All Time Highs
>Hello World!
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This timelessness is achieved when the work remains relevant, accurate, and valuable regardless of cultural, technological, or societal changes. It is determined by the choices and elegance of logic code in the following ways:
Adaptability: The work should be flexible enough to adapt to various contexts and scenarios.
Robustness: The work should be able to handle a wide range of inputs and generate accurate and relevant outputs.
Scalability: The work should be able to handle an increasing volume and variety of inputs without compromising its quality.
Efficiency: The work should be able to generate outputs in a timely and efficient manner.
Elegance: The work should be aesthetically pleasing and easy to understand.
With that in mind, I wanted to share insights gleaned from public information that align seamlessly with A.R.S.E.E. True edges that exhibit a 1:1 correlation with performance. This is the approach investment managers should adopt to hedge against subjectivity in their fundamental theses. Or at least for positioning various entry or exit points.
Consider this scenario: a 'talking head' appears on CNBC and enthusiastically endorses an idea ‘Buy!, Buy!, Buy!’
Fast forward a year, and the idea has aged poorly.
Despite persistent claims that Gazprom is undervalued, some might attribute the situation to geopolitical uncertainty or a risk premium tied to Putin's mood swings.
Ultimately, the outcome is that the individual was mistaken, and capital was eroded due to speculative subjectivity in assessing value.
There's nothing inherently wrong with having a thesis on valuation, just as there's nothing wrong with discussing global warming.
However, tomorrow, I'm having dinner with economist Marc Chandler, and I want to understand the percentage of snow, perception, and weather to make an informed decision. It would be imprudent and frostbite-inducing to wear T-shirts and shorts solely based on my global warming thesis.
The Missing Link:
Explore a curated collection (OTW) of code snippets and formulas tailored for trading platforms and straightforward spreadsheets in this section. Aligned with the philosophy of Big Trade, we emphasize 'simple strategies for maximum market returns'. Our distinctive approach lies in how we choose to channel our focus, resulting in exceptional outcomes. It goes beyond the mere commodification of indicators and analytics.
Frequency of High’s:
The provided code is adept at calculating and visualizing the count and average of new daily highs over a specified number of days on TradingView, utilizing Pine Script. Tailor-made for trading, it serves the purpose of crafting custom indicators and trading algorithms.
Where were you while we were getting (HIGH)?
The reason why counting the frequency of highs is important is that it explains a lot about trends, probabilities, in conjunction with volatility expansion and contraction, as reflected in things like the options market. The longer the trajectory of new highs, the more conducive it is to how trends function.
We postulate that investment duration is a competitive advantage in large-cap liquid assets that function as liquidity instruments for the Street's trading desk, potentially at contracted risk during low volatility. Our approaches exploit the market structures necessary to have a functional stock market, which at the bare minimum requires an OPEN, HIGH, LOW, CLOSE, and some VOLUME. To extrapolate an edge with this understanding is limitless.
Pine Script
Here's how it works:
//@version=5
indicator("Daily High Count and Average", shorttitle="Highs Count & Avg", overlay=false)
//Input for number of days
daysBack = input.int(1000, title="Days back", minval=1)
//Find highest high and lowest low in the last 100 days
highestHigh = ta.highest(high, daysBack)
lowestLow = ta.lowest(low, daysBack)
//Check if today's high is a new daily high
newDailyHigh = (high > highestHigh[1]) ? 1 : 0
//Count number of new daily highs
count = 0
for i = 0 to daysBack - 1
count := count + newDailyHigh[i]
//Calculate average of each new high
var avg = 0.0
if newDailyHigh == 1
avg := high - open
else
avg := avg + 0.0
avg := avg / count
//Plot count of new daily highs and average
plot(count, color=color.blue, linewidth=2, title="New High Count")
plot(avg, color=color.red, linewidth=2, title="Average Highs")
Excel
Enter the number of days to consider in cell E1.
To calculate the highest high, enter the formula
=MAX(Sheet1!B2:B33)
in cell F1.To calculate the lowest low, enter the formula
=MIN(Sheet1!B2:B33)
in cell G1.To calculate the new high count, enter the formula
=SUM(IF(Sheet1!B2:B33>F1,1,0))
in cell E2. This formula uses an array calculation and may require confirmation with the Enter key or Ctrl+Shift+Enter.To calculate the average highs, enter the formula
=SUM(IF(Sheet1!B2:B33>F1,Sheet1!B2:B33-Sheet1!B1:B32,0))/E2
in cell F2. This formula also uses an array calculation and may require confirmation with the Enter key or Ctrl+Shift+Enter.
Note: Make sure to replace the range references ("B2:B33") with the actual range you want to analyze.
After completing these steps, you should see the new high count and average in cells E2 and F2, respectively. Please keep in mind that these formulas use array calculations, which can be computationally intensive and slow down your spreadsheet. Additionally, array formulas must be confirmed with Ctrl+Shift+Enter, rather than just the Enter key.</s