Factor Monitor
Which factors are driving the market, over any horizon — and why Intratio takes them out of your portfolio.
What is driving the market
Each premium is a long/short pair of index ETFs, rebalanced daily, so a positive number means the first leg beat the second over the window.
Over the last 3 months (2026-07-10 to 2026-10-08), Market led with +2.6% — stronger than 36% of all 3 months windows since 2015 — while Size lagged at −8.4%. 2 of 7 style premia were positive. The 10-year yield moved +0.71 pp.
| Factor | Window return | Percentile vs history | Historical mean | Historical median | Trend |
|---|
Percentile: where this window's return sits among every window of the same length since 2015 (overlapping windows, so the distribution is descriptive, not a significance test). Historical mean and median refer to those same windows.
The same factors across every horizon
A factor that leads this month and lags this year is the normal case: premia rotate. Read across a row before concluding anything.
| Factor | 1M | 3M | 6M | YTD | 1Y | 3Y | 5Y | 10Y | Trend |
|---|---|---|---|---|---|---|---|---|---|
| MarketS&P 500 total return · SPY | +1.6%P49.0 | +2.6%P36.0 | +14.2%P79.0 | +14.2%P62.0 | +16.7%P53.0 | +90.0%P98.0 | +92.5%P47.0 | +317.6%P81.0 | Rising since 2026-04-14above its 200-day average |
| SizeSmall caps minus large caps · IWM − SPY | −5.8%P3.0 | −8.4%P6.0 | −6.7%P25.0 | −0.4%P67.0 | −1.3%P66.0 | −11.1%P54.0 | −28.8%P10.0 | −37.5%P35.0 | Falling since 2026-09-09below its 200-day average |
| ValueValue minus growth · IWD − IWF | −4.4%P10.0 | −0.9%P60.0 | −2.0%P59.0 | +10.4%P92.0 | +12.8%P95.0 | −14.3%P73.0 | −17.5%P95.0 | −52.5%P62.0 | Falling since 2026-09-30above its 200-day average |
| MomentumRecent winners minus the market · MTUM − SPY | +1.3%P70.0 | −3.5%P17.0 | +7.0%P84.0 | +12.6%P98.0 | +8.7%P85.0 | +26.7%P98.0 | +0.7%P62.0 | +12.1%P87.0 | Falling since 2026-08-20above its 200-day average |
| Low volatilityLow-volatility stocks minus the market · USMV − SPY | −0.8%P41.0 | −0.2%P59.0 | −6.7%P18.0 | −6.9%P30.0 | −9.8%P26.0 | −25.5%P5.0 | −27.9%P16.0 | −42.9%P19.0 | Falling since 2026-09-22below its 200-day average |
| QualityHigh-quality stocks minus the market · QUAL − SPY | +1.5%P97.0 | +0.4%P62.0 | −1.0%P34.0 | +0.1%P54.0 | −0.5%P51.0 | −6.7%P2.0 | −5.8%P14.0 | −7.6%P62.0 | Rising since 2026-10-08above its 200-day average |
| High betaHigh-beta stocks minus the market · SPHB − SPY | +1.0%P61.0 | −0.6%P45.0 | +9.9%P83.0 | +15.4%P85.0 | +19.0%P86.0 | +24.5%P86.0 | +20.1%P70.0 | +43.9%P71.0 | Falling since 2026-10-08above its 200-day average |
| RatesChange in the 10-year Treasury yield · ^TNX | +0.44 ppP95.0 | +0.71 ppP92.0 | +0.98 ppP93.0 | +1.11 ppP92.0 | +1.15 ppP90.0 | +0.47 ppP37.0 | +3.75 ppP97.0 | +3.71 ppP100.0 | Rising since 2026-08-20above its 200-day average |
| CreditHigh yield minus investment grade · HYG − LQD | +0.4%P53.0 | +1.7%P67.0 | +3.2%P73.0 | +3.7%P66.0 | +5.0%P71.0 | +7.6%P51.0 | +22.4%P84.0 | +22.7%P76.0 | Rising since 2026-06-29above its 200-day average |
Cells: window return (rates: change of the 10-year yield in percentage points) and its percentile against history. Trend: sign of the trailing-quarter return and position against the 200-day average of the premium's index.
Premia through time
Compare up to three premia over the selected window, then see each one's rolling one-year return against its own history to spot inflexion points.
Each panel is the rolling one-year return of the premium since 2015: above zero the factor paid over the preceding year, below zero it cost. The dashed line is the historical mean of one-year returns, the dotted line the median; the marker is the latest date the one-year return changed sign. A premium crossing its mean after a long stretch on the other side is the classic inflexion.
How the premia move together
Correlation of daily premium returns over the selected window. Strongly correlated premia are one bet wearing two names; a negative pair is a natural hedge.
Sector leadership
Industry is the tenth factor: the eleven Select Sector SPDRs relative to the S&P 500 over the selected window.
Pure factor returns, as the optimizer sees them
Every session Intratio regresses the return of about 4,600 US stocks on industry and on the model's own factor scores. The result is the return of each factor in isolation — per one standard deviation of exposure — the exact quantity the portfolio optimizer neutralizes.
Signs follow this page's orientation (small caps, low volatility = positive), so the model's size and volatility factors are shown flipped. Rates and credit appear once the daily pipeline serves their betas for enough of the universe. Short history: the model's first attributable session is September 2026.
The ten factors, one by one
What each factor is, where the evidence comes from, why it is believed to pay, how Intratio measures it, how to own it with ETFs, where it fails — and what the optimizer does with it.
01
Marketnet exposure
The return of owning stocks at all. Every other factor is measured on top of it.
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What it is
The market factor is the return of the whole equity market, held in proportion to company size. Its premium over cash — the equity risk premium — is the oldest and largest factor return: about 5–7% a year over the last century, paid for carrying the risk that stocks fall together in recessions and crises.
Where the evidence comes from
The Capital Asset Pricing Model (Sharpe 1964, Lintner 1965) made the market portfolio the only priced risk: a stock's expected return was its beta to the market times the equity premium. Every later factor is an anomaly relative to this baseline.
Why it is believed to pay
Risk-based: investors demand compensation for bearing the undiversifiable risk of the economy. The premium is real but arrives in lumps — long bull markets interrupted by drawdowns of 30–55% (2000–02, 2008, 2020, 2022).
Where it fails
Timing the market has a dismal record: missing the ten best days of a decade roughly halves its return. The premium compensates for risk; it is not a free lunch.
What Intratio does with it
A dollar-neutral Intratio book has a net exposure near zero, so the market factor contributes close to nothing — by design. A long-only book keeps the market and the optimizer neutralizes the style tilts on top of it.
How it is measured here
Here: the S&P 500 (SPY) total return. In Intratio's model: the cap-weighted return of the whole US universe (about 4,600 names), estimated every session; a portfolio's market contribution is its net exposure times that return.
Monitor: S&P 500 total return · SPY
Track record of the premium
| Window | Annualised | Volatility | Sharpe | Max drawdown |
|---|---|---|---|---|
| 1Y | +16.7% | +13.0% | 1.28 | −8.9% |
| 5Y | +14.0% | +17.1% | 0.82 | −24.5% |
| 10Y | +15.4% | +17.9% | 0.86 | −33.7% |
Positive in 86% of the 2706 one-year windows since 2015; best +77.5%, worst −19.7%, median +16.2%.
ETFs that carry it
| SPY | State Street | S&P 500 |
| VOO | Vanguard | S&P 500 |
| VTI | Vanguard | Total US market |
| ITOT | iShares | Total US market |
Market exposure is the default: any long-only fund has it. Removing it (a market-neutral book) means shorting an index future or ETF against the long positions, which is what Intratio's dollar-neutral portfolios do.
02
Sizeneutralized
Small companies have historically out-earned large ones — unevenly, and mostly in the recovery phase of the cycle.
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What it is
The size premium is the excess return of small-capitalisation stocks over large ones. The monitor shows the Russell 2000 (IWM) minus the S&P 500 (SPY): positive when small caps lead.
Where the evidence comes from
Banz (1981) documented it; Fama and French (1992, 1993) made "small minus big" (SMB) one of the three factors of their model. It is the most contested premium: it has been weak since publication, and much of it sits in the smallest, least liquid names.
Why it is believed to pay
Risk-based explanations point to illiquidity, financing fragility and higher sensitivity to credit conditions; behavioural ones to neglect by analysts and institutions. Small caps tend to lead early in recoveries and lag when credit tightens.
Where it fails
The premium is concentrated in micro caps that ETFs do not hold; small caps also carry a value and low-quality tilt that explains part of the historical return. Long periods (2014–2020) of underperformance are normal.
What Intratio does with it
Neutralized. A book's weighted size exposure is held inside the optimizer's band, so its return does not depend on whether small caps are in favour.
How it is measured here
Intratio's size factor is the log of market capitalisation, standardised across the universe each day. Its model sign is "large = positive"; the monitor flips it so that a positive reading means small caps paid.
Monitor: Small caps minus large caps · IWM − SPY
Track record of the premium
| Window | Annualised | Volatility | Sharpe | Max drawdown |
|---|---|---|---|---|
| 1Y | −1.3% | +10.9% | -0.12 | −13.2% |
| 5Y | −6.6% | +11.9% | -0.55 | −32.8% |
| 10Y | −4.6% | +11.8% | -0.39 | −43.8% |
Positive in 30% of the 2706 one-year windows since 2015; best +39.0%, worst −23.8%, median −5.5%.
ETFs that carry it
| IWM | iShares | Russell 2000 |
| IJR | iShares | S&P SmallCap 600 |
| VB | Vanguard | CRSP US Small Cap |
| AVUV | Avantis | US small-cap value, active |
Long a small-cap ETF, short the same dollar amount of SPY. The pair removes the market and leaves the size spread (plus whatever sector mix small caps carry).
03
Valueneutralized
Cheap stocks versus expensive ones — the premium with the longest drought and the sharpest comebacks.
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What it is
The value premium is the excess return of stocks that are cheap relative to their fundamentals (book value, earnings, cash flow) over expensive "growth" stocks. The monitor shows Russell 1000 Value (IWD) minus Russell 1000 Growth (IWF).
Where the evidence comes from
Graham and Dodd (1934) in practice; Basu (1977) on earnings yield; Fama and French (1992) on book-to-market, "high minus low" (HML). Among the most replicated results in finance, across countries and asset classes.
Why it is believed to pay
Risk: cheap firms are often distressed, levered or cyclical, and suffer most in bad times. Behaviour: investors extrapolate growth and overpay for glamour. Both are probably true; the premium is paid in bursts (2000–06, 2021–22) between long droughts (2017–20).
Where it fails
Value can underperform for a decade. Cheap on one measure (book value) is not cheap on another (cash flow); intangible-heavy firms distort book-based measures. Value crowds with the credit and high-beta factors in recoveries.
What Intratio does with it
Neutralized. Intratio's forecasts are trained to predict the return that remains after the value effect, so a book is neither a value nor a growth bet.
How it is measured here
Intratio's value factor is free-cash-flow yield (trailing free cash flow over market capitalisation), standardised across the universe each day. A positive model exposure and a positive monitor reading mean the same thing: cheap stocks.
Monitor: Value minus growth · IWD − IWF
Track record of the premium
| Window | Annualised | Volatility | Sharpe | Max drawdown |
|---|---|---|---|---|
| 1Y | +12.8% | +14.9% | 0.86 | −11.1% |
| 5Y | −3.8% | +14.4% | -0.26 | −43.5% |
| 10Y | −7.2% | +13.1% | -0.55 | −62.1% |
Positive in 24% of the 2706 one-year windows since 2015; best +28.3%, worst −32.4%, median −6.4%.
ETFs that carry it
| IWD | iShares | Russell 1000 Value |
| VTV | Vanguard | CRSP US Large Value |
| IVE | iShares | S&P 500 Value |
| RPV | Invesco | S&P 500 Pure Value |
Long a value ETF, short its growth counterpart (IWD against IWF): the pair cancels the market and much of the sector mix and leaves the value spread.
04
Momentumneutralized
Recent winners keep winning for a while — the strongest anomaly, with the worst crashes.
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What it is
Momentum is the tendency of stocks that rose over the last 6–12 months to keep outperforming over the next 1–12 months. The monitor shows MSCI USA Momentum (MTUM) minus the S&P 500.
Where the evidence comes from
Jegadeesh and Titman (1993) documented the 12-month-minus-1 effect; Carhart (1997) added it as a fourth factor ("up minus down"). It appears in every equity market and most asset classes studied.
Why it is believed to pay
Behavioural: under-reaction to news, then herding. Risk: momentum books carry a time-varying beta that becomes dangerously negative after a crash, which is when the factor itself crashes (−80% for the long/short version in 2009).
Where it fails
Momentum crashes when leadership reverses abruptly (March 2009, November 2020): the book is long yesterday's winners into a regime change. High turnover makes it the most expensive factor to trade.
What Intratio does with it
Neutralized. The daily forecasts are not momentum in disguise: a book's weighted momentum exposure is held inside the band, so a momentum crash does not become the book's crash.
How it is measured here
Intratio's momentum factor is the 12-month price return, standardised across the universe each day. Same orientation as the monitor.
Monitor: Recent winners minus the market · MTUM − SPY
Track record of the premium
| Window | Annualised | Volatility | Sharpe | Max drawdown |
|---|---|---|---|---|
| 1Y | +8.7% | +18.6% | 0.47 | −16.3% |
| 5Y | +0.1% | +12.0% | 0.01 | −24.0% |
| 10Y | +1.2% | +10.6% | 0.11 | −30.0% |
Positive in 59% of the 2706 one-year windows since 2015; best +20.3%, worst −18.4%, median +2.0%.
ETFs that carry it
| MTUM | iShares | MSCI USA Momentum |
| SPMO | Invesco | S&P 500 Momentum |
| QMOM | Alpha Architect | US quantitative momentum |
| IMTM | iShares | International momentum |
Long a momentum ETF, short SPY. Note that ETF momentum rebalances a few times a year; academic momentum rebalances monthly and turns over far more.
05
Low volatilityneutralized
Boring stocks have delivered market-like returns with far less risk — the anomaly that contradicts the textbook.
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What it is
The low-volatility (or low-beta) anomaly: stocks with the smallest price swings have earned returns similar to or above the market, with much lower risk, so their risk-adjusted return beats the CAPM prediction. The monitor shows MSCI USA Minimum Volatility (USMV) minus the S&P 500.
Where the evidence comes from
Black, Jensen and Scholes (1972) found the security market line too flat; Haugen and Heins (1975), Ang, Hodrick, Xing and Zhang (2006) on idiosyncratic volatility; Frazzini and Pedersen (2014) framed it as "betting against beta".
Why it is believed to pay
Leverage constraints: investors who cannot borrow buy high-beta stocks to reach their return target, overpaying for them; lottery preference does the rest. The premium shows up as a lower drawdown in bear markets and a lag in strong rallies.
Where it fails
The factor lags badly in sharp rallies and in rising-rate periods (its stocks look like bonds: utilities, staples). Crowding in 2016 and 2019 pushed valuations of low-vol names to records.
What Intratio does with it
Neutralized. The optimizer holds the book's weighted volatility exposure inside the band, so the book is neither a defensive nor an aggressive bet in disguise.
How it is measured here
Intratio's volatility factor is 30-day Parkinson (high–low range) volatility, standardised across the universe each day; the model counts high volatility as positive, so the monitor flips the sign: positive means low-volatility stocks paid.
Monitor: Low-volatility stocks minus the market · USMV − SPY
Track record of the premium
| Window | Annualised | Volatility | Sharpe | Max drawdown |
|---|---|---|---|---|
| 1Y | −9.8% | +11.3% | -0.86 | −13.3% |
| 5Y | −6.3% | +10.0% | -0.63 | −35.4% |
| 10Y | −5.5% | +8.5% | -0.64 | −45.8% |
Positive in 32% of the 2706 one-year windows since 2015; best +12.8%, worst −23.4%, median −4.4%.
ETFs that carry it
| USMV | iShares | MSCI USA Minimum Volatility |
| SPLV | Invesco | S&P 500 Low Volatility |
| LVHD | Franklin | Low-volatility high-dividend |
| EFAV | iShares | International minimum volatility |
Long USMV, short SPY. Because low-volatility stocks have a beta near 0.7, the pair is still short some market; a beta-hedged version shorts about 0.7 dollars of SPY per dollar of USMV.
06
Qualityneutralized
Profitable, stable, well-run companies — the premium that holds up when credit cracks.
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What it is
Quality is the excess return of companies with high and stable profitability, low leverage and conservative accounting over "junk". The monitor shows MSCI USA Quality (QUAL) minus the S&P 500.
Where the evidence comes from
Novy-Marx (2013) on gross profitability; Fama and French (2015) added profitability and investment to their model; Asness, Frazzini and Pedersen (2019) "quality minus junk" (QMJ).
Why it is believed to pay
Mostly behavioural: investors under-pay for boring, durable profitability. Quality is a defensive factor — it tends to pay during credit stress (2008, 2020, 2022) and to lag in speculative rallies.
Where it fails
Definitions vary widely across index providers; "quality" ETFs with very different holdings share the name. Quality is expensive after long defensive runs.
What Intratio does with it
Neutralized, so a book's return does not depend on the quality cycle.
How it is measured here
Intratio's quality factor is operating return on assets, standardised across the universe each day. Same orientation as the monitor.
Monitor: High-quality stocks minus the market · QUAL − SPY
Track record of the premium
| Window | Annualised | Volatility | Sharpe | Max drawdown |
|---|---|---|---|---|
| 1Y | −0.5% | +4.4% | -0.10 | −5.0% |
| 5Y | −1.2% | +3.8% | -0.31 | −11.5% |
| 10Y | −0.8% | +3.4% | -0.23 | −11.5% |
Positive in 42% of the 2706 one-year windows since 2015; best +7.7%, worst −8.7%, median −0.6%.
ETFs that carry it
| QUAL | iShares | MSCI USA Quality |
| SPHQ | Invesco | S&P 500 Quality |
| JQUA | JPMorgan | US quality |
| DGRW | WisdomTree | Quality dividend growth |
Long a quality ETF, short SPY. Quality indices overlap heavily with mega-cap growth, so the pair also carries some growth (negative value) exposure.
07
High betaneutralized
The most market-sensitive stocks: the risk-on gauge, and the mirror image of low volatility.
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What it is
Beta measures how much a stock moves with the market. High-beta stocks amplify rallies and sell-offs. The monitor shows S&P 500 High Beta (SPHB) minus the S&P 500: positive when risk appetite is rising.
Where the evidence comes from
Beta is the CAPM's own risk measure (Sharpe 1964). Its anomaly — high-beta stocks earning less than the model predicts — is the other side of the low-volatility literature (Frazzini and Pedersen 2014).
Why it is believed to pay
High-beta stocks are bought as leverage substitutes, which bids their prices up and their expected returns down. The spread is a clean read of risk appetite: it leads in early recoveries and collapses in drawdowns.
Where it fails
A high-beta tilt is mostly a levered market bet, not an independent source of return; it loses money in most long samples once the market is hedged.
What Intratio does with it
Neutralized: the book's weighted beta exposure is held inside the band, so a dollar-neutral book is also close to beta-neutral.
How it is measured here
Intratio's beta factor is the CAPM beta of each stock to the market, standardised across the universe each day. Same orientation as the monitor.
Monitor: High-beta stocks minus the market · SPHB − SPY
Track record of the premium
| Window | Annualised | Volatility | Sharpe | Max drawdown |
|---|---|---|---|---|
| 1Y | +19.0% | +17.4% | 1.09 | −12.2% |
| 5Y | +3.7% | +14.3% | 0.26 | −26.3% |
| 10Y | +3.7% | +15.4% | 0.24 | −34.2% |
Positive in 51% of the 2706 one-year windows since 2015; best +70.7%, worst −24.7%, median +0.2%.
ETFs that carry it
| SPHB | Invesco | S&P 500 High Beta |
| SPLV | Invesco | S&P 500 Low Volatility (the opposite leg) |
| SSO | ProShares | 2x S&P 500 (leverage, not stock selection) |
Long SPHB, short SPY gives the high-beta spread; long SPHB, short SPLV is the classic high-minus-low beta pair.
08
Ratesneutralized
Which stocks win when yields rise — long-duration growth loses, banks and cyclicals gain.
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What it is
The rates factor is a stock's sensitivity to changes in the 10-year Treasury yield. The monitor shows the yield itself (level in percent, window changes in percentage points); the factor is how differently stocks respond to those moves.
Where the evidence comes from
Multi-factor macro models (Chen, Roll and Ross 1986) priced interest-rate and inflation surprises; "equity duration" explains why growth stocks, whose cash flows sit far in the future, fall most when discount rates rise (2022).
Why it is believed to pay
Discounting: higher yields cut the present value of distant cash flows (growth, real estate, utilities) and raise bank margins. The sign and size of rate sensitivity differ by industry and by balance sheet.
Where it fails
Rate betas are unstable: the same stock can be a rate loser in an inflation scare and a rate winner in a growth scare. Hedging with bonds adds a second asset class to manage.
What Intratio does with it
Neutralized when served: the optimizer holds the book's weighted rate beta inside the band, so a yield shock is not the book's shock.
How it is measured here
Intratio's rate factor is each stock's beta to the daily change in the 10-year yield, estimated on its own history and standardised across the universe. It is served by the daily pipeline and neutralized when enough of a book carries it.
Monitor: Change in the 10-year Treasury yield · ^TNX
Track record of the premium
| Window | Annualised | Volatility | Sharpe | Max drawdown |
|---|---|---|---|---|
| 1Y | +1.15 pp | +0.7 pp | 1.78 | −0.3 pp |
| 5Y | +0.75 pp | +1.0 pp | 0.75 | −1.4 pp |
| 10Y | +0.37 pp | +0.9 pp | 0.43 | −2.7 pp |
Positive in 63% of the 2706 one-year windows since 2015; best +2.8 pp, worst −2.1 pp, median +0.4 pp.
ETFs that carry it
| TLT | iShares | 20+ year Treasuries (falls when yields rise) |
| IEF | iShares | 7–10 year Treasuries |
| TBT | ProShares | −2x 20+ year Treasuries (gains when yields rise) |
| KRE | State Street | Regional banks (rate-sensitive sector) |
Rate exposure in an equity book is a by-product of its industries and growth tilt. To isolate it, hedge with Treasury ETFs or futures sized to the book's rate beta.
09
Creditneutralized
Which stocks win when credit spreads tighten — the leverage and distress channel.
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What it is
The credit factor is a stock's sensitivity to the high-yield credit spread. The monitor shows high-yield bonds (HYG) minus investment-grade bonds (LQD): positive when spreads tighten and risk appetite in credit rises.
Where the evidence comes from
Credit risk premia are documented across bond markets; in equities, levered and distressed firms behave like short credit protection (Merton 1974: equity as a call on the firm).
Why it is believed to pay
Highly levered firms, cyclicals and small caps borrow at spreads; when spreads widen their financing cost rises and their equity falls disproportionately. Credit leads equities at turning points more often than not.
Where it fails
Credit spreads gap: the factor is calm for years and then moves in days (March 2020). Credit, value, size and high beta are the same bet in a recovery.
What Intratio does with it
Neutralized when served, so a credit event does not reprice the book through its levered names.
How it is measured here
Intratio's credit factor is each stock's beta to the HYG−LQD return spread, estimated on its own history and standardised across the universe; neutralized when enough of a book carries it.
Monitor: High yield minus investment grade · HYG − LQD
Track record of the premium
| Window | Annualised | Volatility | Sharpe | Max drawdown |
|---|---|---|---|---|
| 1Y | +5.0% | +3.6% | 1.40 | −1.7% |
| 5Y | +4.1% | +6.3% | 0.66 | −7.5% |
| 10Y | +2.1% | +7.8% | 0.27 | −20.2% |
Positive in 72% of the 2706 one-year windows since 2015; best +14.7%, worst −17.1%, median +3.0%.
ETFs that carry it
| HYG | iShares | iBoxx USD high-yield corporate bonds |
| JNK | State Street | High-yield corporate bonds |
| LQD | iShares | iBoxx USD investment-grade corporate bonds |
| HYGH | iShares | High yield, rate-hedged |
Long HYG, short LQD gives the credit-spread return with most of the rate risk cancelled. An equity book's credit exposure is hedged by shorting that pair in proportion to its credit beta.
10
Industrycapped
Sector rotation explains a large share of any stock's return — and of most portfolios' tracking error.
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What it is
Industry membership is a factor in its own right: stocks in the same industry move together on oil prices, rates, regulation and demand. The monitor ranks the eleven Select Sector SPDRs over each window and measures their dispersion.
Where the evidence comes from
King (1966) showed industry effects after the market; every commercial risk model since (Barra, Axioma) carries industry factors alongside the styles.
Why it is believed to pay
Industries share cash-flow drivers; sector rotation is how macro news reaches individual stocks. Dispersion between sectors is a direct measure of how much a stock picker can lose by being in the wrong one.
Where it fails
Sector bets are the fastest way to concentrate risk unknowingly: a "quality" or "momentum" screen often is a technology bet.
What Intratio does with it
Capped: the optimizer limits every industry's net weight, so no sector dominates the book's return; the stock-specific forecasts do.
How it is measured here
Intratio's model regresses every session's cross-section of returns on industry dummies first, then on the style factors; a book's industry contribution is its over- or under-weight in each industry times that industry's return.
Monitor: Eleven Select Sector SPDRs versus the S&P 500 · XLK … XLC − SPY
ETFs that carry it
| XLK | State Street | Technology |
| XLF | State Street | Financials |
| XLE | State Street | Energy |
| XLV | State Street | Health Care |
Long a sector ETF, short SPY isolates that sector's return over the market; the full set of eleven pairs is the sector-rotation book.
ETFs are listed to illustrate how each premium can be owned or isolated; this is quantitative research, not investment advice or a recommendation of any product.
Why Intratio invests factor-free
Most of what moves a stock on a given day is not about that stock. It is the market, its industry and the style premia above — and this page shows those premia are large, rotate without warning, and are far from independent of one another. A portfolio that carries them is making bets it did not choose.
- 34.3% of the daily cross-sectional dispersion of US stock returns is explained by the market, industry and the model's style factors alone (mean R² of Intratio's daily regression). What is left is the stock-specific return the forecasts are built to capture.
- A style premium was positive in only 44% of one-year windows on average since 2015 (from 24% to 72% depending on the factor): holding one unhedged is close to a coin flip on any single year.
- The gap between a premium's best and worst one-year outcome averages 48.8 points: the size of the bet dwarfs most managers' alpha.
- Over the last year, Value moved against their own long-run sign — premia rotate, and timing them is a separate skill with a poor record.
- The premia are not independent: over the last year Momentum and High beta had a correlation of 0.76. Two tilts can be one risk.
Intratio does the opposite of factor investing. The forecasts are trained on the return that remains after the factors are taken out, so they rank stocks on what is specific to each of them; the optimizer then builds the book with every style exposure held inside a band around zero, every industry capped and, for the dollar-neutral setting, the market itself removed. What remains to be earned is pure alpha — the part of the return no ETF on this page can buy — and what remains to be lost is not a factor crash.
The performance page of any portfolio splits its return into exactly these buckets — market, industry, each style, and specific — session by session, so you can verify that the factors contributed close to nothing and the specific return did the work.