Recently for my own trading, I have been researching rotational strategies on both the weekly and monthly timeframes. The most common indicator that I use for ranking stocks is Rate of Change (ROC) of the closing price. I read about using Rate of Change on the EMA to rank stocks. I liked a small

It has been almost 11 years since the first official Bitcoin trades in July of 2010. It's price has experienced quite a run. Although controversial, cryptocurrencies have firmly taken hold of the current investing landscape, won hearts and minds of groups of investors, suggesting they are here

A few weeks ago I saw comments on Twitter regarding the Russell 3,000 Value and Growth indices having approximately the same returns since inception. For example, here is Ben Johnson from Morningstar 1 As viewed from this tweet, and is born out in the data for the Russell indices, it appears that

The world is awash in efforts to model a theoretical value for the stock market – the CAPE ratio, for example. But while the equities hog much of the attention on this front, similar analytics for the world’s most important interest rate are no less valuable. How to begin? Not surprisingly,

This is the sixth article of the copula-based statistical arbitrage series. You can read all the articles in chronological order below. In this series, we dedicate articles 1-3 to pairs-trading using bivariate copulas and 4-6 to multi-assets statistical arbitrage using vine copulas. Copula for Pairs

Contrary to a more developed market, arbitrage opportunities are not readily realised which suggests there might be opportunities for those looking and able to take advantage of them. This project focuses on China's futures market using Statistical Arbitrage and Pair trading techniques. This

The stock market volatility, skewness, and yield curve influence the performance of the value factor Investors require a certain market environment to buy troubled companies The key performance driver of the value factor is risk sentiment INTRODUCTION Ted Theodore first wrote about value versus

For the last seven years since I started trading my own account I've pretty much kept the same set of futures markets: around 40 or so, with very occasional changes. The number is limited, as to trade more markets I'd need more capital. The set of markets I have is a compromise between

This is a follow up to a strategy we’ve covered previously: Accelerating Dual Momentum (ADM) from EngineeredPortfolio.com. See our first test of ADM, which includes a description of the strategy rules and our own analysis of the strategy. Here we’ve extended our test by 20 years to include a

This article is a primer into the methodology we use for the Portfolio Risk Parity report, which is a part of our Quantpedia Pro offering. We explain three risk parity methodologies – Naive Risk Parity (inverse volatility weighted), Equal Risk Contribution and Maximum Diversification. Quantpedia

One year ago, I wrote about the U.S. Value factor and what I found by extending its history back in time before 1926. In summary, I wrote that Value’s drawdown in March 2020 was normal and likely close to its bottom. Without the insights from the extended history, Value had appeared ‘dead’

This is the first part of a series of guest posts by Kai Wu, the CIO & Founder of Sparkline Capital. The Factor Zoo As readers of Alpha Architect’s blog, you’re certainly familiar with factor investing. Factors are quantifiable firm characteristics that explain cross-sectional stock returns.

The dramatic underperformance of value stocks as defined by the HmL (the return on high book-to-market stocks minus the return on low book-to-market stocks) since 2017 has led many to question the existence of the value premium. The recent drawdown has been by far the largest ever experienced. From

Mid-year learning and knowledge sharing for the quant finance community A week of 5 precision-engineered digital summits, laser-focused on the most innovative research. Choose the days that matter to you. Meet the quants finding solutions to the same problems you face.

Bonds have become less useful in asset allocation given low to negative expected returns Liquid alternative strategies can be used to replace bonds From a historic perspective, long volatility strategies would have been especially attractive INTRODUCTION John Maynard Keynes famously asked, “when

Financial markets are not macro information efficient. This means that investment decisions miss out on ample relevant macroeconomic data and facts. Information goes to waste due to research costs, trading restrictions, and external effects. Evidence of macro information inefficiency includes

When it comes to predicting long-term equity returns, several well-known indicators come to mind—for example, the CAPE ratio, Tobin’s Q, and Market Cap to GDP, to name a few. Yet there is another indicator without nearly as high of a profile that has outperformed the aforementioned indicators

Forecasting Bond Risk Premia using Stationary Yield Factors Tobias Hoogteijling (Robeco Asset Management), et al. April 12, 2021 The standard way to summarize the yield curve is to use the first three principal components of the yield curve, resulting in level, slope and curvature factors. Yields,

This is the fifth article of the copula-based statistical arbitrage series. You can read the previous four articles with the first three focusing on pairs-trading: Copula for Pairs Trading: A Detailed, But Practical Introduction. Copula for Pairs Trading: Sampling and Fitting to Data. Copula for

One common problem when looking at financial data is the enormous number of dimensions we have to deal with. For instance, if we are looking at data from the S&P 500® index, we will have around 500 dimensions to work with! If we have enough computing power, we will be able to process so much

I have been thinking a lot about risk lately. The liquidity injections from the FED are pushing risk assets higher and higher. There seem to be bubbles in nearly every speculative assets. The main concern long term would be rising rates at the same time as a falling dollar suggesting there is no

As described in my prior post Learning the Exit (part 1), I have a model that indicates mean reversion entries with ~81% accuracy, however I did not have a good approach in handling the exit. While 81% of MR signals had a minimum profit of 25% (of prior amplitude), the mean profit available was

The data from Professor French has laid the foundation for factor investing However, over time factor portfolio construction grew complex and with many nuances Returns may look more or less attractive, which makes a weak foundation INTRODUCTION When I was growing up one of my favourite TV shows was

Zipline is a fantastic tool for backtesting and data is the main raw material for doing this kind of analysis. In this post, we are going to focus on how to load our own data files. Through an example, we will create a bundle to load data from csv files downloaded from Yahoo finance.

Since the development of the first asset pricing model, the Capital Asset Pricing Model (CAPM), academic research has attempted to develop models that increase the explanatory power of the cross-section of stock returns. We moved from the single-factor CAPM (market beta), to the three-factor

Various research papers show that market sentiment, also called investor sentiment, plays a role in market returns. Market sentiment refers to the general mood on the financial markets and investors’ overall tendency to trade. The mood on the market is divided into two main types, bullish and

This article focuses on “climate-aware” asset allocation and the associated impacts of higher temperatures on equity excess returns and risk. The objective of this research is to demonstrate how portfolios can incorporate climate change risk and rewards into the decision-making process. The

In this series of posts I’m trying some of the ideas in the book Advances in Financial Machine Learning, by Marcos López de Prado. Here I tackle an idea from chapter 5: fractional differencing. the problem Stock prices are nonstationary - their means and variances change systematically over time.

The link between central bank policy, money supply, and inflation seems to have changed QE money printing had no substantial impact on inflation, aside from asset price inflation More direct stimuli might change that INTRODUCTION London ranks ninth on the UBS Global Real Estate Bubble index for

Any asset can use a portfolio of similar assets to hedge against its factor exposure. The factor residual risk of the hedged position is called statistical arbitrage risk. Consequently, the statistical arbitrage risk premium is the expected return of such a hedged position. A recent paper shows that

Every form of strength is also a form of weakness*. I love statistics, but I focus to much on methodology, which is not for everyone. Some people (right or wrong) question: “wonderful sir, but what can I do with it?”. A new paper titled “Beta in the tails” is a showcase application for why

Price curves consist of much noise and little signal. For separating the latter from the former, John Ehlers proposed in the Stocks&Commodities May 2021 issue an unusual approach: Treat the price curve like a radio wave. Apply AM and FM demodulating technology for separating trade signals from

We are proponents of focused (i.e., 50 stock) long-only value and momentum factor strategies. 1 There are also plenty of incredibly talented systematic investing shops that build highly diversified factor portfolios with 500+ stocks. We take no stance on the "best" approach because there

If you have some factor that you think predicts future stock returns (or similar) and you are making charts like below, then here are some tips… We’ll go through an example of trying to “time” SPX with the level of VIX. You get daily SPX index prices and daily VIX close data You align them

The grand experiment of combining massive fiscal and monetary stimulus at a time when the economy is already recovering strongly—the Fed’s latest forecast for 2021 GNP growth is 6.5 percent—has led many investors to begin to worry about the risks of rising inflation. And strong growth is

Copula is a great statistical tool to study the relation among multiple random variables: By focusing on the joint cumulative density of quantiles of marginals, we can bypass the idiosyncratic features of marginal distributions and directly look at how they are “related”. Indeed, traders and

Different markets and different timeframes will need different moving average periods. This article will show a way to construct a self optimising moving average, one which automatically adjusts its period to the charted market and timeframe. Reading a simple moving average I would like to start

When looking to generate appreciable returns and increase diversification, it is natural to consider investing in foreign instruments. Currency risk then comes up, since the returns coming from these funds, stocks, bonds… need to be translated into your home currency. The most straightforward

I am always fascinated by patterns as I believe that our world contains some predictable outcomes even though it is extremely difficult to extract signals from noise, but all we can do to face the future is to be prepared, and what is preparing really about? It is anticipating (forecasting) the

It's April, which means the birds are singing, the trees are leafing, and I'm doing my annual review of my investing and trading performance. The format will be familiar from previous years, but I'm going to be using the fact I've upgraded my live trading system to include a lot

Investors are challenged when evaluating investment opportunities with limited track records Factor exposure analysis can be used to create replication portfolios These empower investors to walk backward and forward in time, enhancing the investment decision process INTRODUCTION Investing is all

With a myriad of new crypto-exchanges popping up every quarter, lots of newcomers to this fields can be overwhelmed by their number. Big names can quickly stand out if you filter the list according to daily trading volume or the total number of cryptocurrencies available for trading. Some offer

Last week I wrote about BVOL - bitcoin volatility index launch on Deribit. However this is not the first crypto volatility index. In fact last year T3 Indexes - the folks behind SPIKES volatility index launched both Bitcoin and Etherium volatility indexes, and already executed trades tied to their

Born at Morgan Stanley in the late 1980s, under the wing of Nunzio Tartaglia and his team, who later split up to start several of the world’s best hedge funds, namely PDT Partners and D.E. Shaw (which then lead to Two Sigma). Pairs trading has proven to be a popular and sophisticated trading

This is the third article in a series of three, the first two are available here and here. Those articles focus on examining from a digital signal processing (DSP) perspective 1 various types of digital filters that are designed to model trends in time series, in order to illustrate their properties

How Much Bitcoin Should I Own? A Mathematical Answer Adam Grealish (Betterment) March 9, 2021 It goes without saying that this is a hard question to answer. But we can borrow a page from modern quantitative finance to help us arrive at a potential answer. For years, Wall Street “quants” have

Many beginner traders don’t realize how variable the p&l of a high-performing trading strategy really is. Here’s an example… I simulated ten different 5 year GBM processes with expected annual returns of 20% and annualized volatility of 10%. (If you speak Sharpe Ratios, I’m simulating a

In my previous post, Adding candlesticks to mean reversion setup, we looked at how various candle patterns could help individual trades. Now we will see how those results translate to a portfolio. And why I usually only do portfolio level testing. The Strategy Setup Rules Stock is a member or was a

The correlation between stock and bond returns is an integral component of hedging strategies, risk assessment, and minimization of risk in allocation decisions. In the context of those strategies, the stock-bond correlation is typically estimated using monthly return data over a recent previous

Our last post examined the correspondence between a logistic regression and a simple neural network using a sigmoid activation function. The downside with such models is that they only produce binary outcomes. While we argued (not very forcefully) that if investing is about assessing the probability