How has Algorithmic Trading Impacted the Futures Markets?

Technological advances have increased by bounds and leaps and changed how a monetary marketplaces are and traded now. Gone would be the days of working with a pencil and paper to run technical investigation or calling your broker to place an order.

The arrival of computers has attracted trading into the domiciles shifting how the normal mom and pop stinks or trades. Every measure of trading, by the manner by which the orders are put into the manner by which the orders are directly hauled into the broker also into the market and also the direction in which they’re full is dependent on technology.

Algorithmic trading continues to be perhaps one of the most mentioned disruptive technologies in the past couple of decades. Still it isn’t something new to the trading world and has existed after all decades. Known by different names such as automated/algorithmic trading systems (ATS) or black-box trading, it is the process of using computer programs that are designed to follow a specific set of instructions to purchase or sell based on a set of rules. Think of algorithmic trading as a robot trading the financial marketplaces when specific requirements are met.

What is Algorithmic Trading?

Algorithmic trading as the name suggests is a piece of code that automatically trades the marketplaces. Think of Algorithmic trading as a set of logical rules a program has to follow.

For example, you could build a trading program and code it to trade the store open based on some criteria, or you could build an automated trading system that buys on a bullish moving average crossover and so on.

Automated trading comes out of a mechanical trading system. It is easier to code a mechanical trading system than a discretionary trading system because the rules are specific and finite and most importantly does not contain any subjective thinking on its part.

Some of the different types of algorithmic trading systems are:

  • Momentum: Momentum based ATS look for strongly trending assets. ATS based on this method can look into entering the strong trend, holding for a few hours or days before exiting for a benefit
  • Mean Reversion: This type of ATS looks at the amount reversing to its mean amount. It is somewhat opposite to how the momentum-based method works
  • Valuation: Some advanced ATS can look to the valuation of assets and identify assets trading at a discount and initiates positions. Common examples could be the Dogs of the Dow
  • Seasonality: In this type, automated trading systems look at the seasonal behavior of an instrument and initiate trades accordingly. For example, sell in May, or purchasing natural gas futures into the winter months
  • Sentiment: The sentiment-based ATS looks at crowd or trader psychology. Example of sentiment-based ATS purchases the rumor, sell the news

Introduction to High-Frequency Trading

People tend to confuse High-Frequency Trading with Algorithmic Trading. However, these two are completely different. In fact, High-Frequency Trading or HFT is a subset of algorithmic trading and HFT is further categorized into different subsets.

Algorithmic Trading and HFT (Source – DBResearch)

The subject of High-Frequency Trading is the one which is usually debated and will provoke powerful feelings among traders, perhaps because of personal issues such to be stopped outside, irrational store behaviour and so forth.

According to recent quotes, as soon as April 2016, HFT is supposed to accounts for roughly more than 70 percent of trading volume from US equities independently and roughly 50 percent at the European equity marketplaces. Inside the futures marketplaces, HFT accounts for almost 80 percent of forex futures volume and not two-thirds of rate of interest and Treasury stock volume.

Percentage of HFT trading across various stocks

HFT trading in percentage terms across various share classes

What is HFT?

High-Frequency Trading works on the concept of speed and information.

  • Speed or latency determines how fast orders are executed
  • Information determines how fast any new information that is released is interpreted by the HFT machines

To obtain an idea on how fast HFT’s work, imagine this. It takes 300 to 400 milliseconds to blink an eye. A millisecond is one-thousandth of a second (1000 milliseconds = 1 second).

For HFT’s, it takes 1 microsecond to complete an order. (1 microsecond = 0.001 millisecond). On average, an HFT can trace 7000 times within a 300 – 400 millisecond time frame.

HFT’s take the subject of automated trading to a whole new level as the machines with high computing power can now read store news as well.

Human information processing when compared with HFT (Source – seangourley.com)

Some of their very common facets which are employed in service of High-Frequency trading include Liquidity, quantity, and tighter spreads.

Liquidity could be the most indispensable part of just about any trading platform or market. Algorithmic trading enhances the potency of the overall marketplaces. On account of the sheer level of HFT predicated trades, the entire costs are lower due to of thin spreads and dependent on the thickness, the amount tag on the stocks are somewhat less influenced by additional trades (non-algo trades). Liquidity is vital as it will help to consume store shocks a lot better compared to an existing store, which increases the robustness of their fiscal systems. Last but not the least, liquidity is imperative to amount discovery that’s an essential aspect for those marketplaces.

Due to the range of trades that an HFT application is likely to create, exchanges especially like HFT firms. More trades out of HFT’s interpret to a greater volume, which subsequently increases more commissions to the market. In March 2016, NYSE had been fined 5 million following having a whistleblower unearthed that the market revealed preferential treatment for an HFT business.

In some scenarios, HFT’s will also be thought to be responsible for lesser spreads from the marketplaces.

Interestingly, every one of these benefits of High-Frequency Trading is readily debunked!

Surviving from the sphere of algorithmic and HFT trading

It is projected that the prevalence of HFT and algorithmic trading will probably go on to grow in lots of major worldwide marketplaces whilst the demand for individual and proprietary trading firms and qualitative trading strategies gain. Despite facing enormous stress especially after being responsible to its March 9, 2020 flash accident which sent the Dow Jones decreasing by 1, 000 points simply to regain straight back about 15minutes, HFT’s aren’t going anywhere.

Dow Jones – How May 6th Flash Crash

New regulations are anticipated to attract more transparency and in addition lessen the volatility in the marketplaces. Pros think that HFT is however a standard phase in the growth of the monetary marketplaces. Nowadays many search papers have been exhibited on areas like compliance and risk administration, technology form, code optimisation and so forth.

The purpose here’s really being the HFT’s and automated trading will be here to remain. However, what does this mean for your typical retail trader who prefers to trade out of the convenience of the house, assessing the graphs and setting their orders by hand (digitally of course)?

First of all, there isn’t any foolproof method which may guarantee you safety against abrupt spikes from the marketplaces brought on by HFT and algorithmic trading, however, you may stick to several techniques to make sure your losses will be lessened.

Stop Looking for a Quick Fix. Learn How to Trade the Right Way

Take fewer trades: This doesn’t follow you ought to trade, but instead once you trade, concentrate on the very best possible pair-ups predicated on a method that you simply follow. By ensuring you trade simply the finest possible trade setups, you do not just limit the losses in the trade, however, also you become discerning on your own trading. Fewer trades will suggest reduced deal costs over a time period plus it is helpful to make sure you make consistent benefits with time. Bear in mind, superior traders manage hazard.

Avoid overnight trading: Lower liquidity spans from the futures marketplaces occur medially the end of their US and the mid-Asian trading session. This era of non-liquidity usually means an HFT or an algo can readily push costs around only using massive quantities of trades. Your best odds of minimizing your losses will be always to trade whenever there is certainly high liquidity such as for example the entire of those European and US trading periods. This guarantees that if a trade proceeds negatively contrary to the circumstance, the top liquidity will be sure your stop-loss is fulfilled at the amount and perhaps not at the second-best available amount.

Skip such marketplaces: Most HFT’s are in their utmost at markets. With the use of big amounts and laborious amount action, HFT’s could make substantial levels of funds. As a retail trader, a Forex store is only going to make you confused and can take out in the trading capital on account of the trades being constantly quit outside. On the flip side, whenever you concentrate on a strong trending store, it will be able to allow one to ride the tendency.

Be well-intentioned: One of the very usual reasons retail trades neglect is since they’re undercapitalized or usually do not utilize decent standing administration. Form a performance bond or initial perimeter that’s demanded, leave enough care allowance and a few extra capital to make sure the trade has enough breathing distance.

Trading using HFT’s and Algos – Final Thoughts

Mike Bellafiore is a Well-known title in the trading sector and he’s your Cofounder of all SMB Trading, a Forex company. He’s also the writer of many powerful trading novels like The Playbook and One Good Trade.

In his novels, Mike summarizes some ways the way you’re able to live in a universe using HFT’s and algos. A number of the things which he highlights are:

You may obtain stopped out of longer rankings. So utilize far better ceases. Stop hunting is actually a frequent occurrence and HFT’s largely donate for the particular. Mike implies that traders must additionally utilize different tools like understanding that the orders by taking a look at the Level-II orders. Obviously, there’s still the probability of spoofing, however, if blending fantastic hazard direction, stops and dictate publication it is possible to at minimum be prepared.

Past trading installments will no longer do the job. Mike claims that since HFT’s go on to cultivate and find out to play with the marketplaces; the retail trader must not obtain blindsided by their trading method. By adapting to the store behaviour and constantly detecting the marketplaces you’ll have the ability to finetune your trading plans while at the equal time never allowing your room to obtain complacently that will be when things start to come.

Institutional buy/sell orders. It’s well known that every time a significant player would like to purchase or buy stocks, they can do so with the use of passive algos that ditch assets without increasing suspicion. Taking a look at the trends in the market purchasing and selling behaviour may help keep you on the perfect side of those marketplaces. Cases include things like awaiting a pullback to proceed long to search for strong store behaviour throughout the intra-day hours.

Beware the fictitious input signs. False signs or fictitious breakouts are a frequent occurrence and it’s implied that the retail trader needs to know about those risks, especially once they trade mistakes.

To complete, whilst HFT’s and algos may have disrupted the store as well as at a sense changed the playing field, the retail trader must be observant and should be quick at adapting their means of investing in the marketplaces. It may look like a struggle for retail traders, however at the close of your afternoon if you don’t go on to find something new and shift with the changing times, you could risk getting quit outside!

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