Re: Looking for papers on Evidence Based Results for T/A and F/A methods/ideas/hypoth
Seminal paper (if you pick one it should be this): "Value and Momentum Everywhere" by Asness et all
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2174501
We study the returns to value and momentum strategies jointly across eight diverse markets and asset classes. Finding consistent value and momentum premia in every asset class, we further find strong common factor structure among their returns. Value and momentum are more positively correlated across asset classes than passive exposures to the asset classes themselves. However, value and momentum are negatively correlated both within and across asset classes. Our results indicate the presence of common global risks that we characterize with a three factor model. Global funding liquidity risk is a partial source of these patterns, which are identifiable only when examining value and momentum simultaneously across markets. Our findings present a challenge to existing behavioral, institutional, and rational asset pricing theories that largely focus on U.S. equities.
Asness doesn't just research this stuff for fun, he is a big player who co-founded AQR Capital with like ~$120b FUM and good track record since 1998.
But realistically, there are sooooo many papers which cover this stuff, it'd be impossible to build a list which does it justice. So I am picking a few random ones from my notes.
Almost all of these papers are the basis for what happens at the worlds largest hedge funds and most of these names work at one or more of these funds as advisers:
On the value front, nobody has produced more mountains of work than Fama+French, who have their own website full of all the data you could ever need to validate and reproduce their findings.
I would say that allocators like James Montier, John Hussman Cliff Asness and so on represent the culmination of implementing all available information (TA and FA) into a single highly performant strategy. Then there are people like Eric Falkenstein who think everything is wrong and we should all just invest in low volatility (which is also hard to disagree with given his justification).
"The Dao of Corporate Finance, Q Ratios, and Stock Market Crashes" by Mark Spitznagel on Tobins Q and valuations.
"Cape Around the World: Update 2014 – The Relationship between Risk and Return"
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2470935
We update our annual analysis of expected returns for 38 equity markets around the world. Based on current CAPE valuations, we expect mid to high single-digit yearly returns in most developed equity markets. However, risks are elevated for some markets. We specifically investigate drawdown risk and find that given its current valuation levels, the US market in particular exhibits a high risk of significant future drawdowns.
Value Versus Growth: Australian Evidence by Gharghori, Stryjkowski and Veeraraghavan
(you can google "ssrn value premium australia" to see a
huge body of work on this)
"The Cross Section of Expected Holding Period Returns and Their Dynamics: A Present Value Approach"
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2182628 (I really like this approach)
We provide a tractable model of firm-level expected holding period returns using two firm fundamentals ― book-to-market ratio and ROE ― and study the cross-sectional properties of the model-implied expected returns. We find that: 1) firm level expected returns and expected profitability are time-varying, but highly persistent; 2) forecasts of holding period returns strongly predict the cross section of future returns up to three years ahead. We document a highly significant predictive pooled regression slope for future quarterly returns of 0.86, whereas the popular factor-based expected return models have either an insignificant or a significantly negative association with future returns. In supplemental analyses, we show that these forecasts are also informative of the time-series variation in aggregate conditions: 1) for a representative firm, the slope of the conditional expected return curve is more positive in good times, when expected short-run returns are relatively low; 2) the model-implied forecaster of aggregate returns exhibits modest predictive ability. Collectively, we provide a simple, theoretically-motivated, and practically useful approach to estimating multi-period ahead expected returns.
"Enhancing the Investment Performance of Yield-Based Strategies"
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2051101
High dividend yield stocks do not reliably earn above-average risk-adjusted returns. More complete measures of shareholder yield, which account for net share repurchases, perform better. We explore the use of net-debt paydown as a way to further enhance shareholder yield. The addition of net-debt paydown enhances risk-adjusted returns and creates a shareholder yield metric that is more robust over time. We also explore the technique of separating yield metrics by payout percentage as a way to enhance return predictability. We find some evidence that using payout percentage within a yield category can systematically improve portfolio performance.
On the T/A side:
"Relative Strength Strategies for Investing" by Mebane Faber (and the various updates to this paper) e.g.
"A Quantitative Approach to Tactical Asset Allocation"
"Absolute Momentum: a Simple Rule-Based Strategy and Universal Trend-Following Overlay" by Gary Antonacci and related
"Risk Premia Harvesting through Dual Momentum"
"Does trend following work on stocks?" by Cole Wilcox and Eric Crittenden
"Feasible Momentum Strategies Evidence from the Swiss Stock Market" by Rey and Schmid (academics, not traders)
"Residual Momentum" by Blitz, Huij, Martens
"MR Swing: A quantitative system for mean‐reversion and swing trading in market regimes" by Abrams and Walker (this one won some kind of award and AFAIK the system is still in use)
"Momentum and Markowitz" by Keller, Butler, Kipnis
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2606884
Mean-Variance Optimization (MVO) as introduced by Markowitz (1952) is often presented as an elegant but impractical theory. MVO is "an unstable and error-maximizing" procedure (Michaud 1989), and "is nearly always beaten by simple 1/N portfolios" (DeMiguel, 2007). And to quote Ang (2014): "Mean-variance weights perform horribly… The optimal mean-variance portfolio is a complex function of estimated means, volatilities, and correlations of asset returns. There are many parameters to estimate. Optimized mean-variance portfolios can blow up when there are tiny errors in any of these inputs...".
In our opinion, MVO is a great concept, but previous studies were doomed to fail because they allowed for short-sales, and applied poorly specified estimation horizons. For example, Ang used a 60 month formation period for estimation of means and variances, while Asness (2012) clearly demonstrated that prices mean-revert at this time scale, where the best assets in the past often become the worst assets in the future.
In this paper we apply short lookback periods (maximum of 12 months) to estimate MVO parameters in order to best harvest the momentum factor. In addition, we will introduce common-sense constraints, such as long-only portfolio weights, to stabilize the optimization. We also introduce a public implementation of Markowitz's Critical Line Algorithm (CLA) programmed in R to handle the case when the number of assets is much larger than the number of lookback periods.
We call our momentum-based, long-only MVO model Classical Asset Allocation (CAA) and compare its performance against the simple 1/N equal weighted portfolio using various global multi-asset universes over a century of data (Jan 1915-Dec 2014). At the risk of spoiling the ending, we demonstrate that CAA always beats the simple 1/N model by a wide margin.
and so on. Basically, SSRN is your friend. Again, I would stress that this is merely a tiny random selection from my research notes, the amount of research out there is more than anyone could hope to read.