💬Introduction: Today we are comparing the Dow Jones, NASDAQ, and the S&P by their annual performance to show how our open source indicator "Alpha Performance of Period" (PoP) can be used and why the results are useful. We will also look at other markets later in the writeup to see how they compare and to get a sense of which markets provide the best risk-to-reward and ROI.
The idea here is to compare highly correlated markets over time to see which of these markets preforms the best overall represented by a period chosen by the user. This will help tell us which of these indexes is the best/worst to trade/invest with on average.
For this article we will assume "best" equates to "best for long positions", but the indicator could be used for other purposes such as best shorting opportunities (largest drawdown amounts).
Comparing these indexes shows that the NASDAQ has historically outperformed, while the DOW underperformed, and the S&P has been somewhere in the middle since the tech bubble on a year-over-year basis.
You can also see this on the chart as represented by the indicator's metrics contained within its label, but we will summarize it below:
NOTE: The figures below are rounded up to the nearest .01%, see charts for exact %'s.
Equity Indices Total Annual performance results: (main chart) (Jan. 2000 - present)
SPX = +111.79% NDX = +156.10% DJI = +117.65%
Now let's look at the quarterly and monthly performance:
Equity Indices Total Quarterly performance results: (Jan. 2000 - present)
SPX = +104.57% NDX = +160.75% DJI = +111.65%
Equity Indices Total Monthly performance results: (Jan. 2000 - present)
SPX = +91.22% NDX = +125.274% DJI = +101.68%
Equities Summary: While the NASDAQ has had periods of underperformance (for example the dot com bubble burst), on each of the charts you can see that not only has the NASDAQ outperformed (and the Dow underperformed) over time, the NASDAQ has also generally outperformed during each different period measurement. We won't do the math for each period here as that's the main purpose of this indicator, but you can apply the indicator on your own chart and take a look at it yourself.
The main takeaways for us are this: 1. [As a swing trader focused on long positions] You are better off trading and/or holding the NASDAQ when compared to the 3 main indexes. 2. You are better off trading the S&P than the DJI. 3. The performance of the NASDAQ during COVID isn't an anomaly, and it doesn't necessarily indicate a tech bubble, outperformance in a specific period and overtime is the norm with this index.
Now that you see how this works on the indexes, let's showcase how it can work for other markets.
Rare Earth Metals Summary: As you can see, despite the general public's love of Gold, Palladium vastly outperforms it. Meanwhile, we can confirm Silver underperforms. Many people wouldn't suspect Palladium was superior, but we now know from the resulting data (Hooray!).
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FOREX~
Main Forex USD pairs Total Annual performance results: (Jan. 2000 - present)
EURUSD = 19.48% GBPUSD = -9.03% AUDUSD = 23.90%
Main Forex USD pairs Total Quarterly performance results: (Jan. 2000 - present)
EURUSD = 20.75% GBPUSD = -16.53% AUDUSD = 20.98%
Main Forex USD pairs Total Monthly performance results: (Jan. 2000 - present)
EURUSD = 19.57% GBPUSD = -16.70% AUDUSD = 21.93%
Forex Summary: As you can see against a USD base-pair, GBP is the worst performing from the 2000's by all periods. One might assume the more popular EUR pair preformed better than for example AUD, but the reality is AUD takes the cake and preformed better than both EUR and USD by each period over time.
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CRYPTOCURRENCY~
Main Crypto USD(T) pairs Total Annual performance results: (Jan. 2017 - present)
Main Crypto USD(T) pairs Total Quarterly performance results: (Jan. 2017 - present)
BLX = 504.60% ETHUSDT = 1124.81% LTCUSD = 824.44%
Main Crypto USD(T) pairs Total Monthly performance results: (Jan. 2017 - present)
BLX = 357.63% ETHUSDT = 739.39% LTCUSD = 530.67%
Crypto Summary: Crypto has the largest period losses, but it also has the largest period gains (by far). Of all the crypto pairs, ETH offers the best ROI. Interestingly, ETH offers the best ROI of all markets mentioned in this article as well (although it also has the biggest losses and highest risk associated with its uptrends). Some might find it odd that Litecoin outperforms Bitcoin (although like with ETH, the drawdown is notably more intense).
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[I]Conclusion:[/I] Use "Alpha Performance of Period" (PoP) to compare markets for what is best suited to your portfolio depending on your individual risk appetite. It is meant to be used on highly correlated markets, but as you can see you can also compare different sets of markets together to get a sense of which offers the best risk-to-reward, ROI, etc. This tool thus has many uses related to figuring out which markets you want to trade based on historical data and offers a simple way to quickly compare past performance. Hope you guys enjoy it! :D
Really nice to see a fully impartial write-up on an analytics tool. It's great to see the breakdown and explanation applied across several markets including Crypto which is my "main" area of interest.
Just curious to know if you have any content on order flow footprint charts?
Really interested (from a programmer point of view) how these work without having a site trying to "sell" me the tool as I'd love to put one together in a Python package.
Currently building my own little micro-bot for trading and impartial takes on analytic tools are really useful to me.
Thanks for the great content!
AlphaBotSystem
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@phoenix1of1, Thanks for the in-depth comment, with how much time this took I appreciate it!
We currently showcase order flow heatmapping on Discord via our bots TradingLite Integration. I can also suggest looking into BookmapDOTcom as well at least for an unincorporated free option before you get your python package built.
derberry
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+1
oshojha
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this is super helpful. especially since I dabble in both tech stocks and crypto which have very correlated choices. one of the reasons i have eschewed portfolio diversification is that in these sectors in particular you're better off choosing one position to size up and this has helped put that in context.
Just curious to know if you have any content on order flow footprint charts?
Really interested (from a programmer point of view) how these work without having a site trying to "sell" me the tool as I'd love to put one together in a Python package.
Currently building my own little micro-bot for trading and impartial takes on analytic tools are really useful to me.
Thanks for the great content!