TCquant is a fundamental, quantitatively-driven fund with monthly rebalancing. Stock selection is based on a blended multifactor model with most weight placed on measures of low-volatility and value. Our backtests indicate this combination of factors has historically yielded the highest risk-adjusted returns over the past thirty years. Perhaps most importantly, the model evaluates equities on a relative basis. Pundit commentary and some measures (e.g. CAPE ratio) suggest that the US stock market is overvalued, but this risk is significantly decreased for the TCquant portfolio.
Quantitative Analysis
The model allows for investing in both bull and bear environments. We prioritize strong balance sheets, but not at the expense of growth. Especially over the past few months, we’ve seen strong balance sheet stocks outperform their weaker peers. The graph below, courtesy of Goldman Sachs and the Daily Shot, illustrates this point.
Strong balance sheet outperformance is a persuasive signal of a late-cycle market. Investors start to flee to safer companies as growth stocks become riskier and monetary policy becomes less accommodative. However, stocks with weak balance sheets outperform during periods of economic expansion, as the markets value growth over safety. This is not a concern for our model. Each period, our PEG ratio has been significantly above that of the S&P despite the TCquant portfolio being underweight technology stocks.
Outside of the focus on value and healthy balance sheets, we prefer companies with historically low risk. This limits our downside exposure, which is particularly important for a fund with monthly rebalancing and a fairly high turnover rate, as is ours. In violation of CAPM (no surprise), stocks with a lower beta actually tend to outperform their risker peers. This is likely the result of irrational decision making among investors. Whatever the reason, when the best of both worlds is available, we take it.
Below is a comparison of $1 invested in our S&P benchmark and a low-volatility ETF based on the S&P (SPLV) since the SPLV’s inception in mid-2011.
Each month, we reevaluate economic conditions and the cycle of the US economy and adjust the weighting given to different sectors accordingly. We act proactively, not reactively.
Qualitative Analysis
After our model provides the top 50 stocks for the month, the equities are further evaluated among their peer group to again maximize relative value. Each stock is considered on its individual merits. We rely heavily on analyst reports to provide clarity on an equity’s expected future performance. The literature has established that analyst recommendations, especially those by top analysts, are excellent predictors of market returns. Where such analysis is unavailable, as is this case for many small-cap stocks we invest in, the equity in question is not penalized. In fact, the semi-strong form of the Efficient Market Hypothesis would suggest that much of our market-beating returns are the result of asymmetric information among investors. The less analysis professionals perform on a stock, the greater the potential for mispricing, and perhaps the more the stock is driven by fundamental levers.
It’s supposedly impossible to beat the market, but that’s the goal. Check back frequently for stock plays and updates on the portfolio’s performance