stock Markets

Some people claim that the stock markets are unpredictable due to how chaotic they are. They say that since markets are fully efficient, they are simply impossible to predict. However, this clearly does not reflect reality. Also, it is not true that stock markets are completely chaotic. The most accurate way to describe markets is that they are complex and chaotic systems with components that are both systematic and random. That allows us to forecast the stock market, with probability but not with certainty. On January 14th, 2016, I Know First published an article comparing mass psychology to algorithmic trading. In that, it talked about the psychology that traders use when they invest. That psychology leads to chaos, making the markets volatile. Market volatility is caused by many factors, causing periods of high uncertainty and stock prices spreading across markets. The knowledge of market regimes, a knowledge that is acquired by algorithms, is a key to success. Using predictive algorithms can give traders a great advantage.

Conclusion

In conclusion, markets tend to get very volatile. At I Know First, we have a predictive algorithm that forecasts over 3,000 markets daily for 6 different time horizons. It attempts to discover the rules of the market, in order to give us accurate predictions. This algorithm uses artificial intelligence and machine learning to make very advanced predictions, using thousands of inputs, with each input affecting the output. The algorithm is completely empirical, eliminating any human bias, and preserving discipline. The Company published a 14 day forecast from 12/27/15 – 01/10/16 for volatile markets, in which it returned an average of 29.72% while the S&P500 actually came in at a loss of 6.74% during the same time horizon. This shows that the algorithm is able to take chaos into consideration when making its predictions. The I Know First algorithm is very advantageous to its subscribers.


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