Risks of Counting on OHLC Costs – the Case of In a single day Drift in GDX ETF
Can we really depend on the opening value in OHLC knowledge for backtesting? Whereas the in a single day drift impact is well-documented in a number of asset courses, we investigated its presence in gold utilizing the GLD ETF after which prolonged our evaluation to the GDX – Gold Miners ETF, the place we noticed an unusually sturdy in a single day return exceeding 30% annualized. Nonetheless, after we examined execution at 9:31 AM utilizing 1-minute knowledge, the anomaly diminished considerably, suggesting that the acute return was partially a knowledge artifact. This discovering highlights the dangers of blindly trusting OHLC open costs and underscores the necessity for higher-frequency knowledge to validate execution assumptions.
Background
The in a single day impact and drift in quantitative finance seek advice from the phenomenon the place inventory returns throughout non-trading hours, notably in a single day, exhibit important patterns that differ from these noticed throughout buying and selling hours. The in a single day impact refers back to the tendency of inventory returns to exhibit substantial actions in the course of the evening, typically influenced by market dynamics and investor sentiment.
One of many newer papers on this area is “The Cross-Part of Intraday and In a single day Returns” by Vincent Bogousslavsky (2021). This influential work investigates the patterns of intraday and in a single day returns and their implications for asset pricing fashions, offering precious insights into the habits of monetary markets throughout non-trading hours.
The paper “In a single day Drift” by Boyarchenko, Larsen, and Whelan (2023) additionally explores this fascinating impact. The principle discovering is that U.S. fairness returns are notably optimistic in the course of the opening hours of European markets, pushed by order imbalances from the earlier buying and selling day. Market sell-offs result in sturdy in a single day reversals, whereas rallies lead to modest reversals, indicating an uneven response to demand shocks.
We at Quantpedia explored this impact considerably, too, and found an in a single day impact on Bitcoin returns and high-yield ETF returns. By constructing on this papers we purpose to increase the understanding of in a single day methods and value drifts, providing new views and leveraging the established SPY drift paradigm and increasing it to the commodities asset class that gold (and gold mining shares) ETFs characterize.
Knowledge
We initially sourced our knowledge from finance.yahoo.com, making mandatory changes for dividends. We examined the close-to-open and open-to-close value actions, which gave us a transparent view of the in a single day and intraday drifts.
Gold ETF
As talked about earlier, we analyzed GLD’s in a single day, intraday, and complete efficiency utilizing historic knowledge from Yahoo Finance. Our evaluation reveals that a good portion of GLD’s efficiency happens in a single day. The GLD ETF’s intraday efficiency over the past 20 years is negligible. These findings are according to the worth motion taking place within the different asset courses we talked about earlier than (particular person shares, fairness indices, cryptocurrencies, or high-yield ETFs).
Nonetheless, as gold is a commodity, there exist corporations specializing within the technique of extracting this gold from the Earth’s crust (sure, we’re talking about gold miners). Due to this fact, we will bridge fairness and commodity markets, by shopping for ETFs which put money into such shares, like GDX (VanEck Gold Miners ETF). In idea, this convergent asset ought to give us the potential for mixed in a single day drift results and better income, proper?
Let’s discover that.
Gold Miners ETF
Following the identical strategy, we carried out the identical process utilizing GDX OHLC (open, excessive, low, shut) knowledge. Our evaluation reveals a big in a single day drift of roughly 30% every year (p.a.), contrasted by a considerable unfavorable intraday drift of about -25% every year. These findings immediate a logical buying and selling technique: iteratively buying at market open and shorting at market shut. Theoretically, this strategy may yield important returns over time.
Wow, we may get wealthy fast right here! Or not? Effectively, really, from the expertise, this seems to be to good to be true. We have to examine the underlying drawback.
From our expertise, the issue is often hidden within the opening costs of the OHLC datasets. Notably, the opening value is derived from the primary commerce quite than the MOO (Market-on-Open) public sale outcomes, resulting in important discrepancies between anticipated and precise opening costs as one is unable to even carefully strategy getting fills in that value area, not talking about volumes traded at that costs which have to be minuscule. That is frequent drawback when utilizing the OHLC knowledge. The shut costs are often achievable in actuality by buying and selling (shopping for/promoting) near the tip of the buying and selling session or collaborating within the closing public sale by way of MOC (Market-on-Shut) orders. Traditionally, closing costs on monetary platforms comparable to Yahoo Finance often align with MOC public sale costs.
Whereas executing on the shut sometimes presents no points for opening costs, the truth is usually very completely different. Due to this fact, our common subsequent step is all the time to revert to testing anomalies and results with higher knowledge granularity (minute-by-minute bars, second-by-second bars, or tick knowledge). Due to this fact, let’s attempt to modify the execution of the promote sign from 9:30 AM to 9:31 AM. One minute mustn’t make a distinction, proper? For that, we transitioned to the QuantConnect atmosphere as intraday TOC (Time-of-Change) knowledge are mandatory.
SPY and GDX In a single day Results Analysis
Let’s transfer to guage the efficiency of in a single day buying and selling methods utilizing
SPDR S&P 500 ETF (SPY) and
VanEck Vectors Gold Miners ETF (GDX).
It focuses on execution timing, specifically
Market-on-Open (MOO), vs.
a selected intraday execution at 9:31 AM.
Varied Situations
SPY Buying and selling Technique:
State of affairs 1: SPY, purchase MOC, promote MOO.
State of affairs 2: SPY, purchase MOC, promote 9:31.
GDX Buying and selling Technique:
State of affairs 1: GDX, purchase MOC, promote MOO.
State of affairs 2: GDX, purchase MOC, promote 9:31.
SPY
State of affairs 1
State of affairs 2
Our backtest outcomes present solely slight variations between executing on the open value and the precise intraday time of 9:31 AM, with the latter exhibiting rather less revenue. The in a single day impact is effectively and alive. Sure, there’s a slight lower in efficiency should you execute a promote order at 9:31 AM (in comparison with the hypothetical execution at 9:30), however the lower is small, and the impact continues to be current as a big a part of the SPY complete return over the past years is registered over the evening session, and it doesn’t matter lots if that evening session ends at 9.30 or 9.31.
GDX
State of affairs 1
Backtest outcomes exhibit extremely unrealistic, excessive numbers.
State of affairs 2
Then again, our backtests on the GDX ETF can’t be extra completely different. The backtest utilizing the OHLC knowledge additionally exhibits completely unrealistic efficiency, roughly 30% every year, for the in a single day drift technique. Then again, the second situation, by which the promote sign is executed at 9:31 AM, yields a considerably extra sensible end result. The efficiency of the GDX in a single day technique (earlier than charges and slippage) is 8,58% every year, with a -40,7% most drawdown and 16.9% volatility. Sure, the in a single day drift in GDX costs is certainly there, too. Nonetheless, the magnitude of the impact will not be as excessive because the evaluation utilizing the OHLC knowledge hinted.
Dialogue & Conclusion
The in a single day drift signifies a notable sample the place many of the asset’s efficiency is pushed by in a single day actions. This discovering aligns with our observations in different asset courses, suggesting a broader applicability of in a single day drift phenomena. Along with elucidating the in a single day drift in conventional asset courses comparable to equities, our investigation underscores the crucial significance of sturdy methodological scrutiny in backtesting buying and selling methods. Particularly, the pronounced discrepancies noticed between theoretically derived and virtually executable costs spotlight potential pitfalls within the naive software of OHLC knowledge.
The discrepancy in backtest efficiency for GDX is attributed to the methodology used to report open costs (open costs) in OHLC knowledge. It’s impractical to count on execution on the reported open costs. Due to this fact, rigorous consideration must be paid when creating methods that presume execution at open costs. It’s advisable to conduct robustness checks and confirm efficiency with intraday execution costs, comparable to these at 9:31 AM, to make sure extra dependable outcomes.
Writer: Cyril Dujava, Quant Analyst, Quantpedia
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