Quant Research: Price Volume Data & Alphas

Introduction to Quant Research and World Quant Brain

• World Quant Brain provides datasets and tools for testing quantitative ideas via a simulation platform.
• The platform gives users real-time feedback on strategies.
• Alphas are defined as mathematical models for predicting future price movements.
• Data categories for building Alphas include price, volume, fundamental, analyst sentiment, options, model, insider transactions, and short interest data.

Price Volume Data Category

• Price Volume Data includes stock prices, open, high, low, close prices, trading volume, and market capitalisation.
• The change in price between open and close is a potential signal.
• A close price lower than the open price may signal a potential reversion.
• Conversely, a close price higher than the open price may signal a potential reversion to a lower price.
• Shorting involves borrowing, selling, buying back, and returning an instrument, with profits realized if the price declines.

Implementing the Price Volume Idea on World Quant Brain

• The Group Rank function ranks the difference between closing and opening prices of stocks.
• Stocks are ranked within the same sub-industry, with values ranging from 0 to 1.
• A value closer to 1 indicates a better rank.
• "Delay" refers to the timing of the data; Delay 1 uses the previous day's price, and Delay 0 uses the current day's.
• Decay is a weighted sum of past alpha values used to smooth fluctuations and reduce turnover.
• The simulation uses Delay 1 data to prevent look-ahead bias and neutralizes the alpha over sub-industry.
• A decay of 10 is applied for signal smoothing, with a maximum capital allocation of 1% to any single stock.
• The backtesting simulation was conducted over five years.
• This simulation yielded a Sharpe ratio of 1.7.

Improving the Price Volume Alpha

• Improved by controlling turnover, specifically by trading only when conditions are suitable for reversion.
• Results may improve by trading during higher volatility and holding during lower volatility.

Fundamental Data Category

• Fundamentals reflect a company's business, financial, and operational health.
• Data is generally reported quarterly.
• Data fields are summarised into the balance sheet, income statement, and cash flow statement.
• The balance sheet details assets, liabilities, and equity.
• The income statement illustrates profitability.
• The cash flow statement tracks cash inflows and outflows.

Using Cash Flow from Operations to Market Cap Ratio

• Cash flow from operations is the cash generated through a company's primary business activities.
• Market capitalization is the total market value of a company's outstanding shares.
• The ratio of cash flow from operations to market capitalization indicates whether a company is fairly valued relative to its cash-generating abilities.
• A high ratio may indicate an undervalued firm with the potential for higher future returns.
• Improvement in this ratio over time may indicate stock outperformance.

Implementing the Fundamental Data Idea on World Quant Brain

• The Time Series Z Score function illustrates changes in the cash flow to market cap ratio over the last 60 trading days.
• The Z score indicates how far a value deviates from the mean of a group in terms of standard deviations.
• Applying the Time Series Z Score function to cash flow to market cap data yielded a consistent Sharpe ratio of approximately 2.
• Utilizing analyst predictions for each stock's operational cash flow may improve the alpha's performance.
• Analyst estimates offer insight into expected company performance prior to quarterly earnings reports.