New strategies:
#456 – Timing High and Low Volatility Equity Factor Strategy
Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Complex strategy
Backtest period: 1963 – 2016
Indicative performance: 12.77%
Estimated volatility: 19.80%
Source paper:
Neo, Poh Ling and Tee, Chyng Wen: Low-Volatility Strategy: Can We Time the Factor?
https://ssrn.com/abstract=3441508
Abstract:
We show that the slope of the volatility decile portfolio’s return profile contains valuable information that can be harvested to time volatility and market condition. During good market condition, high-volatility portfolio produces the highest return, and vice versa. We proceed to devise a volatility timing strategy based on statistical tests on the slope of the volatility decile portfolio return profile. Volatility timing is achieved by being aggressive during strong growth periods, while being conservative during market downturns. Superior performance is obtained, with a 30% increase in Sharpe ratio and an order of magnitude improvement on cumulated wealth. We also demonstrate that stocks in the high-volatility portfolio are more strongly correlated compared to stocks in the low-volatility portfolio. The profitability of the volatility timing strategy can be attributed to holding a diversified portfolio during bear markets, while holding a concentrated growth portfolio during bull markets.
#457 – Momentum Stock Picking Strategy Using RSI Indicator
Period of rebalancing: Daily
Markets traded: equities
Instruments used for trading: stocks
Complexity: Moderately complex strategy
Backtest period: 1998 – 2018
Indicative performance: 2.29%
Estimated volatility: not stated
Source paper:
Hill: Finding Consistent Trends with Strong Momentum – Rsi for Trend-Following and Momentum Strategies
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3412429
Abstract:
Investors and traders typically use the Relative Strength Index (RSI) to find signals that help identify turning points in security prices. This strategy, however, discounts the true nature of the indicator and limits its potential. A breakdown of the RSI formula reveals that its power lies in its ability to identify consistent uptrends with strong momentum. Some practitioners use RSI ranges to identify existing trends and RSI extremes to signal momentum shifts. However, these approaches do not quantify how long RSI should hold its range, how regularly RSI should reach a momentum milestone and, most importantly, if RSI range and momentum indications have predictive value. The goal of this paper is to systematically test RSI range and momentum signals using stocks in the S&P 500. Moreover, this paper will show that the RSI range alone is inadequate because it does not always capture upside momentum. The RSI range measures trend consistency well, but a momentum component is needed to uncover the strongest uptrends. After quantifying and testing, this paper will provide evidence that signals combining an RSI bull range with RSI momentum can foreshadow sizable advances with good success rates. As such, these signals can be part of a successful investing strategy that combines trend-following and momentum.
#458 – End-of-Month Treasury Returns
Period of rebalancing: Daily
Markets traded: bonds
Instruments used for trading: futures, CFDs, bonds, ETFs, forwards, swaps
Complexity: Simple strategy
Backtest period: 1990 – 2018
Indicative performance: 3.96%
Estimated volatility: 7.65%
Source paper:
Hartley, Schwartz: Predictable End-of-Month Treasury Returns
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3440417
Abstract:
We document a distinct pattern in the timing of excess returns on coupon Treasury securities. Average returns are positive and highly significant in the last few days of the month, and are not significantly different from zero at other times. A long Treasury position for just the last few days of each month gives a high annualized Sharpe ratio of around 1. We attribute this pattern to window dressing and portfolio rebalancing. We find evidence in quantities that aggregate insurer transactions contribute to the end-of-month price pattern. In particular life insurers are large net buyers of Treasury securities on benchmark index rebalancing dates.
New research papers related to existing strategies:
#130 – Investment Factor
#224 – Profitability Factor Combined with Value Factor
Kilic, Yang, Zhang: The Great Divorce Between Investment and Profitability
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3447685
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.
#251 – Intraday Momentum in Equities
Li, Sakkas, Urquhart: Intraday Time Series Momentum: International Evidence
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3460965
Abstract:
Gao et al. (2018) provide strong evidence of intraday time-series momentum (ITSM) in US ETFs, in which the first half-hour return of the trading day significantly predicts the last half-hour return. In this paper, we examine the pervasiveness of ITSM around the world by studying 16 developed markets. We find strong economic and statistical evidence of ITSM across markets. Low correlation between them offers substantial diversification benefits to investors. By adopting various portfolio construction techniques we demonstrate that investing in ITSM globally results in superior performance than when investing in individual market ITSM or global passive strategies. A global equally-weighted ITSM portfolio cannot be explained by global equity factors. Instead, it generates significant alphas to which we show that a time-varying factor is a major contributor. We also show that the global ITSM is related to infrequent rebalancing (Bogousslavsky, 2016) and investor inattentiveness (Da et al., 2014).
And two short free blog posts have been published during last 2 weeks:
What is the impact of volatility (and changes in volatility) on popular Currency Momentum and Currency Carry strategies? That’s the topic of recent academic study written by Duc Hong Hoang, which decomposes foreign exchange volatility into two components, namely, secular (long-term) and transitory or mean-reverting (short-term) components. Long term component captures business cycle effects, while short term volatility usually represents funding tightness or shocks. Carry trade strategy is linked (and therefore partially predictable) to long-run volatility while momentum reacts mainly to short-run risks …
Hoang: Long Run and Short Run Risk Premium in Currency Market
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3439109
Abstract:
In this paper, I investigate risk premium of long run and short run volatility component of exchange rate returns in currency market. I find that high interest rate currencies of carry trade strategy load negatively on long run volatility innovation, while low interest rate currencies load positively. Risk price of long run volatility innovation is negative which implies that high carry trade returns are considered as compensation for time varying long run volatility risk. In contrast, risk price of short run volatility innovation is positive. Low interest currencies deliver low returns and high interest rate currencies yield high returns under times of high short run volatility. In terms of momentum strategy, risk price of short run volatility innovation is negative and statistically significant, while risk price of long run component is insignificant. Therefore, long run volatility does not provide any explanation for high returns of currency momentum strategy. High momentum returns, on the other hand are reward for investors to bear short run volatility risk.
Everyone who lived during the 2007 and 2009 crisis knows what the biggest weakness of the equity momentum strategy was. It was right during the spring of 2009 when the financial markets were on its inflection point when the momentum strategy crashed. Right after that inflection point, stocks which were the biggest losers during the previous year performed exceptionally well and caused strong under-performance of classical long-short momentum strategy. How can we prevent this situation from happening again? That’s the topic of our favorite new recent study written by Matthias Hanauer and Steffen Windmueller. They analyze three momentum risk management techniques – idiosyncratic momentum, constant volatility-scaling, and dynamic scaling, to find the remedy for momentum crashes. It’s our recommended read for this week for equity long-short managers …
Matthias Hanauer and Steffen Windmueller: Enhanced Momentum Strategies
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3437919
Abstract:
This paper compares the performance of three momentum risk management techniques proposed in the literature — idiosyncratic momentum, constant volatility-scaling and dynamic scaling. Using data for individual stocks from the U.S. and across 48 international countries, we find that all three approaches decrease momentum crashes, lead to higher risk-adjusted returns and raise break even transaction costs. In a multiple model comparison test that also controls for other factors, idiosyncratic momentum emerges as the best momentum strategy. Finally, we find that the alpha stemming from volatility-scaling is distinctive from the idiosyncratic momentum alpha.
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