There are so many analogies that can be made between sports and trading but few are better than baseball especially when it comes to your stats. Today, we’re going to cover only one: your batting average.
In baseball, hitting a pitch that is flying at 100 miles per hour is one of the most difficult things you can do. Professional ballplayers spend thousands of hours with batting coaches honing their skills. All that time and effort is spent so they can add just a couple tenths of a percent to their batting average!
What a great lesson for all of us traders here at Apiary Fund.
In baseball, your batting average is calculated by how many “hits” you have divided by how times you’re “at bat.” So if you’re up to bat 10 times and you have 3 hits, then you have a 30% batting average - or in baseball terms .300 or sometimes it’s just reported as 300 - it all means the same thing: You have a 3 in 10 chance of hitting the ball.
Batting averages are used to predict the kind of chances a batter will get a hit each time he’s up to bat. In baseball, a batting average of 300 is really good! You might ask how is that possible? How is it possible that having only a 3 in 10 chance of hitting the ball a good thing? Shouldn’t the goal be more like 80% or better?
It’s kind of a sad that we’re raised to think of the success in terms of “school grades” where 60% is passing and anything less is a failure. Nothing could be further from the truth in baseball - or trading.
In fact, in baseball, a 400 batting average is considered off the charts good! And in trading, winning 50% of the time means that you’re doing better than 80% of the traders out there!
At Apiary, our interest is in developing successful traders and so we look at batting average in a similar way a batting coach uses it to help a player. However, while you might think a batting average would be calculated by dividing how many times you win a trade by how many time you place a trade, we look at it a bit differently.
Instead of calculating your trading batting average by dividing your total wins by your total trades, what we’re really interested in is how often you’re able to beat an index.
This is a common measurement for fund managers. Your job as a trader is to do a good job managing the money given to you. In most funds, the fund manager has a choice. Do I give the trader more funds - or - do I allocate funds to an index? The fund manager wants to know that you can manage a portfolio better than a non-managed index and so he uses a trading batting average to help him make allocation decisions. It’s a real statistics, not just a good baseball analogy.
Let me explain how it works.
Let’s suppose you use the S&P 500 as a benchmark for performance. (ie. your goal is to beat the S&P) Your trading batting average will count how often you are able to beat the S&P as a hit and divide that by your “at bats.” Where your “at bats” are all the trades you place during a trading session - usually a period of 24 hours.
So If the S&P is up 1% in a trading session and you’re up 1.1%, then you have beaten the S&P and it counts as a hit!
If the S&P is down 1% and you're up 1%, then you have another hit.
If the S&P is down 1% and you’re down .9% then, again, you beat the S&P and have another hit! (BTW, ties always go in the favor of the trader!) Even though you lost money in the trading session.
So let’s suppose you continue a few more trading sessions and end up with 6 hits (ie you beat the S&P 6 times) and lost 4, then your “batting average” would be 600 or 60%. That’s really good! Chances are good that the fund manager would allocate more money to your account to manage.
As the head trader for the Apiary Fund, instead of using the S&P as our benchmark, I use the performance of the funded traders as the baseline for calculating your trading batting average. I am interested in learning how successful a new trader in a simulation account is at managing money compared to those who are actually doing it in their live accounts! For our unique purposes, I think it’s a more fair comparison than using the S&P as our benchmark.
More than using this statistic to determine allocation. We use it to make adjustments to our training and to Beeline that improve the trading batting average for all the traders at each level. Furthermore, it may be that adding a training class on a concept earlier in the bronze hive will improve the overall batting average in the silver hive. We’re learning how to make the adjustment there are improvements in every part of the business: funding traders faster, improving the payouts when they get funded, and ultimately better performance in the fund.
Remember our purpose is to develop successful traders - not just to beat the S&P. (Fortunately, we can often do both!) The traders batting average is a good statistic to help us make better decisions. It will help you make better decisions. And it helped Justin Turner make better decisions in baseball. See our facebook video here with me, Shawn Lucas!
Good luck and happy trading!