Algorithmic Trading Python for finance python trading

The Spectacular Performance of Quantitative Investment Funds

python for finance

At the start of the pandemic, approximately 75% of hedge funds reported losses, while others rose to new heights, outperforming even their best years. What’s the difference, you might be asking?

One of the biggest factors in the success of investment funds boils down to the kind of business strategies used to make trading decisions with python for finance. Many of the companies that survived the uncertainties of 2020 were quantitative investment funds.

This notable difference between hedge fund business strategies can help businesses continue to navigate around uncertainties that jar the investment world, leading to spectacular performances of those funds.

What Is a Quantitative Investment Fund?

A quantitative investment fund is a hedge fund that uses algorithmic strategies to make decisions regarding trading. By using a combination of automatic computer algorithms and data science to execute python trading decisions, quantitative investment funds are driven by systemic strategies and trends.

what is quantitative-investment in trading?

Compare that to hedge funds that don’t use quantitative investment strategies. These “fundamental” investment funds might use data science to influence trading decisions, but, unlike quantitative python trading algorithm strategies, fundamental trading strategies are more subjective and prone to human error

Quantitative hedge funds use intelligent, mathematical models and principles to analyze dozens or even hundreds of different economic data factors. The automated computer technology allows quantitative investment funds to research and compares both long- and short-term scenarios, cross-sectional data, and other variables to make strategic decisions as free of human judgment as possible.

Quantitative Investment Funds Soaring to New Heights

Over the last few decades, hedge funds implementing quantitative analysis practices in their python stock trading decisions have risen to the forefront of the market.

Companies like DE Shaw, Renaissance, Two Sigma, Bridgewater, and more are just a few examples of algorithmic hedge funds that have significantly outperformed those using more traditional, fundamental analyses.

Take D.E. Shaw, for example for algo trading course. The New York-based company’s largest hedge fund increased by an astonishing 19.4% in 2020 alone, despite the financial uncertainty of the pandemic and election year. The hedge fund has invested approximately $55 billion in sheer assets. Since launching in 2001, D.E. Shaw hasn’t had a single down year, with an impressive annualized net return of 11.7%.


Likewise, the Medallion Fund is considered to be one of the leading hedge funds in the entire world, with a secretive group of scientists behind the spectacular performance of this quantitative investment fund. In the past three decades, the Medallion Fund has racked up over $100 billion in trading gains. What’s most notable about Medallion is that the hedge fund made these gains in less time than its competitors, with fewer assets. Like D.E. Shaw, the company has rarely seen a loss.

Behind almost every successful hedge fund is a methodical team of data scientists and analysts who know the power of using algorithmic trading with python to secure their spot at the top of the markets.

With what we know about these quantitative investment funds, it’s clear that quantitative investment techniques go hand-in-hand with top performances in the stocks.

Lumiwealth can help you get started with stock trading with python to remove the human guesswork from your trading decisions and increase your performance. Contact us today to get started mastering quantitative investments.

Algorithmic Trading

Algorithmic Trading Benefits And Downsides


Algorithmic trading is responsible for approximately 60-73% of all U.S. equity trading, according to BusinessWire. If you’re trading stocks manually, you naturally place yourself at a disadvantage; you’re competing against robots… and who do you think will win that fight? Nine times out of ten, it’s the robots.

Who Uses This Method of Trading?

You may be wondering: who runs these algorithms and who uses this method of trading? The aforementioned stats may shock you, especially if you’ve never heard the phrase “algorithmic trading” before. Hedge funds, investment firms, and other private equity trading groups all use algorithmic trading, mainly due to its decrease in costs, unrivaled speed, and increase in trading accuracy.

If you’re a little lost and don’t know what algorithmic trading is, don’t worry. To understand how this works, we must first explain how an algorithm works. An algorithm is a set of directions, usually inputted on a computer, to solve a complex problem. In basic terms, algorithmic trading, Python utilizes different algorithms to produce meaningful data, that is then used to determine whether to buy, sell, or hold during financial trades.

what is algo trading?

More often than not, when a firm utilizes algorithmic trading, they also use some form of trading technology to make thousands of trades each second. As these trades are real-time, this allows traders to maximize profit at any given moment – there are very few methods quite as accurate. 

In more recent years, and especially since the 1980s, algo trading has increased in popularity, with many investors and investment firms choosing this new method of trading to increase their profit margins and see more accurate trading results. In fact, according to Toptal, hedge funds that utilize algorithmic trading have significantly outperformed their peers and counterparts since this time, all with reduced costs in comparison to regular trading. As of 2019, quantitative funds represented 31.5% of market capitalization, compared to 24.3% of human-managed funds.

The remainder of this article will discuss algorithmic trading in more detail, in particular, how it could make you more money.

What Are The benefits of Algorithmic Trading?

As mentioned beforehand, there are several benefits of algorithmic trading. However, the main benefits include:

  • Cut down on associated trading costs
  • Faster execution of orders
  • Trades are timed perfectly 
  • Ability to backtest
  • Quantitative strategies have dominated the market and returns

Each of these benefits will now be explained below in more detail, helping to provide you with greater insight on how exactly algorithmic trading works.

make money with algo trading

Cut down on associated trading costs 

Firstly, when you use algorithmic trading, you are able to save and cut down on associated trading costs. Transaction costs are cut due to less human interaction, freeing up liquidity towards more investments. Likewise, you will also save money on fees, depending on your investment method – so it’s well worth keeping in mind.

Human interaction previously included general fees, a fundamental analysis performed by a finance manager, and the buying and selling of trades, amongst other actions. Algorithmic trading allows you to set a buy and sell price, cuts fees, and saves you money – let the robots work with you, not against you. 

Faster execution of orders 

With a faster system in place, traders are able to exploit the smallest of profit margins to create mid to large amounts of revenue in seconds. This method is called scalping and is where a trader instantly buys a set number of shares/stocks at a lower price, then rapidly sells these on for a higher price, whether for a small profit margin (which adds up in the long run) or for a slightly larger one.

When you use algorithmic trading, you can set a buy and sell price for a stock or share. For example, if one stock dips below a certain threshold, the algorithm will purchase a set number for you. Similarly, once this same stock increases in price to your pre-determined price, these stocks/shares will be sold instantly to maximize profit. This is much more accurate than human trades, and also removes the emotion involved with investing. 

Trades are timed perfectly

Human trades require you to buy and sell manually, watching particular trades all day to purchase and/or sell at the best prices. With the predetermined buy and sell thresholds, your trades are timed perfectly. 

This allows you to exploit small dips in particular trades, compounding small profits into large gains in the long run. The decision to buy or sell the trades is still yours, but you gain greater accuracy over when to buy and sell these. 

Ability to backtest

One key advantage of algorithmic trading compared to regular trading is the ability to backtest, as mentioned by Nasdaq. Essentially, you can run algorithms based on previous data to see what parts of a trading system works, and what doesn’t. This is super beneficial and removes any potential error before purchasing stock or shares in bulk, possibly reducing a large loss.

Backtesting is not as accurate when human trading and may result in large losses – so keep this in mind if you choose the old fashioned trading method. 

Quantitative strategies have dominated the market and returns

Hedge funds such as Two Sigma, DE Shaw, Renaissance, Bridgewater, and others have been the best performing investment funds in the world for several decades. Renaissance’s average of 39% annual returns have made the founder, Jim Simmons, and everyone else at the firm extraordinarily rich. Doing the math, at 39% per year for 30 years you could have turned just $100 into $1.9 million! That’s incredible, especially considering that they’re taking on much less risk than the stock market as a whole. 

These funds are managed with greater accuracy and with a quantitative strategy, other than trading blindly, with emotion, and with an increased risk of a slip-up. 

algo trading advantages

Are there any downsides?

Now that we’ve covered the benefits of algorithmic trading, you’re likely wondering if there are any downsides, and what they may be. As with all trading, there is an element of risk; however, you wouldn’t be in the business if you didn’t know this was a factor. 

Potential downsides of algorithmic trading include:

  • Loss of internet connection could prevent your order/trade from being processed
  • Without prior testing, you may use the algorithm incorrectly and create a loss 

Once again, each of these downsides will now be discussed individually below.

Loss of internet connection could prevent your order/trade from being processed 

Firstly, as these trades require an internet connection, if your connection is to drop, even for a few seconds then your automated trades may not be placed and/or processed. This could lead to a loss, so it’s integral that you have a strong internet connection and ISP. ideally, you should have business WI-FI, as this is more reliable and more suitable to learn algorithmic trading

The same risk is present with regular human trading, but it is something to be aware of, especially if trading in larger quantities. 

Without prior testing, you may use the algorithm incorrectly and create a loss

The other downside is that without prior testing of the algorithm, you could create yourself a loss. This is easy to combat; all you need to do is play around with the system before placing any large trades. Start small until your comfortable then increase the number of trades and shares you are both purchasing and selling within a short timeframe.

You can also backtest, as mentioned previously to further increase the accuracy of your algorithm. 

How does it work and how can it make you more money?

Algorithmic trading is made possible thanks to pre-programmed computers and a set of instructions to buy and sell trades in bulk. If done correctly, this allows you to make more trades than a human ever could, exploiting slight dips in the market for quick re-sales and easy profit.

First, however, you must identify an opportunity in the market. Running this through the algorithm and calculating the potential returns, deciding whether or the trade is worth it. Some trades will generate more income than others, but algorithmic trading is a long-term game, profiting off of small trades consistently for a greater ROI.

Do you want to learn more about algorithmic trading?

To find out more about algorithmic trading, you can take our unique, top-rated course designed for finance professionals and experienced programmers, allowing you to take your python for finance expertise to the next level. Not to mention make worthwhile investments, increasing your revenue, and be better equipped to solve real-world tasks and problems.

If you would like to learn more about our algorithmic trading course, click here.

Finally, we would like to draw attention to our open-sourced GitHub project, Lumibot. A great tool to use if you trade consistently and are looking to amp up your game, perhaps with algorithmic trading now on your side. 

Algorithmic Trading Python for finance python trading

How Algorithmic Trading Could Make You Money

Did you know that only one out of every five day-traders actually makes a profit? The ever-changing world of trading can be challenging to navigate. In fact, most trading on the stock market is performed by robots, making it like playing a rigged game of chess, where your chances of winning are stacked against you. 

That’s why many day-traders have started to learn algorithmic trading to improve their odds of making money through trading.  

In this post, we discuss just exactly how algo trading using python works and how you can create an algorithmic trading robot to help increase your odds of becoming the next, big money trader. 

What Is Algorithmic Trading?

Algorithmic trading uses data science and computer-automated executions, rather than human guesswork, to create instructions for trading. Since trading activities use data science techniques like technical indicators, financial fundamentals, and economic data, this also eliminates human emotions that can interfere with the success of trading.

How Can Algorithmic Trading Benefit Traders?

Algorithm trading offers numerous benefits for traders. Once you make the switch, you’ll likely be surprised that you hadn’t been incorporating algorithmic trading strategies into your investments all along. 


Here are just a few key benefits that ultimately save you time and money.

Your Trading Strategies Are Back-tested

Algorithmic trading takes the guesswork out of your trading strategies. By reviewing past back-tests, you can more clearly see patterns, which in turn helps you figure out what’s working and what isn’t working. 

Back testing Develop Your Strategies

Your Strategies Are Less Prone to Human Error

We all know just how fallible human calculations can be, and no one wants to make grave errors when it comes to their investments. That’s where algorithmic trading can be immensely beneficial for your financial trades. 

trade losses

Since algorithmic trading strategies are executed by computer software, there’s less room for error. This means that you can steer clear of common mistakes that you would otherwise make. 

You Have More Time to Develop Your Strategies

While computers do make mistakes, it’s far easier to monitor and troubleshoot, saving you time and money on your investment strategies and other areas that are in need of your attention. 

This means you can more easily branch out to other trade markets and strategies, allowing you to have less of a risk per capita of trade investments. In other words, you’re not putting all of your eggs in one investment basket.

Where Can I Learn More?

Are you ready to step up your day trading game? Though learn algorithmic trading may sound like the ultimate secret to your trading success, knowing exactly how to navigate a new arena of the data science world is no easy feat. In fact, if you don’t know what you’re doing, you could actually lose money.

How Algorithmic Trading Could Make You Money


That’s why we have created an algorithmic trading course to help you navigate Python software and start utilizing all that algorithmic trading has to offer & help you develop trading algorithms.  

In this course, you will learn the ins and outs of Python trading, where you can:

  • Analyze your investments
  • Make better decisions about your investments using data
  • Implement back-testing strategies
  • Automate your trades 
  • Calculate the risks and potential returns on investments
  • And, most importantly, start making money from those investments

We also have an open-sourced project, called Lumibot, that you can use to access what we use in our classes. This project is free for the public and can provide you with many resources to support your algorithmic trading journey and help you with coding trading bots yourself.  

If you’re ready to get started, sign up for our free live class, where you can download the course information on how to become the next, big algorithmic trader.