Be an Alpha in Nifty

Alpha in the investing world implies the delta from the expected returns that one can generate from their returns. So if the Nifty index is expected to give an annual CAGR of 12%, and an investment strategy on a similar equity instrument gives 15% returns, then you have a positive alpha. There are of course some additional risk factors (termed Beta) that are connected to come up with the actual ratio.

Expected Return = ¹Risk Free Return + ²Beta x (Equity Market Average Return – Risk Free return)

Alpha then equates to {Real Return – Expected Return}

1. ** Risk-free return could be measured for say from Government Securities ↩︎
2. ** Beta is the risk factor, > 1 implies more risky and aggressive, while < 1 is a less risky and defensive strategy for the instrument. ↩︎

A SIP in the Nifty index would approximately end your investment in zero Alpha in the long term. Yes, it’s a safe bet from an equity risk-reward perspective, but can we do better by timing the market? Okay, no one could precisely time the market, even the greatest of investors resigned to this fact. But what I’m going to show is not just blind speculative bets for timing, but some degree of attempt at timing based on factual numbers. Historical evidences are no guarantees, but I partly agree with it. Many have stayed hung up with the belief that “This time it will be different”, but some things never change! (Check out my post on SAME AS EVER!)

Two very interesting charts will be central to this discussion.

The first one is the historical PE chart of the Nifty50 index which gives the PE variations over time as the price moved up over the last two decades. [Source]

The second one is the Rolling Returns for Nifty50 index over a 3-year window, which gives an impression of what would be your portfolio growth on every 3-year investment timeframe. [Source]

Observations –

• [Snapshot 1] The PE ratio oscillates over time around the Median, wherein the market goes into overbought (upward of Median) or oversold (downward of Median) zones.
• [Snapshot 2] On average, Nifty50 gives 12-13% returns, but there are certain spikes where it has touched 20% or higher.

So when we talk of generating higher alpha returns, can we infer some patterns (at least in many, if not all) where it aligns with the historical facts? For that, let’s interleave both charts and draw some correlation lines of the PE of Nifty50 at the start time of the investment horizon to the Rolling returns at the end time of investment horizon.

What each Green line above correlates is that if one had invested at a PE level below the historical median, there is a high probability of alpha returns. For the sake of this depiction, I have marked points where Nifty 3-year returns touch above 20%. This is significantly more than the average 12% return which is expected over a longer period. Similarly, the Red lines correlate the converse i.e. when the investment was done at PE levels above the historical PE median, those have a high correlation with 3-year zero or negative returns.

As many of you would have already got the obvious, Nifty PE levels just cannot be ignored. They are strong indicators of stock price valuations. But am I suggesting just buying and selling off in those correlation points? No, not at all! What I’m talking here is about building incremental alpha investments.

• Significantly bump up investments either through add-on SIP or lumpsum at the GREEN PE zones.
• Lighten up investment (either continue with SIP, but avoid lumpsum investments at the RED PE zones.

Staying in the market always rewards in the long term. But being smart in the interim by varying your investment bets makes for a more lucrative appreciation. Be brave at times of PE dips, never let go of that opportunity. Because the market always self-corrects. A high PE comes down only due to two reasons –

• The stock earnings outpace the stock price appreciation.
• The stock price comes down.

And in both scenarios, it keeps giving newer opportunities to tap into the GREEN zone. The discipline is to avoid FOMO and wait for those opportunity points.

A final thought – a question would arise as to why I chose a 3-year rolling window interval, instead of a shorter window, or a larger window (say, 5-7 years). My reasoning for both of them would be –

• A shorter 1-2 year window has too much volatility to even do any correlation. These are noises in the system and hardly bring any patterns.
• In a larger timeframe, the market anyway averages out. So correlations loosen out too. Here we are talking of correlations to identify mid-term opportunities (which if tapped will tilt the long-term gains significantly).