Note that month to month returns are more or less completely random at this stage. You should notice that almost all strategies have a very wide H-spread with very subtle differences - particularly in the median return value (which tends to between 1-2% for almost any given strategy).
In the next section we'll see how the differences in monthly returns will change as we start to look at the "sequence of returns" as we compound (multiply) multiple consecutive months together. In other words, the order of the monthly returns above matters far more to the success of a strategy over time than any single month return matters! (This should be obvious.)
${Plot.plot({
y: {grid: true, label: "↑ Frequency"},
x: {grid: true, label: `${sequence_length}-mo Returns`},
width: width,
facet: {
data: selectedStrategyAggregateData,
y: "strategy",
marginRight: 150,
},
marks: [
Plot.frame(),
Plot.ruleX([0]),
Plot.barY(selectedStrategyAggregateData, Plot.binX({y: "count"}, {x: "period_return", fill: "strategy", label: "count"}))
]
})}
Plot.plot({
style: 'overflow: visible;',
width: width,
y: {
grid: true,
label: `↑ Frequency (Number of Months)`,
},
x: {
grid: true,
label: `Sequence Returns (CAGR normalized)`
},
facet: {
data: selectedStrategyAggregateData,
y: "window_length",
label: "Sequence Length (Months)",
},
marks: [
Plot.ruleX([0]),
Plot.ruleY([0]),
Plot.lineY(
selectedStrategyAggregateData, Plot.binX(
{y: "count"},
{x: "period_return", stroke: "strategy", strokeWidth: 3, label: "count"}
)
),
],
})
/**
* Returns a "year+month" based integer that corresponds to the year+month, where 0 represents "January 1970".
* We assume that "January" corresponds to a value of 1 for the month parameter.
*/
function getTimeId(year, month) {
return (year-1970) * 12 + month-1;
}
/** The inverse of getMonthId */
function getMonthAndYearFromTimeId(time_id) {
return {year: Math.floor(time_id / 12) + 1970, month: (time_id % 12 + 1)};
}
test = {
const obj = getMonthAndYearFromTimeId(getTimeId(2021, 2));
return `${obj.year} == 2021? (${obj.year == 2021}) && ${obj.month} == 2 (${obj.month == 2})`;
}
MONTHS = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'];
/** Assumes 1-based month IDs to MONTHS for mapping - not zero-based! */
function getMonthFromMonthIndex(time_id) {
return MONTHS[(time_id - 1 % 12)];
}
quartile1 = V => d3.quantile(V, 0.25)
quartile3 = V => d3.quantile(V, 0.75)
iqr1 = V => Math.max(d3.min(V), quartile1(V) * 2.5 - quartile3(V) * 1.5)
iqr2 = V => Math.min(d3.max(V), quartile3(V) * 2.5 - quartile1(V) * 1.5)
selectedStrategyIds = selectedStrats.map(strat => strat.Alias);
month_intervals = [1, 3, 6, 9, 12, 18, 12*2, 12*3, 12*5]
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
