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Investment Factor

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Fama-French three-factor model is an incomplete model for expected returns because its three factors miss much of the variation in average returns related to profitability and investment. The results suggest that the Fama-French three-factor model is likely to fare poorly when applied to portfolios with strong investment tilts. Motivated by those facts, the investment factor was added to the three-factor model because this factor can be utilized to enhance returns. Investment factor (CMA) is the difference between the returns on diversified portfolios of the stocks of low and high investment firms, which are called conservative and aggressive. Sorting portfolios according to their size and investment, in every size quintile, the average return on the portfolio in the lowest investment quintile is much higher than the return on the portfolio in the highest investment quintile. The aforementioned fact can be exploited to construct a profitable investment strategy that longs the portfolio with the lowest investment and, on the other hand, shorts the portfolio with the highest investment.

Fundamental reason

Past data and research proved that a conservative investment portfolio is connected with greater returns compared to an aggressive investment portfolio. To explain it briefly, aggressive investments do not improve returns in the near future, and yet it is questioned if those investments would improve returns in the future. Moreover, looking at the Size-Inv portfolios, estimates suggest that the five-factor model leaves only around 28% of the cross-section variance of expected returns unexplained. This is far less than the variance ratios produced by the Fama-French three-factor model, which are mostly greater than 50% for the Size-Inv portfolio. As a result, the investment factor could and should be used by investors.

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Keywords

stock pickingequity long shortfundamental analysisfactor investingsmart beta

Market Factors

Equities

Confidence in Anomaly's Validity

Moderate

Notes to Confidence in Anomaly's Validity

OOS back-test shows slightly negative performance. It looks, that strategy's alpha is deteriorating in the out-of-sample period.

Period of Rebalancing

Yearly

Number of Traded Instruments

1000

Notes to Number of Traded Instruments

more or less, it depends on investor's need for diversification, source paper uses a sample of 3000 stocks - all NYSE, Amex, and NASDAQ stocks on both CRSP and Compustat with share codes 10 or 11

Complexity Evaluation

Complex

Financial instruments

Stocks

Backtest period from source paper

1963 – 2013

Indicative Performance

3.54%

Notes to Indicative Performance

Annualized average of monthly returns in excess of the one-month Treasury bill rate, data from Table 1, panel C

Notes to Estimated Volatility

not stated

Maximum Drawdown

-19.81%

Notes to Maximum drawdown

not stated

Regions

United States

Simple trading strategy

The investment universe consists of all NYSE, Amex, and NASDAQ stocks. Firstly, stocks are allocated to five Size groups (Small to Big) at the end of each June using NYSE market cap breakpoints. Stocks are allocated independently to five Investment (Inv) groups (Low to High) still using NYSE breakpoints. The intersections of the two sorts produce 25 Size-Inv portfolios. For portfolios formed in June of year t, Inv is the growth of total assets for the fiscal year ending in t-1 divided by total assets at the end of t-1. Long portfolio with the highest Size and simultaneously with the lowest Investment. Short portfolio with the highest Size and simultaneously with the highest Investment. The portfolios are value-weighted.

Hedge for stocks during bear markets

Partially – Based on the source research paper (see Table 4), the strategy has a negative correlation to the equity market, so it is possible that strategy can be maybe used as a hedge/diversification to equity market risk factor during bear markets. An independent backtest is, however, recommended.

Out-of-sample strategy's implementation/validation in QuantConnect's framework(chart, statistics & code)

Related picture

Investment Factor

Source paper

Fama, Eugene F. and French, Kenneth R.: A Five-Factor Asset Pricing Model

Abstract: A five-factor model directed at capturing the size, value, profitability, and investment patterns in average stock returns performs better than the three-factor model of Fama and French (FF 1993). The five-factor model’s main problem is its failure to capture the low average returns on small stocks whose returns behave like those of firms that invest a lot despite low profitability. The model’s performance is not sensitive to the way its factors are defined. With the addition of profitability and investment factors, the value factor of the FF three-factor model becomes redundant for describing average returns in the sample we examine.

Other papers

  • Lu, Stambaugh, Yuan: Anomalies Abroad: Beyond Data Mining

    Abstract: A pre-specified set of nine prominent U.S. equity return anomalies produce significant alphas in Canada, France, Germany, Japan, and the U.K. All of the anomalies are consistently significant across these five countries, whose developed stock markets afford the most extensive data. The anomalies remain significant even in a test that assumes their true alphas equal zero in the U.S. Consistent with the view that anomalies reflect mispricing, idiosyncratic volatility exhibits a strong negative relation to return among stocks that the anomalies collectively identify as overpriced, similar to results in the U.S.

  • Ward, Muller, Semnarayan: Negative Investment Returns in a Developing Market Context

    Abstract: Financial theory posits a positive relationship between the value of investment that firms undertake and subsequent shareholder returns. Surprisingly, recent studies on United States data have found a negative relationship between investment and subsequent shareholder return. This anomaly contravenes the basic theory of investment, as well as traditional capital asset-pricing models, and several conflicting risk-related and behavioural explanations have been suggested by other researchers. South Africa’s developing market is characterised by relatively high arbitrage costs, and high risk conditions, and offers a suitable context to re-examine this anomaly. This study confirms a negative relationship between the value of investment that firms undertake and subsequent shareholder returns in a developing market context. Over the period from December 2004 to December 2016, shares on the Johannesburg Stock Exchange with lower investment rates consistently outperform shares with higher investment rates. The explanation for this anomaly requires further study.

  • Barroso, Maio: The Risk-Return Tradeoff Among Equity Factors

    Abstract: We examine the risk-return trade-off among equity factors. We obtain a positive in-sample risk-return trade-off for the profitability (RMW) and investment (CMA) factors of Fama and French (2015, 2016), while for the market and momentum factors there is a negative relation. The out-of-sample forecasting power (of factor volatility for factor returns) is economically significant for both RMW and CMA: By constructing a trading strategy that relies on such predictability, we obtain annual Sharpe ratios above one and utility gains above 5% per year. We also find weak evidence that the factor variances are negatively correlated with the aggregate equity premium.

  • Poulsen: Does Debt Explain the Investment Premium?

    Abstract: The investment premium -- the finding that firms with low asset growth deliver high average returns -- is an integral part of recent factor models. I document empirically that the investment premium (1) reflects leverage, (2) does not exist among zero-leverage firms, and (3) increases with firms' refinancing intensities. This new evidence challenges prominent explanations of the investment premium including the q-theory of investment and behavioral finance. To explain the evidence, I develop a model in which firms make both optimal investment and financing decisions. The model shows that the investment premium reflects both leverage and refinancing intensities consistent with my empirical findings.

  • Kilic, Yang, Zhang: The Great Divorce Between Investment and Profitability

    Abstract: We study the cross-sectional relation between investment, profitability, and equity returns over the last century. We document that high-profit firms invest more than low-profit firms before the late 1970s but invest less than low-profit firms afterwards. This reversal coincides with the emergence of the investment and profitability asset pricing factors and a corresponding reversal in the two factors' correlation. We link these changes to decreased long-term discount rates, which we document in the data. We develop a model where firms invest in short- and long-term projects. Responding to low discount rates, firms invest more in long-term projects, leading to high investment from low-profit firms and high average factor returns, as we observe in recent decades. The influx of long-term focused firms following the rise of venture capital in the late 1970s may explain the divorce between investment and profitability.

  • Dong: Risk or Mispricing? Cross-Country Evidence on the Cross-Section of Stock Returns

    Abstract: Using a novel collection of market characteristics from 40 countries, this paper test competing explanations behind five major anomalies classified in Hou, Xue, and Zhang (2015): momentum, value-growth, investment, profitability, and trading frictions. Results show that anomaly returns highly correlate with proxies for market efficiency, investor protection, limits-to-arbitrage, and investor irrationality. New to existing studies, results favor a limits-to-arbitrage explanation for momentum effect, and a mispricing explanation for value-growth and investment effects. Results also suggest that profitability effect may be a result of both rational risk pricing and market inefficiency while remain silent on the cause of trading frictions effect. These findings have new implications on return predictability in both U.S. and international markets.

  • Blitz, Baltussen, van Vliet: When Equity Factors Drop Their Shorts

    Abstract: This paper makes a breakdown of common Fama-French style equity factor portfolios into their long and short legs. We find that factor premiums originate in both legs, but that (i) most added value tends to come from the long legs, (ii) the long legs of factors offer more diversification than the short legs, and (iii) the performance of the shorts is generally subsumed by the longs. These results hold across large and small caps, are robust over time, carry over to international equity markets, and cannot be attributed to differences in tail risk. Portfolio tests suggest that the short legs are of limited value to most investors, while the long legs in small caps are most attractive. We also examine recent claims that the value and low-risk factors are subsumed by the new Fama-French factors, and find that this does not hold for the long legs of these factors. Altogether, our findings show that decomposing canonical factors into their long and short legs is crucial for understanding factor premiums and building efficient factor portfolios.

  • Rizova, Savina and Saito, Namiko: Investment and Expected Stock Returns

    Abstract: Valuation theory predicts that, all else equal, expected investment should be negatively related to expected returns. We study the relation between expected investment and expected stock returns globally. We show that recent asset growth is a systematic proxy for future investment not only in the US, but also in developed ex US and emerging markets. Using this proxy, we find a negative investment effect across developed and emerging markets as well as across sectors in those regions, consistent with the prediction of valuation theory. Globally, the effect is much stronger among small caps than large caps and is mainly driven by the underperformance of high investment firms. Examining the different components of asset growth related to raising of capital as well as those related to use of capital, we find that all components contribute to the investment effect.

  • Conlon, Thomas and Cotter, John and Jin, Chenglu: Horizon-Dependent Profitability and Investment Factors: International Evidence

    Abstract: The sensitivity of systematic factors to the return horizon has attracted researchers’ attention, while the horizon effect on profitability and investment has not yet been assessed. In this paper, we investigate the pricing roles of these two factors, using overlapping profitability and investment returns over horizons from 1 month to 5 years. Using different combinations of lefthand-side test portfolios and factors in the US market as well as international data in 6 other regions, we find consistent evidence that profitability appears to be pervasively more important across the majority of horizons. In particular, the profitability factor has significant pricing power in most horizons, while the investment factor is only priced when 2 to 5-year horizons are considered. Japan stands out as an exception, where the profitability or investment factors have no cross-sectional explanatory power for expected returns across the majority of horizons.

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