Generalized Recovery

Tail-Risk Protection Trading Strategies

I. Trading Strategy Concept: Short-term momentum patterns with a trend filter. Source: Hill, J. R., Pruitt, G., Hill, L. (2000). The Ultimate Trading Guide. New York, N.Y.: John Wiley & Sons, Inc. Research Goal: To benchmark the Gap Pattern – Type B against the Gap Pattern – Type A.

A new paper from Christian Walkshäusl and Sebastian Lobe* called The Enterprise Multiple Investment Strategy: International Evidence examines the performance of the enterprise multiple (EV/EBITDA) in international markets, including Australia, Canada, France, Germany, hong Kong, Japan, Singapore,

Recent academic papers have shown that low-volatility stocks have provided better returns than higher volatility stocks. What’s more, this is a global phenomenon. These findings, however, run counter to economic theory, which predicts that higher expected risk should be compensated with greater

Buffett’s Asset Allocation Advice: Take it … With a Twist Javier Estrada October 26, 2015 One of the most important decisions retirees need to make is the asset allocation of their portfolios. They can have a static or a dynamic allocation, and simplicity usually favors the former. Warren

This paper describes how to create ex-ante expectation for generalized trend-following rules. This report first study the effect of trend-following rules applied to random data with varying degrees of drift and autocorrelation. There is a positive relationship between drift, autocorrelation and the

Jumps in the VIX during the month of December have (almost) always led to year-end stock market gains. It is the time of year when research houses trot out all matters of bullish seasonal stock market patterns pertaining to year-end. It seems as though each year brings more and more attention, and

Value investing was a lot easier in 2012 and 2013 when our value approach beat the market by a substantial margin and we had a reasonable edge on other active value players. But now that we have lived through 2014 and 2015, most value approaches (simple, complex, quant, human, small, large, etc.)

One of our readers, Corey Hoffstein, told me about an interesting paper, “Investor Attention, Visual Price Pattern, and Momentum Investing”, by Li-Wen Chen and Hsin-Yi Yu. Their basic idea is that investors are drawn to stocks that have attention grabbing behavior. And the thing that most grabs

Another day, another piece of evidence that the stock “market” is not what it may appear to be by looking at the major averages. I place the quotes around market as the word has a very different meaning to us than it seems to have for the superficial market observer – or at least mainstream

Awww…modern portfolio theory…that feel-good construct I teach to all of my graduate-level finance students each year. Simply input 1) a vector of expected returns and 2) a covariance matrix into your computer, and voilà, you have your optimal portfolio weights. Like all things viewed with the

I've previously outlined that high yield credit risk is typically less ideal than simply gaining credit exposure through stocks and rate exposure through bonds. Now Larry Swedroe outlines the case for avoiding investment grade credit risk altogether. There are many well-documented anomalies in

This is the third article in a series looking at the backtest results of selling at-the-money (ATM) options straddles on the Russell 2000 index (RUT). For background on the setup for the backtests, as well as the nomenclature used in the tables below, please see the introductory article for this

As we have discussed many times, much of the “conventional wisdom” on investing is simply wrong. For our purposes, we can define conventional wisdom as those ideas that become so commonly accepted that they go unquestioned. Today we’ll look at the idea that rising interest rates would doom

As I wrote about here, here, here and yes, here (and, um, also here), the holiday season tends to be a good time to invest in the stock market in general and in specific sectors in particular (with that pesky fly in the ointment, monkey in the wrench, pain in the rear caveat that “there are no

Choosing an appropriate performance measure is important for fund investors, nevertheless, many researchers find empirically that the choice of measures does not matter because those measures generate identical rank ordering, even though the distribution of fund returns is non-normal. In this paper

There are many well-documented anomalies in finance. Among them is the surprisingly small return that investors historically have earned for taking credit risk in fixed-income markets—the default premium, as measured by the difference in returns between long-term Treasurys and long-term corporate

First draft of 'JavaScript for Financial Analysts' Chapter 12. ~ Starting JavaScript development is like deciding to support the Yankees or Manchester United. It's got a lot of history; the most money; and the deepest bench of developers, but sometimes, sometimes you wish it was a

Basis-Momentum

Option Return Predictability

In multivariate volatility forecasting (4), we saw how to create a covariance matrix which is driven by few principal components, rather than a complete set of tickers. The advantages of using such factor volatility models are plentiful. First, you don't model each ticker separately, you can

Low Risk Anomalies?

In Search of Alpha - Trading on Limited Investor Attention

Average Skewness Matters!

Ninety Years of Media Coverage and the Cross-Section of Stock Returns

Dash for Cash: Month-End Liquidity Needs and the Predictability of Stock Returns

The best quant mashup links for the week ending Saturday, 12/05 as voted by our readers: Predicting volatility [EP Chan] Announcing the QuantStart Advanced Trading Infrastructure Article Series [Quant Start] Exploring mean reversion and cointegration with Zorro and R: part 1 [Robot Wealth] The

This part is awesome. Trust me! Previously, in Part 1, we examined two independent methods in order to estimate the probability of a very rare event (heavy or extreme loss) that an asset could experience on the next day. The first one was based on the computation of the tail probability, i.e.: given

1. Motivating Example A Popular Goal. Financial economists have been looking for variables that predict stock returns for as long as there have been financial economists. For some recent examples, think about Jegadeesh and Titman (1993), which shows that a stock’s current returns are predicted by

This is how your average buy-and-hold investor probably feels right now if they are looking to deploy new capital for the long run. Today, bond yields are puny while stock valuations are rich. In fact, we currently have one of the worst yield and value combinations in history as seen in the charts

Summary Traditionally, stocks have been used for growth and bonds for safety Therefore, investors looking for long-term capital appreciation tended to allocate heavily towards stocks while investors concerned about preservation allocate more heavily towards bonds With an anemic forecast for equity

This post will outline a first failed attempt at applying the ensemble filter methodology to try and come up with a weighting process on SPY that should theoretically be a gradual process to shift from conviction between a bull market, a bear market, and anywhere in between. This is a follow-up post

Most of what I’ve written about have been equity factors. But factors, persistent price predictors, apply to other investments as well. FactorWave will also offer analyses in volatility, equity options and commodity futures. Volatility Equity volatility (tradeable through the VIX) displays two

Liquidity is valuable to investors. Therefore, investors demand higher expected returns for less liquid stocks. The liquidity of an asset market refers to the ability of investors to buy and sell significant quantities of that asset, quickly, at low cost and without a major price concession. Thus,

First draft of 'JavaScript for Financial Analysts' Chapter 11. ~ Finance is a super slow mo movie of investment decision logic colliding into chaotic markets. The narrow space in between is inhabited by statistics. JavaScript has a capable statistics library called jStat which offers a

Wouter, Butler and Kipnis [2015] recently demonstrated Classical Asset Allocation (CAA) for long only portfolios, based on Markowitz’ concepts. The method uses only two parameters thus minimizing the chances of curve-fitting and data snooping. The parameters are lookback period (12 months) and

Last month’s results for trend following were positive, with a strong performance that took the index back into positive territory for the year. The strategy goes into the last month of the year holding modest gains but 2015 will obviously not be a repeat of the runaway performance from last year.

This series of posts is inspired by several chapters from Ernie Chan’s highly recommended book Algorithmic Trading. The book follows Ernie’s first contribution, Quantitative Trading, and focuses on testing and implementing a number of strategies that exploit measurable market inefficiencies.

A few weeks ago, we discussed a method that we implemented to construct more realistic indices using an estimate of time weighted average prices (TWAP) for trade execution. Prior to October, whenever our models required a rebalance, we assumed that it occurred at the opening price on the following

Linear regression slope is another tool one can use to sidestep potentially sticky situations. The following algorithms hold a full position in SPY but liquidate whenever the slope of closing prices turn negative. Starting Capital of $100,000 and backtest period from 2/2003 and 11/2015. Strategy End

Perhaps it is the different jargon used in different disciplines, not sure. But for some reason, the terms ‘predictions’, ‘forecasts’ and ‘projections’ are frequently used interchangeably. There should be at least some distinction, here is what I entertain: The word ‘predictions’

November 2015 Trend Following: UP +6.06% / YTD: +9.86% The Wisdom trend following index gradually made its way up last month to post a strong result for November, and recover a large part of the losses occurred in October. This helped cement the YTD number further in the black. Now nearly in

There has been a lot of research recently that investigates the link between stock returns and higher moments of the return distribution, specifically the skewness of returns. This link, unfortunately, is frequently ignored by more standard measures of market risk and volatility. Skewness, if

One of the most underestimated feature of the financial asset distributions is their kurtosis. A rough approximation of the asset return distribution by the Normal distribution becomes often an evident exaggeration or misinterpretations of the facts. And we know that. The problem arises if we

While the underperformance of high yield bonds since my post The Case Against High Yield has certainly made high yield bonds more attractive (yields went from sub 6% to north of 8%), I still prefer the risk/return profile of a stock/bond allocation (more here). For those that are looking for a

Our Quantitative Momentum (QM) system seeks to identify stocks with the highest quality “momentum.” We consider the term momentum to mean a continuation of past returns—past winners tend to be future winners, while past losers tend to be future losers. How can we exploit this phenomenon? At

I’ve recently written a few posts about the persistency of cross-sectional momentum. But it seems that eventually stocks that go up have to come down. Not only is this somewhat intuitive, but the existence of stock price reversals is also well documented. But actually momentum persistence and

Everybody knows about the Central Limit Theorem, but have you ever seen a visual demonstration? The central limit theorem states that, given certain conditions, the mean of a large number of iterates of independent random variables, will be approximately normally distributed, regardless of the

To date on QuantStart we have considered two major quantitative backtesting and live trading engines. The first arised from the Event-Drive Backtesting series I wrote back in March 2014. The second is QSForex, an open-source backtest and live trading engine that hooks into the OANDA Forex Broker