Quant Corporate Finance – Research Methodology - Monte Carlo Simulation, Share Repurchase & Multiple Assumption

Stochastic process AR-1 is used for sales figures on past quarterly data. Another methodology suggests that we should match our projections with the consensus but relying on either (stochastic model or the consensus) can create errors in the projections. As we know that past volatility play a very important role in the path generation we should always use sales after removing the seasonality. Hence a judicious role here is important.

Dual effects of share repurchase offers features that are not offered in conventional ways to return to shareholders are:

• Volatility / Volumes of share are affected. High volumes bring in our shares in some good index and thus increase trade and liquidity of our stock. We can control volatility of the shares by controlling the down side of the shares using ‘buy on low share price’.
• Best way to give back to shareholders as you kill the number of shares after repo, may be dividend or retained money will not show that much effect over share prices which market don’t react.

Share Repurchase Mechanisms: This could work when we buy shares based on some logic like P/E fall or just the price falls. Price falls and ratio are two different styles where one method is based on input from the market and other is a passive strategy.

P/E and price falls makes the most sense because we can buy the share when market or other quant indexes are short whereas a company we believe on our own fundamentals. In most of the research we have observed that P/E shows the best result because we buy undervalued and strategically ignore overvalued shares, thus we reduce the number of shares that shoots the value of our shares toward the upper side. Finally we would also increase the EPS by doing strategic buy back.

Modeling Considerations: We have used the last number and the grid for finding which repo amount we will flow through the model. In the grids we have used last number function to get the desired amount.

Let us take a simple example to understand the buildup of the model using three parameters:

Assume that we have: 100 shares, market price of $10/share which gives us a market cap of $1000. Furthermore let us assume that the debt is $100 debts, the current multiple is 11 and the EBTIDA is $10.

Hence EV/EBTIDA * multiple =1100

Now, if the company takes a debt of $200 its EV increase to 1300 (if it doesn’t keep it as cash). In our model we have kept the EV constant which means that the new multiple which should have been 1300/10 = 13 to keep the EV to 1300 comes back to 11. The assumption is that share price will react.

Why did the multiple moves and how will this happen in the real market?

Interestingly, in the case above the EV/EBITDA will not move, so that hit will be on Equity which will reduce by 200 which is the amount of new debt taken. In reality this reduction of MV will come as reduction of debt and MC the multiple will again hover close to the old value of 11 (which was the long term multiple). Thus either our debt value decreases or equity decreases or both decreases to keep the multiple close to long term average, thereby in real markets we can assume a combined effect of both on the multiple.

Results, Possible Improvements & Research Pathway

Effect of Share repo on company’s total return for the projected period depends on when we buy the shares. These results would include the effect of stochastic movements in three variables: Sales, Multiple and Margins keeping all other things status quo. Model takes us to a mean path which could be also used to project 90% confidence of remaining in the range X+-Delta, etc. Factors that is most relevant for deciding Optimum Capital Structure will include expected results in all strategies and whether we can increase leverage and still keep the Multiple intact. How does idea of algorithmic share buyback effect returns as compared to traditional dividend policies are shown to in this research.

Excel-VBA models were used create the scenarios and but this work could be extended to R/MATLAB. Modules: Acquisition, Pension Liability, and Share Repo’s effect on return and the best Capital Structure depends on projections of the core elements of company drivers and are dependent on share price which makes the engine useful.  Which assumptions matters the most and how to get other settings for getting realistic simulations can be judged but this research provides a directional indication. Sometimes the very minutatne of basis points contribution of selected policy might be done at the cost of greater leverage that should be avoided. In our models we have used only 10 paths that could be scaled ahead

Internal factors for a company for doing MC sim:

• ·         Sales
•        Multiple
•        Margin
•        EV-EBITDA

Market numbers:

• ·         Interest rate
•        S&P
•        Libor
•        Steepness

We would shake them up.