Market timing

Better Rebalancing Strategy for Static Asset Allocation Strategies

13.March 2019

An interesting financial academic paper which analyzes an alternative approach to rebalancing of static asset allocation strategies:

Authors: Granger, Harvey, Rattray, Van Hemert

Title: Strategic Rebalancing

Link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3330134

Abstract:

A mechanical rebalancing strategy, such as a monthly or quarterly reallocation towards fixed portfolio weights, is an active strategy. Winning asset classes are sold and losers are bought. During crises, when markets are often trending, this can lead to substantially larger drawdowns than a buy-and-hold strategy. Our paper shows that the negative convexity induced by rebalancing can be substantially mitigated, taking the popular 60-40 stock-bond portfolio as our use case. One alternative is an allocation to a trend-following strategy. The positive convexity of this overlay tends to counter the impact on drawdowns of the mechanical rebalancing strategy. The second alternative we call strategic rebalancing, which uses smart rebalancing timing based on trend-following signals – without a direct allocation to a trend-following strategy. For example, if the trend-following model suggests that stock markets are in a negative trend, rebalancing is delayed.

Notable quotations from the academic research paper:

"A pure buy-and-hold portfolio has the drawback that the asset mix tends to drift over time and, as such, is untenable for investors who seek diversification. However, a stock-bond portfolio that regularly rebalances tends to underperform a buy-and-hold portfolio at times of continued outperformance of one of the assets. Using a simple two-period model, we explain the main intuition behind this effect: rebalancing means selling (relative) winners, and if winners continue to outperform, that detracts from performance.

As stocks typically have more volatile returns than bonds, relative returns tend to be driven by stocks. Hence, of particular interest are episodes with continued negative (absolute and relative) stock performance, such as the 2007-2009 global financial crisis. In Figure 2, we contrast the monthly-rebalanced and buy-and-hold cumulative performance over the financial crisis period, where both start with an initial 60-40 stock-bond capital allocation. The maximum drawdown of the monthly-rebalanced portfolio is 1.2 times (or 5 percentage points) worse than that of the buy-and-hold portfolio, right at the time when financial markets turmoil is greatest.

Rebalanced and not rebalanced portfolio

In earlier work, Granger et al. (2014) formally show that rebalancing is similar to starting with a buy-and-hold portfolio and adding a short straddle (selling both a call and a put option) on the relative value of the portfolio assets. The option-like payoff to rebalancing induces negative convexity by magnifying drawdowns when there are pronounced divergences in asset returns. We show that time-series momentum (or trend) strategies, applied to futures on the same stock and bond markets, are natural complements to a rebalanced portfolio. This is because the trend payoff tends to mimic that of a long straddle option position, or exhibits positive convexity.

Trend exposure and portfolio drawdown

We evaluate how 1-, 3-, and 12-month trend strategies perform during the five worst drawdowns for the 60-40 stock-bond portfolio. Allocating 10% to a trend strategy and 90% to a 60-40 monthly-rebalanced portfolio improves the average drawdown by about 5 percentage points, compared to a 100% allocation to a 60-40 monthly rebalanced portfolio. The trend allocation has no adverse impact on the average return over our sample period. That is, while one would normally expect a drag on the overall (long-term) performance when allocating to a defensive strategy, in our sample, the trend-following premium earned offsets the cost (or insurance premium) paid.

An alternative to a trend allocation is strategically timing and sizing rebalancing trades, which we label strategic rebalancing. We first consider a range of popular heuristic rules, varying the rebalancing frequency, using thresholds, and trading only partially back to the 60-40 asset mix. Such heuristic rules reduce the average maximum drawdown level for the five crises considered by up to 1 percentage point. However, using strategic rebalancing rules based on either the past stock or past stock-bond relative returns gives improvements of 2 to 3 percentage points."


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Why Is Allocation to Trend-Following Strategy So Low?

21.February 2019

Related to all trendfollowing strategies:

Authors: Dugan, Greyserman

Title: Skew and Trend Aversion

Link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3315719

Abstract:

Despite evidence of the benefits to portfolio Sharpe ratio and variance, actual investor allocations to Trend Following strategies are typically 5% or less. Why is there such a significant discrepancy between the optimal allocation and actual allocation to Trend? We investigate known behavioral biases as a potential reason. While decision makers have other reasons to exclude Trend Following from their portfolios, in this paper, we explore loss aversion, recency bias, and the ambiguity effect as they pertain to Trend Following, and we call the combination of the three Trend Aversion. We quantify Trend Aversion and show that these biases are a viable explanation for suboptimal allocations to Trend. We demonstrate a direct connection between quantifications of known behavioral biases and current suboptimal allocations to Trend Following. Recognition of these relationships will help highlight the pitfalls of behavioral biases.

Notable quotations from the academic research paper:

"Investors may have reasons for excluding Trend Following from their portfolios ranging from time-horizon for performance, to drawdowns, to potential capacity issues. However, the strategy's long performance history shows that a meaningful allocation would have increased portfolio Sharpe ratio and reduced portfolio variance, and yet typical investments remain at or below 5%. Some investors have no exposure.

The strategy's quantitative nature, positive skew, and frequent but small losses act in concert to trigger loss aversion, recency bias, and the ambiguity e ffect. We call the combination of the three Trend Aversion.

Sharpe ratio vs. Fraction invested in Trend


Our results show Trend Aversion is a viable explanation of suboptimal allocations to Trend Following. Decades of psychological research show that people mentally inflate losses by a factor of two. In this paper, we demonstrated that a loss multiplier between 1.5 and 2.5 would cause the typical allocation to Trend of 5% in a simple two asset portfolio, in an 11-asset portfolio with random allocations, and in two other 11-asset portfolio constructions with dynamic allocations. We showed that loss aversion can decrease allocators Sharpe ratios by up to 50%. Using lookback windows in a dynamically allocated portfolio, we demonstrated that recency bias drives down allocations to Trend. Finally, we showed that combinations of loss aversion and recency bias also drive Trend allocations to suboptimal levels.

Many investors who are subject to Trend Aversion as a practical matter, for example due to investment committees or reporting structures, are unsure of how to balance Trend Aversion with the bene ts of Trend Following to reach an allocation decision. By establishing a methodology to optimize allocations under loss aversion, we provide a framework which investors can use to formalize their allocation decisions. Investors who are subject to typical loss aversion should permanently allocate at least 5% to Trend Following, while investors whose loss aversion is lower can benefi t substantially by allocating materially more than 5%."


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Currency Hedging with Currency Risk Factors

23.January 2019

A new research paper related to multiple currency risk factors:

#5 – FX Carry Trade
#129 – Dollar Carry Trade

Authors: Opie, Riddiough

Title: Global Currency Hedging with Common Risk Factors

Link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3264531

Abstract:

We propose a novel method for dynamically hedging foreign exchange exposure in international equity and bond portfolios. The method exploits time-series predictability in currency returns that we find emerges from a forecastable component in currency factor returns. The hedging strategy outperforms leading alternative approaches out-of-sample across a large set of performance metrics. Moreover, we find that exploiting the predictability of currency returns via an independent currency portfolio delivers a high risk-adjusted return and provides superior diversification gains to global equity and bond investors relative to currency carry, value, and momentum investment strategies.

Notable quotations from the academic research paper:

"How should global investors manage their foreign exchange (FX) exposure? The classical approach to currency hedging via mean-variance optimization is theoretically appealing and encompasses both risk management and speculative hedging demands. However, this approach, when applied out of sample, suff ers from acute estimation error in currency return forecasts, which leads to poor hedging performance.

In this paper we devise a novel method for dynamically hedging FX exposure using mean-variance optimization, in which we predict currency returns using common currency risk factors.

Recent breakthroughs in international macro- nance have documented that the cross-section of currency returns can be explained as compensation for risk, in a linear two-factor model that includes dollar and carry currency factors. The dollar factor corresponds to the average return of a portfolio of currencies against the U.S. dollar, while the carry factor corresponds to the returns on the currency carry trade.

We take the perspective of a mean-variance U.S. investor who can invest in a portfolio of `G10' developed economies. We adopt the standard assumption that the investor has a predetermined long position in either foreign equities or bonds and desires to optimally manage the FX exposure using forward contracts. We form estimates of currency returns using a conditional version of the two-factor model where both factor returns and factor betas are time-varying.

A related literature provides strong empirical evidence, with underpinning theoretical support, that the dollar and carry factor returns are partly predictable. We exploit this predictability to forecast currency returns. Speci ffically, we estimate factor betas and 1-month ahead dollar and carry factor returns in the time series, and then form expected bilateral currency returns using these estimates. This vector of expected currency returns enters the mean-variance optimizer to produce optimal, currency-speci fic, hedge positions. We update the positions monthly and refer to the approach as Dynamic Currency Factor (DCF) hedging.

currency hedging

We evaluate the performance of DCF hedging, over a 20-year out-of-sample period, against nine leading alternative approaches ranging from naive solutions in which FX exposure is either fully hedged or never hedged, through to the most sophisticated techniques that also adopt mean-variance optimization. We nd DCF hedging generates systematically superior out-of-sample performance compared to all alternative approaches across a range of statistical and economic performance measures for both international equity and bond portfolios. As a preview, in Figure 2 we show the cumulative payoff to a $1 investment in international equity and bond portfolios in January 1997. When adopting DCF hedging, the $1 investment grows to over $5 by July 2017 for the global equity portfolio, and to almost $4 for the global bond portfolio. These values contrast with $2 and $1.5, which a U.S. investor would have obtained, if the FX exposure in the equity or bond portfolios was left unhedged."


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ETFs Increase Correlation of International Equity Markets

4.January 2019

Everybody can see that international equity markets are highly correlated (and especially during past 10-15 years). A new interesting financial research paper shows that ETF arbitrage mechanism is one of the key channels through which U.S. shocks propagate to local economies leading to increased return correlation with the U.S. market:

Authors: Filippou, Gozluklu, Rozental

Title: ETF Arbitrage and International Correlation

Link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3287417

Abstract:

Assets under management of exchange-traded funds (ETF) have been growing significantly, yet the majority of ETF trades still occur on U.S. exchanges. We show that investment decisions of both institutional and retail investors when trading international country ETFs are mostly driven by shocks related to U.S. fundamentals, measured by VIX, rather than local country risks. Investors react only to negative news about local economies. When U.S. economic uncertainty increases, investors leave the country ETF market and switch to Cash ETF products. We demonstrate that ETF arbitrage mechanism is one of the key channels through which U.S. shocks propagate to local economies leading to increased return correlation with the U.S. market both in time-series and cross-sectional dimensions. We find that countries with stronger ETF price-discovery and lower limits to arbitrage tend to have a higher comovement with the U.S. market.

Notable quotations from the academic research paper:

"Signi ficant innovations in financial products made international investments increasingly possible. Over the recent years, exchange-traded funds experienced a double-digit growth in assets under management. Nevertheless, the short-run interdependence of trading across major international ETFs and its association with local and global risk aversion remain understudied. While the majority of earlier studies focuses on direct eff ects of ETFs on the underlying securities in the basket that it tracks, we examine the indirect e ffect of ETF trading as a transmission mechanism of U.S. market shocks to foreign country equity markets.

We provide a view that as the U.S. accommodates the largest share of ETF global trading volume, its market conditions directly impact the decisions of country ETF investors. We show that international ETF market participants trade based on shocks related to U.S. fundamentals rather than local ones, and propagate those shocks to local markets. The shock transmission is performed via ETF arbitrage. We argue that such arbitrage activity is one of the few mechanisms responsible for increasing correlation between the U.S. market and the rest of the world.

This high cross-country correlation limits the ability of investors to cheaply diversify U.S. risk via international ETF investments. In addition, ETFs often provide an easier access to less integrated emerging markets or to countries were direct investments are costly (e.g., Brazil). However, the transmission of U.S. shocks to those markets limits the diversi fication bene ts of emerging market strategies.

correlation

We fi rst test the hypothesis whether country ETF investors react to changes in the U.S. rather than local economic uncertainty, as measured by CBOE Volatility Index (VIX). To this end, we compute order imbalances of retail investors (e.g., Boehmer, Jones, and Zhang, 2017), and trades of di fferent size, capturing high frequency trading (HFT) and institutional trades. Focusing on a large cross-section of 41 countries, we find strong association between ETF order imbalances and U.S. VIX, indicating that international investment decisions are mainly driven by the latter measure, rather than its local counterparts. For example, an increase in the U.S. VIX results in a selling pressure in the country ETF market. Such result is robust to di fferent volatility regimes and is consistent across di fferent types of investors. Asymmetric response analysis confi rms that country ETF investors only react to positive changes in local VIX, which correspond to negative news in the local markets. Moreover, we observe that, when reacting to an increase in U.S. uncertainty, investors switch to safer assets such as cash equivalent ETFs. We also find that investors respond to changes in U.S. political uncertainty di fferently than to economic uncertainty – they leave the U.S. stock market and buy international country-level ETFs. However, they do not react to local political uncertainty and the economic eff ect of political risk is much smaller than of changes in U.S. VIX.

In order to access the impact of ETF arbitrage on correlation of country returns with the U.S. market, we regress daily innovations in such correlation on a proxy for ETF arbitrage during di fferent volatility regimes. We provide time-series evidence that during periods of high volatility in the U.S., an increase in the arbitrage activity by the authorized participant (AP) (as measured by net share creation/redemption) results in an increase in innovation in such daily correlation. We argue that during periods of high volatility in the U.S. market, it is harder for investors to distinguish between noise and fundamental component of the order flow. Consequently, based on wake-up call hypothesis investor may treat U.S. shocks as relevant to their own country and consume such shocks via ETF arbitrage.

We also explain cross-country variation in return correlation with the U.S. market. According to Ben-David, Franzoni, and Moussawi (2018), non-fundamental shocks must be reversed over time. This suggests that if all shocks transmitted from ETF market to local economies were non-fundamental, ETF arbitrage would not contribute towards increased correlation. In contrast, if the price deviation from the NAV is due to faster incorporation of fundamental information in ETF market, then arbitrage should a ffect returns of underlying index, and such e ffect should not be reverted. If such fundamental information is common both to U.S. and local market, one should observe a higher correlation between them.

Consistent with the literature, we argue that ETF transmits both fundamental and noise shocks to the underlying economies. We show that countries that have a higher degree of price discovery in their ETFs have on average a higher correlation with the U.S. market. In these markets fundamental information gets incorporated into ETF prices faster than in the Net Asset Value (NAV), and therefore, market makers closely follow and learn from changes in ETF prices. This is the case when derivative securities price the underlying assets, rather than the other way around. In addition, in order for fundamental shocks to get transmitted to underlying markets, the authorised participants (AP) must engage in arbitrage activity. We find that the lower the limits to ETF arbitrage the higher is the correlation between a country and the U.S. market. Neither the international trade channel nor the business cycles alter this result."


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FOMC Equity Drift Occurs in Periods of High Uncertainty

27.December 2018

A new research paper related mainly to:

#75 – Federal Open Market Committee Meeting Effect in Stocks

Authors: Martello, Ribeiro

Title: Pre-FOMC Announcement Relief

Link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3286745

Abstract:

We show that the pre-FOMC announcement drift in equity returns occurs mostly in periods of high market uncertainty or risk premium. Specifically, this abnormal return is explained by a significant reduction in the risk premium (implied volatility and variance risk premium) prior to the announcement, but only when the risk premium is high, e.g., when it is above its median. Likewise, the magnitude of the FOMC Cycle and other related patterns varies with uncertainty and risk premium. Market uncertainty measures are persistent and are not related to policy uncertainty or expectations. Markets become only marginally stressed in the days prior to the announcement and changes in uncertainty appear to be of lower frequency. We also explain why recent studies suggest that the pre-FOMC drift might have disappeared in the past decade, as this moderation is due to time variation that was also present in older data. Additionally, CAPM only works on FOMC dates when the risk premium is high, e.g., implied vol above its prior median level. The results are robust to different samples and measures of risk premium and uncertainty.

Notable quotations from the academic research paper:

"We show that pre-announcement return drift is associated with significant declines in risk (premium) during times of high risk (premium). Implied volatility and the variance risk premium decrease in the hours before the announcement in an almost perfect mirror image of the increase in market prices. Moreover, we show that the magnitude of the return drift and the decline in risk depends on the level of market implied volatility, or other related variables, days or even weeks prior to the announcement.

Just to exemplify, the average pre-FOMC drift when implied volatility is above its prior median is 109 basis points (bps), while it is only 9.7 bps when it is below its median. In the bottom 20% of implied volatilities, the drift is close to zero or even negative, depending on the specification. Lucca and Moench [2015] also showed the importance of the VIX in their analysis, but here we show that this and other market uncertainty variables are actually essential for a better understanding of the pre-announcement return drift and all FOMC announcement related patterns. Figure 2 replicates a figure in Lucca and Moench [2015] that shows stock market performance around FOMC releases. Here we show that the pre-announcement drift is much stronger in periods of high risk premium and uncertainty.

We also provide clear evidence of investor relief, i.e., a decline in implied volatility or other risk measures, hours before the announcement using intraday information. Panel B of Figure 2 also shows that uncertainty is going down as a mirror image of the realized return. The magnitude of this pre-announcement investor relief also depends on the level of market uncertainty, as it tends to go down more when it is high. Considering the squared value of the VIX as our priced risk proxy, we show that, during high volatility periods, implied variance declines by 103.5 bps in anticipation of the announcement, while during low volatility periods, it rises by insignificant 0.3 bps. Hence, high volatility periods present both higher realized equity returns and greater resolution of market uncertainty hours before pre-scheduled announcements.

FOMC return patterns"


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