- The portfolio delivers ~11.5% annualized return with ~8.5% annualized volatility over the observed period.
- Correlations show a cluster of assets that often move together, balanced by at least one asset that moves differently (low or slightly negative correlation)—this provides some diversification but also reveals areas of concentration risk.
- Allocation charts suggest that how weights evolve over time (rebalancing vs drift) is a key driver of the portfolio’s risk/return behavior.
What it shows
- Each asset’s price series is re-scaled so they all start at the same value (e.g., 100). From that common starting line, we can compare relative growth fairly across assets.
How to read it
- If a line ends at 130, that asset gained +30% since the start; 90 means −10%.
- Steeper, choppier lines → potentially higher risk (more ups and downs).
- Crossovers (one line overtaking another) show changes in leadership over time.
What it tells us here
- You can quickly see which asset(s) outperformed over the full period, and which lagged.
- Look for regime shifts (e.g., an asset trending up that later flattens or declines). These often map to macro events or company news.
What it shows
- The day-to-day % change in each asset’s price.
How to read it
- The average daily return (mean) hints at typical gain per day.
- The standard deviation of daily returns measures daily volatility—how “bouncy” the asset is.
- Outliers (very large up/down days) flag events worth investigating.
What it tells us here
- Which assets are steady vs. jumpy.
- Days with unusually large moves help explain short-term portfolio swings and can guide risk controls (position limits, hedges).
What it shows
- How similarly pairs of assets move each day (−1 to +1).
How to read it
- +1: move together; −1: move in opposite directions; 0: unrelated.
- Clusters of high positive correlation indicate concentration (many eggs in one behavioral basket).
- Low/negative correlations are diversifiers that can soften drawdowns.
What it tells us here
- The notebook shows, for example, Asset5 has slight negative correlation with Asset1 (~−0.11)—that’s a mild hedge.
- Asset5 is moderately positively correlated with Asset2 (~0.59), Asset3 (~0.56), and Asset4 (~0.42)—a cluster that can amplify moves (good in rallies, painful in sell-offs).
- Net: some diversification exists, but cluster risk is present.
What it shows
- Each point is a day. X = returns of Asset X, Y = returns of Asset Y.
How to read it
- Upward slanted, tight band → strong positive correlation (move together).
- Downward slanted band → negative correlation (hedge).
- Round, diffuse cloud → low/near-zero correlation (good diversifier).
- Outliers far from the cloud = shock days worth noting.
What it tells us here
- Confirms visually what the correlation number says, and highlights outlier days that drive risk.
What it shows
- A stacked area where each band is an asset’s weight in the portfolio (weights sum to ~100% per day).
How to read it
- Thicker band = larger allocation.
- Changing thickness over time shows rebalancing or tactical tilts.
- Drift (a band keeps getting thicker because it outperforms) can raise risk unintentionally.
Key takeaway here
- Check whether weights stay near targets (disciplined) or drift (potentially riskier). Regular rebalancing usually improves risk control.
How it’s built
- Compute daily portfolio return = sum(weights × asset daily returns).
- Convert to growth of 1: (1 + rₜ).cumprod().
How to read it
- Rising line = wealth growth; flat = stagnation; drawdowns = peak-to-trough declines.
- Look for speed of recovery after drawdowns (resilience).
What it tells us here
- You can see the journey, not just the destination: whether returns came steadily or in bursts and how tough the drawdowns were.
Results in your notebook
- Annualized Return ≈ 11.5%
- Annualized Volatility ≈ 8.5%
How they’re calculated (261 trading days/year)
- Annualized Return: take total growth
∏(1+rt), raise to 261/n, minus 1. - Annualized Volatility: std dev of daily returns × √261.
Why they matter
- Return answers, “How much did we make, annualized?”
- Volatility answers, “How bumpy was the ride?”
- Together they describe risk-adjusted quality (e.g., return/vol ≈ 1.35 here—solid for a diversified mix).
What it shows
- The same weight idea but grouped (e.g., Equity, Fixed Income, Alternatives).
How it’s created
- Use the info table to map each asset → family, sum weights by family per day, and plot as a stacked area.
Why it matters
- Gives a top-down view of risk buckets, helps check policy bands (e.g., 60/40), and reveals drift or tactical tilts at the family level.
- Return (~11.5% annualized) is healthy for a multi-asset portfolio.
- Volatility (~8.5% annualized) is moderate. Combined, this is a solid risk-return profile for the period.
- You have useful diversification (e.g., Asset1 vs Asset5 shows slight negative link),
- but also a correlated cluster (Asset2/3/4/5) that can concentrate risk in certain regimes.
- The weights (and family weights) over time will reveal if you rebalance (good risk control) or drift (risk can creep up). If drift is visible, codify a rebalancing rule.
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Manage cluster risk
- Cap exposures where assets are moderately/highly correlated (e.g., Asset2/3/4/5).
- Increase allocations to lower/negatively correlated assets to stabilize drawdowns.
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Enforce rebalancing
- Use bands (±5%) or a monthly/quarterly cadence. This controls unintended risk increases when winners run.
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Track drawdowns explicitly
- Add a drawdown curve and monitor max drawdown and time to recover. If painful, consider true diversifiers (quality bonds, managed futures, tail hedges) or smaller positions in the jumpiest assets.
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Add risk-adjusted KPIs
- Report Sharpe (or Sortino) and Calmar (ann. return / max drawdown) alongside return and vol. They help judge the quality of returns.
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Regime & attribution checks
- Split the sample into calm vs stress windows: correlations often rise in stress.
- Do a simple attribution to see whether allocation or selection drove most of the return.
- Correlation cluster (Asset2/3/4/5): Great in good times, risky in bad—size it consciously.
- Weight drift: If present, it can stealthily lift portfolio risk—rebalance to policy targets.
- Shock days: Outliers in the returns table—review those dates and decide on controls (limits, hedges) to reduce future damage.
“Our portfolio earned ~11.5% per year with ~8.5% volatility, a solid risk-adjusted profile. We benefit from some diversification, but a correlated asset cluster concentrates risk in certain regimes. The fastest improvements are to enforce rebalancing, size down correlated bets, and add diversifiers that hold up in stress—reducing drawdowns while keeping return potential.”