January 3


Should I Algo Trade, Or Just Buy and Hold?

By Kevin Davey

January 3, 2022

getting started

A subscriber at my YouTube channel left me a great comment the other day:

“Something I wonder about is: Do you compare to Buy and Hold? And if not, why do you think a system can be better than Buy and Hold? I see so many people and companies put out nice graphs with 23% profit for a certain period but the S&P made perhaps 31% the same period and so on.”
I always thought I had the smartest subscribers, and this comment is a great example of that.
Seriously - Why bother going through all the hassle of developing a trading algorithm, if you can do just as well with simple Buy and Hold?
Now, to be fair, when we are looking at Buy and Hold, we are really talking about the stock market, or stock indices, only.  Most other markets, such as energies, are not what I’d consider Buy and Hold markets.  Although, being long 30 year Treasury Bond futures was certainly a smart call:

And I know many people are permanent Gold bulls, but yikes there are some serious drawdowns involved in being always long Gold!

Certainly, most of us are stock market Buy and Holders, at least to some degree – primarily with retirement accounts, 401k’s, etc.  I think this is good – whether you are a trader or not, being a long term Buy & Hold investor with at least some of your funds is a good idea.

Over the long run (albeit with some big hiccups), Buy & Hold definitely makes sense – and is a viable strategy for most people - with the stock market:

So may be instead of trying to create an algo, it is better to just take a Buy and Hold approach.

Why would you choose an algo trading system over Buy and Hold?


With a carefully constructed and properly developed trading system, you have a chance of outperforming Buy and Hold with the same starting capital.  You can also make money in both up and down markets, which Buy and Hold can’t do.  There have been long periods of time where stocks were flat to down (take a look at the 1998 to 2003 for a poor period that was relatively recent).


The worst thing about Buy and Hold is the risk involved.  Since you are always long, you are subject to whatever bear markets come around.  A good example of this is the 2008-9 financial crisis, where the stock market dropped by half.  Buy and Hold was long during this bear market, while an algo could have been position on the short side – making the money that Buy and Hold was losing.

I measure risk through an advanced mathematical technique call Monte Carlo simulation, which I’ll show later.  With it, you can calculate the risk adjusted return of any investment or trading strategy.  I use the ratio of return divided by drawdown to calculate this.


If you have very limited time, building a trading algo is simply not for you.  Stick with Buy and Hold – you’ll probably be better off that way.
But, if you have enough time (10-20 hours per week) to dedicate to investments and trading, algo trading is worth looking into.  It is not easy, but with the right approach, some dedication and a lot effort, you can create algos that outdo Buy and Hold.


If you put 1,000 people in a room and ask them if they are better than average drivers, approximately 70% will claim that they are.  Of course, that is ridiculous – only 50% are likely better than average, and 50% are below average.

But no one wants to be average, and no one – whether it be driving ability, attractiveness or investing acumen – likes to consider themselves average!  Why?  Ego.

Same holds with trading.

Nothing beats outsmarting the market with a well-designed trading algo.  Knowing you did better than 90% of traders is a huge ego boost – assuming you can pull it off.  The problem is that it is REALLY hard to beat the competition; that is why so many traders fail. 

Being able to boast – to friends, family, co-workers, random internet strangers, whoever – it pretty neat, for sure.
With that said, let’s compare Buy and Hold to some sample algorithmic trading strategies…
Buy and Hold

Here is what constantly being long looks like over the past 7 years:

This represents buying one mini S&P contract, and holding it for the duration of the time period.  This does not include rollover costs as contracts expire, which would be approximately $100 per year, or about $700 out of $75,000 profit.

Since this is a leveraged product, you’d have to have a sufficient account size to meet minimum margin requirements.

There are some extreme drawdowns in this equity, periods of time when most people would probably have bailed in a panic (“it is going to zero!”).

So, not only is the profit important, but the risk involved is also important.  As mentioned before, I use Monte Carlo simulation.  On my calculator page, you can download my Monte Carlo simulator.

The Return/DD ratio for Buy and Hold is 1.43, which is OK (not necessarily good, but not terrible either).  But for algo systems I create, I would consider this too low.

As a comparison, let’s look at a few algos.  These algos all go long and short, and were developed using walkforward testing and other principles of the Strategy Factory.

Free Algo

If you sign up for my e-mail list, you get a fully disclosed code for a free algo for the mini S&P.  It has done pretty well, especially in 2020.

This strategy does better than Buy & Hold when looking at Monte Carlo simulation:

This free algo has a Return/DD of 1.87, about 30% better than Buy & Hold.  Even with a smaller profit, this strategy would be preferable to Buy and Hold.  Sometimes less risk outweighs more profit!
I should point out that the equity curve for this strategy is a combination of walkforward (out of sample) and real time out of sample results.  Real time performance is from July 1, 2019. I first started giving this away on my website in January 2020.

Here is a comparison of the equity curves for these first two strategies. You can see that the Free algo avoids some of the terrible drawdown that Buy & Hold experiences (although it does have a few significant drawdowns of its own).

Sys 277 Algo

Here is another algo for the mini S&P.

Here is the equity curve for 1 contract. I show equity curves later with trading 2 contracts, so it is easier to compare equity curves, since the overall Net Profit is comparable.

In general, this strategy is smoother than the first two, but that initial drawdown between trades 10 and 15 causes the CAGR/Max DD stats to be lower.

That is one reason I like Monte Carlo analysis – it incorporates not just the worst drawdown, but ALL the drawdowns, in its analysis.

The Monte Carlo return/dd for this strategy is 2.09, which suggests it is better than the free algo, and better than Buy & Hold, on a risk adjusted basis. Intuitively, you can see that by the smoother equity curve shown below.

The equity curve for this strategy is a combination of walkforward (out of sample) and real time out of sample. Real time performance is from August 2016. The strategy was developed with more walkforward data than that shown – I cut off some of the original walkforward years to make all trading strategies in this study have a consistent start date of January 1, 2014.

As previously mentioned, excluding the initial drawdown, the equity curve for this strategy is smoother than the first two.

Strategy Factory Student Algo

I am a big fan of the adage “if it looks too good to be true, it probably is.” That is certainly what I thought when I saw this strategy, created by J., a Strategy Factory trader/student based in the UK.

I’ve been watching this strategy live for about 18 months now, and it has held up nicely through Covid and the severe downturn in Buy & Hold. There is nothing like live monitoring to really judge a strategy (of course, I consider live real money trading to also be “live monitoring.”)

This strategy does much, much better than Buy & Hold when looking at Monte Carlo simulation. Really, unbelievably well!

To compare the equity curve of this strategy with the other 3 strategies, I am trading 3 MES contracts, which is 30% of 1 mini S&P contract. So, this strategy hits roughly the same profit as the others, with 1/3 the trade size!

Overall Hypothetical Results

So clearly, Buy & Hold can be beat with a trading algorithm - and that is pretty awesome!

The question is, do you have the time, desire, skills and education to create a trading strategy that will beat Buy & Hold?

  •  Kevin J. Davey of KJ Trading Systems
  • Kevin Davey

    About the author

    Kevin Davey is a professional trader and a top performing systems developer. Kevin is the author of “Building Algorithmic Trading Systems: A Trader's Journey From Data Mining to Monte Carlo Simulation to Live Trading” (Wiley Trading, 2014.) . He generated triple digit annual returns 148 percent, 107 percent, and 112 percent in three consecutive World Cup of Futures Trading Championships® using algorithmic trading systems.

    His web site, www.kjtradingsystems.com, provides trading mentoring, trading signals, and free trading videos and articles. He writes extensively in industry publications such as Futures Magazine and Active Trader and was featured as a “Market Master” in the book The Universal Principles of Successful Trading by Brent Penfold (Wiley, 2010).
    Active in social media, Kevin has over 15,000 Twitter followers. An aerospace engineer and MBA by background, he has been an independent trader for over 20 years. Kevin continues to trade full time and develop algorithmic trading strategies.

  • Thanks for sharing this – I’ve long thought Buy & Hold was a great way to go, but it is nice to realize that I can do better.

  • {"email":"Email address invalid","url":"Website address invalid","required":"Required field missing"}

    Learn To Code & Build Strategies
    Using EasyLanguage.