9 – M4 L3b 09 Winners And Losers Creating A Joint Factor V3

Going back to the question I asked earlier, based on whether the gain coefficient and the accelerate coefficient are positive or negative, can you decide which scenarios we would rather go long or short? We’ll take a look at how the coefficients of the stock price approximation formula can inform our decision as to which … Read more

8 – M4 L3b 08 Winners And Losers Approximating Curves With Polynomials V4

Now that we have a sense for how accelerated or decelerated gains and losses look like visually, how do we represent their relative convexity or concavity in numbers? One way to approximate a curve, is with a formula that looks like y equals x squared. Or more accurately, y equals ax plus bx squared. The … Read more

7 – M4 L3b 07 Winners And Losers Accelerated And Decelerated Gains And Losses V2

The paper titled, The Formation Process of Winners and Losers in Momentum Investing, discusses how the trajectory of a stock is an indicator for whether its momentum is accelerated or decelerated. When a stock is recently showing higher returns, this paper refers to these as accelerated gains. When a stock is recently showing minimal positive … Read more

6 – M4 L3b 06 Winners And Losers In Momentum Investing V2

Here’s a question for you. If two stocks begin and end at the same point over a period of time, does it matter how they got there? If you ever heard the fable about the tortoise and the hare, then you might remember the saying, “slow and steady wins the race.” Maybe that idea is … Read more

5 – M4 L3b 05 Overnight Returns Methods Quantile Analysis V3

In section three titled Weekly Overnight Returns, the authors check if the weekly close-to-open returns persist one, two, three, or four weeks into the future. The authors make use of quantiles to analyze the data. They sort the weekly overnight returns and then divide these into deciles or 10 quantiles. If we jump to table … Read more

4 – M4 L3b 04 Overnight Returns Data Universe Methods V2

The paper identifies its dataset as the Center for Research and Security Prices, which is often abbreviated as CRSP and can be referred to as CRISP. This is a fairly well-known pricing dataset. And if you check out their website, you can see that the data is available via subscription. We don’t use that data … Read more

3 – M4 L3b 03 Overnight Returns Possible Alpha Factors V2

From reading the introduction, we see that the authors refer to investor sentiment as the positive or negative views of investors, especially individuals who tend to cluster their orders around a market open. The authors also define overnight returns as the close to open returns and describe the following hypothesis. Individual investors may notice attention … Read more

22 – M4 L3b 22 Summary V2

You did it. This lesson was pretty advanced, but also very meaningful in that we practice reading academic research, thinking about Alpha ideas based on the papers, and then coding up these factors. I want to emphasize that the value of this lesson isn’t that I’m giving you four Alpha factors that will help you … Read more

21 – M4 L3b 21 IVol Generalizing The Volatility Factor V2

Now that we’ve walked through risk factor models and Alpha factors, I hope you’ll start to see how you can try out different variations that deviate from the specific methods you see in academic papers. For instance, instead of using the Fama French model to extract idiosyncratic volatility, you may try other risk factor models … Read more

20 – M4 L3b 20 IVol Volatility Enhanced Price Earnings Ratio V2

Fundamentals such as price to earnings ratio and price to book ratios have often been used in alpha factors that represent the ratio of market price to intrinsic value. We could use these fundamental factors by themselves to indicate whether a stock is underpriced or overpriced. One thing to be aware of though when dealing … Read more

2 – M4 L3b 02 Overnight Returns Abstract V2

Let’s read the abstract of the paper, Overnight Returns and Firm Specific Investor Sentiment. We can see that the authors tried to analyze something called overnight returns. If we skip ahead to Section 2 titled sample, variable definitions, and descriptive statistics, we can see that overnight returns are defined as the percent change from the … Read more

19 – M4 L3b 19 IVol Quantamental Investing V2

One of the most exciting developments in investing in the last couple of years is the convergence of the quants and fundamental processes. This is called quantamental investing in the popular press, as a combination of the words quant and fundamental. But don’t let that goofy name fool you. It’s more than just a fad … Read more

18 – M4 L3b 18 IVol Value Fundamental Or Discretionary Investing V2

The concept of value in factor modeling is one of the two most widely known concepts, the other being the concept of momentum. The significance of value can be traced to the work of Ben Graham and David Dodd, who wrote about value investing, which seeks to estimate accompanies intrinsic value than by companies that … Read more

17 – M4 L3b 17 IVol Idiosyncratic Volatility V2

Remember from our prior discussions, especially the one about risk models, the returns can be broken up into a systematic and idiosyncratic component. Likewise, the volatility of returns can be broken up into systematic and idiosyncratic components. Idiosyncratic risk maybe a more helpful indicator of arbitrage risk. Why is this? Because market participants who pursue … Read more

16 – M4 L3b 16 IVol Arbitrage Risk V3

Not all arbitrage opportunities are created equal. If you found two similar stocks with similar mispricing, all else being equal, you’d prefer to act on the stock that is less risky. For example, let’s imagine we have identified through a model in which we have high confidence two stocks, A and B, which are each … Read more

15 – M4 L3b 15 IVol Arbitrage And Efficient Pricing Of Stocks V3

You may recall that overcharge is a process that seeks profits due to mis-pricing of assets. In other words, overcharge looks for inefficiencies in the market in order to profit from these inefficiencies. Moreover, the act of overcharge actually reduces the mis-pricing of assets, and the individual acts of overcharge by market participants as a … Read more

14 – M4 L3b 14 IVol Value And Idiosyncratic Volatility Overview V2

The last alpha factor that we’ll construct is based on the paper titled “Arbitrage asymmetry and the idiosyncratic volatility puzzle.” This paper uses a lot of the concepts that we’ve learned, including a unique example of using some of the output of a risk model as part of alpha factor construction. Personally, I enjoy this … Read more

13 – M4 L3b 13 Skewness And Momentum Conditional Factor V2

Let’s see how we can create a conditional factor based on momentum and skew. We first might want to convert both momentum and skew to ranks, since ranks are generally more stable and more robust to outliers. Notice though, that skew is a reversal or mean-reversion signal. So, we want to rank the skew in … Read more

12 – M4 L3b 12 Skewness And Momentum Momentum Enhances Or Weakened By Skew V2

Let’s walk through four hypothetical examples and assume that skewness is a reversal factor, which is another word for mean reversion. We’ll be more specific and say that the maximum daily return over the trailing month is our measure of skew. Let’s also assume that the return over the trailing year is a momentum vector. … Read more

11 – M4 L3b 11 Skewness And Momentum Defining Skew V2

I hinted previously, that we could use skewness as a signal that stocks may be over bought in the short-term and may revert back soon afterwards. To help you understand skewness, I’ll first introduce a visual notion of skew. Then the common academic definition of skew, followed by the proxy for skewness that we will … Read more