Optimizing Trading Strategies: Mastering Effective Regime Selection
A Systematic Approach to Regime Targeting
Introduction
In the trading business it is a well known fact that we should not place trades against the general direction of the trend. There’s exceptions to this rule, of course, such as when trading mean reversion strategies or other type of strategies that require the trader to bet against the market. But the focus of this article will be momentum strategies.
This claim is especially true to traders that only rely on directionality for their trading. When the market is in agreement with the direction of your bets, your trading will feel more natural and easier. Not that trading will be easy, but will definitely decrease the degree of complexity that trading against the main narrative entails.
Have you ever traded a really strong bull market that seemed that any position you took you touched gold? That is what I call a positive regime for your strategy. It is a regime where you are in sync with the general market and not trading against it.
“There is a time to go long, a time to go short, and a time to go fishing.”
Jesse Livermore
A trader needs to flow with the market and not try to fight it. If you are going to fight the market you are better just donating your money to charity our spending it because you won’t win. The market always wins and is always right.
So there’s a few questions that arise:
How can we take advantage of these regimes?
How can we preserve the money we made during good regimes and identify when the market is shifting?
What does data show us about regimes?
If we are going to make claims we need to back it with data in order to have a better understanding. In this article it is my goal to look at the data and make it clear the importance of targeting the best regimes.
“A rising tide lifts all boats.”
Looking into the data
Let’s start by using a simple analysis such as the commonly used moving averages. Why use a moving average? Moving averages represent the average price of any numeric sequence. This data point tells you if the trend within that numeric sequence is growing, diminishing or stable. At this point we don’t know if it can be helpful but we start with the assumption that it might provide us better than random guidance on market directionality.
Since we are analysing crypto, we will use its main asset, Bitcoin, as the guide for the entire sector. In general it is a well known fact that Bitcoin’s performance does have major impact on the performance of the other assets within this sector.
The chart above shows the equity curve when buying every alt when BTC is above its 200SMA regardless of the asset price action. If BTC is over 200SMA I assumed a buy on that day.
It does require some tweaking but you can see that the general inclination of its trend it’s up. Let’s look at the opposite. What happens if you buy when BTC is below its 200SMA?
This is what happens. Completely random and negative performance. It’s just not a good bet.
With a simplistic approach you can already get an idea how to eliminate trading on the long side when BTC is below its 200SMA and focus more when the entire market is in favour of your bet.
This is statistical evidence that there is edge in knowing your regime and how to target the ones that fit your trading system the best. If you are a mainly long sided trader, trading when BTC is below its 200SMA is a bad long-term bet and you are going to have a hard time doing so because in general the market will show you negative returns.
This can also lead to better capital application when the market is right. If your capital is only put to work when you have a statistical edge of better performance, over large periods of time your capital will grow even more efficiently.
Even though that the moving average as a stand alone system is not the most advisable course of action, it does help in identifying market regimes and to completely eliminate trading when there is no edge for you.
If you were using this simple 200SMA filter, you’d have avoided most of the bear market and only returned a few weeks ago when the market started going up and favouring longs again.
Knowing when to trade is important but knowing when NOT to trade is even more important. How many traders have lost their portfolios by gambling on the long side in 2022 when they clearly had no business trading in such market?
Learn how to target regimes, expand on this theory, and your life as a trader will be much easier because you won’t ever have to trade against the market again.
I must say that obviously you won’t find a perfect regime filter, it will always have imperfections which will lead you to enter either too soon or sometimes too late on trades. A combination of factors will lead to avoid some these problems and with proper risk management regime targeting will be another powerful tool in your arsenal.
I hope you enjoyed this simple backtest.
Can you list down various methods one can try to find out these filters that help to predict the regimes