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020

Case 020Risk limits and drawdownsCore

Dhoran Capital is long Rs 100 crore of stocks with a beta of 1.0 and short Rs 80 crore of an index basket. In a sell-off the index falls 10%, but the longs fall 14%. What does the book lose, what did the beta model predict, and what failed?

1The situation

A pod at Dhoran Capital, a multi-manager platform, runs Rs 100 crore of capital. It holds Rs 100 crore of long positions in mid cap consumer and technology names whose beta to the index, estimated over the past two years, is 1.0. Against them it is short Rs 80 crore of an index futures basket. The platform's rule is that a pod losing 5% of capital is cut in half.

In a sharp two-week sell-off the index falls 10%. The pod's longs fall 14%. The risk manager calls the portfolio manager the same afternoon.

2Your task

What did the book lose, what did the beta model predict, and what failed?

Quick check

What loss did the beta model predict for a 10% index fall?

Worked solution

Try it on paper, then open one step at a time.

30-second answerThe answer to give first

The book lost Rs 6 crore against a predicted Rs 2 crore, 6% of capital and through the 5% limit. The longs lost Rs 14 crore and the index short made Rs 8 crore. The hedge did its job on the market move; what failed was the assumption that the longs behave like the index. They fell 4 points more, a Rs 4 crore residual from factor and crowding risk that no index short can remove.

Step 1What did the model predict, and what happened?

Net the positions in beta terms. Rs 100 crore of beta-one longs against Rs 80 crore of index short leaves Rs 20 crore of net market exposure, so a 10% fall should cost Rs 2 crore, 2% of capital. In fact the longs fell 14%, a Rs 14 crore loss, and the short made Rs 8 crore, leaving a Rs 6 crore loss. That is three times the prediction and enough to cut the pod's capital in half under the platform's rule.

The hedge worked; the longs did not behave like the indexBeta model predicted-2 crore, 2% of capitalActual loss-6 crore, 6% of capitalPod loss limit: 5% of Rs 100 croreRs crore lost; the bars grow to the right as the loss grows
The beta model predicted a Rs 2 crore loss for a 10% index fall, well inside the pod's Rs 5 crore limit, but the book lost Rs 6 crore, 6% of capital, because the longs fell 14%.
Step 2Where did the extra Rs 4 crore come from?

Split the loss into the part the hedge was built for and the part it was not. The market move cost the longs Rs 10 crore and the short recovered Rs 8 crore; the extra Rs 4 crore is the longs falling 4 points more than a beta of one implies. An umbrella keeps off the rain but not a splash from a passing bus: the index short covered the market, and the residual came from somewhere else. The longs' realised beta in the sell-off was 14 over 10, about 1.4, not 1.0.

Decompose the loss: the hedge covered the market, not the residual-10Longsmarket move-4Longsfell more than market+8Index short-6Net result0
The Rs 6 crore loss splits into Rs 10 crore from the market move on the longs and Rs 4 crore from the longs falling more than the market, offset by an Rs 8 crore gain on the index short.
Step 3What failed, and what would you change?

Three things, each common in a sell-off. First, beta was measured over two calm years, and betas of mid cap growth names rise when markets fall. Second, the longs shared a factor exposureA common driver such as size, growth, momentum or value that moves a group of stocks together, separately from the overall market.: mid cap growth, which the broad index barely holds. Third, crowding: if other funds own the same names, they all sell at once when they cut risk. A beta hedge removes market risk only; factor and crowding risk stay in the book unless they are hedged with baskets that share them. The fix is to hedge with a custom basket or factor-matched shorts, stress test the book with sell-off betas rather than average ones, and size gross exposure to the worst plausible residual, not the average.

Where candidates lose it

The trap is reporting the Rs 2 crore prediction as the risk of the book. A beta model gives the expected loss from the market, and candidates who stop there have told the interviewer they believe a hedged book's loss is capped by its net exposure.

The second is blaming bad luck. The residual has causes, factor exposure, crowding and beta instability, and naming them with a fix is what separates a risk answer from an excuse.

What the interviewer asks next

  • How much index short would the pod have needed if it had used the sell-off beta of 1.4?
  • How would you measure the crowding in the long book before the next sell-off?
  • The risk manager halves the pod. Which positions do you cut first, and why?
← Case 019Hillsan Credit Opportunities Fund reports annualised volatility of 4% with first-order autocorrelation of 0.5 in its monthly returns, because it marks illiquid loans to model. What is its likely true volatility, and what does that do to its Sharpe ratio?Case 021 →Kovil Realty's promoters own 55% and have pledged 70% of that stake. Lenders call for more collateral if the stock falls 30% and start selling at a 40% fall. The free float is 45% and daily volume is 0.3% of shares. Build the short thesis and the risk to it.

Company names and figures are illustrative.

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