Mathematician Credit Spread & Zen Credit Spread settings

[gjrao75]

Hi, I have subscribed for Mathematician Credit Spread & Zen Credit Spread algos, these are getting executed successfully, however, I am concerned about the profit booking. One algo gave me ~9k profits and but when the market reversed, the Algo did not exit with profits. Eventually the trade become 9k loss and at 50% of loss it closed the trade. I am seeing the same set-up in the Zen credit as well. At the same time, another Algo also placed in the reverse and end with losses. Any body suggest the best way of deploying these algos? Should both be active, should I manually exit when I get good profits? Is there a combo that I can depoy along with these? please suggest.

Jagadeesh

[jay.gori]

Hi @gjrao75

Welcome to Stratzy, and thank you for sharing your experience.

Please note that the Algos manage their exits based on their predefined strategy logic and exit criteria. An open position moving into profit does not necessarily mean that the Algo will book the profit immediately, as the strategy may continue to hold the position until its defined exit conditions are met.

Similarly, we generally recommend not manually intervening in LIVE Algo trades based on short-term price movements or the profit visible at a particular point in time. The objective of Algo Trading is to follow a disciplined, rule-based approach.

Regarding deploying Mathematician and Zen together or selecting additional Algos, there is no single combination that would be suitable for every user. The appropriate portfolio depends on factors such as your risk appetite, trading ideology, return expectations, and overall portfolio objectives. We recommend evaluating the historical performance, drawdowns, risk metrics, and correlation of Algos before building your portfolio.

For a better understanding of Algo portfolio construction, I would also recommend referring to our community post on building a diversified Algo portfolio:

Which algo trading strategy should you deploy? A cheat sheet — and the philosophy behind it

This is one of the most asked questions in our community. The honest answer is: it depends. But here’s a framework to think about it properly. The big idea: more uncorrelated algos = more stable returns WorldQuant — one of the world’s top quantitative hedge funds — manages $15–16 billion using millions of individual alphas (their term for small, rule-based signals). Not one big strategy. Millions of tiny, uncorrelated ones working together. The reason? No single algo is right all the time. Ma…

[gjrao75]

Hi Jay,Thank you for your response. Much apprecaited. I understand that the algos are currently working based on predefined conditions/statuses. However, my concern is specifically around profit booking and dynamic exits when the market reverses.

I observed the same pattern again today. The algos are able to identify the market conditions and place orders correctly, but they are not exiting at the right time to protect the profits. Instead, when the market reverses, the profits are given back and the positions eventually exit at a significant loss.

For example, today the market was in the red, and the algo placed the orders correctly without any issue. At one point, the account was showing approximately ₹12K profit, which was very good. However, during the afternoon, the market reversed. At that point, my expectation was that the algo should have dynamically evaluated the changing market conditions and activated a trailing stop-loss—for example, either locking in 50% of the profit or moving the stop-loss to at least the cost/break-even level.

Unfortunately, nothing was triggered. The market reversed, the entire profit disappeared, and the position ultimately ended up with approximately ₹26K loss.

This raises two important questions that I believe need to be addressed in the use case:

1. Why is the algo not exiting or protecting the position when the market condition reverses after the trade has moved significantly into profit?

2. Why is the algo continuing to wait for the predefined exit/loss condition while simultaneously identifying the changed market conditions well enough to place new PUT orders?

The second point is particularly important. If the algo is capable of dynamically evaluating the market and placing new PUT orders when the conditions change, it clearly indicates that the algo is continuously checking the market conditions. In that case, the same dynamic logic should also be applied to existing positions for profit protection and timely exits.

I believe the use case needs to be revisited to include a dynamic profit-protection and reversal-exit mechanism, rather than relying only on predefined exit conditions.

The objective should be: once a trade moves into meaningful profit, the algo should prioritize protecting that profit when the market reverses, instead of allowing the position to move from profit into a substantial loss.

Best Regards,

Jagadeesh.

[jay.gori]

Hi @gjrao75

I understand the point you’re making. However, the conclusion here is largely based on hindsight bias, looking at the peak profit that was visible during the trade and then determining that the Algo should have exited at that point once we know how the trade subsequently ended.

The Algo is not designed for a profit-protection mechanism simply because a position has temporarily moved into profit. Its exits are determined by the predefined strategy logic and criteria, which are applied consistently irrespective of what the eventual outcome of the trade may be.

Entry logic and exit logic serve different purposes and are evaluated independently.

Introducing a different exit mechanism based on the outcome of individual trades would fundamentally change the strategy itself. This is why the Algo should be evaluated based on its complete trade history and predefined methodology rather than individual instances where hindsight makes an alternative exit appear obvious.

We have noted your feedback regarding profit protection and dynamic exits.

[gjrao75]

Hi Jay,

Great. I completely agree with your perspective on the strategies and the way they operate within predefined rules and fixed targets. The reports shown that the algorithms have strong potential to perform successfully and deliver consistent results over the period of time.

Given my strong interest in technology and trading, I continuously explore different market scenarios and evaluate how strategies could potentially adapt to changing market conditions. From that perspective, the concept of a dynamic exit has been on my mind, not as a concern with the existing approach, but as an opportunity to evaluate whether it could further enhance the strategy under specific market conditions or as a new straegy it self.

Ultimately, every trader’s objective is to maintain a consistently “green” account. If these algorithms can help traders achieve that level of consistency and discipline, I believe they have the potential to make a significant difference in people’s trading journeys and, ultimately, contribute toward greater financial independence.

Thank you for considering my feedback. I appreciate your perspective and the opportunity to share these thoughts.

Best Regards,

Jagadeesh.

[ProTrader]

@jay.gori

hindsight bias

Hi @jay.gori There is one good point you have mentioned, that changing the exit criteria will fundamentally change the algo.

Can you bring up new algos with entry criteria as per existing Curvature, Damper and Zen but exit criteria based on Trailing SL. So those will be entirely new algos, users concerned about trailing SL will use those.

I hope this is workable as there are already some algos with and without TSL and early-exit.

[jay.gori]

Hi @ProTrader

That’s a valid suggestion. I’ve shared this with our quant team for further discussion and consideration. If it aligns with the strategy design and testing results, we can explore it as a potential new Algo.

We’ll take it forward as part of our ongoing evaluation of new strategy ideas.