backtest-expert

Name: backtest-expert
Author: ajeeshworkspace

48stars41forks

How to install backtest-expert?

ajeeshworkspace/indian-trading-skills/backtest-expert

$npx -y skills add ajeeshworkspace/indian-trading-skills --skill backtest-expert

Installs into the current project.

Summary

Expert guidance for systematic backtesting of trading strategies on Indian markets (NSE/BSE). Use when developing strategies, testing robustness, avoiding overfitting, or validating trading ideas.

Files · 1

View on GitHub

SKILL.md

1	# Backtest Expert — Indian Market Strategy Validation
2
3	## Core Philosophy
4
5	> "Find strategies that break the least, not profit the most."
6
7	A strategy that survives stress testing across multiple market regimes, transaction cost assumptions, and parameter perturbations is far more valuable than one that shows spectacular returns on a single optimized parameter set. Overfitting is the silent killer of trading accounts.
8
9	---
10
11	## 6-Step Backtesting Workflow
12
13	### Step 1: State the Hypothesis (1 Sentence Edge)
14
15	Before writing a single line of code, articulate why the strategy should work in one clear sentence.
16
17	Good hypotheses:
18	- "Stocks that gap up >3% on above-average volume after consolidation tend to continue higher for 2-5 days on NSE."
19	- "Nifty 50 stocks that revert to their 20-day mean after RSI drops below 30 produce positive expectancy within 5 trading sessions."
20	- "Selling strangles on Bank Nifty on Wednesday expiry with delta <0.15 captures time decay faster than gamma risk materializes."
21
22	Bad hypotheses:
23	- "This indicator combination looks good on the chart." (no edge articulated)
24	- "I saw someone on Twitter making money with this." (no reasoning)
25
26	Ask yourself:
27	- What behavioral or structural edge am I exploiting?
28	- Why would this edge persist? (Structural > Behavioral > Statistical)
29	- Who is on the other side of this trade, and why are they losing?
30
31	---
32
33	### Step 2: Codify Rules (No Ambiguity)
34
35	Every rule must be binary — a computer must be able to execute it without interpretation.
36
37	#### Rule Categories
38
39	\| Category \| What to Define \| Example \|
40	\|----------\|---------------\|---------\|
41	\| Universe \| Which stocks/instruments \| Nifty 200 constituents, F&O stocks only, market cap >5000 Cr \|
42	\| Entry \| Exact trigger conditions \| Close > 20 EMA AND RSI(14) crosses above 40 AND volume > 1.5x 20-day avg \|
43	\| Exit — Target \| Profit-taking rule \| Close 3% above entry OR trailing stop of 1.5 ATR \|
44	\| Exit — Stop \| Loss-cutting rule \| Close below entry-day low OR 2% fixed stop \|
45	\| Exit — Time \| Maximum holding period \| Exit after 10 trading sessions if neither target nor stop hit \|
46	\| Position Sizing \| How much capital per trade \| 5% of equity per position, max 10 concurrent positions \|
47	\| Filters \| When NOT to trade \| Skip if stock is in F&O ban period, skip 2 days around results \|
48
49	#### India-Specific Rules to Consider
50	- Circuit limits: Stocks hitting upper/lower circuit cannot be exited. Define handling.
51	- F&O ban period: Stocks crossing 95% MWPL cannot add fresh F&O positions.
52	- T+1 settlement: Cash equity settles next trading day (changed from T+2 in 2023).
53	- Pre-open session: 9:00-9:08 AM orders, 9:08-9:15 AM matching. Define if you use pre-open.
54	- Muhurat trading: Special Diwali session — include or exclude?
55	- Corporate actions: Adjust for splits, bonuses, dividends, rights issues.
56
57	---
58
59	### Step 3: Run Initial Backtest
60
61	#### Minimum Requirements
62
63	\| Parameter \| Minimum \| Recommended \|
64	\|-----------\|---------\|-------------\|
65	\| Time period \| 5 years \| 8-10+ years \|
66	\| Number of trades \| 100 \| 200+ \|
67	\| Market regimes covered \| 2 (bull + bear) \| 4+ (bull, bear, sideways, high-vol) \|
68	\| Data quality \| Adjusted for corporate actions \| Survivorship-bias-free universe \|
69
70	#### Indian Market Regimes to Cover
71
72	\| Regime \| Period Examples \| Characteristics \|
73	\|--------\|----------------\|-----------------\|
74	\| Bull market \| 2014-2017, 2020-2021 \| Nifty trending up, broad participation \|
75	\| Bear market \| 2008, 2020 (Mar), 2022 (Jun) \| Sharp drawdowns, high correlation \|
76	\| Sideways/Range \| 2018-2019, 2023 H1 \| Nifty in 10% range, stock-specific moves \|
77	\| High volatility \| 2008, 2020, Budget days \| India VIX > 25 \|
78	\| Low volatility \| 2017, 2021 H2 \| India VIX < 15 \|
79	\| Pre/Post Budget \| Every Feb 1 \| Gap moves, policy-driven sectors \|
80	\| Election cycle \| 2014, 2019, 2024 \| Uncertainty then rally pattern \|
81	\| Monsoon impact \| Jun-Sep annually \| Agri, FMCG, rural economy impact \|
82	\| RBI policy shifts \| Rate hike/cut cycles \| Banking, NBFC, rate-sensitive sectors \|
83	\| Global crude shock \| 2018, 2022 \| INR weakness, OMC impact, inflation \|
84
85	#### Key Metrics to Record
86
87	```
88	Returns: CAGR, total return, monthly returns distribution
89	Risk: Max drawdown, average drawdown, drawdown duration, Calmar ratio
90	Efficiency: Sharpe ratio (use 6% risk-free for India), Sortino ratio
91	Trade quality: Win rate, avg win/loss, profit factor, expectancy per trade
92	Consistency: % profitable months, worst month, longest losing streak
93	```
94
95	---
96
97	### Step 4: Stress Test (Spend 80% of Your Time Here)
98
99	This is where most backtests fail — and where the real value lies.
100
101	#### 4a. Parameter Sensitivity
102
103	Perturb every

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backtest-expert

48stars41forks

View on GitHub

How to install backtest-expert?

ajeeshworkspace/indian-trading-skills/backtest-expert

$npx -y skills add ajeeshworkspace/indian-trading-skills --skill backtest-expert

Installs into the current project.

Summary

Expert guidance for systematic backtesting of trading strategies on Indian markets (NSE/BSE). Use when developing strategies, testing robustness, avoiding overfitting, or validating trading ideas.

Files · 1

View on GitHub

SKILL.md

1	# Backtest Expert — Indian Market Strategy Validation
2
3	## Core Philosophy
4
5	> "Find strategies that break the least, not profit the most."
6
7	A strategy that survives stress testing across multiple market regimes, transaction cost assumptions, and parameter perturbations is far more valuable than one that shows spectacular returns on a single optimized parameter set. Overfitting is the silent killer of trading accounts.
8
9	---
10
11	## 6-Step Backtesting Workflow
12
13	### Step 1: State the Hypothesis (1 Sentence Edge)
14
15	Before writing a single line of code, articulate why the strategy should work in one clear sentence.
16
17	Good hypotheses:
18	- "Stocks that gap up >3% on above-average volume after consolidation tend to continue higher for 2-5 days on NSE."
19	- "Nifty 50 stocks that revert to their 20-day mean after RSI drops below 30 produce positive expectancy within 5 trading sessions."
20	- "Selling strangles on Bank Nifty on Wednesday expiry with delta <0.15 captures time decay faster than gamma risk materializes."
21
22	Bad hypotheses:
23	- "This indicator combination looks good on the chart." (no edge articulated)
24	- "I saw someone on Twitter making money with this." (no reasoning)
25
26	Ask yourself:
27	- What behavioral or structural edge am I exploiting?
28	- Why would this edge persist? (Structural > Behavioral > Statistical)
29	- Who is on the other side of this trade, and why are they losing?
30
31	---
32
33	### Step 2: Codify Rules (No Ambiguity)
34
35	Every rule must be binary — a computer must be able to execute it without interpretation.
36
37	#### Rule Categories
38
39	\| Category \| What to Define \| Example \|
40	\|----------\|---------------\|---------\|
41	\| Universe \| Which stocks/instruments \| Nifty 200 constituents, F&O stocks only, market cap >5000 Cr \|
42	\| Entry \| Exact trigger conditions \| Close > 20 EMA AND RSI(14) crosses above 40 AND volume > 1.5x 20-day avg \|
43	\| Exit — Target \| Profit-taking rule \| Close 3% above entry OR trailing stop of 1.5 ATR \|
44	\| Exit — Stop \| Loss-cutting rule \| Close below entry-day low OR 2% fixed stop \|
45	\| Exit — Time \| Maximum holding period \| Exit after 10 trading sessions if neither target nor stop hit \|
46	\| Position Sizing \| How much capital per trade \| 5% of equity per position, max 10 concurrent positions \|
47	\| Filters \| When NOT to trade \| Skip if stock is in F&O ban period, skip 2 days around results \|
48
49	#### India-Specific Rules to Consider
50	- Circuit limits: Stocks hitting upper/lower circuit cannot be exited. Define handling.
51	- F&O ban period: Stocks crossing 95% MWPL cannot add fresh F&O positions.
52	- T+1 settlement: Cash equity settles next trading day (changed from T+2 in 2023).
53	- Pre-open session: 9:00-9:08 AM orders, 9:08-9:15 AM matching. Define if you use pre-open.
54	- Muhurat trading: Special Diwali session — include or exclude?
55	- Corporate actions: Adjust for splits, bonuses, dividends, rights issues.
56
57	---
58
59	### Step 3: Run Initial Backtest
60
61	#### Minimum Requirements
62
63	\| Parameter \| Minimum \| Recommended \|
64	\|-----------\|---------\|-------------\|
65	\| Time period \| 5 years \| 8-10+ years \|
66	\| Number of trades \| 100 \| 200+ \|
67	\| Market regimes covered \| 2 (bull + bear) \| 4+ (bull, bear, sideways, high-vol) \|
68	\| Data quality \| Adjusted for corporate actions \| Survivorship-bias-free universe \|
69
70	#### Indian Market Regimes to Cover
71
72	\| Regime \| Period Examples \| Characteristics \|
73	\|--------\|----------------\|-----------------\|
74	\| Bull market \| 2014-2017, 2020-2021 \| Nifty trending up, broad participation \|
75	\| Bear market \| 2008, 2020 (Mar), 2022 (Jun) \| Sharp drawdowns, high correlation \|
76	\| Sideways/Range \| 2018-2019, 2023 H1 \| Nifty in 10% range, stock-specific moves \|
77	\| High volatility \| 2008, 2020, Budget days \| India VIX > 25 \|
78	\| Low volatility \| 2017, 2021 H2 \| India VIX < 15 \|
79	\| Pre/Post Budget \| Every Feb 1 \| Gap moves, policy-driven sectors \|
80	\| Election cycle \| 2014, 2019, 2024 \| Uncertainty then rally pattern \|
81	\| Monsoon impact \| Jun-Sep annually \| Agri, FMCG, rural economy impact \|
82	\| RBI policy shifts \| Rate hike/cut cycles \| Banking, NBFC, rate-sensitive sectors \|
83	\| Global crude shock \| 2018, 2022 \| INR weakness, OMC impact, inflation \|
84
85	#### Key Metrics to Record
86
87	```
88	Returns: CAGR, total return, monthly returns distribution
89	Risk: Max drawdown, average drawdown, drawdown duration, Calmar ratio
90	Efficiency: Sharpe ratio (use 6% risk-free for India), Sortino ratio
91	Trade quality: Win rate, avg win/loss, profit factor, expectancy per trade
92	Consistency: % profitable months, worst month, longest losing streak
93	```
94
95	---
96
97	### Step 4: Stress Test (Spend 80% of Your Time Here)
98
99	This is where most backtests fail — and where the real value lies.
100
101	#### 4a. Parameter Sensitivity
102
103	Perturb every

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