FAQ Automated Trading Magazine
– What’s the difference between the monthly and the yearly subscription?
The monthly subscription gives you access to our current month issue and future issues as long as you have an active subscription. You can also download each publication as a pdf file to your computer.
The yearly subscription gives you full access to monthly issues, all back issues that we have published so far downloadable as pdf, 24/7 priority support for quantitative research related questions, complete code repository , market patterns and scenario analysis.
– What time frames are the strategies covering?
Our research covers long term investing strategies that cover less frequent rebalancing and can be traded manually. We backtest long term asset allocation for example the Meb Faber model and other trend following models.
Our mid term strategy research covers trades that last for up to several days or sometimes weeks before exiting the position. An example of such a strategy is the use of mean standard deviation bands.
Short term strategies that we include in our magazine are automated intraday strategies. We come up with all sort of ideas whether we backtest a pairs trading strategy or some momentum analyzing volume patterns.
– What kind of strategies are included in your research?
The list is long and we always strive to come up with some new and unique idea. Here is a list of some of the strategies that we have backtested so far:
- Seasonality Trading
- Volume Effect
- Volatility Trading
- Trend Following
- Pairs Trading
- Sentiment Analysis
- Machine Learning
- Crypto Trading
- Spread Trades
- Mean Reversion
- Sector Rotation
– Which coding languages do you use for backtesting your ideas?
We use Python, R and EasyLanguage.
Python is a high-level programming language that is more deployed in machine learning and for automation of trading systems. Python has got exclusive library functions that facilitate ease of coding the algorithmic trading strategies.
R is a language of choice for many data scientists and statisticians at every level. It has a large and rapidly growing community and more than 10,000 contributed packages as of the time of writing. Packages include software suites for data management, machine learning, graphics and plotting, and much more. Installing a new package takes a few seconds and opens up a ton of capabilities within R. If a trader wants to experiment he is not required to have prior experience with R and it is generally speaking easier to learn then python. Here is an interesting article that can get you going quickly.
EasyLanguage is a proprietary programming language that was developed by TradeStation and built into its electronic trading platform. It is used to create custom indicators for financial charts and also to create algorithmic trading strategies for the markets. External DLL’s can be referenced using EasyLanguage which greatly extends its functionality. It can be described as the swiss army knife for backtesting. However, if you want to become more serious testing asset allocation models and working with very large data sets then there will be no way around Python.
– Do you offer code for quantconnect?
The short answer, yes.
– Do you offer historical data?
We are not a historical data provider, but here is a vendor list you can choose from.
– What is the What-If Market Analysis?
As a quant you should always test the outer edges of knowledge, to validate or debunk current assumptions.
Our analysis uses decision-logic to quantify market behavior after a higher monthly close or lower monthly close. It tests for a condition and then the results of a specific trade taken because of that condition. For example we ask questions like:
- If a security closes lower in any given month A than in the previous month, what has been the potential for the market to trade higher than month A’s low in either of the two subsequent months?
We do not recommend you to take any trades the purpose of this analysis is rather to spur further fought and as a starting point in the strategy development process. Some of our subscribers might want to integrate these findings in their trading system or others might want to investigate these patterns and the relationship with other markets further.
The patterns can be as simple as buying security A on day x and selling it on day y, we then backtest all possible combinations and also search for explanations why this might the case.
For example, if we look at the U.S. Treasury Bond futures contract we have found a huge profit factor and consistent pattern with a 93.80% winning rate. On a 15 year cycle this trade gave us a win 15 out of 16 times entering long on trading day 13 in August of every year and exiting the trade on trading day 17 on that same month. This gives us a return of 270% with a very low downside deviation from the entry price. In simple words this trade goes up almost straight away.
The patterns we research can be viewed as highlight markers pinpointing you where you should take a closer look at. For the pattern to repeat the setup prior to trade entry must be similar to previous years. So, let’s assume that every time this pattern occurred the month of July was positive as well and the S&P 500 Index was down by 2% or more. In that case you have a high probability of this pattern repeating again and it is something you can trade on.
We also include other patterns related to the time series but using different indicators. An example for this would be the COT report that we analyzed for the Wheat futures market. The results look promising. We can see returns of up to 250%.
Setup: When large speculator shorts > large speculator longs enter on the 8th trading day after this signal occurred. With a profit target of $1600 and stop loss of $1200 we have a return of 248.8% and a profit factor of 4.34. The winning percentage for this strategy is 77.8%. With a stop loss of $2000 and profit target of $1000 we have a winning percentage of 88.9 % (16 winners and 2 losers). The entry rule is large spec. shorts > large spec longs enter long on 6th trading day after trading signal occurrence.
– Is this publication for me and vice versa?
Take us for a test drive and read our sample issues. Sign up for our newsletter and read our blog posts. Browse through a ton of free resources we are offering to make your journey easier in designing an alpha generating trading system .
When you’re ready, we’ll welcome you with open arms into the select circle of subscribers. To say no one in the financial publishing industry is working harder to educate and empower active traders would be an overstatement. However, we definitely say that we are working very hard to deliver you the content you can benefit the most from. At the end of the day we all pursue the same goal: generate alpha with our strategy. Our research aims to bring you one big step closer to this goal.
– How do I get started with algorithmic trading?
Well, there is not straight forward answer to. Anyway, here is guideline for you to start with.
We highly recommend to work your way through our reading list. Master the theoretical background and get some valuable input from publications like the one we are offering and read some good research papers. Hone your knowledge on statistics and money management (very important).
Next you learn a programming language or another tool that can help you with your research and backtests. You should start learning Python as this programming language is the most popular one among the quant community and their are plenty of resources. You should become sophisticated enough to code and test almost any strategy or idea that you come across.
Finally, stay focused. If you have an idea stick to it and run extensive tests before reaching a conclusion. Do not jump from one idea to the next one. This will lead you nowhere. Again, focus on a particular market or idea and disassemble it into all its individual parts.
– Do you offer any support?
Yes! It is something that sets us apart from all other publications. We are here for you 24/7 to help you with your algorithmic trading/quantitative research related questions. This service is available to our premium members (yearly subscribers)
– Can I write an article for your blog or publication?
Yes, we are open to both options. Contact us for more details. Our best writers even get compensated for their research. More on it here.
– Is your publication worth the money?
Years of experience are distilled into our publication of carefully crafted and well-tested tutorials. They are a bargain for someone looking to rapidly build skills in the field of algorithmic trading. The ideas, code and research included in our subscription will definitely give you the input in the right direction.
– What forms of payment do you accept?
We use Stripe for Credit Card and PayPal services to support secure and encrypted payment processing on our website.
We accept bank issued debit and credit cards: Visa, MasterCard, American Express, Discover, JCB, and Diners Club.
– How do I change my password and e-mail address?
There is an option to change your password and or e-mail address in your account settings.
– How do I find out when my subscription ends?
Within you client portal you can check the current status of your subscription.
– How can I get support?
The support email is send to you when signing up for an account. If you forget it contact us directly via the contact form.