FOMC Equity Drift Occurs in Periods of High Uncertainty Thursday, 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"


Are you looking for more strategies to read about? Check http://quantpedia.com/Screener

Do you want to see an overview of our database of trading strategies? Check https://quantpedia.com/Chart

Do you want to know how we are searching new strategies? Check https://quantpedia.com/Home/How

Do you want to know more about us? Check http://quantpedia.com/Home/About


Follow us on:

Facebook: https://www.facebook.com/quantpedia/

Twitter: https://twitter.com/quantpedia

US Fiscal Cycle and the Dollar Wednesday, 19 December, 2018

A new research paper related mainly to:

#129 - Dollar Carry Trade
#8 -
FX Momentum

Authors: Jiang

Title: US Fiscal Cycle and the Dollar

Link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3278339

Abstract:

When the US fiscal condition is strong, the dollar is strong and continues to appreciate against foreign currencies in the next 3 years. This pattern is unique to the US, explaining 50% of the low-frequency variation in the dollar's value and absorbing the return predictability of the forward premium. In a model with sticky prices, I show this pattern is driven by the comovement between the US fiscal cycle and the US investors' risk appetite: During US expansions, higher US government surpluses increase the nominal value of the dollar, while less risk-averse US investors require lower returns to hold foreign currencies. Consistent with this view, the US fiscal cycle also explains the term premium, the dollar carry trade, the currency return momentum, and the US investors' capital flows.

Notable quotations from the academic research paper:

"The US fiscal cycle lines up with the dollar's value and future return against foreign currencies. Figure 1 plots the US government surplus-to-debt ratio along with the dollar index and the dollar's excess return against foreign currencies in the following 4 quarters. The surplus-to-debt ratio measures the net fraction of its outstanding debt the US government pays down in each quarter, reflecting a slow-moving fiscal cycle. Since the late 1980s, a higher US government surplus-to-debt ratio corresponds to a stronger dollar today and predicts a higher expected return on the dollar in the future.

us dollar cycle

This finding is also unique to the US: Higher government surplus-to-debt ratios do not correlate with higher nominal exchange rates in 8 out of 10 other developed countries, and do not predict higher currency returns in 9 out of 10 other developed countries.

I conjecture that this relationship between the US fiscal cycle and the dollar is driven by two mechanisms. On the one hand, the fiscal theory of the price level shows that currency value reflects the present value of government surpluses. When the US government surpluses are higher, the dollar is stronger. On the other hand, higher US government surpluses indicate US expansions. During expansions US investors require a lower compensation for holding foreign currencies. As foreign currencies have a lower risk premium with respect to the dollar, the dollar has a higher expected return with respect to foreign currencies.

The fiscal theory mechanism a ects the dollar's nominal value, whereas the risk premium mechanism a ffects the dollar's real return. Price stickiness is required to connect the nominal and the real exchange rates. In a reduced-form new-Keynesian model, I derive the dollar's real exchange rate as future cash flows minus future expected returns. Higher government surpluses increase the dollar's cash flows, whereas a lower risk premium of the US investors increases the dollar's expected returns against foreign currencies. In this way, the dollar is a special asset whose cash flow is positively correlated with its expected return. When the US fiscal condition is stronger, the dollar has a higher valuation and a higher expected return.

Because the US investors' risk premium also a ffects other asset returns and capital flows, the comovement between the US fi scal cycle and the risk premium has broader implications. Indeed, it provides an organizing principle for the following asset pricing phenomena:

First, the forward premium puzzle finds that a higher forward premium of the dollar predicts a higher excess return on the dollar in the short run.

Second, a higher US government surplus-to-debt ratio is associated with a lower term premium and a lower Cochrane and Piazzesi (2005) bond factor, both of which measure the risk premium of long-term US government bonds.

Third, Lustig, Roussanov and Verdelhan (2014) construct a dollar carry trade that buys foreign currencies against the dollar whenever the dollar's forward premium is below 0, and shorts foreign currencies against the dollar otherwise. Since the US government surplus-to-debt ratio comoves with the dollar's forward premium, I construct currency portfolios that exploit the time-series variation in the surplus-to-debt ratio. These portfolios have similar Sharpe ratios and explain the abnormal return of the dollar carry trade, providing evidence for the out-of-sample return predictability of the surplus-to-debt ratio.

Fourth, Burnside, Eichenbaum and Rebelo (2011) find momentum e ects in currency returns. My model shows that when the US government fiscal condition improves, the dollar appreciates and is expected to have a higher return in the future. In this way, the US fiscal cycle drives the common variation in past and future currency returns. Consistent with this result, past currency returns no longer predict future currency returns once I control for the US government surplus-to-debt ratio."


Are you looking for more strategies to read about? Check http://quantpedia.com/Screener

Do you want to see an overview of our database of trading strategies? Check https://quantpedia.com/Chart

Do you want to know how we are searching new strategies? Check https://quantpedia.com/Home/How

Do you want to know more about us? Check http://quantpedia.com/Home/About


Follow us on:

Facebook: https://www.facebook.com/quantpedia/

Twitter: https://twitter.com/quantpedia

Are Equity Markets Manipulated? Thursday, 13 December, 2018

We present two interesting research papers written by Bruce Knuteson. He contemplates why the cyclically adjusted price to earnings ratio of the S&P 500 index has been oddly high for the past two decades. He states that persistently strong equity market in US (and therefore also its high valuation in a comparison to history) and also in other developed countries can be an outcome of intraday trading pattern of several huge quant equity long-short funds which aggressively buy in the morning and sell in the afternoon to expand their trading book (or alternatively to simply manipulate market - push prices of stocks in their portfolio up).

Authors: Bruce Knuteson

Title: Information, Impact, Ignorance, Illegality, Investing, and Inequality

Link: https://arxiv.org/pdf/1612.06855.pdf

Abstract:

We note a simple mechanism that may at least partially resolve several outstanding economic puzzles, including why the cyclically adjusted price to ear nings ratio of the S&P 500 index has been oddly high for the past two decades, why gains to capital have outpaced gains to wages, and the persistence of the equity premium.

Notable quotations from the academic research paper:

"In United States equity markets, bid-ask spreads early in the trading day are typically larger than spreads later in the trading day. The price impact of aggressive trades early in the trading day is therefore typically larger than the price impact of equally sized aggressive trades later in the day.

Market makers make wider markets early in the trading day. The market, viewed as an information aggregator, respects the information content of aggressive orders early in the day more than the information content of equally sized aggressive orders later in the day. A repeated sequence of intraday round trips – e.g., buying in the morning and selling in the afternoon, repeated over many days – can therefore be expected to result in net price impact in the direction of the morning trade.

If some market participant (M) performs the same round trip each day – e.g., aggressively buying in the morning and selling in the afternoon – M’s trading will, on average, nudge the market’s midprice in the direction of his morning trading. If M has a large, slowly varying portfolio, the mark to market gains resulting from M’s daily intraday round trip trades can exceed the cost M incurs by crossing the spread twice each day.

In light of the above, it is striking that the returns to the S&P 500 index over the fifteen years spanning 1993 to 2007, inclusive, all came at the start of the trading day. Indeed, Figure 1 of Ref. [M. J. Cooper,  M. T. Cliff,  and H. Gulen (2008), Return Differences Between Trading and Non-trading Hours:  Like Night and Day, URL http://ssrn.com/abstract=1004081] is so striking it calls for a simple explanation. We propose such an explanation. We propose some market participant M, tending to trade in one direction early in the trading day and in the other direction later in the day, has had a much larger long-term effect on United States equity prices than has so far been widely appreciated.

day vs night return"

And:

Authors: Bruce Knuteson

Title: How to Increase Global Wealth Inequality for Fun and Profit

Link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3282845

Abstract:

We point out a simple equities trading strategy that allows a sufficiently large, market-neutral, quantitative hedge fund to achieve outsized returns while simultaneously contributing significantly to increasing global wealth inequality. Overnight and intraday return distributions in major equity indices in the United States, Canada, France, Germany, and Japan suggest a few such firms have been implementing this strategy successfully for more than twenty-five years.

Notable quotations from the academic research paper:

"The Strategy is very simple: construct a large, suitably leveraged, market-neutral equity portfolio and then systematically expand it in the morning and contract it in the afternoon, day after day. The Strategy works because your trading will, on average, move prices in a direction that nets you mark-to-market gains. Bid-ask spreads are wider and depths are thinner near market open than near market close, so aggressive trades early in the trading day move prices more than equally sized aggressive trades later in the day. An intraday round trip (e.g., aggressively buying in the morning and selling in the afternoon) thus nudges the market's midprice in the direction of your morning trading. A reasonable level of daily round-trip trading combined with a suciently large portfolio will therefore produce expected mark-to-market gains exceeding the expected cost of your daily round-trip trading.

Figure 1, which shows cumulative overnight and intraday returns over the past 25 years in six major stock market indices: the S&P 500 index and the NASDAQ Composite index in the United States, Canada's TSX 60, France's CAC 40, Germany's DAX, and Japan's Nikkei 225 [20]. The return pattern in the S&P 500 index was rst pointed out over a decade ago. Similar return patterns have been identi ed in major indices of other developed countries. The only plausible explanation so far advanced for the highly suspicious return patterns in Figure 1 is someone using the Strategy.

day vs. night in other countries

"


Are you looking for more strategies to read about? Check http://quantpedia.com/Screener

Do you want to see an overview of our database of trading strategies? Check https://quantpedia.com/Chart

Do you want to know how we are searching new strategies? Check https://quantpedia.com/Home/How

Do you want to know more about us? Check http://quantpedia.com/Home/About


Follow us on:

Facebook: https://www.facebook.com/quantpedia/

Twitter: https://twitter.com/quantpedia

A Portfolio of Leveraged Exchange Traded Funds vs. Benchmark Asset Allocation Wednesday, 5 December, 2018

A new interesting financial research paper gives an idea to build a diversified portfolio of leveraged ETFs (scaled down to have the same risk as a benchmark asset allocation built from a non-leveraged ETFs) to beat benchmark asset allocation. However, caution is needed as the most of the outperformance is due to inherent leveraged position in bonds because excess ratio of cash in portfolio (which is the result of using leveraged ETFs instead of non-leveraged ETFs) is invested in a short to medium term bonds:

Authors: Trainor, Chhachhi, Brown

Title: A Portfolio of Leveraged Exchange Traded Funds

Link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3272486

Abstract:

Leveraged exchange traded funds (LETFs) are marketed as short-term trading vehicles that magnify the daily returns of an underlying index. With the proliferation of LETFs over the last 10 years, a diversified portfolio that mimics the returns of a 100% investment can be created using only a fraction of the investor’s wealth. Results suggest a portfolio created with LETFs outperforms a portfolio using traditional ETFs by approximately 0.6% to 1.4% annually by investing the excess wealth in a diversified or short to mid-duration bond portfolio. Downside risk is reduced using LETFs because the majority of the LETF portfolio is invested in a relatively safe bond fund.

Notable quotations from the academic research paper:

"Leveraged exchange traded funds (LETFs) were first listed in 2006 by Proshares, although leveraged mutual funds have been around since 1993. Although Proshares introduced +/- 2x products, Direxion upped the leverage ante with +/- 3x funds in late 2008. Because LETFs are designed to return a daily multiple, the constant daily leverage results in uncertain realized leverage over longer periods of time. In general, realized leverage tends to fall over time due to the volatility of returns.

With the expanded scope of the LETF market, it is now possible to create a diversified portfolio of LETFs that mimic a typical investor’s portfolio. By using 2x or even 3x funds, only a fraction of the investor’s portfolio is needed to attain the same exposure an investor has using standard ETFs and/or mutual funds. The downside is the higher expense ratios of LETFs, their internal financing costs, general leverage decay, and trading costs due to needed rebalancing to maintain the correct exposure. The upside is the excess wealth available that can be invested in relatively safe assets, and if the return to the invested excess wealth exceeds the higher cost of LETFs, returns should be enhanced.

This study shows a portfolio using 2x or 3x LETFs outperforms a portfolio using standard ETFs based on the same underlying indexes. This is possible since a 2x needs only 50% while a 3x needs only 33% of the wealth to create the same exposure to the underlying indexes. Even in the low interest environment from 2010-17, a portfolio of 2x LETFs outperforms a portfolio of standard ETFs by 0.9% annually. A portfolio of 3x LETFs outperforms by 1.8% annually.

Simulated LETF returns since 1946 show a portfolio of 2x LETFs can be expected to outperform a standard portfolio by 0.6% while a 3x LETFs outperforms by 1.4% after expenses. The caveat to this strategy is LETF portfolios must be rebalanced as their initial positions deviate from “optimal” asset allocations even faster than standard portfolios. A 10% barrier threshold keeps the risk exposure within reasonable bounds while keeping 2x rebalancing requirements to roughly each quarter and 3x to approximately monthly.

performance table

A critical determinant of the success of this strategy is the magnitude of returns to the capital not invested in the LETFs. This study assumes excess capital is invested in a short-term bond ladder and if the return to this ladder exceeds the borrowing cost from the implied leverage of LETFs and their higher expense ratios, LETF portfolios outperform. Historically, this occurs the majority of the time with 0.6% to 1.4% average annual outperformance with a simultaneous reduction in downside risk."


Are you looking for more strategies to read about? Check http://quantpedia.com/Screener

Do you want to see an overview of our database of trading strategies? Check https://quantpedia.com/Chart

Do you want to know how we are searching new strategies? Check https://quantpedia.com/Home/How

Do you want to know more about us? Check http://quantpedia.com/Home/About


Follow us on:

Facebook: https://www.facebook.com/quantpedia/

Twitter: https://twitter.com/quantpedia

A Turn of the Month Strategy in Asset Allocation Monday, 26 November, 2018

A new research paper related mainly to:

#41 - Turn of the Month in Equity Indexes

Authors: McGroarty, Platanakis, Sakkas, Urquhart

Title: A Seasonality Factor in Asset Allocation

Link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3266285

Abstract:

Motivated by the seasonality found in equity returns, we create a Turn-of-the-Month (ToM) allocation strategy in the U.S. equity market and investigate its value in asset allocation. By using a wide variety of portfolio construction techniques in an attempt to address the impact of estimation risk in the input parameters, we show significant out-of-sample benefits from investing in the ToM factor along with a traditional stock-bond portfolio. The out-of-sample benefits remain significant after taking into account transaction costs and by using different rolling estimation windows indicating that a market timing strategy based on the ToM offers substantial benefits to investors when determining the allocation of assets.

Notable quotations from the academic research paper:

"Seasonality is a well-known characteristic of financial markets with much empirical literature noting various types of seasonality in stock returns. Simple seasonality-driven investment strategies have attracted significant interest from academics and investors over the last forty years.

Amongst the calendar effects, the turn-of-the-month (ToM hereafter) has been acknowledged as one of the strongest and persistent seasonality found in stock returns. The ToM effect is the tendency of the stock market returns to display particularly high returns on the last trading day of the month and the first three trading days of the next month.

This study contributes to the literature on calendar anomalies in several dimensions. We examine the out-of-sample portfolio benefits resulting from adding the ToM portfolio to (i) a traditional equity-bond mix, (ii) a market portfolio, (iii) a portfolio which consists of the market portfolio, the small size portfolio and the value portfolio, and (iv) a portfolio, which consists of the market, the small size, the value portfolio and the winner portfolio.

performance of selected strategies

We employ a wide variety of sophisticated and popular asset allocation techniques to provide robustness to our results. Specifically, we employ the mean-variance (Markowitz) portfolio optimization, portfolio optimization with higher moments, Bayes-Stein shrinkage, Bayesian diffuse-prior portfolio, Black-Litterman and another portfolio construction method that combines individual portfolio techniques, to ensure that our results are not just a peculiar artefact on one particular asset allocation technique. Finally, we assess the ToM for low, medium and high-risk averse investors, as its effectiveness in the portfolio might depend on the investor’s level of risk aversion.

Our empirical evidence suggests that the ToM portfolio adds value when included in different portfolios. Our results hold for different levels of risk aversion, portfolio techniques and estimation windows. Finally, our results are not eliminated by the including realistic transaction cost estimates, indicating that the creation and implementation of a ToM factor should be of great interest and potential value to investors.

allocation to turn of the month strategy"


Are you looking for more strategies to read about? Check http://quantpedia.com/Screener

Do you want to see an overview of our database of trading strategies? Check https://quantpedia.com/Chart

Do you want to know how we are searching new strategies? Check https://quantpedia.com/Home/How

Do you want to know more about us? Check http://quantpedia.com/Home/About


Follow us on:

Facebook: https://www.facebook.com/quantpedia/

Twitter: https://twitter.com/quantpedia