backtesting

Taiwan’s short-selling signals are often misleading because the market operates under a dual-track system: retail investors short stocks through margin accounts, while institutional investors use securities borrowing and lending (SBL). Only SBL-based short selling reflects informed institutional sentiment, while margin shorting introduces noise. This study isolates SBL to construct the Short Interest Ratio (SIR) and evaluates its ability to predict cross-sectional returns and reveal size-dependent patterns in informed short-selling behavior.

This study examines whether incorporating the Short Interest Ratio (SIR) can improve the performance of a 52-week high momentum strategy in Taiwan. By comparing a baseline momentum model with two SIR-enhanced versions—one using SIR as a filter and another integrating it into a composite score—we find consistent gains in returns, lower volatility, and reduced drawdowns. The results show that SIR strengthens momentum strategies by identifying stocks under institutional short-selling pressure.

LazyBear is a highly influential indicator developer on the internationally renowned trading platform, TradingView. He has created a large number of popular custom technical indicators, and his open-source code has inspired countless quantitative traders and technical analysis enthusiasts around the world. LazyBear's indicators often focus on reducing the lag of traditional indicators and incorporate unique market observations to better capture trends and momentum. One of his representative works, the "Impulse MACD," is adopted here. This indicator is not a traditional Moving Average Convergence Divergence (MACD), but rather a significantly improved version. It uses a zero-lag Double Exponential Moving Average (DEMA) to respond more quickly to price changes and combines a smoothed high-low price channel (SMMA) to determine market "impulse." The core idea is that trading signals are more valuable only when price momentum aligns with the trend direction. This helps to filter out some of the noise typically found in ranging markets.

The concept of the Moving Average (MA) originates from the Dow Theory developed in the early 20th century. Dow Theory emphasizes that markets exhibit trends, and such trends can be observed through price movements themselves. From the Simple Moving Average (SMA) and Exponential Moving Average (EMA) to more sophisticated variants such as the Double Exponential Moving Average (DEMA) and Hull Moving Average (HMA), all these improvements aim to address the inherent lag problem of traditional moving averages, allowing them to reflect price trends more quickly or more smoothly.

In the Taiwan stock market, credit trading (margin buying and short selling) serves as a critical mechanism for observing market leverage and investor sentiment. Unlike institutional investors with ample capital, retail investors often face capital constraints and therefore resort to margin buying to  increase their purchasing power. Consequently, margin data serves as a key barometer for retail trading heat.  Key indicators for monitoring credit trading include daily margin/short volume, balance, margin utilization rates, and—most crucially—the Margin Maintenance Ratio (MMR).  The MMR is a core metric used to assess the risk status of margin accounts and determine how close investors are to a margin call. Brokers set specific MMR thresholds to mitigate default risks during periods of high market volatility.

In financial markets, Contrary Thinking is a timeless strategic wisdom. It stems from a simple yet profound observation: when most people are overly optimistic, the market is often overheated; when the crowd falls into fear, it may actually present a buying opportunity. However, contrarian investing has long remained at the level of a proverb, lacking concrete and quantifiable standards of action, making it difficult to implement in practice.

Analyze industry rotation between Taiwan’s shipping and semiconductor sectors using momentum and valuation factors. This study reveals how factor-based strategies capture cyclical shifts—and why semiconductors ultimately outperformed over time.

TEJ (Taiwan Economic Journal) is a renowned financial information service platform in Taiwan. It provides a wide range of data and analysis tools covering various aspects such as economics, finance, stock markets, bond markets, and futures. With its extensive database and professional analytical features, the TEJ platform is widely used by financial institutions, research units, and investors to access real-time, accurate market data and conduct in-depth data analysis to support decision-making.

This series of articles uses Alphalens to examine the application and effectiveness of various factors in the market. In previous articles, we analyzed "foreign capital factors," exploring how foreign investments influence the market. This article will focus on "value factors," examining valuation-related indicators that reveal intrinsic value and affect long-term returns. You can use the alphalens-tej tool within TQuant Lab. This tool not only integrates TEJ data but also eliminates tedious data processing, allowing you to easily assess factor performance and further support the development of investment strategies.

This series of articles will use Alphalens to explore several key factors, gradually analyzing their impact on market performance. The first article focuses on "foreign capital," examining the effects of foreign capital flows into the market. Next, we'll delve into "value factors," studying how they reflect a company's intrinsic value. Finally, the last article will analyze "price-volume factors," uncovering the interplay between price and trading volume.

When using TQuant Lab for backtesting and strategy analysis, beginners may encounter various technical challenges and questions. This article provides solutions and tips to help users develop and backtest strategies more smoothly, improving efficiency and accuracy. Hopefully, this information will help resolve common problems faced by newcomers.

This article will explore the common types of quantitative investment strategies as well as the advantages and potential challenges of this trading model.