Pensions and Investments wrote about the interest pension plans have shown in put writing (seemingly one of the more misunderstood investment strategies out there) in a recent article Funds Go Exotic with Put-write Options to Stem Volatility. I thought the article did a nice job of outlining the

Gary Antonacci popularized dual momentum with an effective and simple approach for dynamic asset allocation: Global Equities Momentum (GEM). Using simulated ETF data series, GEM’s performance over past market conditions can be approximated. For longer investment horizons GEM’s implementation

As readers hear us repeat often, our results tend to be less optimistic than you’ll find elsewhere. We do our best to show backtested results that are as realistic as possible (even though showing results that are as good as possible would probably be better for business). That’s partially a

In the previous article in the series Hidden Markov Models were introduced. They were discussed in the context of the broader class of Markov Models. They were motivated by the need for quantitative traders to have the ability to detect market regimes in order to adjust how their quant strategies

This post documents some of my research on index front running. This trading strategy is simply buying stocks before they are added to indexes that passively managed funds are designed to track. I initially came across this idea through a Bloomberg article, The Hugely Profitable, Wholly Legal Way to

Mean-variance optimization assumes that you can fully describe the risks and returns of assets in a few simple numbers. Extreme market events often cause volatilities and correlations to spike dramatically, but stress testing on an individual asset basis can allow our own biases and oversights to

In the previous article on IBPy Tutorial to implement Python in Interactive Brokers API, I talked about Interactive Brokers, its API and implementing Python codes using IBPy. In this article, I will be talking about implementing python in IB’s C++ API using a wrapper, written by Dr. Hui Liu. About

This is a summary of the recent performance of a number of excellent tactical asset allocation strategies. These strategies are sourced from books, academic papers, and other publications. While we don't (yet) include every published TAA model, these strategies are broadly representative of the

Who wants a steadily rising equity curve with little or no drawdown? I'm sure most traders do, but unfortunately it doesn't usually end up that way. Drawdown is a big part of trading and can be one of the the biggest challenges traders face, so what techniques can we use to potentially

A lot of attention has been paid to share repurchases recently, which makes sense given the amount of money involved. As of June 30th, 2016, there had been almost $450 billion net transferred from companies to shareholders over the trailing twelve months through repurchase programs, very close to

I wrote in a previous article about why we should backtest even end-of-day (daily) strategies with intraday quote data. Otherwise, the performance of such strategies can be inflated. Here is another brilliant example that I came across recently. Consider the oil futures ETF USO and its evil twin,

Managed portfolios that take less risk when volatility is high produce large alphas, substantially increase factor Sharpe ratios, and produce large utility gains for mean-variance investors. We document this for the market, value, momentum, profitability, return on equity, and investment factors in

This paper examines option pricing methods used by investors in the late 19th century. Based on the book called “PUT-AND-CALL” written by Leonard R. Higgins in 1896 and published in 1906 it is shown that investors in that period used routinely the put-call parity for option conversion and static

Time frames are used in order to forecast future price trends. Many traders are missing out on this important aspect of trading by only looking at one time frame when trying to define a trend. Therefore its important to categorize trends as primary, intermediate and short-term trends. As a rule of

If the unemployment rate is higher than three months ago the model exits the stock market and enters the bond market, and re-enters the market when the unemployment rate is equal or lower than where it was three months ago. From 2001 to 2016 switching between bonds and stocks provided significant

How do stock prices react to earnings announcements? Sometimes prices go up, and sometimes they go down. But here is a potentially more interesting question: What is the average performance across all stocks that have an announcement? The question of whether stocks earn excess returns in

In one of my previous posts, I wrote about my framework for choosing ETFs since I wanted a method of choosing the optimal ETFs for expressing my market views. Generally, the framework is to choose an ETF with a low expense ratio, low trading costs, low tracking error, and a tax-advantaged structure.

I was at a recent talk of the Northwest Traders and Technical Analysts group where they presented a VXX strategy with some huge return and drawdown numbers. Trading this would be very difficult. This got me thinking. If I had a strategy like this, how could I tame the numbers? Through the years, I

Time series pervade financial markets and, although some embrace the so-called efficient market hypothesis, stating that current market prices reflect all available information about a security into its price, I am more inclined to think they provide us with a lot of information that we rarely know

I've received several requests for details on the AmiBroker (AB) code and settings used for the backtest shown in my April post: Momentum Rotation 60 Day ROC System Results. That post used the AmiBroker Formula Language (AFL) code from my article in March 2015. That was a long time ago, so here

This is a short post to let QuantStart readers know that I'll be speaking at some events in New York and Singapore over the next couple of months: Wednesday, October 5th 2016, NYC - I'll be talking about "The Quest for Profitability", along with Seong Lee who will be talking

It’s well known that long volatility Exchange Traded Products (ETPs) like VXX, UVXY, and TVIX often experience devastating losses during market quiet spells—even when the value of the VIX is staying relatively stable. These heavy losses occur when the VIX futures that underlie these funds are in

Low volatility funds are some of the best performers in the market these days. As such, they have attracted renewed attention in addition to significant asset flows. (note: a refresher on low volatility investing is here, h.t. Eric Falkenstein). But a question remains — What does the future hold

The investment industry has investors convinced that the only path to better performance is through stock selection. As a result, most investors approach the challenge of portfolio construction exactly backward, and miss out on the most important opportunities to produce differentiated performance.

You can download the ETF metadata I scraped here and the price history here. You can also take a look at the code I used to scrape this data at my Github repository. Why Scrape ETFs? At the investment management firm I worked at, we had teams of people that devoted lots of time just trying to

Many of the tactical asset allocation strategies that we track are designed to only trade at the end of the month. When tracking these strategies for members however, we show the results of trading on other days of the month as well. We don’t do this to show off our backtesting prowess; it’s an

In the first part of this webinar, we will review the most common ways to conduct the task of portfolio optimization with R. After this introduction, we will address some remarks on the modeling of portfolio problems. In the second part, we will demonstrate a revolutionary way to model and solve

The value premium has been talked about in investment circles going all the way back to the 1934 release of Benjamin Graham’s Security Analysis. At its core value investing relies on buying undervalued securities, something every investor can or should be able to intuitively understand. You buy

Many articles expounding upon the risks of ETFs that invest in illiquid assets (high yield bonds, bank loans, emerging markets, etc.) have been published in recent years. While there are additional risks inherent to these ETFs, the ETF structure provides an additional layer of liquidity that is not

Previously on QuantStart we have considered the mathematical underpinnings of State Space Models and Kalman Filters, as well as the application of the pykalman library to a pair of ETFs to dynamically adjust a hedge ratio as a basis for a mean reverting trading strategy. In this article we will

We show that part of the outperformance of low volatility stocks can be explained by a premium for interest rate exposure. Low volatile portfolios have a positive exposure to interest rates, whereas the more volatile stocks have a negative exposure. Incorporating an interest rate premium explains

Imagine you’ve just seen Apple’s most recent return, r, which is Apple’s long-run expected return, \mu^\star, plus some random noise, \epsilon \overset{\scriptscriptstyle \mathrm{iid}}{\sim} \mathrm{N}(0, \, 1): (1) \begin{align*} r &= \mu^\star + \epsilon. \end{align*} You want to use

Morningstar tells us that efforts at taming volatility in a multi-asset class framework generally turns up mixed results among publicly traded funds. Studying 60 products that are labeled “multiasset volatility-protection funds,” a recent Morningstar article reports that “as a group,

Earlier this week, we examined a study that sought to determine whether the publication of academics’ findings on the momentum factor have led to a disappearing premium. To review, Steven Dolvin and Bryan Foltice, authors of the 2016 study “Where Has the Trend Gone? An Update on Momentum Returns

The prospect of being able to successfully anticipate and predict future market returns is irresistible to practitioners and academics alike, although success has proven elusive. Many have fallen short while seeking this “holy grail” of investing. For instance, Goyal and Welch (2008) examined

How many times has MS Excel given you a hard time while building complex models or importing that extra-large data set into the spreadsheet? As a trader, I would love to see crisp formulas in my worksheets and more importantly, I would want that my models are less prone to errors when I am trading

This is a test of a tactical asset allocation strategy from Adam Butler and the excellent team at GestaltU, as described in the paper: Adaptive Asset Allocation: A Primer. The model combines momentum with a minimum variance portfolio to trade a diverse array of global asset classes. The paper is a

Stock market anomalies behave in mysterious ways. Over long periods of time they can provide expected outperformance versus passive indexes, but in the short run they can experience bouts of gut-wrenching underperformance (e.g., value and momentum). What accounts for this sporadic performance and

At Dorsey Wright, we believe momentum can be used as a stand-alone investment strategy, however, combining it with other smart beta factors to which momentum is negatively correlated has its advantages. We have referenced this in previous blog posts, noting that it allows for a portfolio to capture

You would be forgiven for thinking that Moore's law is a law like Newton's laws. It really does seem that as surely as an apple will fall to the ground, so too shall our computers, phones, tablets, and (now) watches capacity increase year-after-year at an exponential rate ... but

Extreme Value Theory (EVT) is busy with understanding the behavior of the distribution, in the extremes. The extreme determine the average, not the reverse. If you understand the extreme, the average follows. But, getting the extreme right is extremely difficult. By construction, you have very few

When carried through a traditional mean-variance optimization process, J.P. Morgan’s capital market assumptions imply a significant overweight to satellite bonds. Many portfolios have significant capital gains as a result of strong equity and fixed income markets over the last 30+ years. However,

Since we are gearing up for our webinar on Trading with Interactive Brokers using Python, I thought it would be very good if give you a brief insight on Interactive Brokers API and using IBPy to implement Python in IB’s TWS. As we proceed Interactive Brokers demo account and IBPy. Towards the end

Momentum is the tendency for assets that have performed well (poorly) in the recent past to continue to perform well (poorly) in the future, at least for a short period of time. Mark Carhart, in his 1997 study “On Persistence in Mutual Fund Performance,” was the first to use momentum, together

From a seasonality standpoint, there isn’t a more reliable time of the year to have a selloff than this week. In the past I have referred to is as “The Weakest Week”. Since 1961 the week following the 3rd Friday in September has produced the most bearish results of any week. Below is a graphic

The world of quantitative finance continues to evolve at a rapid pace. Even in the last four years of the existence of this site the market for quant jobs has shifted significantly. In this article we outline these shifts. The advice on what is likely to be in demand in the next few years will be

Building robust trading strategies that can detect and adapt to market conditions can be a real challenge, and failure to do so can often result in poor trading performance and drawdowns. How can we build more robust trading strategies that adapt to market conditions as they change? Our guest for

We delayed adding the latest strategy to our site (GestaltU’s Adaptive Asset Allocation) for a week due to technical hurdles running the minimum variance component of the strategy in near real-time for members. Historical results on GestaltU’s strategy are exceptional though, and we plan to have

Most people look back at the dot-com bubble and acknowledge valuations were elevated far above historical norms. Investors ignored historically useful fundamentals, such as earnings and book value, and started relying on measures like eyeballs and clicks. Investors really started to believe, “This

A highlight of the 2016 Morningstar ETF Conference was the keynote address by the former leader of U.S. Navy Seal Team Six, Rob O’Neill. Chief O’Neill shared some stories about his training and operations as an elite Navy Seal. The take away lessons from his talk were the importance of