Summary We often hear trend following being referred to as “market timing” In all active strategies, timing is an important concept Market timing is a distinct process whereby investors try to predict the future Momentum is reactionary, not predictive, and is therefore no more a form of market

Approach to Designing Amazing Strategies “Add a SMA(30)! No add an EMA(18). Optimise it to find the best parameter value. Ok we’ll stick to EMA(15). Throw in 3 date and time filters, 3 optimised price indicators and 3 volume indicators (that are essentially saying the same thing in different

Robert Carver is an independent systematic trader, freelance writer and research consultant. He spent more than seven years working for AHL, one of the worlds largest systematic hedge funds. Robert was responsible for the inception of AHL's fundamental strategies group and subsequently managed

Michael Edesses is out with a scathing article lambasting the field of empirical finance. He draws inspiration from Harvey, Liu and Zhu's (HLZ) recent article, entitled "…and the Cross Section of Expected Returns", but extends HLZ's conclusions to an absurd limit. In this

Wow, I enjoyed replicating this neatly written paper by Ronald Hochreiter. Ronald is an Assistant Professor at the Vienna University of Economics and Business (Institute for Statistics and Mathematics). In his paper he applies evolutionary optimization techniques to compute optimal rule-based

Following on from my last post I thought I would, as a first step, code up a "straightforward" Runge-Kutta function and show how to deal with the fact that there is no "magic mathematical formula" to calculate the slopes that are an integral part of Runge-Kutta. My approach is to

Momentum and Risk Adjustment

Market Condition and Momentum

Extreme Events in Stock Market Fundamental Factors

Measuring Multiscaling in Financial Time Series

Understanding Systematic Risk: A High-Frequency Approach

The best quant mashup links for the week ending Saturday, 09/26 as voted by our readers: Sorry Jim, trend following probably still works (though not the fast stuff) [Investment Idiocy] Sorry Bob But Jim Simons is Probably Laughing At Your T-Statistics [Price Action Lab] Hypothesis-Driven Development

I want a strategy that is able to choose the assets that makes it look like an index Yt. -Then take the ones most correlated to it. -Ok, but look: CC1 The Xt and the Xt+c series have exactly the same correlation with Yt -I prefer Xt+c!! -Yes, but I am trying to be very similar to Yt and Xt+c have a

In my last post I had a bit of a controversial pop at a brilliant and successful billionaire hedge fund manager; Jim Simons. In continuing my futile quest to raise the level of debate in the quantitative investment community I thought I'd have a go at another clever and very wealthy guy, Cliff

At the end of August 2015 the 50-day moving average of the S&P500 crossed its 200-day moving average to the downside – the 33rd occurrence of a “Death Cross” since 1950. The performance of the S&P500 was investigated for periods ranging from one year before to two years after a Death

As stated in my previous post I have been focusing on getting some meaningful features as possible inputs to my machine learning based trading system, and one of the possible ideas that has caught my attention is using Runge-Kutta methods to project ( otherwise known as "guessing" ) future

This post will demonstrate a stop-loss rule inspired by Andrew Lo’s paper “when do stop-loss rules stop losses”? Furthermore, it will demonstrate how to deflate a Sharpe ratio to account for the total number of trials conducted, which is presented in a paper written by David H. Bailey and

There is plenty of evidence that stocks with low volatility have better subsequent performance. There is also plenty of evidence that stocks with low beta outperform. Other studies have shown that low downside deviation and skewness are also predictive of good returns. None of these measures are

Andreas Clenow is CIO of Zurich-based ACIES Asset Management ($300+ million AuM), and author of 'Stocks on the Move: Beating the Market with Hedge Fund Momentum Strategies'. Why would he give up the super secret sauce in a tell-all? Automated Trader finds out. CTAsHedge Funds Andreas

The first chapter ended with code which included a map and a filter which we will dive back into now with a less applied more intuitive example. Open up the JavaScript console and paste or type in the following code, [0,1,2,3,4,5,6,7,8,9] .filter( function(j){ return j%2===1; } ); This code filters

In one of the previous posts I considered market timing with moving averages on 9 quite different equity indices that were chosen in other post, and came to the conclusion that the rule is the viable alternative to the standard B&H, allowing to avoid large drawdowns in one cases and even improve

Machine learning is a powerful tool for not only coming up with new strategies (like we do in TRAIDE) but also for improving your existing strategies. In this article, we’ll cover adjusting your position size using a random forest algorithm and turning your strategy on an off using a Hidden Markov

irst draft of 'JavaScript for Financial Analysts' Chapter 2. ~ Most bankers, whether they admit it or not are really high tech plumbers. They receive data; process it; and send it on to a fancy risk or aggregation system. Extract, Transform and Load (ETL) takes up an inordinate amount of

#38 - Accrual Anomaly Authors: Patatoukas Title: Asymmetrically Timely Loss Recognition and the Accrual Anomaly Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2653979 Abstract: Conditionally conservative accounting practices mandate the more timely recognition of losses relative to gains

Back in May, I posted A Guide to Creating Your Own Hedge Fund outlining how the application of momentum to the two worst performing funds within the Morningstar Multialternative category over the previous ten years would have provided an investor with better risk-adjusted returns than the Barclays

In this article I show that very basic quantitative trading strategies that generate returns from different market behaviours, when combined, can provide a more desirable and stable returns stream, as reflected in a Sharpe ratio higher than any individual strategy. We show how absolute returns can

In this article we are going to consider the famous Generalised Autoregressive Conditional Heteroskedasticity model of order p,q, also known as GARCH(p,q). GARCH is used extensively within the financial industry as many asset prices are conditional heteroskedastic. We will be discussing conditional

Summary Trend-following can be used as an objective methodology to seek to participate with market growth and protect against significant declines Common models may work on average but can fail in very specific scenarios Parabolic moves are particularly tough for simple trend following methods to

There is an interesting discussion in the geeky world of academic finance literature between the intellectual muscle at AQR and academia. aqr versus the academics on active share The discussion revolves around the following question: “Does Active Share matter?” This is an important topic for

Impact of Proliferation of Automated Trading Systems and Technology on Financial Markets With the advent of automated trading everything has become computerized. Risk management takes a whole new level in this technologically fast paced world. The trends in day-to-day trading have been changing.

There was lots of action in financial markets last week, with much of the attention focused on the U.S. Federal Reserve. The interest rate on a 10-year U.S. Treasury bond edged up 10 basis points early in the week in anticipation that the Fed might finally raise its target for the short-term

This post is about copulas and heavy tails. In a previous post we discussed the concept of correlation structure. The aim is to characterize the correlation across the distribution. Prior to the global financial crisis many investors were under the impression that they were diversified, and they

First draft of 'Javascript for Financial Analysts' Chapter 1. ~ Much of our coding time is spent in an interactive environment, colloquially called the 'REPL', 'Read-Eval-Print Loop' or console. The REPL reads input, evaluates it according to our code and prints it.

Like it’s bullish counterpart, the hammer, this bearish reversal pattern has been inconsistent in its forecasting abilities, except under certain conditions. We’ve covered the “hammer” candlestick chart pattern on a couple occasions over the past few years, most extensively in this October

The best quant mashup links for the week ending Saturday, 09/19 as voted by our readers: Hacking the Random Walk Hypothesis [Turing Finance] Getting Started: Building a Fully Automated Trading System [Quants Portal] Interview with Euan Sinclair [EP Chan] Interview with Dr Ernest Chan [Factor Wave]

In this post we look at the backtest results of selling a one-lot, at-the-money (ATM) straddle on the S&P 500 Index (SPX), initiated at 38 days-to-expiration (DTE). In this third post of five on 38 DTE straddles, we look at trades that use the same loss exits as shown in the first post, and in

I have been a big fan of options trader and author Euan Sinclair for a long time. I have cited his highly readable and influential book Option Trading in my own work, and it is always within easy reach from my desk. His more recent book Volatility Trading is another must-read. I ran into him at the

Today’s article is an update on this oldie but goodie. When people ask me if momentum investing “works”, at this point – because I am older and (even) crankier than I used to be – I typically refer them to the linked article above and grunt “decide for yourself.” Sorry, it’s just my

This past year we examined the possibility of replicating commodity exposure via equities. The project was spurred by an insightful research report from MSCI, which showed some impressive results. Other research outfits have proposed similar concepts. The figure below, taken from the MSCI report,

In this post we look at the backtest results of selling a one-lot, at-the-money (ATM) straddle on the S&P 500 Index (SPX), initiated at 38 days-to-expiration (DTE). In this second post of five on 38 DTE straddles, we look at trades that use the same loss exits as shown in the first post, and in

This week on the podcast I have algorithmic trader, Kevin Davey. Who like many guests in the past, he comes from a background in engineering – there’s something about these engineers, they seem to make really great traders… After getting off to a bumpy start 25 years ago, Kevin has come a very

First draft of an introduction to the "Javascript for Financial Analysts" book. ~ The humble spreadsheet is the workhorse of the finance industry. Every financial analyst has spent hours, preparing complex spreadsheets, only for an error to creep in here or there. The spreadsheet is a gift

Dr Ernie Chan does something difficult well: he explains quantitative trading ideas to retail traders without over-simplifying them. He has written two books," Quantitative Trading:How to Build Your Own Algorithmic Trading Business" and "Algorithmic Trading: Winning Strategies and

The NFL is back!!! Unfortunately, the Eagles may need a new kicker…and now we have to listen to Wes talk trash about the Cowboys victory around the office. Tragic! In the spirit of the new NFL season, I figured it was a good time to highlight a newer paper titled “Corporate Sport Sponsorship and

This post will deal with applying the constant-volatility procedure written about by Barroso and Santa Clara in their paper "Momentum Has Its Moments". The last two posts dealt with evaluating the intelligence of the signal-generation process. While the strategy showed itself to be

My previous post The Health of Stock Mean Reversion: Dead, Dying or Doing Just Fine generated good reader’s suggestions on other ways to check on mean reversion health. Let us see what these tests tell us. The Base Test Date Range: 1/1/1995 to 6/30/2015. Entry: Stock is part of the Russell 1000

SPX closed at a 10-day high on Tuesday. New short-term (and intermediate-term) highs will sometimes get traders excited. When the market is in long-term downtrend mode, this excitement is often misplaced. Way back in a blog post on 4/3/09 I showed a number of “systems” that looked to sell short

I. Trading Strategy Developer: Toby Crabel (ORBP: Opening Range Breakout Preference); Richard D. Donchian (Price Channel Filter). Source: Crabel, T. (1990). Day Trading with Short Term Price Patterns and Opening Range Breakout. Greenville: Traders Press, Inc. Concept: Volatility expansion with a

Usign 9 equity markets I talked about in the previous post, I’m going to compare «avoid death cross» or «moving average crossover» market timing rule with vanilla B&H. Formal specification of the rules used: — if at day t we have for some index that MA(10) — if at day t we have for

Hackers would make great traders. At a meta level, hackers and traders do the same thing: they find and exploit the weaknesses of a system. The difference is that hackers hack computers, networks, and even people for various good and bad reasons whereas traders hack financial markets to make