Michael Batnick, Director of Research at Ritholtz Wealth Management, and blogger of the always interesting Irrelevant Investor, recently shared the historical performance of U.S. stocks when they fall below their 200-day moving average, something that occurred early last week (bold mine, quotes

The concept of building “optimal” portfolios—maximizing return and minimizing risk–is a foundational concept in quantitative finance. Unfortunately, it’s not terribly practical. The problem, as many researchers have demonstrated over the years, is the elusive aspect of developing reliable

othing could be further from my intention than to give an extensive mathematical approach to this post but an slightly idea is desirable. In this post we will approach to the problem of convolution from a matricial point of view. Well, what we mean by convolution is about composing 2 different

#100 - Trading WTI/BRENT Spread Authors: Donninger Title: The Poverty of Academic Finance Research: Spread Trading Strategies in the Crude Oil Futures Market Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2617585 Abstract: Harvey, Liu and Zhu argue that probably most of the Cross-Section

The core of capitalism is its extremely democratic nature. The masses crush wily contrarians on a daily basis, The market can stay irrational longer than you can stay solvent Being correct in science however, is never democratic. One contrarian can commit mass killings amongst cherished beliefs.

James Harris Simons has been described as "the world's smartest billionaire", amassing a fortune through the clever use of mathematics and computers. He is now a renowned philanthropist.

The best links of the week ending Saturday, 07/04 as voted by our readers: Fitness Landscape Analysis for Computational Finance [Turing Finance] VIX Trading Strategies in June [Volatility Made Simple] Switching From Stocks to Bonds Based on a 200-day Moving Average Crossover [Price Action Lab]

Can Anomalies Survive Insider Disagreements?

Mispricing Factors

Another down month for the State of Trend Following index. After a fairly good start to the year – until mid-March where the index registered its high for the year – the trend has been fairly clearly down. Possibly a drawdown phase following the very strong performance from 2014 and beginning

June 2015: Trend Following DOWN -4.16% — YTD: +0.89% After a good start to the year, with the first three months being up and the index peaking in mid-March, a downtrend has now taken place. This has built a drawdown roughly equal to a third of the Max Drawdown figure (12% vs 34%), which is not

Defining and Dating Bull and Bear Markets: Two Centuries of Evidence

Factor Investing Revisited

As of pixel time the VIX is up over 7% and the S&P 500 is basically unchanged; we feel this situation arises when traders desire protection today for the possibility of danger tomorrow. In other words, the price of risk is rising and markets are stabilizing. Intuitively (i.e. the feeling our rat

Here is one of the figures in a Journal of Finance paper published in 2013 by N. Garleanu and L Pedersen. The figure depicts various portfolio optimizations under different assumptions and then has a visualization equivalent with hockey players, skeet shooters, and missile systems. I’m not sure

Most time series techniques such as the ADF test for stationarity, Johansen test for cointegration, or ARIMA model for returns prediction, assume that our data points are collected at regular intervals. In traders' parlance, it assumes bar data with fixed bar length. It is easy to see that this

We mentioned in a post yesterday on 90% Down Days that one of the challenges for risk managers is to correctly distinguish a minor market “dip” from something that is developing into a more serious decline. One potential aid in addressing that challenge comes from the behavior of the S&P 500

The holy grail of financial markets is finding strategies that have misaligned risk and reward characteristics. In the traditional view, investors try to do the following: Identify strategies that have high returns, then… find ways to get the exposure with the lowest risk possible. However, there

In last week's article we looked at Time Series Analysis as a means of helping us create trading strategies. In this article we are going to look at one of the most important aspects of time series, namely serial correlation (also known as autocorrelation). Before we dive into the definition of

During the last several posts, we expanded our Iron Condor exit analysis to include results where trades were held to higher loss thresholds. You can review both the first and second sets of articles at the following pages: Dynamic Exit Iron Condor Articles High Loss Threshold Iron Condor Articles

It is commonly believed that option markets are “smarter” than equity markets. There could be several reasons for this. Trading options is mathematically complex. It involves estimating volatility, solving differential equations and devising hedging algorithms. It is true that most professional

A few times over the years I have shared this study. It breaks down the bullish “1st trading day of the month” tendency by month. I thought it would be interesting to take another look at it today. Below is an updated version of the study orginally shown here on July 1, 2009. July has continued

“Is this to end or just begin?” - All My Love by Led Zeppelin As risk managers, one of the challenges is to determine whether a market pullback is just a minor dip or a precursor to a larger decline. The correct interpretation determines the appropriateness of “buying the dip” versus selling

The Ivy Portfolio spreadsheet track the 10 month moving average signals for two portfolios listed in Mebane Faber’s book The Ivy Portfolio: How to Invest Like the Top Endowments and Avoid Bear Markets. Faber discusses 5, 10, and 20 security portfolios that have trading signals based on long-term

Glenn@AlignCapital mentioned how the seminal Momentum paper by Jegadeesh and Titman (1993) recommends forming and buying a momentum portfolio a week a part. In the cracks of their beseeching everyone to 'skip a week' and avoid wicked 'short term reversals' I accidentally grew the

Although I've spent the majority of this month researching time series analysis for the upcoming article series, I've also been working on QSForex attempting to improve the API somewhat. In particular I've made the interface for beginning a new backtest a lot simpler by encapsulating

Every few years, people start to question whether value investing is dead. A recent Google search along these lines generated 3.1 million results: 2015-06-15 10_49_59-the death of value investing - Google Search Likewise, people sometimes question whether the size effect is permanently going away.

Isn't it pretty? The website, and pre-order page, for my magnum opus are now ready: www.systematictrading.org http://www.harriman-house.com/book/view/4598/trading/robert-carver/systematic-trading/ Like it says on the back "This is not just another book with yet another trading system. This

Some of the most interesting new research coming out of the Computational Intelligence Research Group (CIRG), which is applicable to numerous computational finance and machine learning optimization problems, is the development of fitness landscape analysis techniques. Fitness landscape analysis aims

In my previous article I introduced the two main methods of backtesting, vectorised and event driven. In this article I will cover an example of a vectorised backtest in Excel. One of the benefits of using Excel is that you are able to see a visual representation of the data as the model progresses.

Foreword by Joshua Ulrich: Jacques reached out to me to discuss the Backtesting in Excel and R series on my blog, FOSS Trading. Inspired by that series, Jacques wanted to create a more detailed explanation of how to backtest a strategy in Excel and R, and then to extend the examples to an

This is a phenomenon in the equity markets where the market rises over the weekend. There is still some debate over the existence and persistence of this effect but, as long as we carefully define exactly what we mean it is easy to test this idea. We are going to examine the S&P 500 since 1990

We’re all backtesters in some degree, but not all backtested strategies are created equal. One of the more common (and dangerous) mistakes is 1) backtesting a strategy based on the historical record; 2) documenting an encouraging performance record; and 3) assuming that you’re done. Rigorous

#118 - Time Series Momentum Effect Authors: Georgopoulou, Wang Title: The Trend is Your Friend: Time-Series Momentum Strategies Across Equity and Commodity Markets Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2618243 Abstract: Using a dataset of 67 equity and commodity indices from 1969

Over the last six blog posts we looked at eight different exit approaches for a standard RUT iron condor with 20 point wings. These exits included: STD - NA%:NA% - exit at 8 DTE. STD - NA%:50% - exit if the trade has a profit of 50% of its initial credit OR 8 DTE. STD - 100%:50% - exit if the trade

Lifetime of a Financial Bubble

Do Index Futures and ETFs Affect Stock Return Correlations?

The best five links of the week ending Saturday, 06/27, as voted by our readers: Interview with Ernest Chan [Better System Trader] Think MPT Doesn't Work? Clearing Up Some Misconceptions [CSS Analytics] Creating an Open Source Hedge Fund Strategy [Quants Portal] Losing Streak Indicator [System

Andreas Clenow is a hedge fund manager who specialises in developing and trading quantitative strategies across all asset classes. He is currently a principal at ACIES Asset Management, which he joined after having successfully established his own hedge fund. Prior to his role as a hedge fund trader

This post concerns a paper I came across checking the nominations for best paper published in International Journal of Forecasting (IJF) for 2012-2013. The paper bears the annoyingly irresistible title: “The illusion of predictability: How regression statistics mislead experts”, and was written

little scepticism is healthy, however, many of you know the feeling of being plagued non-stop by this awkward feeling. My level of scepticism is always bobbing around unhealthy levels. So it's nice when a guy like Ilya questions numbers and kicks the tyres a little. An opportunity to treble

The S&P Dow Jones data source is now available to use in the Lazy Backtesting IDE. All manner of interesting investable strategies and asset classes, including volatility and retirement date targeting; Vix contango & backwardation and other quant-style strategies; which you can combine,

We’ve been discussing the weakening market breadth recently, especially as it pertains to New Highs vs. New Lows. Again, our contention is that the more stocks participating in a rally, the healthier the rally is. The most recent example of this weak breadth was Wednesday’s post on the fact that

Structured Products: Performance, Costs and Investments

A reader suggested a review of the Decision Moose asset allocation framework of William Dirlam. “Decision Moose is an automated framework for making intermediate-term investment decisions.” Decision Moose focuses on asset class momentum, as augmented by monetary policy, exchange rate and

Central banks the world over are buying high-quality bonds, thereby removing them from the market and forcing savers to find alternative strategies to meet their income needs. In this environment of financial repression and near-zero interest rates, dividend-yield (or equity income) investing has

History shows rather clearly that the stock market is prone to extreme events, aka crashes. The challenge is deciding when the risk for a repeat performance is unusually high. The literature offers endless possibilities, which is a reminder that the market can crumble for any number of reasons. The

Kyle (1985) introduces an information-based asset-pricing model where informed traders keep trading until the marginal benefit of holding one additional share of the asset is exactly offset by the marginal cost of this last trade’s price impact. This model has really nice intuition, but it also

I have spent many years toiling with creating different asset allocation methodologies including the application of traditional and non-traditional portfolio optimization. Given the recent flare of articles on this topic in the blogosphere, I felt it was worthwhile to share my two cents. Applying

My previous article detailed backtest results for the ETFReplay.com portfolio. Aggregate, risk-adjusted results since 2004 were impressive when compared to a 60/40 Vanguard mutual fund. However, results over the past 2-3 years lagged the benchmark. The test below was conducted using Portfolio123