Interview with Ivan (Founder of PyInvesting)

Updated: Aug 15


In recent weeks, I came across PyInvesting.com and got fascinated with what the website could do- allowing retail investors to create their own quantitative investment strategy. In the local investment scene, such sites are definitely rare and I struggle to find another similar site which caters to local stocks . Being data-driven myself, I find PyInvesting particularly fascinating and decided to reach out to its founder, Ivan, for an interview to find out more about his motivations behind starting such a site.


Below is a brief biography of him and the series of Q&As which I have with him.

Short Biography

Ivan is the founder of PyInvesting.com. He built PyInvesting to help investors backtest their own investment strategies and support them in their journey towards financial freedom.


Interview

Q: Hi Ivan, could you give a brief introduction about yourself?


Hi Jason, I’ve been working in the investment management industry for 6 years. My first job fresh out of college was as a quant at an equities asset management fund. I was responsible for the performance analysis of the fund where I built software to automate the generation of factsheets to our clients. I also worked on developing a long short investment strategy that combines smart beta factors such as value quality and momentum with the fund’s proprietary sustainability ESG (environmental, social, governance) factors. After 3 years I moved on to work at a commodity futures hedge fund where I was the chief technologist for systematic strategies. I was responsible for building the technology for the fund’s trading system. 


I’m passionate about finance and software development and enjoy spending my free time working on coding projects. I occasionally play video games (Starcraft II) as a hobby to relax when I’m feeling stressed. My wife and I are also dog lovers. We own a female Japanese Spitz (Summer) and a male Shiba Inu (Haku) and enjoy taking them out for walks everyday.


Q: I see that you started this site called PyInvesting. Could you describe what this site is about?


PyInvesting is a backtesting platform for people to backtest and go live with their investment strategies. A backtest is a simulation of an investment strategy using historical prices which allows you to understand how your strategy would have performed in the past and helps you determine whether it is likely to be profitable for you going forward. 


All you need to do is fill in a form with your backtest details and you will be able to simulate how your strategy would have done over the past 15 years. My target audience are DIY investors like myself and financial advisers who want to adopt a data driven approach towards investing. 


There are 4 main features of the website. The first feature is the screening tool where you are able to screen for your investment universe. This involves narrowing down a list of stocks based on a certain criteria such as selecting the top 100 stocks with the largest market cap. 


The second feature is the backtester where users are able to select a specific backtest type (fundamentals, relative strength, moving average or strategic allocation) to run their simulation.


The third feature is the user’s backtest results where PyInvesting will analyze the performance of your strategy. You will be able to view how your portfolio’s net asset value (NAV) has changed over time vs its benchmark, some basic statistics, the historical positions of your strategy, and the risk return profile of each stock in your investment universe. 


The final feature is the ability to go live with your strategy. If you are happy with the backtest results and want to profit from your strategy, this feature will run your strategy daily and send you email updates with your current positions and live orders that you can trade on your personal account.

Q: Why did you start PyInvesting?


I started PyInvesting to help investors make data driven decisions. Investing is similar to a game of poker. The investor who is able to make the most number of bets with favourable odds is likely to win at this game. By using a strategy that has proven to be profitable based on backtests results, investors are able to significantly improve their odds of success. 


Unfortunately this process of simulating your investment strategy and analyzing its effectiveness is not easy to set up. Most people do not have the software skills to build a backtester and set up a platform to run a quantitative strategy. I also could not find a website or platform that allows users to backtest their own custom strategy using historical prices and fundamental data without writing a single line of code. Hence, I started PyInvesting as a solution for users to create and go live with their investment strategy. 


Q: Do you think results from backtesting is useful in helping individuals make investment decisions?


Backtesting your investment strategy is important because it confirms whether your strategy is profitable over the past 15 years. If your strategy performed well during the last 15 years, it gives you confidence to invest your hard earned money using the strategy. Conversely if the backtest shows that the strategy has lost money consistently over the last 15 years, there is no reason to expect the strategy to suddenly perform well going forward. 


The backtest also allows you to understand the risk of your strategy during different key periods in the past such as the 2008 global financial crisis and the current Covid-19 public health crisis. How much money will you expect to lose during these black swan events? This has huge implications for investors because you need to know how much risk you can afford to take before investing in any strategy. For older investors, taking on too much risk could mean significantly delaying your retirement. For younger investors who are investing on margin (borrowed money), a large drawdown could mean receiving the dreaded margin call from your stock broker. By backtesting your investment strategy, you will know how much money you can expect to lose during similar difficult periods and be able to determine how much risk you can afford to take before you actually start investing.


Q: What do you think about the quantitative finance scene in Singapore?


I think quantitative finance is growing among professional fund managers as more and more money is being invested with quant funds that are fully systematic. For retail investors however, my impression is that quantitative finance is still very much neglected. Most retail investors that I come across seem to be focusing on technical indicators, fundamental factors or the news for a particular stock but very few of them would actually run a backtest to confirm that these signals work based on historical data.  


Q: How did you get interested in the topic of investing?


I always wanted to retire early and be financially free. While there are many possible ways to achieve financial freedom such as starting your own business, I feel that investing has the best odds of success. While 90% of startups end up failing, do you know that no investor has ever lost money holding the S&P 500 for any 15 year period or longer? Even if an investor bought the S&P 500 at the very top before the 2008 crisis, he would have broke even within 15 years. The odds of success improves significantly if you have a decent quantitative strategy that beats the S&P 500. As a result, I’ve always been interested in investing and finding the most profitable investment strategy because it is my ticket to early retirement.

Q: What is your investing strategy? What is your portfolio like?


I only invest in stocks since I’m 30 this year and can afford to take on some risk. I use a combination of trend following and some smart beta factors as my main signal for selecting stocks. And of course, I use pyinvesting.com to run my live investment strategy where the website will send me email updates of the orders I need to trade on my personal account.


Q: What are your thoughts about the stock market in the near term (~3 years) given the current COVID situation?


I’m a trend follower at heart so I do not care where the stock market is going in the near term. While many gurus on social media are advising against entering the stock market during this uncertain period, I simply follow the market trend. In April when the stock market started to rebound, more and more markets switched from a down trend into an up trend. My strategy started to increase allocation to stocks and it turned out really well for me so far as markets continued to recover and is currently almost back to it’s all time high. I’m currently fully invested in stocks and will continue to do so unless the market trend changes.


Q: What are your future plans with regard to PyInvesting?


I’m receiving a lot of helpful feedback from my existing users which I use to improve the website and add new features. Recently, I’ve added fundamental data to the backtester so users can include factors such as PE ratio and return on equity to construct their signals. One of the biggest items on my list is to include stocks from other countries such as Hong Kong and London as well. I currently only include stocks from Singapore and the US. 


Q: Any key messages you like to share with the readers of this blog?


To readers who are interested in quantitative investment strategy but are clueless about this topic, we’ve included a tutorial section with YouTube videos for users that are new to the website. Also, our website has a free tier for you to try out. Do check it out at https://pyinvesting.com/tutorial/


Ending thoughts

I personally resonate with most of the points which Ivan has highlighted, especially on the part where quantitative finance still seems to be an area neglected by most retail investors. I’m also pretty sure that this would change in due time, and more retail investors would begin to realize the importance of applying quantitative investment strategy to their portfolio instead of just focusing on picking individual stocks.


Having said that, such a site like PyInvesting could help most retail investors already jumpstart their foray into quantitative finance by heavy lifting most of the technical or coding parts which you would need to do yourself otherwise. Not to forget, it has SG stocks included for backtesting and I currently struggle to find another site that allows me to do so. 


You can give it a try (https://PyInvesting.com) and judge for yourself if this is something useful for you. Backtesting with limited results is available free to everyone. If you are interested in being a paid subscriber to his site after trying to access more premium features, do remember to sign up through my link (https://pyinvesting.com/datascienceinvestor/). You will be entitled to a 20% off the subscription rates.

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