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Volatility Effects

Reward goes with risk, and volatility represents risk. Therefore, volatility means reward; investors/traders get paid for riding roller coasters. Right? These blog entries relate to volatility effects.

Exploit U.S. Stock Market Dips with Margin?

A subscriber requested evaluation of a strategy that seeks to exploit U.S stock market reversion after dips by temporarily applying margin. Specifically, the strategy:

  • At all times holds the U.S. stock market.
  • When the stock market closes down more than 7% from its high over the past year, augments stock market holdings by applying 50% margin.
  • Closes each margin position after two months.

To investigate, we assume:

  • The S&P 500 Index represents the U.S. stock market for calculating drawdown over the past year (252 trading days).
  • SPDR S&P 500 (SPY) represents the market from a portfolio perspective.
  • We start a margin augmentation at the same daily close as the drawdown signal by slightly anticipating the drawdown at the close.
  • 50% margin is set at the opening of each augmentation and there is no rebalancing to maintain 50% margin during the two months (42 trading days) it is open.
  • If S&P 500 Index drawdown over the past year is still greater than 7% after ending a margin augmentation, we start a new margin augmentation at the next close.
  • Baseline margin interest is U.S. Treasury bill (T-bill) yield plus 1%, debited daily.
  • Baseline one-way trading frictions for starting and ending margin augmentations are 0.1% of margin account value.
  • There are no tax implications of trading.

We use buying and holding SPY without margin augmentation as a benchmark. Using daily levels of the S&P 500 Index, daily dividend-adjusted SPY prices and daily T-bill yields from the end of January 1993 (limited by SPY) through May 2020, we find that: Keep Reading

Rational Uses of Leveraged and Inverse ETPs

What are rational uses of leveraged and inverse exchange-traded products (ETP), which offer easy access to amplified positions in various benchmark indexes spanning stocks, bonds, commodities and volatility? In their April 2020 paper entitled “Levered and Inverse ETPs: Blessing or Curse?”, Colby Pessina and Robert Whaley review the mechanics of leveraged and inverse ETPs, simulate their expected performance of those based on six popular benchmarks and document actual performance of 35 ETPs. They employ Monte Carlo simulations assuming normally distributed log returns for underlying indexes, with mean and standard deviation estimates based on historical daily returns during December 20, 2005 through March 13, 2020. Using simulation inputs as specified and data for 35 actual ETPs as available through mid-March 2020, they find that:

Keep Reading

Best Stock Portfolio Styles During and After Crashes

Are there equity styles that tend to perform relatively well during and after stock market crashes? In their April 2020 paper entitled “Equity Styles and the Spanish Flu”, Guido Baltussen and Pim van Vliet examine equity style returns around the Spanish Flu pandemic of 1918-1919 and five earlier deep U.S. stock market corrections (-20% to -25%) in 1907, 1903, 1893, 1884 and 1873. They construct three factors by:

  1. Separating stocks into halves based on market capitalization.
  2. Sorting the big half only into thirds based on dividend yield as a value proxy, 36-month past volatility or return from 12 months ago to one month ago. They focus on big stocks to avoid illiquidity concerns for the small half.
  3. Forming long-only, capitalization-weighted factor portfolios that hold the third of big stocks with the highest dividends (HighDiv), lowest past volatilities (Lowvol) or highest past returns (Mom).

They also test a multi-style strategy combining Lowvol, Mom and HighDiv criteria (Lowvol+) and a size factor calculated as capitalization-weighted returns for the small group (Small). Using data for all listed U.S. stocks during the selected crashes, they find that: Keep Reading

Comparing Ivy 5 Allocation Strategy Variations

A subscriber requested comparison of four variations of an “Ivy 5” asset class allocation strategy, as follows:

  1. Ivy 5 EW: Assign equal weight (EW), meaning 20%, to each of the five positions and rebalance annually.
  2. Ivy 5 EW + SMA10: Same as Ivy 5 EW, but take to cash any position for which the asset is below its 10-month simple moving average (SMA10).
  3. Ivy 5 Volatility Cap: Allocate to each position a percentage up to 20% such that the position has an expected annualized volatility of no more than 10% based on daily volatility over the past month, recalculated monthly. If under 20%, allocate the balance of the position to cash.
  4. Ivy 5 Volatility Cap + SMA10: Same as Ivy 5 Volatility Cap, but take completely to cash any position for which the asset is below its SMA10.

To perform the tests, we employ the following five asset class proxies:

iShares 7-10 Year Treasury Bond (IEF)
SPDR S&P 500 (SPY)
Vanguard REIT ETF (VNQ)
iShares MSCI EAFE Index (EFA)
PowerShares DB Commodity Index Tracking (DBC)

We consider monthly performance statistics, annual performance statistics, and full-sample compound annual growth rate (CAGR) and maximum drawdown (MaxDD). Annual Sharpe ratio uses average monthly yield on 3-month U.S. Treasury bills (T-bills) as the risk-free rate. The DBC series in combination with the SMA10 rule are limiting with respect to sample start date and the first return calculations. Using daily and monthly dividend-adjusted closing prices for the five asset class proxies and T-bill yield as return on cash during February 2006 through March 2020, we find that:

Keep Reading

Shorting VXX with Crash Protection

Does shorting the iPath S&P 500 VIX Short-Term Futures ETN (VXX) with crash protection (attempting to capture the equity volatility risk premium safely) work? To investigate, we apply crash protection rules to three VXX shorting scenarios:

  1. Let It Ride – shorting an initial amount of VXX and letting this position ride indefinitely.
  2. Fixed Reset – shorting a fixed amount of VXX and continually resetting this fixed position (so the short position does not become very small or very large).
  3. Gain/Loss Adjusted – shorting an initial amount of VXX and adjusting the size of the short position according to periodic gains/losses.

We consider two simple monthly crash protection rules based on the assumption that volatility changes are somewhat persistent, as follows:

  • Prior Month Positive Rule – short VXX (go to cash) when the prior-month short VXX return is positive (negative).
  • Prior Week Positive Rule – short VXX (go to cash) when the prior-week short VXX return is positive (negative).

For tractability, we ignore trading frictions, costs of shorting and return on retained cash from shorting gains. Using monthly closes for the S&P 500 Volatility Index (VIX) and monthly and weekly reverse split-adjusted closing prices for VXX from February 2009 through March 2020, we find that: Keep Reading

The Low-down on Low-risk Investing

Low-risk investment strategies buy or overweight low-risk assets and sell or underweight high-risk assets. Growth in low-risk investing is stimulating much pro and con debate in the financial community. Which assertions are valid, and which are not? In their February 2020 paper entitled “Fact and Fiction about Low-Risk Investing”, Ron Alquist, Andrea Frazzini, Antti Ilmanen and Lasse Pedersen identify five facts and five fictions about low-risk investing. They employ long-short U.S. stock portfolio strategies to illustrate relative performance of low-risk versus high-risk assets. They consider six statistical and four fundamental risk metrics, emphasizing differences between dollar-neutral and market-neutral strategy designs. Focusing on a few prominent low-risk metrics, they compare performances of low-risk strategies to those based on conventional size, value, profitability, investment and momentum factors. Using daily returns for U.S. stocks since January 1931 and firm fundamental data since January 1957, all through August 2019, they find that:

Keep Reading

Simple Volatility Harvesting?

Findings in “Add Stop-gain to Asset Class Momentum Strategy?” suggest that systematic capture of upside volatility may enhance the base strategy. Does this conclusion hold for a simpler application to a single liquid asset over a longer sample period? To investigate, we apply a stop-gain rule to SPDR S&P 500 (SPY) that: (1) exits SPY if its intra-month return exceeds a specified threshold (sacrificing any dividend paid that month); and, (2) re-enters SPY at the end of the month. We also look at a corresponding stop-loss rule. Using monthly unadjusted highs, lows and closes (for stop-gain and stop-loss calculations) and dividend-adjusted closes (for return calculations) for SPY during February 1993 through February 2020, we find that:

Keep Reading

Characterizing S&P 500 Index Bear Market Rallies

A subscriber asked about frequency, magnitude and duration of bear market rallies. To investigate, we employ the S&P 500 Index and consider three ways to define a bear market:

  1. From the day the index is first down over 20% from a prior peak until the day it closes no more than 20% down (< -20% Drawdown).
  2. From the day the index is first down over 30% from a prior peak until the day it closes nor more than 30% down (< -30% Drawdown).
  3. From the day the index crosses below its 200-day simple moving average until the day it crosses back above this moving average (SMA200).

Based on bear market statistics for these three definitions, we then look at ways to characterize bear market rallies. Using daily S&P 500 Index closes from the end of December 1927 through March 2020, we find that: Keep Reading

Update on Shorting Leveraged ETF Pairs

“Monthly Rebalanced Shorting of Leveraged ETF Pairs” finds that shorting some pairs of leveraged ETFs may be attractive. How has the strategy worked recently and how sensitive are findings to execution costs? To investigate, we consider three pairs of monthly reset equal short positions in:

  1. ProShares Ultra S&P500 (SSO) and ProShares UltraShort S&P500 (SDS)
  2. ProShares UltraPro S&P500 (UPRO) and ProShares UltraPro Short S&P500 (SPXU)
  3. ProShares UltraPro QQQ (TQQQ) and ProShares UltraPro Short QQQ (SQQQ)

We take initially, and at the end of each month renew, a -$100,000 short position in each pair member. This strategy generates an initial $200,000 cash in the portfolio and subsequently adds to or subtracts from this cash monthly based on short position performance. We initially assume return on cash covers any costs (transaction fees, bid/ask spread and interest on borrowed positions), but then test sensitivity to net carrying cost. Using monthly adjusted closes for these ETFs from respective inceptions through January 2020, we find that: Keep Reading

Exploiting Liquidity Needs of Futures-based ETFs

Has growth in futures-based exchange-traded funds (ETF) predictably affected pricing of underlying assets? In his November 2019 paper entitled “Passive Funds Actively Affect Prices: Evidence from the Largest ETF Markets”, Karamfil Todorov investigates impacts of ETF trading on pricing of futures on equity volatility (VIX) and commodities, the two asset classes most dominated by ETFs. He decomposes sources of these impacts into three rebalancing needs: (1) rolling of futures contracts as they expire; (2) inflow/outflow of investor funds; and, (3) maintenance of constant daily leverage. By modeling the fundamental value of VIX futures contracts using S&P 500 Index and VIX option prices, he quantifies non-fundamental ETF rebalancing impacts on VIX futures prices. Finally, he tests a strategy to exploit the need for daily leverage rebalancing by trading against it. Specifically, he approximates daily liquidity provision by each intraday reforming portfolios that short a pair of long and short futures-based ETFs on the same underlying asset (volatility, natural gas, gold or silver). In other words, he shorts at the open and covers at the close each day. Using daily data for selected ETFs and their underlying futures for VIX, U.S. natural gas, silver, gold and oil as available during January 2000 through December 2018, he finds that: Keep Reading

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