diff --git a/src/trade-matcher/trade_gradient.ts b/src/trade-matcher/trade_gradient.ts
new file mode 100644
index 0000000..4f285bf
--- /dev/null
+++ b/src/trade-matcher/trade_gradient.ts
@@ -0,0 +1,243 @@
+import { BigNumber } from '../utils/numerics';
+
+const R_ONE          = BigNumber.from(1).shl(48);  // = 2 ^ 48
+const M_ONE          = BigNumber.from(1).shl(24);  // = 2 ^ 24
+const EXP_ONE        = BigNumber.from(1).shl(127); // = 2 ^ 127
+const MAX_VAL        = BigNumber.from(1).shl(131); // = 2 ^ 131
+const RR             = R_ONE.mul(R_ONE);           // = 2 ^ 96
+const MM             = M_ONE.mul(M_ONE);           // = 2 ^ 48
+const RR_MUL_MM      = RR.mul(MM);                 // = 2 ^ 144
+const RR_DIV_MM      = RR.div(MM);                 // = 2 ^ 48
+const EXP_ONE_MUL_RR = EXP_ONE.mul(RR);            // = 2 ^ 223
+const EXP_ONE_DIV_RR = EXP_ONE.div(RR);            // = 2 ^ 31
+const EXP_ONE_DIV_MM = EXP_ONE.div(MM);            // = 2 ^ 79
+
+const MAX_UINT128 = BigNumber.from(2).pow(128).sub(1);
+const MAX_UINT256 = BigNumber.from(2).pow(256).sub(1);
+
+function check(val: BigNumber, max: BigNumber) {
+  if (val.gte(0) && val.lte(max)) {
+    return val;
+  }
+  throw null;
+}
+
+const uint128 = (n: BigNumber) => check(n, MAX_UINT128);
+const add = (a: BigNumber, b: BigNumber) => check(a.add(b), MAX_UINT256);
+const mul = (a: BigNumber, b: BigNumber) => check(a.mul(b), MAX_UINT256);
+const mulDivF = (a: BigNumber, b: BigNumber, c: BigNumber) =>
+  check(a.mul(b).div(c), MAX_UINT256);
+const mulDivC = (a: BigNumber, b: BigNumber, c: BigNumber) =>
+  check(a.mul(b).add(c).sub(1).div(c), MAX_UINT256);
+
+enum GradientType {
+  LINEAR_INCREASE,
+  LINEAR_DECREASE,
+  LINEAR_INV_INCREASE,
+  LINEAR_INV_DECREASE,
+  EXPONENTIAL_INCREASE,
+  EXPONENTIAL_DECREASE
+}
+
+function calcTargetAmount(
+  gradientType: GradientType,
+  initialRate: BigNumber,
+  multiFactor: BigNumber,
+  timeElapsed: BigNumber,
+  sourceAmount: BigNumber
+): BigNumber {
+  const rate = calcCurrentRate(gradientType, initialRate, multiFactor, timeElapsed);
+  return mulDivF(sourceAmount, rate[0], rate[1]);
+}
+
+function calcSourceAmount(
+  gradientType: GradientType,
+  initialRate: BigNumber,
+  multiFactor: BigNumber,
+  timeElapsed: BigNumber,
+  targetAmount: BigNumber
+): BigNumber {
+  const rate = calcCurrentRate(gradientType, initialRate, multiFactor, timeElapsed);
+  return mulDivC(targetAmount, rate[1], rate[0]);
+}
+
+/**
+* @dev Given the following parameters:
+* r - the gradient's initial exchange rate
+* m - the gradient's multiplication factor
+* t - the time elapsed since strategy creation
+*
+* Calculate the current exchange rate for each one of the following gradients:
+* +----------------+-----------+-----------------+----------------------------------------------+
+* | type           | direction | formula         | restriction                                  |
+* +----------------+-----------+-----------------+----------------------------------------------+
+* | linear         | increase  | r * (1 + m * t) |                                              |
+* | linear         | decrease  | r * (1 - m * t) | m * t < 1 (ensure a finite-positive rate)    |
+* | linear-inverse | increase  | r / (1 - m * t) | m * t < 1 (ensure a finite-positive rate)    |
+* | linear-inverse | decrease  | r / (1 + m * t) |                                              |
+* | exponential    | increase  | r * e ^ (m * t) | m * t < 16 (due to computational limitation) |
+* | exponential    | decrease  | r / e ^ (m * t) | m * t < 16 (due to computational limitation) |
+* +----------------+-----------+-----------------+----------------------------------------------+
+*/
+function calcCurrentRate(
+  gradientType: GradientType,
+  initialRate: BigNumber, // the 48-bit-mantissa-6-bit-exponent encoding of the initial exchange rate square root
+  multiFactor: BigNumber, // the 24-bit-mantissa-5-bit-exponent encoding of the multiplication factor times 2 ^ 24
+  timeElapsed: BigNumber, /// the time elapsed since strategy creation
+): [BigNumber, BigNumber] {
+  if ((R_ONE.shr(initialRate.div(R_ONE).toNumber())).eq(0)) {
+    throw new Error('InitialRateTooHigh');
+  }
+
+  if ((M_ONE.shr(multiFactor.div(M_ONE).toNumber())).eq(0)) {
+    throw new Error('MultiFactorTooHigh');
+  }
+
+  const r = initialRate.mod(R_ONE).shl(initialRate.div(R_ONE).toNumber()); // = floor(sqrt(initial_rate) * 2 ^ 48)    < 2 ^ 96
+  const m = multiFactor.mod(M_ONE).shl(multiFactor.div(M_ONE).toNumber()); // = floor(multi_factor * 2 ^ 24 * 2 ^ 24) < 2 ^ 48
+  const t = timeElapsed;
+
+  const rr = mul(r, r); // < 2 ^ 192
+  const mt = mul(m, t); // < 2 ^ 80
+
+  if (gradientType == GradientType.LINEAR_INCREASE) {
+    // initial_rate * (1 + multi_factor * time_elapsed)
+    const temp1 = rr; /////////// < 2 ^ 192
+    const temp2 = add(MM, mt); // < 2 ^ 81
+    const temp3 = mulDivC(temp1, temp2, MAX_UINT256);
+    const temp4 = RR_MUL_MM;
+    return [mulDivF(temp1, temp2, temp3), temp4.div(temp3)]; // not ideal
+  }
+
+  if (gradientType == GradientType.LINEAR_DECREASE) {
+    // initial_rate * (1 - multi_factor * time_elapsed)
+    const temp1 = mul(rr, sub(MM, mt)); // < 2 ^ 240
+    const temp2 = RR_MUL_MM;
+    return [temp1, temp2];
+  }
+
+  if (gradientType == GradientType.LINEAR_INV_INCREASE) {
+    // initial_rate / (1 - multi_factor * time_elapsed)
+    const temp1 = rr;
+    const temp2 = sub(RR, mul(mt, RR_DIV_MM)); // < 2 ^ 128 (inner expression)
+    return [temp1, temp2];
+  }
+
+  if (gradientType == GradientType.LINEAR_INV_DECREASE) {
+    // initial_rate / (1 + multi_factor * time_elapsed)
+    const temp1 = rr;
+    const temp2 = add(RR, mul(mt, RR_DIV_MM)); // < 2 ^ 129
+    return [temp1, temp2];
+  }
+
+  if (gradientType == GradientType.EXPONENTIAL_INCREASE) {
+    // initial_rate * e ^ (multi_factor * time_elapsed)
+    const temp1 = rr; //////////////////////// < 2 ^ 192
+    const temp2 = exp(mul(mt, EXP_ONE_DIV_MM)); // < 2 ^ 159 (inner expression)
+    const temp3 = mulDivC(temp1, temp2, MAX_UINT256);
+    const temp4 = EXP_ONE_MUL_RR;
+    return [mulDivF(temp1, temp2, temp3), temp4.div(temp3)]; // not ideal
+  }
+
+  if (gradientType == GradientType.EXPONENTIAL_DECREASE) {
+    // initial_rate / e ^ (multi_factor * time_elapsed)
+    const temp1 = mul(rr, EXP_ONE_DIV_RR); /////// < 2 ^ 223
+    const temp2 = exp(mul(mt, EXP_ONE_DIV_MM)); // < 2 ^ 159 (inner expression)
+    return [temp1, temp2];
+  }
+
+  throw new Error(`Invalid gradientType ${gradientType}`);
+}
+
+function sub(one: BigNumber, mt: BigNumber): BigNumber {
+  if (one.lte(mt)) {
+    throw new Error('InvalidRate');
+  }
+  return one.sub(mt);
+}
+
+/**
+* @dev Compute e ^ (x / EXP_ONE) * EXP_ONE
+* Input range: 0 <= x <= MAX_VAL - 1
+* Detailed description:
+* - Rewrite the input as a sum of binary exponents and a single residual r, as small as possible
+* - The exponentiation of each binary exponent is given (pre-calculated)
+* - The exponentiation of r is calculated via Taylor series for e^x, where x = r
+* - The exponentiation of the input is calculated by multiplying the intermediate results above
+* - For example: e^5.521692859 = e^(4 + 1 + 0.5 + 0.021692859) = e^4 * e^1 * e^0.5 * e^0.021692859
+*/
+function exp(x: BigNumber): BigNumber {
+  // prettier-ignore
+  if (x.gte(MAX_VAL)) {
+    throw new Error('ExpOverflow');
+  }
+
+  let res = BigNumber.from(0);
+
+  let y: BigNumber;
+  let z: BigNumber;
+
+  z = y = x.mod(BigNumber.from('0x10000000000000000000000000000000')); // get the input modulo 2^(-3)
+  z = z.mul(y).div(EXP_ONE); res = res.add(z.mul(BigNumber.from('0x10e1b3be415a0000'))); // add y^02 * (20! / 02!)
+  z = z.mul(y).div(EXP_ONE); res = res.add(z.mul(BigNumber.from('0x05a0913f6b1e0000'))); // add y^03 * (20! / 03!)
+  z = z.mul(y).div(EXP_ONE); res = res.add(z.mul(BigNumber.from('0x0168244fdac78000'))); // add y^04 * (20! / 04!)
+  z = z.mul(y).div(EXP_ONE); res = res.add(z.mul(BigNumber.from('0x004807432bc18000'))); // add y^05 * (20! / 05!)
+  z = z.mul(y).div(EXP_ONE); res = res.add(z.mul(BigNumber.from('0x000c0135dca04000'))); // add y^06 * (20! / 06!)
+  z = z.mul(y).div(EXP_ONE); res = res.add(z.mul(BigNumber.from('0x0001b707b1cdc000'))); // add y^07 * (20! / 07!)
+  z = z.mul(y).div(EXP_ONE); res = res.add(z.mul(BigNumber.from('0x000036e0f639b800'))); // add y^08 * (20! / 08!)
+  z = z.mul(y).div(EXP_ONE); res = res.add(z.mul(BigNumber.from('0x00000618fee9f800'))); // add y^09 * (20! / 09!)
+  z = z.mul(y).div(EXP_ONE); res = res.add(z.mul(BigNumber.from('0x0000009c197dcc00'))); // add y^10 * (20! / 10!)
+  z = z.mul(y).div(EXP_ONE); res = res.add(z.mul(BigNumber.from('0x0000000e30dce400'))); // add y^11 * (20! / 11!)
+  z = z.mul(y).div(EXP_ONE); res = res.add(z.mul(BigNumber.from('0x000000012ebd1300'))); // add y^12 * (20! / 12!)
+  z = z.mul(y).div(EXP_ONE); res = res.add(z.mul(BigNumber.from('0x0000000017499f00'))); // add y^13 * (20! / 13!)
+  z = z.mul(y).div(EXP_ONE); res = res.add(z.mul(BigNumber.from('0x0000000001a9d480'))); // add y^14 * (20! / 14!)
+  z = z.mul(y).div(EXP_ONE); res = res.add(z.mul(BigNumber.from('0x00000000001c6380'))); // add y^15 * (20! / 15!)
+  z = z.mul(y).div(EXP_ONE); res = res.add(z.mul(BigNumber.from('0x000000000001c638'))); // add y^16 * (20! / 16!)
+  z = z.mul(y).div(EXP_ONE); res = res.add(z.mul(BigNumber.from('0x0000000000001ab8'))); // add y^17 * (20! / 17!)
+  z = z.mul(y).div(EXP_ONE); res = res.add(z.mul(BigNumber.from('0x000000000000017c'))); // add y^18 * (20! / 18!)
+  z = z.mul(y).div(EXP_ONE); res = res.add(z.mul(BigNumber.from('0x0000000000000014'))); // add y^19 * (20! / 19!)
+  z = z.mul(y).div(EXP_ONE); res = res.add(z.mul(BigNumber.from('0x0000000000000001'))); // add y^20 * (20! / 20!)
+  res = res.div(BigNumber.from('0x21c3677c82b40000')).add(y).add(EXP_ONE); // divide by 20! and then add y^1 / 1! + y^0 / 0!
+
+  if (!x.and(BigNumber.from('0x010000000000000000000000000000000')).eq(0)) res = res.mul(BigNumber.from('0x1c3d6a24ed82218787d624d3e5eba95f9')).div(BigNumber.from('0x18ebef9eac820ae8682b9793ac6d1e776')); // multiply by e^2^(-3)
+  if (!x.and(BigNumber.from('0x020000000000000000000000000000000')).eq(0)) res = res.mul(BigNumber.from('0x18ebef9eac820ae8682b9793ac6d1e778')).div(BigNumber.from('0x1368b2fc6f9609fe7aceb46aa619baed4')); // multiply by e^2^(-2)
+  if (!x.and(BigNumber.from('0x040000000000000000000000000000000')).eq(0)) res = res.mul(BigNumber.from('0x1368b2fc6f9609fe7aceb46aa619baed5')).div(BigNumber.from('0x0bc5ab1b16779be3575bd8f0520a9f21f')); // multiply by e^2^(-1)
+  if (!x.and(BigNumber.from('0x080000000000000000000000000000000')).eq(0)) res = res.mul(BigNumber.from('0x0bc5ab1b16779be3575bd8f0520a9f21e')).div(BigNumber.from('0x0454aaa8efe072e7f6ddbab84b40a55c9')); // multiply by e^2^(+0)
+  if (!x.and(BigNumber.from('0x100000000000000000000000000000000')).eq(0)) res = res.mul(BigNumber.from('0x0454aaa8efe072e7f6ddbab84b40a55c5')).div(BigNumber.from('0x00960aadc109e7a3bf4578099615711ea')); // multiply by e^2^(+1)
+  if (!x.and(BigNumber.from('0x200000000000000000000000000000000')).eq(0)) res = res.mul(BigNumber.from('0x00960aadc109e7a3bf4578099615711d7')).div(BigNumber.from('0x0002bf84208204f5977f9a8cf01fdce3d')); // multiply by e^2^(+2)
+  if (!x.and(BigNumber.from('0x400000000000000000000000000000000')).eq(0)) res = res.mul(BigNumber.from('0x0002bf84208204f5977f9a8cf01fdc307')).div(BigNumber.from('0x0000003c6ab775dd0b95b4cbee7e65d11')); // multiply by e^2^(+3)
+
+  return res;
+}
+
+// TODO: get the encoded-order as input (similar to how it's done in trade.ts)
+export const getEncodedTradeTargetAmount = (
+  gradientType: GradientType,
+  initialRate: BigNumber,
+  multiFactor: BigNumber,
+  timeElapsed: BigNumber,
+  sourceAmount: BigNumber
+): BigNumber => {
+  try {
+    return uint128(calcTargetAmount(gradientType, initialRate, multiFactor, timeElapsed, sourceAmount));
+  } catch (error) {
+    return BigNumber.from(0); /* rate = zero / amount = zero */
+  }
+};
+
+// TODO: get the encoded-order as input (similar to how it's done in trade.ts)
+export const getEncodedTradeSourceAmount = (
+  gradientType: GradientType,
+  initialRate: BigNumber,
+  multiFactor: BigNumber,
+  timeElapsed: BigNumber,
+  targetAmount: BigNumber
+): BigNumber => {
+  try {
+    return uint128(calcSourceAmount(gradientType, initialRate, multiFactor, timeElapsed, targetAmount));
+  } catch (error) {
+    return MAX_UINT128; /* rate = amount / infinity = zero */
+  }
+};
+
+export const getEncodedCurrentRate = calcCurrentRate;
\ No newline at end of file
diff --git a/tests/trade_gradient.spec.ts b/tests/trade_gradient.spec.ts
new file mode 100644
index 0000000..12fdcd9
--- /dev/null
+++ b/tests/trade_gradient.spec.ts
@@ -0,0 +1,106 @@
+import { expect } from 'chai';
+import { getEncodedCurrentRate } from '../src/trade-matcher/trade_gradient';
+import {
+  encodeScaleInitialRate,
+  decodeScaleInitialRate,
+  encodeFloatInitialRate,
+  decodeFloatInitialRate,
+  encodeScaleMultiFactor,
+  decodeScaleMultiFactor,
+  encodeFloatMultiFactor,
+  decodeFloatMultiFactor,
+} from '../src/utils/encoders';
+import { Decimal, BnToDec, DecToBn } from '../src/utils/numerics';
+
+const ONE = new Decimal(1);
+const TWO = new Decimal(2);
+
+const EXP_ONE = new Decimal(2).pow(127);
+const MAX_VAL = new Decimal(2).pow(131);
+
+function expectedCurrentRate(
+  gradientType: number,
+  initialRate: Decimal,
+  multiFactor: Decimal,
+  timeElapsed: Decimal
+) {
+  switch (gradientType) {
+    case 0: return initialRate.mul(ONE.add(multiFactor.mul(timeElapsed)));
+    case 1: return initialRate.mul(ONE.sub(multiFactor.mul(timeElapsed)));
+    case 2: return initialRate.div(ONE.sub(multiFactor.mul(timeElapsed)));
+    case 3: return initialRate.div(ONE.add(multiFactor.mul(timeElapsed)));
+    case 4: return initialRate.mul(multiFactor.mul(timeElapsed).exp());
+    case 5: return initialRate.div(multiFactor.mul(timeElapsed).exp());
+  }
+  throw new Error(`Invalid gradientType ${gradientType}`);
+}
+
+function testCurrentRate(
+  gradientType: number,
+  initialRate: Decimal,
+  multiFactor: Decimal,
+  timeElapsed: Decimal,
+  maxError: string
+) {
+  it(`testCurrentRate: gradientType,initialRate,multiFactor,timeElapsed = ${[gradientType, initialRate, multiFactor, timeElapsed]}`, async () => {
+    const rEncoded = encodeFloatInitialRate(encodeScaleInitialRate(initialRate));
+    const mEncoded = encodeFloatMultiFactor(encodeScaleMultiFactor(multiFactor));
+    const rDecoded = decodeScaleInitialRate(BnToDec(decodeFloatInitialRate(rEncoded)));
+    const mDecoded = decodeScaleMultiFactor(BnToDec(decodeFloatMultiFactor(mEncoded)));
+    const expected = expectedCurrentRate(gradientType, rDecoded, mDecoded, timeElapsed);
+    if (expected.isFinite() && expected.isPositive()) {
+      const retVal = getEncodedCurrentRate(gradientType, rEncoded, mEncoded, DecToBn(timeElapsed));
+      const actual = BnToDec(retVal[0]).div(BnToDec(retVal[1]));
+      if (!actual.eq(expected)) {
+        const error = actual.div(expected).sub(1).abs();
+        expect(error.lte(maxError)).to.be.equal(
+          true,
+          `\n- expected = ${expected.toFixed()}` +
+          `\n- actual   = ${actual.toFixed()}` +
+          `\n- error    = ${error.toFixed()}`
+        );
+      }
+    } else {
+      expect(() => {
+        getEncodedCurrentRate(gradientType, rEncoded, mEncoded, DecToBn(timeElapsed));
+      }).to.throw('InvalidRate');
+    }
+  });
+}
+
+describe.only('trade_gradient', () => {
+  for (let a = 1; a <= 10; a++) {
+    for (let b = 1; b <= 10; b++) {
+      for (let c = 1; c <= 10; c++) {
+        const initialRate = new Decimal(a).mul(1234.5678);
+        const multiFactor = new Decimal(b).mul(0.00001234);
+        const timeElapsed = new Decimal(c).mul(3600);
+        testCurrentRate(0, initialRate, multiFactor, timeElapsed, '0');
+        testCurrentRate(1, initialRate, multiFactor, timeElapsed, '0');
+        testCurrentRate(2, initialRate, multiFactor, timeElapsed, '0');
+        testCurrentRate(3, initialRate, multiFactor, timeElapsed, '0');
+        testCurrentRate(4, initialRate, multiFactor, timeElapsed, '0.00000000000000000000000000000000000002');
+        testCurrentRate(5, initialRate, multiFactor, timeElapsed, '0.00000000000000000000000000000000000002');
+      }
+    }
+  }
+
+  for (let a = -27; a <= 27; a++) {
+    for (let b = -14; b <= -1; b++) {
+      for (let c = 1; c <= 10; c++) {
+        const initialRate = new Decimal(10).pow(a);
+        const multiFactor = new Decimal(10).pow(b);
+        const timeElapsed = Decimal.min(
+          MAX_VAL.div(EXP_ONE).div(multiFactor).sub(1).ceil(),
+          TWO.pow(25).sub(1)
+        ).mul(c).div(10).ceil();
+        testCurrentRate(0, initialRate, multiFactor, timeElapsed, '0');
+        testCurrentRate(1, initialRate, multiFactor, timeElapsed, '0');
+        testCurrentRate(2, initialRate, multiFactor, timeElapsed, '0');
+        testCurrentRate(3, initialRate, multiFactor, timeElapsed, '0');
+        testCurrentRate(4, initialRate, multiFactor, timeElapsed, '0.000000000000000000000000000000000002');
+        testCurrentRate(5, initialRate, multiFactor, timeElapsed, '0.000000000000000000000000000000000002');
+      }
+    }
+  }
+});