Wealth creator for conservative investors

Harish Krishnan

Fund Manager – Equity

Kotak AMC

Kotak AMC’s new Balanced Advantage Fund has a clear mandate to manage money in a conservative manner even as it seeks to create long term wealth for those who wish to minimize equity volatility. Harish takes us through its 2 factor model that governs asset allocation and why the fund house opted for trailing P/E as its primary factor. Equity allocation currently will be in the 35-40% range due to valuations remaining above average.

WF: In your Balanced Advantage Fund’s 2 factor model, you have chosen trailing P/E as the valuation metric while many others have opted variously for forward P/E, P/B, dividend yield etc. What drove the decision in favour of trailing P/E?

Harish: Setting out to build a model, we had 2 primary objectives – have valuation parameter as a primary factor for allocation and second, ensure the robustness of the model by testing it across as many scenarios as possible. As we tried various fundamental parameters, we found that in certain cases like say, P/B – the sectoral skew of some large sectors (for eg: in dotcom era, tech had a disproportionate dominance in Nifty and now, financials have a large weightage). Given the varying P/B and RoE characteristics of these sectors, they tend to impact Nifty P/B as well. So, while the 2002-07 had a high-low of P/B from 1.92 to 6.55, the range of P/B in 2008-2010 was from 2.12 to 3.95 and the latest cycle from 2.62 to 3.82. Given the significant regime shifts in the range of P/B, testing it across various scenarios over the last 20 years brings in significant discretion. Similarly, forward P/E captures the market expectations 12 months forward at any point of time. For example, data of Mar 2001 should ideally therefore be on expectations of earnings in 2002, however, in our opinion data in distant past are more likely to be based on actual delivery of numbers than the expected earnings. This distorts the data series impacting the robustness of back-test. Given these vagaries, we decided to keep trailing P/E as primary factor, as it has over time moved in similar high-low ranges across various cycles and has no scope of errors in estimation.

WF: Your second factor in your 2 factor model is market trends. What quantitative parameters do you use to discern market trends? How do you ensure that this factor doesn’t get too subjective and therefore potentially lacking discipline?

Harish: We look at objective data to understand the market trends. Some of the factors considered are long range Nifty rolling returns, short-range rolling Nifty returns, volatility and in extreme cases, ratios like 52week High-low etc. A combination of these trend variables helps in understand the overall sentiment of the market and is added to output of the range provided by the first factor – Nifty trailing P/E to arrive at allocation to equity in the fund on a daily basis.

WF: When trailing P/E is high but trend is favourable, which factor assumes more weightage in your asset allocation decisions?

Harish: The first factor – Nifty trailing P/E determines the broad range of equity allocation. Within this range, the trend data is used to arrive at a specific allocation. Thus, if trailing P/E is high, equity allocation would be in lower range, say between 20-40%. Now, even if trend is very favourable, the equity allocation would be capped at the upper limit of 40%, in this example.

WF: We have a situation today where trailing P/E is high, trend in large caps is strong while that in mid and small caps is relatively much weaker. How does your model throw up an asset allocation in today’s circumstances and what is the allocation now?

Harish: While few parameters like 52w high – Low captures the overall trend of broader market which are used in the model, the model by and large uses various parameters of Nifty. At this point of time, equity allocation determined by the model is in range of 35-40%.

WF: What allocation has back tested data thrown up for your model in the last 5 years? How does this compare with a single factor model based only on trailing P/E?

Harish: The net equity allocation over the last 5 years is show below

We know from intuition, that markets can continue to remain expensive or cheap for long periods of time, which is why too primary factor of valuations, we add the trend variable. Let us take an example of Aug 2015 to Feb 2016. This was a period where concerns on China lead to significant fall in currencies and commodities. During this period (Aug end 2015 – Feb end 2016), Nifty corrected by 12% and trailing Nifty P/E corrected by 14%. However, as the trend factors warranted a significantly higher allocation, net equity of the model moved from 50% to 78% during the same period. A single factor model would also have increased allocation, but the extent of increase was magnified by use the second factor.

WF: What return numbers has back tested data thrown up for your model in the last 5 years and how does that compare with the market indices and BAF category average?

Harish: It won’t be fair to compare back-tested results of the model with others in the category as it is based on assumptions and past data. However, what can be observed is that the model’s 5 year daily rolling returns since September 2004 displays that on an average the corpus doubles in 5-8 years whereas it would take 9-12 years (assuming 8% & 6% pa. respectively) for a traditional investment such as FDs to double. The results also display that it helps iron out the volatility through asset allocation over a longer time horizon of 5 years. Please refer the fund presentation on the website for the detailed results along with all the assumptions and disclaimers. This will help understand the working of the fund better and in no way should be construed as any indication of future returns which is dependent on lot of market variables.

WF: What is the strategy for your equity and debt components? Which of your existing funds do they closely resemble in terms of style and strategy?

Harish: The mandate of this fund is to manage monies in a conservative fashion, which is why we have chosen a conservative range of 20-80% of net equity allocation for the fund. Each of the individual asset classes will also be managed in a conservative fashion. The core equity is managed from a universe of Top 150 stocks at most points of time. In occasions when the model suggests higher equity allocation (60-80%), we would incrementally be increasing allocations to midcaps. The strategy would be similar to a multicap offering, like Kotak Standard Multicap Fund (erstwhile Kotak Select Focus Fund). On core debt portion, again the endeavour is to conservatively manage the same, with relatively low maturity profile and high grade paper at most points in time. Occasionally, as the view emerges of a significant fall in yields, the fund has the flexibility of taking duration calls as well. This will be closer to Kotak Short Term Fund.

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