New strategies:
#295 – Seasonality Effect in Anomalies
Period of rebalancing: monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Very complex strategy
Bactest period: 1963-2011
Indicative performance: 17.88%
Estimated volatility: 17.01%
Source paper:
Keloharju, Linnainmaa, Nyberg: Return Seasonalities
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2224246
Abstract:
A strategy that selects stocks based on their historical same-calendar-month returns earns an average return of 13% per year. We document similar return seasonalities in anomalies, commodities, international stock market indices, and at the daily frequency. The seasonalities overwhelm unconditional differences in expected returns. The correlations between different seasonality strategies are modest, suggesting that they emanate from different systematic factors. Our results suggest that seasonalities are not a distinct class of anomalies that requires an explanation of its own – rather, they are intertwined with other return anomalies through shared systematic factors. A theory that is able to explain the risks behind any systematic factor is thus likely able to explain a part of the seasonalities.
#296 – Management Diversity Strategy
Period of rebalancing: yearly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Complex strategy
Bactest period: 2002-2014
Indicative performance: 8.47%
Estimated volatility: 9.81%
Source paper:
Manconi, Rizzo, Spalt: Diversity Investing
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2706550
Abstract:
Using a new dataset on more than 50,000 top executives in US firms from 2002 to 2014, we show that top management team diversity — a new text-based measure of how diverse managers are in terms of personal characteristics and prior experiences — matters for stock returns. Firms with diverse management teams have significantly higher risk-adjusted returns than firms with homogenous management teams. A long-short strategy on the diversity characteristic yields higher risk-adjusted returns, and higher Sharpe ratios, than most leading asset pricing anomalies over our sample period. Diversity returns are driven by large-cap stocks and the long leg of the strategy, so diversity investing seems feasible for investors. Additional results suggest the large returns to diversity investing are due to (i) diversity being a new dimension of "quality" stocks and (ii) mispricing.
New research paper related to existing strategies:
#26 – Value (Book-to-Market) Anomaly
Kok, Ribando, Sloan: Facts About Formulaic Value Investing
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2716542
Abstract:
The term ‘value investing’ is increasingly being adopted by quantitative investment strategies that use ratios of simple fundamental metrics (e.g., book value, earnings) to market price. A hallmark of such strategies is that they do not involve a good faith effort to determine the intrinsic value of the underlying securities. We document two facts about such strategies. First, we see little compelling evidence that such strategies deliver superior investment performance for U.S. equities. Second, instead of identifying undervalued securities, these strategies typically identify firms with temporarily inflated accounting numbers. We argue that these strategies should not be confused with value strategies that are based on a good faith effort to determine the intrinsic value of the underlying securities.
#210 – Adaptive Asset Allocation
Zakamulin: Optimal Dynamic Portfolio Risk Management
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2679498
Abstract:
Numerous econometric studies report that financial asset volatilities and correlations are time-varying and predictable. Over the recent decade, this knowledge has stimulated an increasing interest in various dynamic portfolio risk control techniques. The two basic types of risk control techniques are: risk control across assets and risk control over time. At present, the two types of risk control techniques are not implemented simultaneously. Surprisingly little has been done from a theoretical perspective in terms of studying the optimal dynamic portfolio risk management. In this paper we fill this gap in the literature by formulating and solving the multi-period portfolio choice problem of an investor with mean-variance preferences. In terms of dynamic portfolio risk control, our solution shows that it is optimal to control portfolio risk both across assets and over time simultaneously. Using several datasets and performing out-of-sample simulations, we demonstrate the superiority of dynamic portfolio risk control both across assets and over time. Specifically, we show that portfolios with risk control only across assets outperform the equally-weighted portfolios and that portfolios with risk control both across assets and over time outperform portfolios with risk control across assets only.
Two additional related research paper have been included into existing free strategy reviews during last 2 week:
Related to Private Equity and Value investing:
Stafford: Replicating Private Equity with Value Investing, Homemade Leverage, and Hold-to-Maturity Accounting
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2720479
Abstract:
Private equity funds tend to select relatively small firms with low EBITDA multiples. Publicly traded equities with these characteristics have high risk-adjusted returns after controlling for common factors typically associated with value stocks. Hold-to-maturity accounting of portfolio net asset value eliminates the majority of measured risk. A passive portfolio of small, low EBITDA multiple stocks with modest amounts of leverage and hold-to-maturity accounting of net asset value produces an unconditional return distribution that is highly consistent with that of the pre-fee aggregate private equity index. The passive replicating strategy represents an economically large improvement in risk- and liquidity-adjusted returns over direct allocations to private equity funds, which charge average fees of 6% per year.
#41 – Turn of the Month in Equity Indexes
Giovanis: The Turn-of-the-Month-Effect: Evidence from Periodic Generalized Autoregressive Conditional Heteroskedasticity (PGARCH) Model
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2584213
Abstract:
The current study examines the turn of the month effect on stock returns in 20 countries. This will allow us to explore whether the seasonal patterns usually found in global data; America, Australia, Europe and Asia. Ordinary Least Squares (OLS) is problematic as it leads to unreliable estimations; because of the autocorrelation and Autoregressive Conditional Heteroskedasticity (ARCH) effects existence. For this reason Generalized GARCH models are estimated. Two approaches are followed. The first is the symmetric Generalized ARCH (1,1) model. However, previous studies found that volatility tends to increase more when the stock market index decreases than when the stock market index increases by the same amount. In addition there is higher seasonality in volatility rather on average returns. For this reason the Periodic-GARCH (1,1) is estimated. The findings support the persistence of the specific calendar effect in 19 out of 20 countries examined.
