Get the weekly summary of crypto market analysis, news, and forecasts! This Week’s Summary The crypto market ends the week at a total market capitalization of $2,17 trillion. Bitcoin continues to trade at around $62,300. Ethereum experiences no changes and stagnates at around $2,400. XRP is down by 2%, Solana by 1%, and Dogecoin by 3%. Almost all altcoins are trading in the red, with very few exceptions. The DeFi sector decreased the total value of protocols (TVL) to around…
A Look into Algorithmic Trading Strategies – What You Need to Know
Algorithmic trading, also called automated, or black-box trading is an emerging trend that has seen a massive surge in recent years. A study shows that it now accounts for up to 80% of all forex trading.
As the name implies, algorithmic trading involves the execution of orders using a defined set of instructions or algorithms on a computer program. The aim is to maximize speed and data processing beyond human capabilities, replacing the slower traditional human trading.
Opportunities at faster profitability drive the choice of strategies employed. This article shall comprehensively review the various strategies employed.
Algorithmic trading strategies
Trend-following Strategies
They are the most common and straightforward of all strategies to implement simply because they lack the need to predict or forecast prices. Instead, they apply the following trends to estimate channel breakouts, movements in price levels, averages, and other technical indicators.
The occurrence of a favorable or desired trend kick-starts trades. Such a trend involves buying an asset as its price trend increases and selling it as it goes down. Complex predictive analysis is, therefore, not required.
Trading before Index Fund Rebalancing
The nature of index funds requires a periodic rebalancing or adjustment of their portfolio within a set period. Rebalancing helps match such funds’ holdings or new prices with their benchmark indices. Thus, a profitable opportunity is created for active investors and many algorithmic traders, capitalizing on the index rebalancing effect.
Depending on the stock number, the stake may be up to 80 basis points of profits. Algorithmic trading systems initiate the trade by timely executing it at the best prices.
Arbitrage
In a forex trade, there exist stocks that are dual-listed in various markets at different prices. Taking advantage of the price difference by buying the such stock at a lower price from one market and selling it to the other market at a higher price is referred to as arbitrage. It allows for a risk-free profit with no negative outflows.
The term can also refer to current stocks vs. futures since prices vary from time to time. Again, algorithms are crucial in identifying price differences and making orders on time.
Delta-neutral Strategy
It is a type of mathematical model-based strategy. Such strategies use proven mathematical models to allow trading on a set of options and related security.
The delta-neutral strategies create a reference position unlikely to be affected by small changes in stock prices. To ensure this, the “delta” value is made as close to zero.
Mean Reversion
Also referred to as range trading, it relies on the idea that both a stock’s highs and lows have a temporary aspect and should periodically move back to their mean prices (average price). A market price lower than the mean price means stocks are attractive to buy as they are speculated to rise. A market price above the mean is also expected to fall.
An algorithm automatically trades assets when a deviation from the defined average price is observed.
Percentage of Volume (POV)
An algorithm is set following a defined ratio of the traded market volume to continue trading until the trade order is met. There’s an automatic adjustment of the participation rate, limiting it to a specified percentage of stocks in the total traded volume.
Implementation Shortfall
In trade, implementation shortfall refers to the difference between the trader’s decision price and the average trade prices, including taxes and commissions. The reference price quoted by the trader is used as a benchmark.
The strategy aims to benefit from opportunity cost delays by trading off the real-time market and saving on the order’s cost. The algorithmic speed of executing the order capitalizes on this, increasing as stock prices become desirable and slowing when prices become untenable.
Volume-weighted Average Price (VWAP)
The strategy is effective with short-term time frames, usually a day. The VWAP strategy starts by first breaking up a large order. Using stock-specific profiles of historical volumes, smaller chunks of the order are traded in the market. The action aims to keep the price within the average.
Time-weighted Average Price (TWAP)
The time-weighted average price starts with breaking down a larger order. These smaller chunks of the order are then traded as evenly distributed time slots from the start to the end time. Again, the aim is to keep the price close to the average.
High-tech Front-running
This strategy is also referred to as beyond the usual strategy. Some algorithms will try and spot out ongoings from the opposite side of the trade. For instance, a market maker algorithm from the sellers’ side can recognize an algorithm from the buyers’ side with a large order. Such knowledge enables the market maker to spot the massive order opportunity and fill these orders at a higher price.
Requirements for Algorithmic Trading
The trading strategy is only complete when the algorithm is implemented using a computer program. The requirements are:
- Computer programming knowledge to craft the strategy.
- Access to stock trading platforms and a stable network connectivity
- Access to data feeds from the markets that the algorithm will analyze.
- Infrastructure and ability to carry a backtest of the system before real-life market usage
- Access to historical data for backtesting as per the rules on complexity implemented by the algorithm
Takeaway
Algorithmic trading allows for correctly timed trades, reducing the risk of manual errors when placed. An article by Nasdaq states that algorithm trading’s main advantage is eliminating human emotions, which causes irrational decisions during trading. The other advantages include the ability to backtest and reduced costs.
The loss of human control and the need for constant monitoring of power loss and connectivity are otherwise key drawbacks to algorithmic trading. The need to know the programming language necessitates traders to learn the skill of developing the algorithms.
CryptX Review – A Crypto Wallet with Swiss Vault Storage
How to Become a Successful Crypto Bounty Hunter
Written by
More author posts
Publish your own article
Guest post article. Guaranteed publishing with just a few clicks
START PUBLISHING ADVERTISE WITH US