Market-Implied Cost of Equity (MICE):
Quantification and Implications for Asset Allocation Strategy
Introduction to MICE
The market has a mean-reverting characteristic across the cycle, highlighted by increasing risk premium during period of risk aversion, and vice versa. Valuation ratio, such as P/E or P/B ratio, although useful to gauge the cheapness of a stock or equity market, is a poor market timing tool. This is because valuation ratios capture not only the cost of equity implied by the market, but also changing growth expectation, profitability, and payout ratio. Cheaper stocks could always go cheaper when earnings collapse or expectation of future growth decline. Expensive stocks, such as FAANG, could also become more expensive when the long-term growth outlook improves. Hence, a better indicator needs to be developed for investors to be able to quantify the pure risk premium embedded in the stock prices. After months of brainstorming and research session, Putamen Capital proudly introduce our effort to quantify the Market-Implied Cost of Equity (MICE), a proprietary indicator calculated by our in-house team. MICE aim to give investors a pure market-timing tools with regards to global equity. Investors should buy equities when its MICE is higher than its historical average and is going downward. We also build a systematic trading strategy based on this concept and the result is very encouraging; more on this under the ERP Quant Strategy section. During highly competitive environment today when every edge could make or break an active fund performance, we believe this indicator will help our fund generate positive absolute return across the cycle. In the next few months, we will be incorporating the MICE indicator into a new quantitative equity strategy model, aside our currently running Global Equity Strategy (GES) and Global Equity Relative Strategy (GERS) model.
MICE in Asset Allocation Strategy
Portfolio managers have largely relied on bits of information to gauge the growth expectation and risk premium for a stock. Many of this information is highly subjective and not quantifiable, which result in a sub-optimal portfolio allocation. MICE attempt to quantify both factors and provide a framework of thinking for fundamental managers. For quantitative funds, engineers could use MICE as a valuable input to model’s allocation decision. For the later approach, at Putamen Capital we build a portfolio strategy based mainly on Equity Risk Premium (ERP) input of our MICE model, whose performance turned out to be much better than we expect. Several implementations of MICE for a fund manager:
• Top down equity allocation based on growth attractiveness, risk, and return
MICE and our measure of Long-Term Growth (LTG) expectation help manager to classify sector and country profile into four quadrants based on risk (cost of equity) and growth. For growth-oriented manager, this means focusing on the top right corner of Chart 1, which includes the high-growth IT sector and several Emerging Market equities. On the other side, energy sector, currently with a negative LTG expectation should be treated closer to a REITS or a fixed-income security. With low oil price and hence lower capex in recent years, energy firms have already paid out 90% of its profit as dividends. This means that energy stock is more akin to a floating-rate bond with the yield fluctuating based on oil prices.
• Return Expectation in Portfolio Construction
In the fourth and fifth section of this report, we provide historical charts of stock prices, ERP, LTG, and 5-year return expectation of each country and sector in our equity universe. By studying historical events since 1990’s, on the following pages we show the annualized 5-year return for every level of ERP that investors should expect. Currently, for most country, ERP is higher than historical average, meaning that investors would be well rewarded by investing in global equities. Our research shows that for today’s ERP level of global equities at 8.1%, investor could expect 6% to 13% annualized return in the following 5 years.
• Sector and country rotation
As the economic cycle turned from bust to boom, portfolio managers would generally shift its allocation weight from defensive to cyclical. By observing MICE, comparing it to history and across other sectors, managers are able to estimate the depth of a cycle and impending turning point.
• Gauging the extremeness of market movement
Our MICE indicator helps manager to get a sense of bullish/bearish sentiment of the market and its turning point. For example, in the current cycle the turning point of global equity was not just prior to COVID-19 rout but rather in late 2018 when ERP is at post-crisis low (Chart 2). Had managers notice the fact that despite stock had been rebounding strongly after the late 2018 correction, ERP has been widening, (s)he would have realized that the peak of market bullish sentiment is turning and allocate more to a defensive strategy.
•Equity movement attribution analysis
Our proprietary calculation decomposes price movement into several factors, with equity risk premium and growth expectation as the major components. By observing the trend in LTG and ERP, investors could quantify the economic cycle in every country in a direct manner and implement a portfolio strategy based on cycle turning points.
• Contrarian market indicator
At Putamen Capital, we monitor 42 countries/regions and 11 equity sectors. Our ERP quant model gives a daily investment recommendation on whether we should be invested in certain countries. By counting the number of country the model recommends, we have an indicator that gauge the bullish/bearish magnitude in the market. Currently, the model recommends investing in over 95% of our country/region universe, implying a very bearish market stance, which from contrarian point of view means a perfect time to invest more in risky assets.
• Screening for equity investment opportunities
We build ERP with the goal of building a systematic trading strategy based on the indicator. However, for fundamental investors, ERP is useful for screening opportunities across equity market based on the deviation of current ERP from its historical average. An ERP close to its historical low warrants caution and vice versa.
Quantification of MICE
Although MICE indicator are based on proprietary quantitative method, there are several underlying economic theories that underlie the model’s decisions. First, the growth of a company/country/sector depends on the amount of investment it made and the return of that investment. The higher the part of profit a company pays to its shareholder, the less it is able to spend for capital expenditures that are important for long-term earnings growth.
Countries such as Australia, Canada, Chile, South Africa, all of which has a large commodity dependence has seen a rising payout ratio this decade, mainly attributable to the declining commodity prices and hence lower investment in the industry. Consequently, we saw the long-term earnings growth of these countries also declining in the past decade. Meanwhile, countries with higher growth and more investment opportunities, such as Turkey, Philippines, India, and China, have seen much lower payout ratio and a relatively higher growth expectation.
The second point is that as a global investor with no capital flow restriction, MICE reflect the cost of equity associated with investing in that country. This includes political, geopolitical, and other risk that commonly affect earnings expectation and/or return required by investors. For most countries, ERP has been fluctuating between 4% to 10% in the past two decades. Note that the much lower U.S. Treasury yield currently means that earnings multiple has to be much higher than it was for equity risk premium to go back to pre-crisis level.
MICE and 5-Year Return Expectation: Sector
In this section and the following, we provide data, as of April 2020, on the latest reading of sector and country payout ratio, Market-Implied Cost of Equity (MICE) and Long-Term Growth (LTG) expectation.
In the next several pages, we show charts on global sector and country’s historical stock price, ERP and LTG for reader to digest the correlation between these moving variables. On the top panel of each pages, we plot each sector/country historical ERP and the subsequent 5-year return, which we hope help investors gauge the risk/return profile of each equity market.
Shown below is the general overview of each sector’s payout ratio, MICE and LTG expectation
Slide through the image below to see the details of each sector stock price, equity risk premium (ERP), long-term growth (LTG) expectation and 5-year expected return.
Shown below is the general overview of each country’s payout ratio, MICE and LTG expectation
Slide through the image below to see the details of each country stock price, equity risk premium (ERP), long-term growth (LTG) expectation and 5-year expected return.
Putamen Capital ERP Quant Strategy
Using ERP as the sole driver of equity allocation strategy, we build a quant model that provides country recommendation based on the expectation of narrowing risk premium and invest that recommendation in an equal-weighted portfolio. For example, if there are twenty countries recommended at the end of the day, then the model will assign 5% allocation for each country to be invested the following day. Although the recommendation is given on a daily basis, the country recommendation does not shift as often. Since June 2003 to end of April 2020, the average turnover for each country is 3.1%, or roughly 136 trades in 4413 trading days. Whenever there is an addition or elimination of a country recommendation, however, the model has to be rebalanced.
In the simulated return, barring any transaction cost, $100 invested in June 2003 would have turned into $7734 at the end of April 2020, 31 times greater relative to the $244 return from the MSCI ACWI benchmark. This translates to 29.3% annualized return during the 17-year period, compared to 5.4% for the benchmark. Moreover, drawdown is reduced to 25% vs 60% for the benchmark.
The model’s rolling downside tracking error, measured as the underperformance of the model on a 2-year rolling basis, also never breached 12%. In plain terms, this mean that investors could expect that at any time they invest in the fund, historically they would not underperform the benchmark by more than 12%.
Long/Short (Pure Alpha) ERP Quant Strategy
We also constructed a pure alpha or long/short strategy derived purely from the ERP indicator. For the short-leg of the portfolio, we use MSCI All Country World index, whereas the long-leg is our ERP Strategy Portfolio.
In the simulated return, barring any transaction cost, $100 invested in June 2003 would have turned into $2941 at the end of April 2020, 12 times greater relative to the $244 return from the MSCI ACWI benchmark. This translates to 22.1% annualized return during the 17-year period, compared to 5.4% for the benchmark. The main attractiveness of this strategy is the much lower standard deviation and drawdown performance, averaging only 11.9% (annualized) and 11.55%, respectively, since June 2003 to April 2020.
Market-Implied Cost of Equity (MICE) and its Equity Risk Premium (ERP) counterpart prove to be highly valuable for both fundamental research and quantitative model’s input. We classify ERP functions into two-fold: first, as an overview of global and country-level risk/return trade-off and second, as an input to portfolio asset allocation strategy.
We believe that the quantification of ERP will further enhance our knowledge and get a better grasp of the market. There are several further research and development that could be expanded from ERP indicator, such as:
– Portfolio optimization using ERP
– ERP-based predictive model on equity return
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