Authors: Nilsson Title: The Pre-FOMC Drift Explored Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2640477 Abstract: The pre-FOMC drift was first published in 2011 and is a strong driver of equity market performance over the last 30 years. The effect is able to explain approximately half

The term “quant trader” gets thrown around a lot these days. For any trader who has been in the industry for more than a decade, the adoption of the term is driven by survival. There’s a running joke in some HFT circles: these days, older traders would never get past HR using the same criteria

We have a pretty arbitrary practice in the financial services industry: we reset the performance clock of portfolios to zero every January. Consider this hypothetical scenario: it’s December and markets are up 20% for the year. They even got a nice 5% pop in the last month. The clock strikes

It’s amazing to think that just last Monday, August 17th, the S&P 500 closed at 2102. Today, it closed at 1868, falling 11.1% in 6 trading days. The shocking speed of the decline has injected a level of fear into markets not scene since the fall of 2011, when the Eurozone debt crisis was

Big 'O' is a measure of many things, with respect to backtesting it helps because results are always ambiguous. Backtesting results are almost iffy for a variety of reasons, but a salient one is the 'day bump' problem. Say, I have a strategy that trades at the 'beginning of

I’m back. Anyone that wants to know “what happened at Graham”, I felt there was very little scaffolding/on-boarding, and Graham’s expectations/requirements changed, though I have a reference from one of the quantitative directors. In any case, moving on. Harry Long recently came out with a

I like Five Thirty Eight. Their data driven approach certainly appeals like a quant to me. However, like many people out there, when they apply their logic to the stock market things start to go a little screwy. They posted a piece titled :”Worried About The Stock Market? Whatever You Do, Don’t

What is the Impossible Trinity When we think about the number of lots to trade (position sizing), we may face an interesting situation called the Impossible Trinity of Sizing. The Impossible Trinity of Sizing is a trilemma which states that it is impossible for us to control over all 3 of the

Recently, we wrote two posts about how to combine Value and Momentum for stock selection purposes (Part 1 and Part 2). We followed this piece with a post on combining value and momentum for market timing purposes. In this post, we review the use of combined Value and Momentum for both stock

I recently wrote about the link between quantitative analysis and technical analysis (deeply upsetting some people in the process). Today I'm going to write about the link between behavioral finance and technical analysis. But possibly not in the way you will be expecting. It is common for

In Part 1 we considered the Autoregressive model of order p, also known as the AR(p) model. We introduced it as an extension of the random walk model in an attempt to explain additional serial correlation in financial time series. Ultimately we realised that it was not sufficiently flexible to truly

As I write this on Aug. 10, despite all the economic problems facing investors (such as Greece, the slowing Chinese economy, a bear market in Chinese stocks, the collapse in commodity prices and Puerto Rico’s default), the VIX index, a measure of the market’s expectation of 30-day volatility,

A timely piece on S&P 500 put option prices. The authors find that S&P 500 put options get too expensive during wild times because of 2 effects: Demand for insurance sky rockets (investor utility demands safety) Supply for insurance becomes restricted (credit constraints cripple market

My Lazy PCA analysis tool plots returns against lagged returns and then fits principal components to the data. ('SP5HBI' S&P 500 High Beta index weekly) The surprising thing is that the fitted components almost always have a slope of plus or minus one (except when there's a lack

Last Friday the S&P 500 did something it hadn’t done in a very long time (949 trading days to be exact): it went down by more than 3% in a day. Nearly eight months ago we highlighted the length of this non-losing streak as it stood then at 787 trading days (the market seems to like palindromes

This post reviews the backtest results of selling one-lot options strangles on the Russell 2000 Index (RUT), initiated at 73 days-to-expiration (DTE). The results in this post were derived from 2312 individual trades entered by the backtester. The results are grouped by the delta of the short

Ahead of the upcoming Turn of the Month May/June, the statistics are always calculated after closing price and from year 1987 to 2014. This statistics applies only to Turn of the Month August/September. Last trading day of the month is -1 and the first trading day of the new month is 1. The trading

The best quant mashup links for the week ending Saturday, 08/22 as voted by our readers: The Kalman Filter and Pairs Trading [MKTSTK] The Gamblers’ Fallacy [Factor Wave] Strategy Gamma Overview [John Orford] The Health of Stock Mean Reversion: Dead, Dying or Doing Just Fine [Alvarez Quant Trading]

I. Trading Strategy Developer: Toby Crabel (ORBP: Opening Range Breakout Preference). Source: Crabel, T. (1990). Day Trading with Short Term Price Patterns and Opening Range Breakout. Greenville: Traders Press, Inc. Concept: Volatility expansion with a trend filter. Research Goal: Performance

Here's a cumulative return plot of the lazy Drop the Mic trading strategy outlined yesterday. Long periods of flatlining show when the strategy is in hibernation. Just for fun, here is how the strategy weights its holding in the S&P 500 over time. How often do you see a symmetric picture

Two of the most-well-known factors that help explain stock returns are the value effect (where equities with lower prices relative to metrics—such as book value, earnings, cash flow, sales and dividends—tend to outperform the equities with higher prices relative to those metrics), and the

Building on research in psychology, we predict that unpleasant weather negatively affects capital market participants’ moods and activity levels, causing a muted response to information events… The table below highlights that unpleasant weather seems to be correlated with slower market

One of the major themes of War and Peace will resonate with all practitioners of stochastic finance. Essentially, Napoleon's nemesis, the Russian general Kutuzov, keeps dropping back before the invading French until at last he spots a weakness in the French and pounces. Tolstoy tells us that

At the start of the week I wrote a post about the effect of weather and the markets. Leo Cheng thought (quite reasonably) that this might just be data mining. If you look at enough things, some will appear to have an influence on the market just by chance. I've done a little more reading and I

This post reviews the backtest results of selling one-lot options strangles on the Russell 2000 Index (RUT), initiated at 66 days-to-expiration (DTE). The results in this post were derived from 2336 individual trades entered by the backtester. The results are grouped by the delta of the short

This is somewhat based on an an article I wrote for the sadly departed "Active Trader" magazine but is more directly spurred by a conversation I had with a reader about my last post. Her point was that by buying dips we are just engaging in a classic Martingale, buying when things go

I was recently quoted in ETF.com and its sister publication, ETF Report, in an article titled Global Sector Investing in Early Stages. The article discusses global sectors – and in particular, global sector ETFs – and why they haven't seen the growth of their domestic peers. At Newfound, we

You can count dead air on the radio by the millisecond, when you expect to hear something but don't, your ears become acutely aware of not hearing anything at all. This doesn't happen with white space on a page. Look at a well designed website; your eyes will happily swim around it;

Investing in the current environment is difficult. Most, if not all, asset classes have high nominal prices, suggesting low nominal expected returns. Not exactly exciting. And for many investors who are retired and/or have near-term liquidity needs, investing in equity exposures–while necessary to

Given a constant speed, time and distance are fully correlated. Provide me with the one, and I’ll give you the other. When two variables have nothing to do with each other, we say that they are not correlated. You wish that would be the end of it. But it is not so. As it is, things are perilously

Passive Hedge Funds (via @carlfischer101)

My second post on this blog was a look at mean reversion, Is mean reversion dead? Given I am using a new data provider(Premium Data), it has been almost two years since that post and there have been other articles on this recently, I figured it was time to check again. The research will focus on

Yesterday I had a coffee with a person I have known for 20 years. He has worked as a quantitative analyst, a trader and a finance professor for at least as that long. He is one of the most knowledgeable people I know. When he says something it is worth listening. What he said was (roughly), "

We assume that the drift in the returns of asset prices consists of an idiosyncratic component and a common component given by a co-integration factor. We analyze the optimal investment strategy for an agent who maximizes expected utility of wealth by dynamically trading in these assets. The optimal

Dynamic Mode Decomposition for Financial Trading Strategies

Forecasting Stock Market Returns over Multiple Time Horizons

Volatility Forecast in Crises and Expansions

Imagine this scenario: you are a statistical arbitrage trader at a prop desk or HF. As such, you routinely hold an inventory of ETF exposure that you must hedge. The previous night, you instructed your overnight traders to calculate the hedge ratios for a matrix of ETF’s. The next morning before

The Quality factor is a composite measure designed to identify companies with the characteristics that typically lead to success. It is particularly useful to identify "value traps": companies which are cheap by current metrics but are losing money. I wrote a little about quality here.

July saw a bounce back up in the index after several months of downwards action. The YTD performance is still negative though. Please check below for more details. Detailed Results The figures for the month are: July return: 3.86% YTD return: -1.47% Below is the chart displaying individual system

Taking a leaf out of Mike Harris' recent Momersion theme, here's a PCA point of view of the balance between momentum and mean reversion over the previous 10 years from the Lazy PCA tool. August 2015 - 2014 PCA fits momentum and mean reversion components to the daily returns, they balance

In the last article we looked at random walks and white noise as basic time series models for certain financial instruments, such as daily equity and equity index prices. We found that in some cases a random walk model was insufficient to capture the full autocorrelation behaviour of the instrument,

Summary Rising interest rates are on the horizon … somewhere Yield curve dynamics – including the absolute level of rates, their direction of change, and the slope of the yield curve – all play an important role in the returns for managed futures The cost of carry in shorting fixed-income

The debate over passive versus active investing is akin to Eagles vs. Cowboys or Coke vs. Pepsi. In short, once our preference for one style over the other is established, it becomes a proven fact or incontrovertible reality in our minds. This post is not meant to convert a passive investor into an

The Monte Carlo, filled with a lot of mystery is defined by Anderson et al (1999) as the art of approximating an expectation by the sample mean of a function of simulated variables. Used as a code word between Stan Ulam and John von Neumann for the stochastic simulations they applied to building

Economics 101 tells us that people have 'convex' utility curves. Which means there are diminishing returns to having more, but losing what you currently have diminishes your well being precipitously. Convexity is such a human property, it shows up again and again in unexpected places.

It should be fairly obvious to anyone who has been involved with investing for any time, that traders decisions are heavily influenced by their mood. Actually, some interesting recent research has shown that people generally make decisions intuitively before using their conscious thought processes

This post reviews the backtest results of selling one-lot options strangles on the Russell 2000 Index (RUT), initiated at 59 days-to-expiration (DTE). The results in this post were derived from 2312 individual trades entered by the backtester. The results are grouped by the delta of the short

On the show this week we have Larry Williams who has been trading futures and stocks for over 50 years. In 1987 he won the world cup trading championship, turning $10,000 in to over $1.1 million in 12 months, that's a cool 11,000% return and the highest return to ever be achieved in that

Grabbing the data. How do you grab the latest news on your favorite ticker symbol? It all starts with the following URL. https://www.google.com/finance/company_news?q=SPY&output=rss You'll want to change "q=SPY" to whatever symbol you're interested in. You can add something