PyInvesting

Helping investors beat the market.


Ivann Fok
1 week, 2 days ago · 228 Views

WRITTEN BY

Ivann Fok

Ivan is the founder of PyInvesting.com. He is passionate about technology and finance and has worked as a software developer at a hedge fund where he was responsible for building the fund's trading system. He hopes that PyInvesting will help investors adopt a data driven approach to investing and support them in their journey towards financial freedom.


Top 3 factors that determine which investment strategy is right for you
When it comes to investing, every investor has their own personal tastes and preferences. Investors approaching retirement tend to be more conservative and prefer strategies with lower risks while young working adults usually have a higher risk appetite and are willing to stomach some volatility in exchange for higher returns. Whichever strategy you choose, it is important that you are comfortable with the risk it entails so that you are able to stick to your strategy and avoid making emotional decisions.  There are three key factors that determine which investment strategy is right for you.  Risk tolerance Expected returns Effort required to implement the strategy Risk tolerance The first factor is your risk tolerance which is the amount of risk you are willing to take on in exchange for a return on your investment. Generally, investment strategies with higher risks should be rewarded with higher returns. You should choose an investment strategy with a target risk that you are comfortable with and will not cause you to lose sleep at night. Many investors are often attracted to the high returns from an investment strategy. However when markets get volatile, and they start seeing huge fluctuations in their portfolio’s value, they are unable to stick to the plan and get shaken out of their positions. They end up panic selling and crystalizing huge losses on their portfolio.  One way you can measure the risk of your strategy is to backtest your investment strategy and find out the maximum drawdown of your strategy. The maximum drawdown tells us what is the maximum amount of money you can lose on your portfolio during a crisis. For example, during the 2008 crisis, the S&P 500 lost 55% from it’s peak value in October 2007 to March 2009.  You need to ask yourself how much are you prepared to lose if markets were to crash and are you willing to stay the course. Retirees who need to gradually withdraw their funds for their daily expenses should only invest a small percentage of their wealth that they can afford to lose. Young working adults on the other hand should take on more risk because they have time on their side to ride out any market crashes.  For me personally at 30 years old, I’m comfortable with a 50% drawdown on my portfolio if a black swan event such as the 2008 global financial crisis were to happen again. When I’m 50 years old, I would be comfortable with a 30% drawdown on my portfolio.  Expected Returns The second factor that determines your investment strategy is expected returns. How quickly do you need your money to grow to achieve your financial goals?  The math shows that if you save $50 a day for 20 years at a 10% rate of return, you will end up with over a million dollars. However, if your investment strategy is expected to make 5% a year, it is extremely unlikely that you will hit a million dollars at the same saving rate. This could mean being able to free yourself from the corporate rat race a few years earlier and being able to provide a significantly higher standard of living for your loved ones.  You can measure the expected returns of your strategy by backtesting it using historical prices and calculating the annualized returns. Check out this tutorial video below to find out how you can analyze the performance of your investment strategy.   Once you get the annualized returns from your backtested investment strategy as shown below, you can plug that value into the CPF retirement calculator to find out whether you are able to hit your financial goals. Effort Required  The third factor is how much effort you are willing to spend on managing your investments. Some strategies require less work to maintain than others and would appeal to more hands off investors. It is important to choose a strategy that fits the amount of effort you are willing to commit to implement the strategy. This is because if you choose a strategy that requires more time to implement than you are willing to commit, you could end up finding it a chore to manage your portfolio and eventually give up on following your strategy. For investors who are not willing to spend a lot of time managing their portfolio, long term strategies such as the Ray Dalio all weather strategy, would be a great fit. This strategy involves allocating a fixed percentage of your portfolio in specific asset classes such as stocks, bonds, REITs and commodities and rebalancing the portfolio once a year to the portfolio’s target allocation. Investors that are able to spend more time managing their portfolios are able to adopt more active strategies such as a moving average strategy where they monitor their positions on a weekly basis. Note that actively monitoring your positions does not necessarily mean you are trading every week. The investor could simply be frequently checking each position more frequently but only opportunistically trading a small number of stocks in the portfolio if they change their buy or sell conviction.  Backtest your investment strategy When choosing our investment strategy, it is important to consider our risk tolerance, our expected return and the amount of effort we are willing to spend on managing our portfolio. Having the right investment strategy will allow us to stay invested even when markets are volatile and help us achieve our financial goals.  Backtesting your investment strategy will allow you to estimate the strategies expected risk and return, and understand the amount of effort required to manage your portfolio. While most portfolio backtesting methods involve expertise in programming and statistics, we can use platforms such as PyInvesting.com to simply fill in a form and create a backtest. The website will run your investment strategy using live prices and send you an email with the orders you need to trade on your personal account.  Stay the course, and may the odds be in your favor.
Ivann Fok · 6 days, 4 hours ago
Here's Why Every Investor Should Backtest Their Investment Strategy
What is Backtesting? Backtesting is the process of simulating an investment strategy using historical prices to test how well the strategy would have done in the past. Why is Backtesting Important? Investment backtesting allows investors to analyze the historical behaviour of an investment strategy and determine how profitable the strategy is. If the backtest results show that a strategy has high returns and low risk, investors will have greater confidence of going live with the strategy. The main idea is that any investment strategy that has performed well in the past is likely to perform well going forward. Conversely if a backtest on a particular investment strategy shows poor performance, the strategy should be rejected because if it performs poorly in the past, it is unlikely to perform well in the future.  Backtesting investment strategies also helps investors understand their strategy’s behaviour during different key periods in history such as the global financial crisis and the Covid-19 public health crisis. They will know how much money they can expect to lose during these black swan events. 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 our investment strategy, we are able to know exactly how much money we will lose during these difficult periods so we are able to determine how much risk we can afford to take before we actually start investing. What kind of investment strategies can be backtested? Any strategy that can be expressed as a set of rules can be backtested. For example, a value investor might be interested in a strategy that selects 10 stocks with the lowest price to earnings ratio every year. Similarly an investor that relies on technical analysis might look at buying a stock when its fast moving average crosses above its slow moving average.These strategies all follow a consistent set of rules that can be simulated using historical data. The advantage of rules based investing is that it removes emotions from the picture. Every decision to buy or sell a stock is driven completely based on logic. This prevents investors from making behavioural mistakes such as panic selling or buying due to the fear of missing out. How do we create a realistic backtest? As the purpose of investment strategy backtesting is to find out how effective an investment strategy is, it is important to ensure that our backtest is as realistic as possible. This prevents us from creating backtests that look very attractive on paper but yet perform poorly during live trading. There are a few ways to achieve a more realistic backtest. 1. Choose a large investment universe of at least 100 stocks  A large universe will allow your strategy to select from a wide variety of stocks. This is important because it allows us to test whether the strategy is able to pick winning stocks from a large basket of stocks. A great strategy will be able to differentiate between winners and losers. However, if we restrict our investment universe to a small number of stocks, there are not many stocks for the strategy to select from. This makes it difficult for us to confirm whether a strategy works because both a great and a poor strategy are likely to pick the same stocks when there are so few to choose from. 2. Include at least 20 stocks in your portfolio Having 20 stocks equally weighted in your portfolio will reduce your portfolio’s concentration risk. This means that no single stock will have a huge impact on your portfolio’s performance which allows us to reduce the chance that your strategy just happened to be lucky and picked a winning stock. For example, if our strategy only picked Tesla and was 100% invested, it would have made huge returns over the last few months. However I would not be convinced that the strategy works because it could have picked another stock out of sheer randomness. It is much harder for a strategy to pick 20 winning stocks than a single winning stock. By ensuring that our strategy holds a diversified portfolio, we can confirm that the strategy is able to consistently pick multiple winning stocks and include them in a high sharpe ratio basket of stocks. 3. Choose a sufficiently long backtest period Ideally, your backtest period should be at least 15 years. This allows us to observe how the strategy performs over multiple economic regimes. For example, by including the 2008 financial crisis which happened 12 years ago, we can understand how much money our strategy would lose during a crisis. This allows us to manage the risk of our portfolio. For older investors that are retiring soon, this means deciding how much money they should invest in the market such that even if a crisis were to happen, they would have enough cash savings to retire as planned. For younger investors investing with leverage, it could mean understanding how much money they can afford to lose during a crisis without being hit by a margin call.  4. Include transaction cost The backtest should include your broker’s transaction cost. Whenever an investor buys or sells stocks, they would incur transaction cost that is paid to the broker. Over time as the number of transactions increase, your transaction cost will increase which would have a significant impact on your strategy’s returns. Moreover, strategies that have high turnovers and make a lot of trades will incur higher transaction costs than strategies that have low turnovers. Hence it is important to include transaction cost so we get a realistic idea of how much money our strategy will make during live trading.  How do we create a backtest? While backtesting requires a great deal of calculations, there are multiple websites we can use to create a backtest easily without writing a single line of code. These platforms include https://www.portfoliovisualizer.com/, https://www.etfreplay.com/, https://www.tradingview.com/ and https://pyinvesting.com/. In the table below, I compare the different backtesting platforms and weigh the pros and cons. To be able to backtest a portfolio of different stocks, all platforms except TradingView provide this functionality. TradingView is used more for backtesting a single stock and does not allow users to analyze the performance of a portfolio with multiple stocks. In terms of allowing users to backtest different kinds of strategies, Portfolio Visualizer is the only platform that lacks options. They only allow users to run an allocation backtest where the user has to specify the weights of each stock in the portfolio. All other platforms allow users to choose from multiple types of backtests such as relative strength and moving average backtests.  Regarding stock coverage, all platforms have extensive coverage across multiple exchanges except ETF Replay which is limited to ETFs and a handful of US stocks. If you invest in the Singapore market, unfortunately this platform will not be very helpful as it does not include Singapore stocks.  Among the different platforms, only PyInvesting provides fundamental data such as price to earnings ratio, free cash flow, return on equity, profit growth and more. These fundamental data are obtained from the company’s financial statements going as far back as 15 years. For investors that rely on fundamental data, this is currently the only platform that allows you to create a backtest using fundamental data without writing a single line of code. All other backtesting platforms above only provide technical indicators based on price or volume data which is not suitable for most long term investors. Finally, only PyInvesting allows users to go live with their backtest and create their own personal robo adviser on the cloud. The website will send users an email to update them on their live positions and orders which they can trade on their personal account.  Final Thoughts Every investor should backtest their investment strategy because it allows them to analyze the historical behaviour of their investment strategy and determine how effective it is. Backtesting also helps investors understand their strategy’s behaviour during different key periods in history which allows them to manage their risk. Finally backtesting allows investors to follow a logical set of rules which removes emotion from the picture and helps them make data driven decisions.
Ivann Fok · 3 weeks, 5 days ago
Ivann Fok · 1 month ago
Beating the S&P 500 by selecting US stocks with strong fundamentals
investing.com Most long term investors rely on fundamental data to decide which stocks they should include in their portfolios. Fundamental data can be obtained from financial statements such as the company’s balance sheet, income statement and cash flow statement. These reports provide valuable insights into the company’s financial health, profitability and growth. These are key fundamental factors that investors should look out for as they are highly correlated to the stocks performance.  However, measuring these fundamental factors is a tedious process. Investors need to comb through hundreds of financial reports to search for these factors and then combine these different factors together to rank the available stocks. Fortunately with the help of technology, this whole process has been simplified for us. Here is how you can go live and profit from a fundamental strategy for US stocks.  Introducing PyInvesting.com PyInvesting is a website that provides financial data and backtesting tools to help you go live with your own investment strategies. Think of it as a platform where you can build your own personal robo adviser that helps you comb through hundreds of financial reports and tells you which stocks you should buy or sell. We are going to use PyInvesting to create our fundamental strategy for US stocks. Let’s go! First go to https://pyinvesting.com/backtest/fundamentals/ where we will be creating a fundamental backtest. A backtest is a simulation of our investment strategy using historical data. If the simulation results are poor where the strategy significantly underperformed its benchmark, it confirms that the strategy does not work. In contrast, if the strategy significantly outperforms its benchmark, it gives us confidence that it’s likely to perform well going forward. The backtest also tells us what stocks we should be holding in our portfolio so we know which stocks to buy or sell when we go live with our strategy.  Click on the “Select your stocks” button which opens a window to select stocks for your fundamentals backtest. Under template portfolios, click on “S&P 500” to select s&p 500 stocks from the index. The default benchmark is the SPDR S&P 500 Index (which passive investors can use to invest in the s&p 500) where we will compare the historical performance of our fundamentals investment strategy against the s&p 500 historical prices. Financial Health We want to select companies with a healthy balance sheet and a low debt to equity ratio because these companies have strong abilities to repay their creditors. Because these companies have relatively low leverage, these companies are usually quite resilient and are able to survive through tough periods without going bankrupt. As a result, investors holding these stocks tend to lose less money during a crisis because these stocks are well positioned to weather a storm.  Profitability Next, we want to select companies that are highly profitable, and have a high return on equity. A high return on equity implies that the company’s management is efficient in using investment financing to grow their business and is hence able to provide better returns to investors. A low return on equity implies that the company could be mismanaged where the management is investing in unproductive assets. Return on equity is also a measure of how efficient the company is using its resources. A high return on equity could mean that the company is increasing its profits with a relatively low amount of capital.  Growth Finally, we want to select growth companies whose earnings increase at a much faster rate than the overall economy. These companies have high profit growth and tend to reinvest their earnings into profitable areas of their business. They usually do not pay dividends and choose to reinvest profits to further grow their business. Most growth companies such as Tesla, Google, and Amazon are in the technology sector where they are constantly investing in innovative ideas and expanding into new businesses. Growth companies are able to provide huge returns to investors by focusing on revenue growth and maintaining leadership in their industry. Constructing our portfolio strategy To select stocks with strong financial health, profitability and growth, we are going to select 3 factors shown below. Stocks with the highest return on equity, highest profit growth and lowest debt to equity. These 3 factors are equally weighted at 33% each. All other factors in the table are allocated a weight of 0%. The website will automatically combine these 3 factors for you using a z-scoring approach where the factors are normalized using the mean and volatility. Subsequently, we need to decide how many stocks to hold in the portfolio. I decided to hold 20 equally weighted stocks in my portfolio to avoid concentration risks. Every month, the stocks from the S&P 500 are ranked based on these 3 fundamental factors and the top 20 stocks are selected to form an equal weighted portfolio.  Performance The results show that our fundamental strategy for US stocks significantly outperforms the S&P 500 benchmark with an annualized return of 17.8% vs 9.0% since 2006. The strategy also has a higher Sharpe Ratio of 0.73 vs the S&P 500 which has a Sharpe Ratio of 0.37 implying that the strategy has higher risk adjusted returns. While the strategy has a higher volatility than the S&P 500, it has a lower semi deviation than the S&P 500. This means that the strategy has lower downside volatility and higher upside volatility. The max drawdown of the strategy is also significantly lower than the S&P 500 where it lost 46% during the 2008 crisis vs the S&P 500 which lost 55.2%.  Overall, this backtest confirms that the fundamental strategy for US stocks works where if we select stocks with the highest return on equity, highest profit growth and lowest debt to equity ratio, we can expect to outperform the S&P 500 by 8.8% every year. This strategy is suitable for long term fundamental investors who can afford to take on some market risk in exchange for significantly higher returns.   The website also shows the current positions in the portfolio which users can trade on their own personal account. Subscribers have the option of “going live” with their portfolios where they will receive daily email updates to notify them if their strategy decides to make a trade. I’ve added a link below for users to check out the backtest results from this strategy.  https://pyinvesting.com/invest/results/ab3d20df353143a7a41cdb5ab05e83c2 Do consider signing up for a free account with PyInvesting to receive future updates. In my next article, I will be explaining how to use the relative strength backtest. Stay tuned and I’ll see you guys next time!
Ivann Fok · 1 month, 1 week ago