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5 Oct, 7 tweets, 2 min read
Been a fulfilling ~1 month since our launch. For hitting 1k followers, we have a special thread for you, including a premium alpha report and a case study. 🔥

MEGA Thread (N = 60+) : Robust Alpha Research Processes; HangukQuant

↓ ↓ ↓ ↓ ↓
On Alpha Research, and Quantitative Alpha
On Trading Edges, and Adopting Research Methods
My Processes and Systems, and The Alpha Origin
Quantifying Ideas as Alpha, and Vertical/Horizontal Alpha Research
Our Alpha Product, and Sample Premium Reports
Also would like to thank @robertmartin88 who helped me "introduce" me to the FinTwit space and gave me unsolicited tips on writing threads back when I had 30 followers😳

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More from @HangukQuant

HangukQuant Profile picture
6 Oct
1\13 One of the biggest challenges in quant and alpha research is obtaining clean, error-free data. Models need be built, using assumptions to reduce “dimensions” of reality for tractability.

A THREAD ▼ ▼ ▼
Machine Learning, Sparse Datasets and Error-Free Simulations
2\ Mathematical models, by definition are built to simulate and capture some phenomena, practical or abstract. Often, they are built on data, which themselves are derived from some unknown, statistical distribution.
3\ For example, an alpha model, is backtested upon data where prices/returns are drawn from some distribution. Widely in quantitative finance, they are assumed to be drawn from a log-normal distribution.
Read 13 tweets
HangukQuant Profile picture
5 Oct
Sub-Thread 5

HangukQuant’s Alpha
Sample Article
📌 HangukQuant’s Alpha

1) We adopt the Hybrid (Type 3) approach in the alpha research process. The hybridity is reflected in our team’s dynamic, with practitioners working on the theoretical models, and traders providing input on the heuristical discovery of alpha.
2) The result is a coherent product in the form an “alpha report”, that premium subscribers get access to weekly.
Read 11 tweets
HangukQuant Profile picture
5 Oct
Sub-Thread 4

Numerical Expression of the Thought Process

“Horizontal Alpha Research”; Alpha Fracking

Alpha Probing
📌 Numerical Expression of the Thought Process

1)

-1 * cor ( returns(1) , delay( returns(1) , 1 ) , 90)

“The alpha is the negative correlation between time-series of daily returns and its 1-lagged series, taken across, say, 90 days.”
2) The strategy of numerically ranking the outputs from above and going risk-neutral L/S quantiles on 30 stochastically sampled S&P assets:
Read 16 tweets
HangukQuant Profile picture
5 Oct
Sub-Thread 3

The Research Process

The Alpha Leak

“Vertical Alpha Research”, A Thought Process
📌 The Research Process

1)
 Type 1: To keep my knowledge of finance, I both subscribe to financial literature, academic or otherwise. That means reading books/papers on finance, trading, economics, podcasts for general knowledge, and a working knowledge “Mathematical Finance”.
2)
Type 2: My knowledge on Computer Science and Statistical methods comes from my background in academia. I also keep up to date on new state-of-the-art research by reading academic literature.
Read 14 tweets
HangukQuant Profile picture
5 Oct
Sub-Thread 2

Finding “Edges”

Adopting Alpha Research Methods
📌 Finding “Edges”

1)
 Type 1: Understanding market structure and market incentives, and the corresponding flows

Type 2: Finding statistical anomalies within price/non-price data

Type 3: Hybrid approach.

Let’s seek to understand this further.
2)
 Type 1: There are many reasons for actionable price flows, such as price insensitive liquidation, factor premia et cetera. For an example, a previous thread

Read 20 tweets
HangukQuant Profile picture
5 Oct
Sub-Thread 1

What is Alpha Research?

Introduction to Quantitative Alphas
📌 What is Alpha Research?

1) First, what is alpha research? It is the undertaking of research operations towards finding excess returns on the market. It may come in many forms, from both fundamental and quantitative perspectives.
2) In the quant sphere, it often takes on the form of parametric formulae/rules designed to express underlying trading edge. They also come in many forms, such as stat arb, risk arb, factor models (mom, rev), idiosyncratic premia, predictive modelling et cetera.
Read 9 tweets

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