The left panel (Scenario Performance) shows how the current portfolio would perform under all preset stress scenarios available on Novus.
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The right panel (Factor Contribution) shows the portfolio return broken down by factor for a scenario. This section updates dynamically to reflect the scenario that the user is hovering over in the Scenario Performance.
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Clicking on a portfolio return bar on a scenario will update the Factor Contribution panel broken down by factor for the clicked scenario. 

GIF

Value at risk (VaR) is a statistic that measures and quantifies the level of financial risk within a firm, portfolio or position over a specific time frame. This metric is most commonly used by investment and commercial banks to determine the extent and occurrence ratio of potential losses in their institutional portfolios.
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Risk managers use VaR to measure and control the level of risk exposure. One can apply VaR calculations to specific positions or whole portfolios or to measure firm-wide risk exposure. 

VaR 95: 95% confident that the change will be less than the value
VaR 99: 99% confident that the change will be less than the value 

This graph plots the portfolio return (bars) against the VaR 95 (light blue) and the VaR 99 (dark blue) envelopes over the date range selected by the user. Any portfolio return that exceeds the calculated VaR for the day/month is marked as red and flagged as a VaR trigger. Users can quickly grasp the trend and volatility of their VaR and returns, or gain insight by cross-referencing trigger dates with other analyses (e.g. benchmarks, asset allocations).
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Users can double-click on any date which opens a new window showing the Positions - Risk tab, sorted by either descending (for periods of positive PNL) or ascending (for periods of negative PNL contribution). 

This graph shows both snapshot VaRs (blue bars) and historical max VaRs (orange bars).  
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VaR 95 and VaR 99 are calculated with five different look-back windows for the current date selected, giving users the flexibility of either emphasizing or de-emphasizing recent data. In monthly mode, the look-back windows are: 1, 2, 3, 4, and 5 years. In daily mode, the look-back windows are 1, 3, 6, 9 and 12 months.  
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The current defaults windows in Alpha are 3 years and 12 months for monthly and daily, respectively.  
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Max VaR 95 and Max VaR 99 are the maximum VaRs calculated in the period selected via the “From” and “To” date. Users can quickly compare current VaRs to historical maximums. - Needs followup (ticket) 

The underlying data of the summary chart above.
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This table will only show data when the returns exceeded VaR as displayed in the Historical VaR Bands chart. It shows the number of triggers for any point where returns exceed VaR, the maximum exceedance over VaR, the date of said exceedance, and the portfolio return and VaR calculated for said date.
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These histograms represent the incremental, marginal, individual and conditional VaR at the aggregation level selected by the user.  
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The X Axis are the bucketed ranges for each statistic. The ranges are inclusive of the lower end of the range and exclusive of the higher end. The Y Axis is the number of positions that fall into these buckets.
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Users can quickly identify how risk is distributed within their portfolio and identify any outliers or concentrations. The data is a snapshot of the portfolio based on the latest date in the selected range. 

 
​cVaR: Conditional value at risk. Average expected loss if losses were to exceed VaR.
​Marginal VaR: The additional amount of VaR that a 1% increase in the position adds to the total portfolio.
​Incremental VaR: Security's contribution to total portfolio Value at Risk (Sum of all iVaR = Portfolio VaR)
​VaR = The portfolio is expected to lose less than the Value at Risk, based on the set percentile (95% or 99%). 

The Novus Equalizer is the heart of the Platform’s stress and scenario modeling analytics. The Equalizer consists of factor Faders that control factor levels as well as analysis output.  
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The Faders
Each Equalizer bar corresponds to a factor in the portfolio’s multi-factor model. Adjust the Fader bars to adjust the factor levels in the stress scenario.  
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Hovering over the Faders will show the historical max, mean, min, current, and scenario levels.  
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Alternatively, click the Lock checkbox (image instead of words) under a Fader bar to allow that factor level be determined automatically: when updated, the multi-factor model will regress the locked factors on the unlocked factors and adjust the locked factors levels in direction and degree proportional to their exposure to the unlocked factors.

NEEDS A GIF

The Expected Portfolio Contribution by Position (%) table decomposes the simulated performance by position and factor, and explain the total contribution along each factor along the regression framework.
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Click a historical scenario from the drop-down to adjust the factors to reflect an actual market scenario.
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Portfolio (Expected): the expected portfolio return given the set factor scenario.   

For the Platform’s single-factor sensitivity analysis, the portfolio as of the selected date is run against multiple single-factor models for each factor.  
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Historical factor tracking simulates the portfolio returns implied by the factor model versus the actual returns. When the actual portfolio return is greater than the factor-tracking portfolio, the un-modeled performance implies the return from elements that aren't being modeled, like alpha.
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​Tracking Return: the projected return based on the portfolio’s historical factor exposures.
​Actual Return: the return of the portfolio based on position-level P&L.
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The Factor Stats table shows the actual annualized return, volatility, max drawdown, skew and kurtosis for both the actual and factor-tracking portfolio.
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Sensitivities can be aggregated across categories in the Categories tab.

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