Cash Flow at Risk (CFAR) for commodity trading firms: a practical guide

By Saurabh Goyal, Founder & CEO of Phlo Systems. Published 22 April 2026.

Cash Flow at Risk (CFAR) is the most useful single risk metric for commodity trading firms — and the least understood. Where Value at Risk (VaR) tells you the maximum P&L loss expected with a given confidence over a given horizon, CFAR tells you the maximum cash shortfall expected with a given confidence over a given horizon.

For a commodity trader, that's often the more important number. Firms don't go bankrupt from P&L losses; they go bankrupt when they run out of cash to meet an obligation. CFAR puts a number on that risk.

What CFAR actually is

The standard formal definition: CFAR is the maximum expected cash shortfall (or surplus) over a given time horizon, at a given confidence level, given the firm's exposures.

In practice, for a commodity trading firm, CFAR captures the cash flow risk from:

• Variation margin movements on open futures and options positions
• Counterparty payment timing (days late, defaults)
• Inventory revaluation effects on borrowing base availability
• FX movements on USD-denominated cash flows
• Commodity price effects on margin calls under inventory finance facilities

The output is a number like: "At 95% confidence, our cash position could be £4.2M lower than projected over the next 4 weeks."

If your committed undrawn credit is £5M, you're fine. If it's £3M, you have a CFAR-driven liquidity risk that needs to be addressed — by raising more credit, hedging less, or holding more cash.

How to calculate CFAR

The simplest practical calculation, which works for most SME commodity traders:

CFAR(t, α) = Z(α) × σ_cash × √t

Where:

• t = time horizon in days
• α = confidence level (typically 95% or 99%)
• Z(α) = the standard normal critical value (1.645 for 95%, 2.33 for 99%)
• σ_cash = the daily standard deviation of net cash flows from market drivers (variation margin, inventory revaluation, FX translation)

To compute σ_cash you need historical or simulated daily cash flows for at least 6 months. Most firms don't have this data because their cash management lives in spreadsheets and bank portals. An integrated CM platform produces it natively.

A worked example: a firm has σ_cash of £400K per day (i.e., daily cash from market drivers normally varies ±£400K). CFAR at 95% over 20 trading days (~1 month):

CFAR = 1.645 × £400K × √20 = 1.645 × £400K × 4.47 = £2.94M

Interpretation: at 95% confidence, the firm's cash position over the next month could be up to £2.94M below the expected baseline due to market movements. Add the projected baseline cash flow (operational receipts and payments) to get the full picture.

Why CFAR beats VaR for commodity traders

VaR tells you the P&L impact of market moves. CFAR tells you the cash impact. For a trading firm with substantial physical inventory and futures hedges, these can be very different.

• A long physical position with a short futures hedge has near-zero VaR (the legs offset).
• The same position has substantial CFAR (the futures leg pays variation margin daily; the physical leg doesn't generate offsetting cash).

In other words, the more you hedge, the lower your VaR and the higher your CFAR. Risk management decisions made on VaR alone systematically miss this.

How to use CFAR operationally

Three practical applications:

1. Sizing your committed credit facility. Your committed undrawn credit should comfortably exceed CFAR over the horizon you'd need to act on a stress event. A practical rule: undrawn committed credit ≥ 1.5 × 4-week 95% CFAR.

2. Setting hedging policy. The cash impact of a proposed hedge is its incremental contribution to CFAR. If a new hedge would push CFAR above your credit headroom, partial hedging or no hedging is the safer answer regardless of P&L benefit.

3. Stressed scenario planning. Run CFAR under stressed σ — typically 2x or 3x the historical observation, to capture episodes like 2008, 2020, or 2022 when commodity volatility spiked. This is your worst-case capital adequacy test.

A practical example

A mid-market metals trader has:

• £45M of physical inventory (copper, aluminium)
• £30M short futures hedge (LME)
• £20M of receivables, average DSO 45 days
• £15M committed working capital facility, currently £10M drawn (£5M undrawn)
• Reported equity: £18M

Daily cash volatility from market drivers (variation margin + inventory borrowing base effects + FX): observed σ_cash = £350K/day.

4-week 95% CFAR = 1.645 × £350K × √20 = £2.57M

The firm's £5M undrawn credit comfortably exceeds 1.5 × £2.57M = £3.86M required headroom. Liquidity is adequate.

Run the stressed scenario at 2x σ: stressed CFAR = £5.14M. Now the firm is at the edge — £5M undrawn covers the stress but doesn't comfortably exceed it. The CFO should consider raising the facility, reducing the hedge ratio, or holding additional cash before the next round of facility renewal.

This is the kind of analysis that should drive treasury decisions but rarely does because the data isn't available.

CFAR in your treasury policy

A defensible CFAR policy for an SME commodity trader has four elements:

1. Calculation methodology — parametric, Monte Carlo, or historical simulation. The simple parametric approach above works for most firms.
2. Confidence level — 95% for normal monitoring, 99% for capital adequacy.
3. Headroom requirement — e.g., committed undrawn credit ≥ 1.5x 4-week CFAR at 95%; or covers 4-week CFAR at 99%.
4. Escalation triggers — e.g., when 4-week CFAR exceeds 80% of available headroom, escalate to CEO; when CFAR exceeds headroom, mandatory action.

Document this in a one-page policy. Review quarterly. Update when the business changes (new commodity, new hedging strategy, new geography).

Frequently Asked Questions

What's the difference between CFAR and Liquidity at Risk (LaR)?

Some practitioners distinguish them: CFAR focuses on market-driven cash flow uncertainty; LaR adds operational and event-driven risks (delayed payments, supplier disputes). For SME purposes the distinction is academic — use a comprehensive cash-flow stress methodology and call it whichever you prefer.

Can I calculate CFAR in Excel?

Yes, for the parametric form above. Monte Carlo CFAR (more accurate but more complex) requires either a script (Python/R) or a CM platform that supports it natively. For most SME purposes the parametric form is adequate.

How often should we recalculate CFAR?

Weekly for monitoring, daily during periods of high volatility, immediately when material new positions are taken (large new inventory, large new hedge, new counterparty).

Should banks expect to see CFAR in our reporting?

Sophisticated commodity trade finance lenders increasingly ask for it. Even those that don't ask explicitly will respond well to a borrower who can demonstrate this discipline — it's a credibility signal.

Does Phlo's software calculate CFAR natively?

opsPhlo calculates parametric CFAR daily on the firm's full position book — physical inventory, futures hedges, receivables, payables, FX — and projects it forward over user-defined horizons against committed credit. This makes CFAR a daily management number rather than a quarterly board exercise.

How Phlo Systems helps

opsPhlo treats cash as a first-class risk dimension alongside P&L. Daily CFAR calculation, stress scenarios, alerts when CFAR approaches credit headroom, and a 13-week cash forecast that incorporates the CFAR distribution — all native, all updated on every transaction.

For SME commodity traders who currently track P&L risk in detail and cash risk by intuition, opsPhlo closes that gap. Your CFO sees what your bank wants to see, and you can size your credit facilities to your actual risk profile rather than to a guess.

If you'd like to see a CFAR analysis run on your live position data, request a CFAR demo at opsphlo.com.

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Related reading:

• The cash flow implications of hedging commodity positions with futures
• The risk metrics that actually matter for SME commodity traders who don't hedge
• Does the CEO of an SME commodity trading firm need a full-time risk manager?

Saurabh Goyal is the Founder & CEO of Phlo Systems. He has built CFAR and liquidity-risk infrastructure for trading firms across base metals, soft commodities, and energy.